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1. Non-Standard Errors

Author: Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Lu, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, Van Dijk, Matthijs A., Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Lu, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, and Van Dijk, Matthijs A.
Abstract: In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
Published: 2024

2. Nonstandard Errors

Author: Universidad de Alicante. Departamento de Economía Financiera y Contabilidad, Menkveld, Albert J., Dreber, Anna, Holzmeister, Felix, Huber, Juergen, Johannesson, Magnus, Kirchler, Michael, Neusüß, Sebastian, Razen, Michael, Weitzel, Utz, Abad, David, Abudy, Menachem (Meni), Adrian, Tobias, Ait-Sahalia, Yacine, Akmansoy, Olivier, Alcock, Jamie T., Alexeev, Vitali, Aloosh, Arash, Amato, Livia, Amaya, Diego, Angel, James J., Avetikian, Alejandro T., Bach, Amadeus, Baidoo, Edwin, Bakalli, Gaetan, Bao, Li, Barbon, Andrea, Bashchenko, Oksana, Bindra, Parampreet C., Bjønnes, Geir H., Black, Jeffrey R., Black, Bernard S., Bogoev, Dimitar, Bohorquez Correa, Santiago, Bondarenko, Oleg, Bos, Charles S., Bosch-Rosa, Ciril, Bouri, Elie, Brownlees, Christian, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera Romero, Laura M., Caporin, Massimiliano, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chen, Jian, Chernov, Mikhail, Cheung, William, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung-Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca F., Declerck, Fany, Deev, Oleg, Degryse, Hans, Deku, Solomon Y., Desagre, Christophe, Van Dijk, Mathijs A., Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip A., Dudda, Tom, Duevski, Teodor, Dumitrescu, Ariadna, Dyakov, Teodor, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, Ellen, Saskia Ter, Eugster, Nicolas, Evans, Martin D. D., Farrell, Michael, Felez-Vinas, Ester, Ferrara, Gerardo, Ferrouhi, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan T., Foley, Sean D. V., Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco, Frijns, Bart, Frömmel, Michael, Fu, Servanna M., Füllbrunn, Sascha C., Gan, Baoqing, Gao, Ge, Gehrig, Thomas P., Gemayel, Roland, Gerritsen, Dirk, Gil-Bazo, Javier, Gilder, Dudley, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Grammig, Joachim, Grégoire, Vincent, Güçbilmez, Ufuk, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, He, Xue-Zhong (Tony), Heath, Davidson, Hediger, Simon, Hendershott, Terrence, Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth A., Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ilczuk, Konrad, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylhä, Petri, Kaeck, Andreas T., Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, Van Kervel, Vincent, Khan, Saad A., Khomyn, Marta K., Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Krahnen, Jan P., Kuhle, Paul, Kwan, Amy, Lajaunie, Quentin, Lam, F. Y. Eric C., Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, Hui, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver, Liu, Jiacheng, Liu, Anqi, Llorente, Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis, Lopez-Lira, Alejandro, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah, Mi, Michael G., Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Norden, Lars L., O'neill, Peter, Obaid, Khaled, Ødegaard, Bernt A., Östberg, Per, Pagnotta, Emiliano, Painter, Marcus, Palan, Stefan, Palit, Imon J., Park, Andreas, Pascual, Roberto, Pasquariello, Paolo, Pastor, Lubos, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelli, Michele, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Press, Oliver-Alexander, Prodromou, Tina, Prokopczuk, Marcel, Putnins, Talis, Qian, Ya, Raizada, Gaurav, Rakowski, David, Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Renjie, Rex W., Reno, Roberto, Riddiough, Steven J., Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Roesch, Dominik, Rognone, Lavinia, Roseman, Brian, Roşu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen R., Rzayev, Khaladdin, Rzeźnik, Aleksandra A., Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus R., Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Seeger, Norman J., Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Sönksen, Jantje, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nick, Tham, Wing Wah, Theissen, Erik, Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Vaduva, M. Andreea, Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, Van Der Wel, Michel, Werner, Ingrid M., Westerholm, P. Joakim, Westheide, Christian, Wika, Hans C., Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Wu, Zhen-Xing, Xia, Shuo, Xiu, Dacheng, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Yihe, Yu, Shihao, Yueshen, Bart Z., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan M., Zhang, Lu, Zhang, S. Sarah, Zhang, Xiaoyu, Zhao, Lu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu S., Zoican, Marius, Zwinkels, Remco, Universidad de Alicante. Departamento de Economía Financiera y Contabilidad, Menkveld, Albert J., Dreber, Anna, Holzmeister, Felix, Huber, Juergen, Johannesson, Magnus, Kirchler, Michael, Neusüß, Sebastian, Razen, Michael, Weitzel, Utz, Abad, David, Abudy, Menachem (Meni), Adrian, Tobias, Ait-Sahalia, Yacine, Akmansoy, Olivier, Alcock, Jamie T., Alexeev, Vitali, Aloosh, Arash, Amato, Livia, Amaya, Diego, Angel, James J., Avetikian, Alejandro T., Bach, Amadeus, Baidoo, Edwin, Bakalli, Gaetan, Bao, Li, Barbon, Andrea, Bashchenko, Oksana, Bindra, Parampreet C., Bjønnes, Geir H., Black, Jeffrey R., Black, Bernard S., Bogoev, Dimitar, Bohorquez Correa, Santiago, Bondarenko, Oleg, Bos, Charles S., Bosch-Rosa, Ciril, Bouri, Elie, Brownlees, Christian, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera Romero, Laura M., Caporin, Massimiliano, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chen, Jian, Chernov, Mikhail, Cheung, William, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung-Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca F., Declerck, Fany, Deev, Oleg, Degryse, Hans, Deku, Solomon Y., Desagre, Christophe, Van Dijk, Mathijs A., Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip A., Dudda, Tom, Duevski, Teodor, Dumitrescu, Ariadna, Dyakov, Teodor, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, Ellen, Saskia Ter, Eugster, Nicolas, Evans, Martin D. D., Farrell, Michael, Felez-Vinas, Ester, Ferrara, Gerardo, Ferrouhi, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan T., Foley, Sean D. V., Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco, Frijns, Bart, Frömmel, Michael, Fu, Servanna M., Füllbrunn, Sascha C., Gan, Baoqing, Gao, Ge, Gehrig, Thomas P., Gemayel, Roland, Gerritsen, Dirk, Gil-Bazo, Javier, Gilder, Dudley, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Grammig, Joachim, Grégoire, Vincent, Güçbilmez, Ufuk, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, He, Xue-Zhong (Tony), Heath, Davidson, Hediger, Simon, Hendershott, Terrence, Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth A., Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ilczuk, Konrad, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylhä, Petri, Kaeck, Andreas T., Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, Van Kervel, Vincent, Khan, Saad A., Khomyn, Marta K., Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Krahnen, Jan P., Kuhle, Paul, Kwan, Amy, Lajaunie, Quentin, Lam, F. Y. Eric C., Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, Hui, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver, Liu, Jiacheng, Liu, Anqi, Llorente, Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis, Lopez-Lira, Alejandro, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah, Mi, Michael G., Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Norden, Lars L., O'neill, Peter, Obaid, Khaled, Ødegaard, Bernt A., Östberg, Per, Pagnotta, Emiliano, Painter, Marcus, Palan, Stefan, Palit, Imon J., Park, Andreas, Pascual, Roberto, Pasquariello, Paolo, Pastor, Lubos, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelli, Michele, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Press, Oliver-Alexander, Prodromou, Tina, Prokopczuk, Marcel, Putnins, Talis, Qian, Ya, Raizada, Gaurav, Rakowski, David, Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Renjie, Rex W., Reno, Roberto, Riddiough, Steven J., Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Roesch, Dominik, Rognone, Lavinia, Roseman, Brian, Roşu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen R., Rzayev, Khaladdin, Rzeźnik, Aleksandra A., Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus R., Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Seeger, Norman J., Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Sönksen, Jantje, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nick, Tham, Wing Wah, Theissen, Erik, Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Vaduva, M. Andreea, Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, Van Der Wel, Michel, Werner, Ingrid M., Westerholm, P. Joakim, Westheide, Christian, Wika, Hans C., Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Wu, Zhen-Xing, Xia, Shuo, Xiu, Dacheng, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Yihe, Yu, Shihao, Yueshen, Bart Z., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan M., Zhang, Lu, Zhang, S. Sarah, Zhang, Xiaoyu, Zhao, Lu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu S., Zoican, Marius, and Zwinkels, Remco
Abstract: In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
Published: 2024

3. Modeling the green cloud continuum : integrating energy considerations into cloud-edge models

Author: Patel, Yashwant Singh, Townend, Paul, Singh, Anil, Östberg, Per-Olov, Patel, Yashwant Singh, Townend, Paul, Singh, Anil, and Östberg, Per-Olov
Abstract: The energy consumption of Cloud–Edge systems is becoming a critical concern economically, environmentally, and societally; some studies suggest data centers and networks will collectively consume 18% of global electrical power by 2030. New methods are needed to mitigate this consumption, e.g. energy-aware workload scheduling, improved usage of renewable energy sources, etc. These schemes need to understand the interaction between energy considerations and Cloud–Edge components. Model-based approaches are an effective way to do this; however, current theoretical Cloud–Edge models are limited, and few consider energy factors. This paper analyses all relevant models proposed between 2016 and 2023, discovers key omissions, and identifies the major energy considerations that need to be addressed for Green Cloud–Edge systems (including interaction with energy providers). We investigate how these can be integrated into existing and aggregated models, and conclude with the high-level architecture of our proposed solution to integrate energy and Cloud–Edge models together.
Published: 2024
Full Text: View/download PDF

4. Modeling the green cloud continuum : integrating energy considerations into cloud-edge models

Author: Patel, Yashwant Singh, Townend, Paul, Singh, Anil, Östberg, Per-Olov, Patel, Yashwant Singh, Townend, Paul, Singh, Anil, and Östberg, Per-Olov
Abstract: The energy consumption of Cloud–Edge systems is becoming a critical concern economically, environmentally, and societally; some studies suggest data centers and networks will collectively consume 18% of global electrical power by 2030. New methods are needed to mitigate this consumption, e.g. energy-aware workload scheduling, improved usage of renewable energy sources, etc. These schemes need to understand the interaction between energy considerations and Cloud–Edge components. Model-based approaches are an effective way to do this; however, current theoretical Cloud–Edge models are limited, and few consider energy factors. This paper analyses all relevant models proposed between 2016 and 2023, discovers key omissions, and identifies the major energy considerations that need to be addressed for Green Cloud–Edge systems (including interaction with energy providers). We investigate how these can be integrated into existing and aggregated models, and conclude with the high-level architecture of our proposed solution to integrate energy and Cloud–Edge models together.
Published: 2024
Full Text: View/download PDF

5. Modeling the green cloud continuum : integrating energy considerations into cloud-edge models

Author: Patel, Yashwant Singh, Townend, Paul, Singh, Anil, Östberg, Per-Olov, Patel, Yashwant Singh, Townend, Paul, Singh, Anil, and Östberg, Per-Olov
Abstract: The energy consumption of Cloud–Edge systems is becoming a critical concern economically, environmentally, and societally; some studies suggest data centers and networks will collectively consume 18% of global electrical power by 2030. New methods are needed to mitigate this consumption, e.g. energy-aware workload scheduling, improved usage of renewable energy sources, etc. These schemes need to understand the interaction between energy considerations and Cloud–Edge components. Model-based approaches are an effective way to do this; however, current theoretical Cloud–Edge models are limited, and few consider energy factors. This paper analyses all relevant models proposed between 2016 and 2023, discovers key omissions, and identifies the major energy considerations that need to be addressed for Green Cloud–Edge systems (including interaction with energy providers). We investigate how these can be integrated into existing and aggregated models, and conclude with the high-level architecture of our proposed solution to integrate energy and Cloud–Edge models together.
Published: 2024
Full Text: View/download PDF

6. Non-Standard Errors

Author: Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, Sub General Pharmaceutics, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Lu, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, Van Dijk, Matthijs A., Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, Sub General Pharmaceutics, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Lu, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, and Van Dijk, Matthijs A.
Published: 2024

7. Modeling the green cloud continuum : integrating energy considerations into cloud-edge models

Author: Patel, Yashwant Singh, Townend, Paul, Singh, Anil, Östberg, Per-Olov, Patel, Yashwant Singh, Townend, Paul, Singh, Anil, and Östberg, Per-Olov
Abstract: The energy consumption of Cloud–Edge systems is becoming a critical concern economically, environmentally, and societally; some studies suggest data centers and networks will collectively consume 18% of global electrical power by 2030. New methods are needed to mitigate this consumption, e.g. energy-aware workload scheduling, improved usage of renewable energy sources, etc. These schemes need to understand the interaction between energy considerations and Cloud–Edge components. Model-based approaches are an effective way to do this; however, current theoretical Cloud–Edge models are limited, and few consider energy factors. This paper analyses all relevant models proposed between 2016 and 2023, discovers key omissions, and identifies the major energy considerations that need to be addressed for Green Cloud–Edge systems (including interaction with energy providers). We investigate how these can be integrated into existing and aggregated models, and conclude with the high-level architecture of our proposed solution to integrate energy and Cloud–Edge models together.
Published: 2024
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8. Formal models for the energy-aware cloud-edge computing continuum : analysis and challenges

Author: Patel, Yashwant Singh, Townend, Paul, Östberg, Per-Olov, Patel, Yashwant Singh, Townend, Paul, and Östberg, Per-Olov
Abstract: Cloud infrastructures are rapidly evolving from centralised systems to geographically distributed federations of edge devices, fog nodes, and clouds. These federations (often referred to as the Cloud-Edge Continuum) are the foundation upon which most modern digital systems depend, and consume enormous amounts of energy. This consumption is becoming a critical issue as society's energy challenges grow, and is a great concern for power grids which must balance the needs of clouds against other users. The Continuum is highly dynamic, mobile, and complex; new methods to improve energy efficiency must be based on formal scientific models that identify and take into account a huge range of heterogeneous components, interactions, stochastic properties, and (potentially contradictory) service-level agreements and stakeholder objectives. Currently, few formal models of federated Cloud-Edge systems exist - and none adequately represent and integrate energy considerations (e.g. multiple providers, renewable energy sources, pricing, and the need to balance consumption over large-areas with other non-Cloud consumers, etc.). This paper conducts a systematic analysis of current approaches to modelling Cloud, Cloud-Edge, and federated Continuum systems with an emphasis on the integration of energy considerations. We identify key omissions in the literature, and propose an initial high-level architecture and approach to begin addressing these - with the ultimate goal to develop a set of integrated models that include data centres, edge devices, fog nodes, energy providers, software workloads, end users, and stakeholder requirements and objectives. We conclude by highlighting the key research challenges that must be addressed to enable meaningful energy-aware Cloud-Edge Continuum modelling and simulation.
Published: 2023
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9. COGNIT: challenges and vision for a serverless and multi-provider cognitive cloud-edge continuum

Author: Townend, Paul, Martí, Alberto P., De La Iglesia, Idoia, Matskanis, Nikolaos, Ohlson Timoudas, Thomas, Hallmann, Torsten, Lalaguna, Antonio, Swat, Kaja, Renzi, Francesco, Bocheński, Dominik, Mancini, Marco, Bhuyan, Monowar H., González-Hierro, Marco, Dupont, Sébastien, Kristiansson, Johan, Montero, Rubén S., Elmroth, Erik, Valdés, Iván, Massonet, Philippe, Olsson, Daniel, Llorente, Ignacio M., Östberg, Per-Olov, Abdou, Michael, Townend, Paul, Martí, Alberto P., De La Iglesia, Idoia, Matskanis, Nikolaos, Ohlson Timoudas, Thomas, Hallmann, Torsten, Lalaguna, Antonio, Swat, Kaja, Renzi, Francesco, Bocheński, Dominik, Mancini, Marco, Bhuyan, Monowar H., González-Hierro, Marco, Dupont, Sébastien, Kristiansson, Johan, Montero, Rubén S., Elmroth, Erik, Valdés, Iván, Massonet, Philippe, Olsson, Daniel, Llorente, Ignacio M., Östberg, Per-Olov, and Abdou, Michael
Abstract: Use of the serverless paradigm in cloud application development is growing rapidly, primarily driven by its promise to free developers from the responsibility of provisioning, operating, and scaling the underlying infrastructure. However, modern cloud-edge infrastructures are characterized by large numbers of disparate providers, constrained resource devices, platform heterogeneity, infrastructural dynamicity, and the need to orchestrate geographically distributed nodes and devices over public networks. This presents significant management complexity that must be addressed if serverless technologies are to be used in production systems. This position paper introduces COGNIT, a major new European initiative aiming to integrate AI technology into cloud-edge management systems to create a Cognitive Cloud reference framework and associated tools for serverless computing at the edge. COGNIT aims to: 1) support an innovative new serverless paradigm for edge application management and enhanced digital sovereignty for users and developers; 2) enable on-demand deployment of large-scale, highly distributed and self-adaptive serverless environments using existing cloud resources; 3) optimize data placement according to changes in energy efficiency heuristics and application demands and behavior; 4) enable secure and trusted execution of serverless runtimes. We identify and discuss seven research challenges related to the integration of serverless technologies with multi-provider Edge infrastructures and present our vision for how these challenges can be solved. We introduce a high-level view of our reference architecture for serverless cloud-edge continuum systems, and detail four motivating real-world use cases that will be used for validation, drawing from domains within Smart Cities, Agriculture and Environment, Energy, and Cybersecurity.
Published: 2023
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10. Difference-in-differences with Economic Factors and the Case of Housing Returns

Author: Huang, Jiyuan; https://orcid.org/0000-0002-5456-1482, Östberg, Per; https://orcid.org/0000-0001-9100-8080, Huang, Jiyuan; https://orcid.org/0000-0002-5456-1482, and Östberg, Per; https://orcid.org/0000-0001-9100-8080
Abstract: This paper studies how to incorporate observable factors in difference-in-differences and document their empirical relevance. We show that even under random assignment directly adding factors with unit-specific loadings into the difference-in-differences estimation results in biased estimates. This bias, which we term the “bad time control problem” arises when the treatment effect covaries with the factor variation. Researchers often control for factor structures by using: (i) unit time trends, (ii) pre-treatment covariates interacted with a time trend and (iii) group-time dummies. We show that all these methods suffer from the bad time control problem and/or omitted factor bias. We propose two solutions to the bad time control problem. To evaluate the relevance of the factor structure we study US housing returns. Adding macroeconomic factors shows that factors have additional explanatory power and estimated factor loadings differ systematically across geographic areas. This results in substantially altered treatment effects.
Published: 2023

11. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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12. The ASSISTANT project: AI for high level decisions in manufacturing

Author: Castañé, G., Dolgui, A., Kousi, N., Meyers, B., Thevenin, S., Vyhmeister, E., Östberg, Per-Olov, Castañé, G., Dolgui, A., Kousi, N., Meyers, B., Thevenin, S., Vyhmeister, E., and Östberg, Per-Olov
Abstract: This paper outlines the main idea and approach of the H2020 ASSISTANT (LeArning and robuSt deciSIon SupporT systems for agile mANufacTuring environments) project. ASSISTANT is aimed at the investigation of AI-based tools for adaptive manufacturing environments, and focuses on the development of a set of digital twins for integration with, management of, and decision support for production planning and control. The ASSISTANT tools are based on the approach of extending generative design, an established methodology for product design, to a broader set of manufacturing decision making processes; and to make use of machine learning, optimisation, and simulation techniques to produce executable models capable of ethical reasoning and data-driven decision making for manufacturing systems. Combining human control and accountable AI, the ASSISTANT toolsets span a wide range of manufacturing processes and time scales, including process planning, production planning, scheduling, and real-time control. They are designed to be adaptable and applicable in a both general and specific manufacturing environments.
Published: 2022
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13. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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14. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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15. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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16. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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17. Longitudinal changes in functional connectivity in speech motor networks in apraxia of speech after stroke

Author: Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, Lindberg, Påvel G., Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, and Lindberg, Påvel G.
Abstract: ObjectiveThe cerebral substrates of apraxia of speech (AOS) recovery remain unclear. Resting state fMRI post stroke can inform on altered functional connectivity (FC) within cortical language networks. Some initial studies report reduced FC between bilateral premotor cortices in patients with AOS, with lowest FC in patients with the most severe AOS. However, longitudinal FC studies in stroke are lacking. The aims of the present longitudinal study in early post stroke patients with AOS were (i) to compare connectivity strength in AOS patients to that in left hemisphere (LH) lesioned stroke patients without a speech-language impairment, (ii) to investigate the relation between FC and severity of AOS, aphasia and non-verbal oral apraxia (NVOA) and (iii) to investigate longitudinal changes in FC, from the subacute phase to the chronic phase to identify predictors of AOS recovery. MethodsFunctional connectivity measures and comprehensive speech-language assessments were obtained at 4 weeks and 6 months after stroke in nine patients with AOS after a LH stroke and in six LH lesioned stroke patients without speech-language impairment. Functional connectivity was investigated in a network for speech production: inferior frontal gyrus (IFG), anterior insula (aINS), and ventral premotor cortex (vPMC), all bilaterally to investigate signs of adaptive or maladaptive changes in both hemispheres. ResultsInterhemispheric vPMC connectivity was significantly reduced in patients with AOS compared to LH lesioned patients without speech-language impairment. At 6 months, the AOS severity was associated with interhemispheric aINS and vPMC connectivity. Longitudinal changes in FC were found in individuals, whereas no significant longitudinal change in FC was found at the group level. Degree of longitudinal AOS recovery was strongly associated with interhemispheric IFG connectivity strength at 4 weeks. ConclusionEarly interhemispheric IFG connectivity may be a strong predictor of AOS recove
Published: 2022
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18. Longitudinal changes in functional connectivity in speech motor networks in apraxia of speech after stroke

Author: Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, Lindberg, Påvel G., Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, and Lindberg, Påvel G.
Abstract: ObjectiveThe cerebral substrates of apraxia of speech (AOS) recovery remain unclear. Resting state fMRI post stroke can inform on altered functional connectivity (FC) within cortical language networks. Some initial studies report reduced FC between bilateral premotor cortices in patients with AOS, with lowest FC in patients with the most severe AOS. However, longitudinal FC studies in stroke are lacking. The aims of the present longitudinal study in early post stroke patients with AOS were (i) to compare connectivity strength in AOS patients to that in left hemisphere (LH) lesioned stroke patients without a speech-language impairment, (ii) to investigate the relation between FC and severity of AOS, aphasia and non-verbal oral apraxia (NVOA) and (iii) to investigate longitudinal changes in FC, from the subacute phase to the chronic phase to identify predictors of AOS recovery. MethodsFunctional connectivity measures and comprehensive speech-language assessments were obtained at 4 weeks and 6 months after stroke in nine patients with AOS after a LH stroke and in six LH lesioned stroke patients without speech-language impairment. Functional connectivity was investigated in a network for speech production: inferior frontal gyrus (IFG), anterior insula (aINS), and ventral premotor cortex (vPMC), all bilaterally to investigate signs of adaptive or maladaptive changes in both hemispheres. ResultsInterhemispheric vPMC connectivity was significantly reduced in patients with AOS compared to LH lesioned patients without speech-language impairment. At 6 months, the AOS severity was associated with interhemispheric aINS and vPMC connectivity. Longitudinal changes in FC were found in individuals, whereas no significant longitudinal change in FC was found at the group level. Degree of longitudinal AOS recovery was strongly associated with interhemispheric IFG connectivity strength at 4 weeks. ConclusionEarly interhemispheric IFG connectivity may be a strong predictor of AOS recove
Published: 2022
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19. Longitudinal changes in functional connectivity in speech motor networks in apraxia of speech after stroke

Author: Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, Lindberg, Påvel G., Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, and Lindberg, Påvel G.
Abstract: ObjectiveThe cerebral substrates of apraxia of speech (AOS) recovery remain unclear. Resting state fMRI post stroke can inform on altered functional connectivity (FC) within cortical language networks. Some initial studies report reduced FC between bilateral premotor cortices in patients with AOS, with lowest FC in patients with the most severe AOS. However, longitudinal FC studies in stroke are lacking. The aims of the present longitudinal study in early post stroke patients with AOS were (i) to compare connectivity strength in AOS patients to that in left hemisphere (LH) lesioned stroke patients without a speech-language impairment, (ii) to investigate the relation between FC and severity of AOS, aphasia and non-verbal oral apraxia (NVOA) and (iii) to investigate longitudinal changes in FC, from the subacute phase to the chronic phase to identify predictors of AOS recovery. MethodsFunctional connectivity measures and comprehensive speech-language assessments were obtained at 4 weeks and 6 months after stroke in nine patients with AOS after a LH stroke and in six LH lesioned stroke patients without speech-language impairment. Functional connectivity was investigated in a network for speech production: inferior frontal gyrus (IFG), anterior insula (aINS), and ventral premotor cortex (vPMC), all bilaterally to investigate signs of adaptive or maladaptive changes in both hemispheres. ResultsInterhemispheric vPMC connectivity was significantly reduced in patients with AOS compared to LH lesioned patients without speech-language impairment. At 6 months, the AOS severity was associated with interhemispheric aINS and vPMC connectivity. Longitudinal changes in FC were found in individuals, whereas no significant longitudinal change in FC was found at the group level. Degree of longitudinal AOS recovery was strongly associated with interhemispheric IFG connectivity strength at 4 weeks. ConclusionEarly interhemispheric IFG connectivity may be a strong predictor of AOS recove
Published: 2022
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20. Domain Models and Data Modeling as Drivers for Data Management : The ASSISTANT Data Fabric Approach

Author: Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, Van Noten, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, and Van Noten, Johan
Abstract: To develop AI-based models capable of governing or providing decision support to complex manufacturing environments, abstractions and mechanisms for unified management of data storage and processing capabilities are needed. Specifically, as such models tend to include and rely on detailed representations of systems, components, and tools with complex interactions, mechanisms for simplifying, integrating, and scaling management capabilities in the presence of complex data requirements (e.g., high volume, velocity, and diversity of data) are of particular interest. A data fabric is a system that provides a unified architecture for management and provisioning of data. In this work we present the background, design requirements, and high-level outline of the ASSISTANT data fabric - a flexible data management tool designed for use in adaptive manufacturing contexts. The paper outlines the implementation of the system with specific focus on the use of domain models and the data modeling approach used, as well as provides a generic use case structure reusable in many industrial contexts.
Published: 2022
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21. Lessons learn on responsible AI implementation : the ASSISTANT use case

Author: Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, and Östberg, Per-Olov
Abstract: Currently, pioneer companies are working hard to construct applied ethical frameworks in different sectors for using AI components that generate trust in their clients and workforce. However, independent of these few companies, there is still a considerable gap between understanding the impact of using responsible AI components, the implications of the lack of use, and what is currently applied in the industrial sector. Given that industry has shown an increased commitment to incorporating AI components, works focus on broadening the understanding of manufacturing sector stakeholders of what approaches could be considered within AI life-cycle, reducing the gap between principles and actionable requirements, and defining fundamental considerations based on risk management for incorporating, and managing, AI-based on responsible AI are required. In this work, we present a summary of the most suitable approaches that can be used for implementation and the lessons learned from a European Funded project (ASSISTANT).
Published: 2022
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22. Longitudinal changes in functional connectivity in speech motor networks in apraxia of speech after stroke

Author: Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, Lindberg, Påvel G., Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, and Lindberg, Påvel G.
Abstract: ObjectiveThe cerebral substrates of apraxia of speech (AOS) recovery remain unclear. Resting state fMRI post stroke can inform on altered functional connectivity (FC) within cortical language networks. Some initial studies report reduced FC between bilateral premotor cortices in patients with AOS, with lowest FC in patients with the most severe AOS. However, longitudinal FC studies in stroke are lacking. The aims of the present longitudinal study in early post stroke patients with AOS were (i) to compare connectivity strength in AOS patients to that in left hemisphere (LH) lesioned stroke patients without a speech-language impairment, (ii) to investigate the relation between FC and severity of AOS, aphasia and non-verbal oral apraxia (NVOA) and (iii) to investigate longitudinal changes in FC, from the subacute phase to the chronic phase to identify predictors of AOS recovery. MethodsFunctional connectivity measures and comprehensive speech-language assessments were obtained at 4 weeks and 6 months after stroke in nine patients with AOS after a LH stroke and in six LH lesioned stroke patients without speech-language impairment. Functional connectivity was investigated in a network for speech production: inferior frontal gyrus (IFG), anterior insula (aINS), and ventral premotor cortex (vPMC), all bilaterally to investigate signs of adaptive or maladaptive changes in both hemispheres. ResultsInterhemispheric vPMC connectivity was significantly reduced in patients with AOS compared to LH lesioned patients without speech-language impairment. At 6 months, the AOS severity was associated with interhemispheric aINS and vPMC connectivity. Longitudinal changes in FC were found in individuals, whereas no significant longitudinal change in FC was found at the group level. Degree of longitudinal AOS recovery was strongly associated with interhemispheric IFG connectivity strength at 4 weeks. ConclusionEarly interhemispheric IFG connectivity may be a strong predictor of AOS recove
Published: 2022
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23. The 6G Computing Continuum (6GCC) : Meeting the 6G computing challenges

Author: Tarneberg, William, Fitzgerald, Emma, Bhuyan, Monowar H., Townend, Paul, Arzen, Karl-Erik, Östberg, Per-Olov, Elmroth, Erik, Eker, Johan, Tufvesson, Fredrik, Kihl, Maria, Tarneberg, William, Fitzgerald, Emma, Bhuyan, Monowar H., Townend, Paul, Arzen, Karl-Erik, Östberg, Per-Olov, Elmroth, Erik, Eker, Johan, Tufvesson, Fredrik, and Kihl, Maria
Abstract: 6G systems, such as Large Intelligent Surfaces, will require distributed, complex, and coordinated decisions through-out a very heterogeneous and cell free infrastructure. This will require a fundamentally redesigned software infrastructure accompanied by massively distributed and heterogeneous computing resources, vastly different from current wireless networks. To address these challenges, in this paper, we propose and motivate the concept of a 6G Computing Continuum (6GCC) and two research testbeds, to advance the rate and quality of research. 6G Computing Continuum is an end-to-end compute and software platform for realizing large intelligent surfaces and its tenant users and applications. One for addressing the challenges or orchestrating shared computational resources in the wireless domain, implemented on a Large Intelligent Surfaces testbed. Another simulation-based testbed is intended to address scalability and global-scale orchestration challenges.
Published: 2022
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24. Lessons learn on responsible AI implementation : the ASSISTANT use case

Author: Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, and Östberg, Per-Olov
Abstract: Currently, pioneer companies are working hard to construct applied ethical frameworks in different sectors for using AI components that generate trust in their clients and workforce. However, independent of these few companies, there is still a considerable gap between understanding the impact of using responsible AI components, the implications of the lack of use, and what is currently applied in the industrial sector. Given that industry has shown an increased commitment to incorporating AI components, works focus on broadening the understanding of manufacturing sector stakeholders of what approaches could be considered within AI life-cycle, reducing the gap between principles and actionable requirements, and defining fundamental considerations based on risk management for incorporating, and managing, AI-based on responsible AI are required. In this work, we present a summary of the most suitable approaches that can be used for implementation and the lessons learned from a European Funded project (ASSISTANT).
Published: 2022
Full Text: View/download PDF

25. Domain Models and Data Modeling as Drivers for Data Management : The ASSISTANT Data Fabric Approach

Author: Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, Van Noten, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, and Van Noten, Johan
Abstract: To develop AI-based models capable of governing or providing decision support to complex manufacturing environments, abstractions and mechanisms for unified management of data storage and processing capabilities are needed. Specifically, as such models tend to include and rely on detailed representations of systems, components, and tools with complex interactions, mechanisms for simplifying, integrating, and scaling management capabilities in the presence of complex data requirements (e.g., high volume, velocity, and diversity of data) are of particular interest. A data fabric is a system that provides a unified architecture for management and provisioning of data. In this work we present the background, design requirements, and high-level outline of the ASSISTANT data fabric - a flexible data management tool designed for use in adaptive manufacturing contexts. The paper outlines the implementation of the system with specific focus on the use of domain models and the data modeling approach used, as well as provides a generic use case structure reusable in many industrial contexts.
Published: 2022
Full Text: View/download PDF

26. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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27. Lessons learn on responsible AI implementation : the ASSISTANT use case

Author: Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, and Östberg, Per-Olov
Abstract: Currently, pioneer companies are working hard to construct applied ethical frameworks in different sectors for using AI components that generate trust in their clients and workforce. However, independent of these few companies, there is still a considerable gap between understanding the impact of using responsible AI components, the implications of the lack of use, and what is currently applied in the industrial sector. Given that industry has shown an increased commitment to incorporating AI components, works focus on broadening the understanding of manufacturing sector stakeholders of what approaches could be considered within AI life-cycle, reducing the gap between principles and actionable requirements, and defining fundamental considerations based on risk management for incorporating, and managing, AI-based on responsible AI are required. In this work, we present a summary of the most suitable approaches that can be used for implementation and the lessons learned from a European Funded project (ASSISTANT).
Published: 2022
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28. Domain Models and Data Modeling as Drivers for Data Management : The ASSISTANT Data Fabric Approach

Author: Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, Van Noten, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, and Van Noten, Johan
Abstract: To develop AI-based models capable of governing or providing decision support to complex manufacturing environments, abstractions and mechanisms for unified management of data storage and processing capabilities are needed. Specifically, as such models tend to include and rely on detailed representations of systems, components, and tools with complex interactions, mechanisms for simplifying, integrating, and scaling management capabilities in the presence of complex data requirements (e.g., high volume, velocity, and diversity of data) are of particular interest. A data fabric is a system that provides a unified architecture for management and provisioning of data. In this work we present the background, design requirements, and high-level outline of the ASSISTANT data fabric - a flexible data management tool designed for use in adaptive manufacturing contexts. The paper outlines the implementation of the system with specific focus on the use of domain models and the data modeling approach used, as well as provides a generic use case structure reusable in many industrial contexts.
Published: 2022
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29. Longitudinal changes in functional connectivity in speech motor networks in apraxia of speech after stroke

Author: Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, Lindberg, Påvel G., Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Deboussard, Catharina, Plantin, Jeanette, Borg, Jörgen, and Lindberg, Påvel G.
Abstract: ObjectiveThe cerebral substrates of apraxia of speech (AOS) recovery remain unclear. Resting state fMRI post stroke can inform on altered functional connectivity (FC) within cortical language networks. Some initial studies report reduced FC between bilateral premotor cortices in patients with AOS, with lowest FC in patients with the most severe AOS. However, longitudinal FC studies in stroke are lacking. The aims of the present longitudinal study in early post stroke patients with AOS were (i) to compare connectivity strength in AOS patients to that in left hemisphere (LH) lesioned stroke patients without a speech-language impairment, (ii) to investigate the relation between FC and severity of AOS, aphasia and non-verbal oral apraxia (NVOA) and (iii) to investigate longitudinal changes in FC, from the subacute phase to the chronic phase to identify predictors of AOS recovery. MethodsFunctional connectivity measures and comprehensive speech-language assessments were obtained at 4 weeks and 6 months after stroke in nine patients with AOS after a LH stroke and in six LH lesioned stroke patients without speech-language impairment. Functional connectivity was investigated in a network for speech production: inferior frontal gyrus (IFG), anterior insula (aINS), and ventral premotor cortex (vPMC), all bilaterally to investigate signs of adaptive or maladaptive changes in both hemispheres. ResultsInterhemispheric vPMC connectivity was significantly reduced in patients with AOS compared to LH lesioned patients without speech-language impairment. At 6 months, the AOS severity was associated with interhemispheric aINS and vPMC connectivity. Longitudinal changes in FC were found in individuals, whereas no significant longitudinal change in FC was found at the group level. Degree of longitudinal AOS recovery was strongly associated with interhemispheric IFG connectivity strength at 4 weeks. ConclusionEarly interhemispheric IFG connectivity may be a strong predictor of AOS recove
Published: 2022
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30. Domain Models and Data Modeling as Drivers for Data Management : The ASSISTANT Data Fabric Approach

Author: Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, Van Noten, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, and Van Noten, Johan
Abstract: To develop AI-based models capable of governing or providing decision support to complex manufacturing environments, abstractions and mechanisms for unified management of data storage and processing capabilities are needed. Specifically, as such models tend to include and rely on detailed representations of systems, components, and tools with complex interactions, mechanisms for simplifying, integrating, and scaling management capabilities in the presence of complex data requirements (e.g., high volume, velocity, and diversity of data) are of particular interest. A data fabric is a system that provides a unified architecture for management and provisioning of data. In this work we present the background, design requirements, and high-level outline of the ASSISTANT data fabric - a flexible data management tool designed for use in adaptive manufacturing contexts. The paper outlines the implementation of the system with specific focus on the use of domain models and the data modeling approach used, as well as provides a generic use case structure reusable in many industrial contexts.
Published: 2022
Full Text: View/download PDF

31. Lessons learn on responsible AI implementation : the ASSISTANT use case

Author: Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, and Östberg, Per-Olov
Abstract: Currently, pioneer companies are working hard to construct applied ethical frameworks in different sectors for using AI components that generate trust in their clients and workforce. However, independent of these few companies, there is still a considerable gap between understanding the impact of using responsible AI components, the implications of the lack of use, and what is currently applied in the industrial sector. Given that industry has shown an increased commitment to incorporating AI components, works focus on broadening the understanding of manufacturing sector stakeholders of what approaches could be considered within AI life-cycle, reducing the gap between principles and actionable requirements, and defining fundamental considerations based on risk management for incorporating, and managing, AI-based on responsible AI are required. In this work, we present a summary of the most suitable approaches that can be used for implementation and the lessons learned from a European Funded project (ASSISTANT).
Published: 2022
Full Text: View/download PDF

32. Lessons learn on responsible AI implementation : the ASSISTANT use case

Author: Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castane, Gabriel G., Buchholz, Johan, and Östberg, Per-Olov
Abstract: Currently, pioneer companies are working hard to construct applied ethical frameworks in different sectors for using AI components that generate trust in their clients and workforce. However, independent of these few companies, there is still a considerable gap between understanding the impact of using responsible AI components, the implications of the lack of use, and what is currently applied in the industrial sector. Given that industry has shown an increased commitment to incorporating AI components, works focus on broadening the understanding of manufacturing sector stakeholders of what approaches could be considered within AI life-cycle, reducing the gap between principles and actionable requirements, and defining fundamental considerations based on risk management for incorporating, and managing, AI-based on responsible AI are required. In this work, we present a summary of the most suitable approaches that can be used for implementation and the lessons learned from a European Funded project (ASSISTANT).
Published: 2022
Full Text: View/download PDF

33. Domain Models and Data Modeling as Drivers for Data Management : The ASSISTANT Data Fabric Approach

Author: Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, Van Noten, Johan, Östberg, Per-Olov, Vyhmeister, Eduardo, Castañé, Gabriel G., Meyers, Bart, and Van Noten, Johan
Abstract: To develop AI-based models capable of governing or providing decision support to complex manufacturing environments, abstractions and mechanisms for unified management of data storage and processing capabilities are needed. Specifically, as such models tend to include and rely on detailed representations of systems, components, and tools with complex interactions, mechanisms for simplifying, integrating, and scaling management capabilities in the presence of complex data requirements (e.g., high volume, velocity, and diversity of data) are of particular interest. A data fabric is a system that provides a unified architecture for management and provisioning of data. In this work we present the background, design requirements, and high-level outline of the ASSISTANT data fabric - a flexible data management tool designed for use in adaptive manufacturing contexts. The paper outlines the implementation of the system with specific focus on the use of domain models and the data modeling approach used, as well as provides a generic use case structure reusable in many industrial contexts.
Published: 2022
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34. The 6G Computing Continuum (6GCC): Meeting the 6G computing challenges

Author: Tärneberg, William, Fitzgerald, Emma, Bhuyan, Monowar, Townend, Paul, Årzén, Karl-Erik, Östberg, Per-Olov, Elmroth, Erik, Eker, Johan, Tufvesson, Fredrik, Kihl, Maria, Tärneberg, William, Fitzgerald, Emma, Bhuyan, Monowar, Townend, Paul, Årzén, Karl-Erik, Östberg, Per-Olov, Elmroth, Erik, Eker, Johan, Tufvesson, Fredrik, and Kihl, Maria
Abstract: 6G systems, such as Large Intelligent Surfaces, will require distributed, complex, and coordinated decisions throughout a very heterogeneous and cell free infrastructure. This will require a fundamentally redesigned software infrastructure accompanied by massively distributed and heterogeneous computing resources, vastly different from current wireless networks.To address these challenges, in this paper, we propose and motivate the concept of a 6G Computing Continuum (6GCC) and two research testbeds, to advance the rate and quality of research. 6G Computing Continuum is an end-to-end computeand software platform for realizing large intelligent surfaces and its tenant users and applications. One for addressing the challenges or orchestrating shared computational resources in the wireless domain, implemented on a Large Intelligent Surfaces testbed. Another simulation-based testbed is intended to address scalability and global-scale orchestration challenges.
Published: 2022

35. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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36. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
Full Text: View/download PDF

37. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
Full Text: View/download PDF

38. Self-reported changes in everyday life and health of significant others of people with aphasia : a quantitative approach

Author: Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, Sonnander, Karin, Blom Johansson, Monica, Carlsson, Marianne, Östberg, Per, and Sonnander, Karin
Abstract: Background: Changes in the everyday life and health of the significant others (SOs) of people living with stroke sequalae have been widely investigated. However, information regarding the frequency of the changes in daily life and the variables most associated with these perceived life changes is limited. Aims: To examine the extent to which SOs of persons with aphasia (PWAs) experience changes in everyday life and health after the stroke event and how they evaluate these changes and to identify which variables are associated with these perceived life changes. Methods & Procedures: A study-specific questionnaire about perceived changes in everyday life and health was completed by 173 SOs of PWAs living in Sweden (response rate 67.8%). The items concerned the SO’s working and financial situation, leisure time and social life, relationship with the PWA, household work and responsibility, and health and quality of life. Outcomes & Results: The everyday life and health of the SOs were greatly affected by the stroke event. The changes the SOs experienced were mainly appraised negatively. The relationships with the PWA and immediate family were least affected by the stroke. The perceived existence and severity of physical, cognitive, and language impairments of the PWA were the variables most strongly associated with the everyday life situation of the participants. The sex and age of the participants and the nature of the relationship with the PWA were only marginally associated with the experience of the situation. Conclusions: SOs’ perceptions of the PWA’s stroke-related disabilities and need for assistance may be a key factor in identifying SOs who may require support and guidance to help them cope with their new life situation.
Published: 2022
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39. The Sovereign Debt Crisis: Flights or Freezes?

Author: Östberg, Per; https://orcid.org/0000-0001-9100-8080, Richter, Thomas, Östberg, Per; https://orcid.org/0000-0001-9100-8080, and Richter, Thomas
Abstract: Multiple asset pricing theories predict that large price changes should be associated with abnormal trading volume, inducing investor rebalancing and possibly leading to flights. In contrast, consistent with market microstructure theories, this paper documents freezes, a reduction in trading volume (approximately 30% relative to the previous trading week) during market stress episodes in the European sovereign bond market. We trace the market freezes to increasing transaction costs driven by reduced risk bearing capacity of market makers.
Published: 2022

40. Intra- and Interjudge Reliability of the Apraxia of Speech Rating Scale in Early Stroke Patients

Author: Hybbinette, Helena, Östberg, Per, Schalling, Ellika, Hybbinette, Helena, Östberg, Per, and Schalling, Ellika
Published: 2021
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41. Recovery of Apraxia of Speech and Aphasia in Patients With Hand Motor Impairment After Stroke

Author: Hybbinette, Helena, Schalling, Ellika, Plantin, Jeanette, Nygren-Deboussard, Catharina, Schütz, Marika, Östberg, Per, Lindberg, Påvel G., Hybbinette, Helena, Schalling, Ellika, Plantin, Jeanette, Nygren-Deboussard, Catharina, Schütz, Marika, Östberg, Per, and Lindberg, Påvel G.
Published: 2021
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42. Assistant: Learning and robust decision support system for agile manufacturing environments

Author: Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, Östberg, Per-Olov, Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, and Östberg, Per-Olov
Abstract: The European project ASSISTANT will provide a set of AI-based digital twins that helps process engineers and production planners to operate collaborative mixed-model assembly lines based on the data collected from IoT devices and external data sources. Such a tool will help planners to design the assembly line, plan the production, operate the line, and improve process tuning. In addition, the system monitors the line in real-time, ensures that all required resources are available, and allows fast re-planning when necessary. ASSISTANT aims to make cost-effective decisions while ensuring product quality, safety and wellbeing of the workers, and managing the various sources of uncertainties. The resulting digital twin systems will be data-driven, agile, autonomous, collaborative and explainable, safe but reactive.
Published: 2021
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43. Assistant: Learning and robust decision support system for agile manufacturing environments

Author: Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, Östberg, Per-Olov, Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, and Östberg, Per-Olov
Abstract: The European project ASSISTANT will provide a set of AI-based digital twins that helps process engineers and production planners to operate collaborative mixed-model assembly lines based on the data collected from IoT devices and external data sources. Such a tool will help planners to design the assembly line, plan the production, operate the line, and improve process tuning. In addition, the system monitors the line in real-time, ensures that all required resources are available, and allows fast re-planning when necessary. ASSISTANT aims to make cost-effective decisions while ensuring product quality, safety and wellbeing of the workers, and managing the various sources of uncertainties. The resulting digital twin systems will be data-driven, agile, autonomous, collaborative and explainable, safe but reactive.
Published: 2021
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44. Non-Standard Errors

Author: Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, LS Algemene Literatuurwetenschap, Hydrogeology, Sub General Pharmaceutics, Finance and Financial Markets, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Sarah, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Zhang, Lu, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, Van Dijk, Matthijs A., Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, LS Algemene Literatuurwetenschap, Hydrogeology, Sub General Pharmaceutics, Finance and Financial Markets, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Sarah, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Zhang, Lu, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, and Van Dijk, Matthijs A.
Published: 2021

45. Multivariate Time Series Synthesis Using Generative Adversarial Networks

Author: Leznik, Mark, Michalsky, Patrick, Willis, Peter, Schanzel, Benjamin, Östberg, Per-Olov, Domaschka, Jörg, Leznik, Mark, Michalsky, Patrick, Willis, Peter, Schanzel, Benjamin, Östberg, Per-Olov, and Domaschka, Jörg
Abstract: Collection and analysis of distributed (cloud) computing workloads allows for a deeper understanding of user and system behavior and is necessary for efficient operation of infrastructures and applications. The availability of such workload data is however often limited as most cloud infrastructures are commercially operated and monitoring data is considered proprietary or falls under GPDR regulations. This work investigates the generation of synthetic workloads using Generative Adversarial Networks and addresses a current need for more data and better tools for workload generation. Resource utilization measurements such as the utilization rates of Content Delivery Network (CDN) caches are generated and a comparative evaluation pipeline using descriptive statistics and time-series analysis is developed to assess the statistical similarity of generated and measured workloads. We use CDN data open sourced by us in a data generation pipeline as well as back-end ISP workload data to demonstrate the multivariate synthesis capability of our approach. The work contributes a generation method for multivariate time series workload generation that can provide arbitrary amounts of statistically similar data sets based on small subsets of real data. The presented technique shows promising results, in particular for heterogeneous workloads not too irregular in temporal behavior.
Published: 2021
Full Text: View/download PDF

46. Multivariate Time Series Synthesis Using Generative Adversarial Networks

Author: Leznik, Mark, Michalsky, Patrick, Willis, Peter, Schanzel, Benjamin, Östberg, Per-Olov, Domaschka, Jörg, Leznik, Mark, Michalsky, Patrick, Willis, Peter, Schanzel, Benjamin, Östberg, Per-Olov, and Domaschka, Jörg
Abstract: Collection and analysis of distributed (cloud) computing workloads allows for a deeper understanding of user and system behavior and is necessary for efficient operation of infrastructures and applications. The availability of such workload data is however often limited as most cloud infrastructures are commercially operated and monitoring data is considered proprietary or falls under GPDR regulations. This work investigates the generation of synthetic workloads using Generative Adversarial Networks and addresses a current need for more data and better tools for workload generation. Resource utilization measurements such as the utilization rates of Content Delivery Network (CDN) caches are generated and a comparative evaluation pipeline using descriptive statistics and time-series analysis is developed to assess the statistical similarity of generated and measured workloads. We use CDN data open sourced by us in a data generation pipeline as well as back-end ISP workload data to demonstrate the multivariate synthesis capability of our approach. The work contributes a generation method for multivariate time series workload generation that can provide arbitrary amounts of statistically similar data sets based on small subsets of real data. The presented technique shows promising results, in particular for heterogeneous workloads not too irregular in temporal behavior.
Published: 2021
Full Text: View/download PDF

47. Non-Standard Errors

Author: Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, LS Algemene Literatuurwetenschap, Hydrogeology, Sub General Pharmaceutics, Finance and Financial Markets, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Sarah, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Zhang, Lu, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, Van Dijk, Matthijs A., Leerstoel Stigchel, Helmholtz Institute, Experimental Psychology (onderzoeksprogramma PF), Finance, UU LEG Research UUSE Multidisciplinary Economics, LS Algemene Literatuurwetenschap, Hydrogeology, Sub General Pharmaceutics, Finance and Financial Markets, Menkveld, Albert J., Abudy, Menachem (Meni), Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, Adrian, Tobias, He, Xue-Zhong 'Tony', Heath, Davidson, Hediger, Simon, Hendershott, Terrence J., Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth, Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Ait-Sahalia, Yacine, Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian R., Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Akmansoy, Olivier, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, van Kervel, Vincent, Khan, Saad, Alcock, Jamie, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Alexeev, Vitali, Lajaunie, Quentin, Lam, Full Yet Eric Campbell, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, (Michael) Hui, Aloosh, Arash, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente-Alvarez, Jesus-Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Amato, Livia, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah C, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Amaya, Diego, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Nordén, Lars L., O'Neill, Peter, Angel, James J., Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual Gascó, Roberto, Pasquariello, Paolo, Pastor, Lubos, Dreber, Anna, Bach, Amadeus, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Pelster, Matthias, Pérignon, Christophe, Pfiffer, Cameron, Philip, Richard, Plíhal, Tomáš, Prakash, Puneet, Baidoo, Edwin, Press, Oliver-Alexander, Prodromou, Tina, Putnins, Talis J., Raizada, Gaurav, Rakowski, David A., Ranaldo, Angelo, Regis, Luca, Reitz, Stefan, Renault, Thomas, Wang, Renjie, Bakalli, Gaetan, Renò, Roberto, Riddiough, Steven, Rinne, Kalle, Rintamäki, Paul, Riordan, Ryan, Rittmannsberger, Thomas, Rodríguez Longarela, Iñaki, Rösch, Dominik, Rognone, Lavinia, Roseman, Brian, Barbon, Andrea, Rosu, Ioanid, Roy, Saurabh, Rudolf, Nicolas, Rush, Stephen, Rzayev, Khaladdin, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Bashchenko, Oksana, Scaillet, Olivier, Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Bindra, Parampreet Christopher, Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Bjonnes, Geir Hoidal, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Black, Jeffrey R., Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Black, Bernard S., Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, van der Wel, Michel, Werner, Ingrid M., Bohorquez, Santiago, Westerholm, P. Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christian C. P., Wolk, Leonard, Wong, Wing-Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Holzmeister, Felix, Bondarenko, Oleg, Xu, Ke, Xu, Caihong, Yadav, Pradeep K., Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Bos, Charles S., Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Sarah, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu, Bosch-Rosa, Ciril, Zoican, Marius, Zwinkels, Remco C.J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Bouri, Elie, Sönksen, Jantje, Zhang, Lu, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Brownlees, Christian T., Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Huber, Juergen, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William Ming Yan, Chincarini, Ludwig B., Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Johanneson, Magnus, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Kirchler, Michael, Deku, Solomon, Desagre, Christophe, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Razen, Michael, Dyhrberg, Anne Haubo, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, ter Ellen, Saskia, Eugster, Nicolas, Evans, Martin D.D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Weitzel, Utz, FERROUHI, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco A., Frijns, Bart, Frömmel, Michael, Abad, David, Fu, Servanna Mianjun, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, and Van Dijk, Matthijs A.
Published: 2021

48. Non-standard errors

Author: Menkveld, Albert J., Dreber, Anna, Holzmeister, Felix, Huber, Jürgen, Johannesson, Magnus, Kirchler, Michael, Razen, Michael, Weitzel, Utz, Abad Díaz, David, Abudy, Menachem, Adrian, Tobias, Ait-Sahalia, Yacine, Akmansoy, Olivier, Alcock, Jamie, Alexeev, Vitali, Aloosh, Arash, Amato, Livia, Amaya, Diego, Angel, James, Bach, Amadeus, Baidoo, Edwin, Bakalli, Gaetan, Barbon, Andrea, Bashchenko, Oksana, Bindra, Parampreet Christopher, Bjonnes, Geir Hoidal, Black, Jeff, Black, Bernard S., Bohorquez, Santiago, Bondarenko, Oleg, Bos, Charles S., Bosch-Rosa, Ciril, Bouri, Elie, Brownlees, Christian, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William M., Chincarini, Ludwig Boris, Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Deku, Solomon, Desagre, Christophe, Dijk, Mathijs van, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Haubo Dyhrberg, Anne, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, Ellen, Saskia ter, Eugster, Nicolas, Evans, Martin D. D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Ferrouhi, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco, Frijns, Bart, Frömmel, Michael, Fu, Servanna, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, He, Xuezhong, Heath, Davidson, Hediger, Simon, Hendershott, Terrence, Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth A., Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian Rama, Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, Kervel, Vincent van, Khan, Saad, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Lajaunie, Quentin, Lam, FY Eric C, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, Hui, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente, Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Norden, Lars L., O'Neill, Peter, Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual, Roberto, Pasquariello, Paolo, Pastor, Lubos, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Scaillet, O., Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, Wel, Michel van der, Werner, Ingrid M., Westerholm, Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christiaan Cornelis Petrus, Wolk, Leonard, Wong, Wing Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Xu, Ke, Xu, Caihong, Yadav, Pradeep, Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Sarah, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu Sonya, Zoican, Marius, Zwinkels, Remco C. J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Sönksen, Jantje, Zhang, Lu, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, Wu, Zhen-Xing, Menkveld, Albert J., Dreber, Anna, Holzmeister, Felix, Huber, Jürgen, Johannesson, Magnus, Kirchler, Michael, Razen, Michael, Weitzel, Utz, Abad Díaz, David, Abudy, Menachem, Adrian, Tobias, Ait-Sahalia, Yacine, Akmansoy, Olivier, Alcock, Jamie, Alexeev, Vitali, Aloosh, Arash, Amato, Livia, Amaya, Diego, Angel, James, Bach, Amadeus, Baidoo, Edwin, Bakalli, Gaetan, Barbon, Andrea, Bashchenko, Oksana, Bindra, Parampreet Christopher, Bjonnes, Geir Hoidal, Black, Jeff, Black, Bernard S., Bohorquez, Santiago, Bondarenko, Oleg, Bos, Charles S., Bosch-Rosa, Ciril, Bouri, Elie, Brownlees, Christian, Calamia, Anna, Cao, Viet Nga, Capelle-Blancard, Gunther, Capera, Laura, Caporin, Massimiliano, Carrion, Allen, Caskurlu, Tolga, Chakrabarty, Bidisha, Chernov, Mikhail, Cheung, William M., Chincarini, Ludwig Boris, Chordia, Tarun, Chow, Sheung Chi, Clapham, Benjamin, Colliard, Jean-Edouard, Comerton-Forde, Carole, Curran, Edward, Dao, Thong, Dare, Wale, Davies, Ryan J., De Blasis, Riccardo, De Nard, Gianluca, Declerck, Fany, Deev, Oleg, Degryse, Hans, Deku, Solomon, Desagre, Christophe, Dijk, Mathijs van, Dim, Chukwuma, Dimpfl, Thomas, Dong, Yun Jiang, Drummond, Philip, Dudda, Tom, Dumitrescu, Ariadna, Dyakov, Teodor, Haubo Dyhrberg, Anne, Dzieliński, Michał, Eksi, Asli, El Kalak, Izidin, Ellen, Saskia ter, Eugster, Nicolas, Evans, Martin D. D., Farrell, Michael, Félez-Viñas, Ester, Ferrara, Gerardo, Ferrouhi, El Mehdi, Flori, Andrea, Fluharty-Jaidee, Jonathan, Foley, Sean, Fong, Kingsley Y. L., Foucault, Thierry, Franus, Tatiana, Franzoni, Francesco, Frijns, Bart, Frömmel, Michael, Fu, Servanna, Füllbrunn, Sascha, Gan, Baoqing, Gehrig, Thomas, Gerritsen, Dirk, Gil-Bazo, Javier, Glosten, Lawrence R., Gomez, Thomas, Gorbenko, Arseny, Güçbilmez, Ufuk, Grammig, Joachim, Gregoire, Vincent, Hagströmer, Björn, Hambuckers, Julien, Hapnes, Erik, Harris, Jeffrey H., Harris, Lawrence, Hartmann, Simon, Hasse, Jean-Baptiste, Hautsch, Nikolaus, He, Xuezhong, Heath, Davidson, Hediger, Simon, Hendershott, Terrence, Hibbert, Ann Marie, Hjalmarsson, Erik, Hoelscher, Seth A., Hoffmann, Peter, Holden, Craig W., Horenstein, Alex R., Huang, Wenqian, Huang, Da, Hurlin, Christophe, Ivashchenko, Alexey, Iyer, Subramanian Rama, Jahanshahloo, Hossein, Jalkh, Naji, Jones, Charles M., Jurkatis, Simon, Jylha, Petri, Kaeck, Andreas, Kaiser, Gabriel, Karam, Arzé, Karmaziene, Egle, Kassner, Bernhard, Kaustia, Markku, Kazak, Ekaterina, Kearney, Fearghal, Kervel, Vincent van, Khan, Saad, Khomyn, Marta, Klein, Tony, Klein, Olga, Klos, Alexander, Koetter, Michael, Krahnen, Jan Pieter, Kolokolov, Aleksey, Korajczyk, Robert A., Kozhan, Roman, Kwan, Amy, Lajaunie, Quentin, Lam, FY Eric C, Lambert, Marie, Langlois, Hugues, Lausen, Jens, Lauter, Tobias, Leippold, Markus, Levin, Vladimir, Li, Yijie, Li, Hui, Liew, Chee Yoong, Lindner, Thomas, Linton, Oliver B., Liu, Jiacheng, Liu, Anqi, Llorente, Guillermo, Lof, Matthijs, Lohr, Ariel, Longstaff, Francis A., Lopez-Lira, Alejandro, Mankad, Shawn, Mano, Nicola, Marchal, Alexis, Martineau, Charles, Mazzola, Francesco, Meloso, Debrah, Mihet, Roxana, Mohan, Vijay, Moinas, Sophie, Moore, David, Mu, Liangyi, Muravyev, Dmitriy, Murphy, Dermot, Neszveda, Gabor, Neumeier, Christian, Nielsson, Ulf, Nimalendran, Mahendrarajah, Nolte, Sven, Norden, Lars L., O'Neill, Peter, Obaid, Khaled, Ødegaard, Bernt Arne, Östberg, Per, Painter, Marcus, Palan, Stefan, Palit, Imon, Park, Andreas, Pascual, Roberto, Pasquariello, Paolo, Pastor, Lubos, Patel, Vinay, Patton, Andrew J., Pearson, Neil D., Pelizzon, Loriana, Rzeźnik, Aleksandra, Sanford, Anthony, Sankaran, Harikumar, Sarkar, Asani, Sarno, Lucio, Scaillet, O., Scharnowski, Stefan, Schenk-Hoppé, Klaus Reiner, Schertler, Andrea, Schneider, Michael, Schroeder, Florian, Schürhoff, Norman, Schuster, Philipp, Schwarz, Marco A., Seasholes, Mark S., Seeger, Norman, Shachar, Or, Shkilko, Andriy, Shui, Jessica, Sikic, Mario, Simion, Giorgia, Smales, Lee A., Söderlind, Paul, Sojli, Elvira, Sokolov, Konstantin, Spokeviciute, Laima, Stefanova, Denitsa, Subrahmanyam, Marti G., Neusüss, Sebastian, Szaszi, Barnabas, Talavera, Oleksandr, Tang, Yuehua, Taylor, Nicholas, Tham, Wing Wah, Theissen, Erik, Thimme, Julian, Tonks, Ian, Tran, Hai, Trapin, Luca, Trolle, Anders B., Valente, Giorgio, Van Ness, Robert A., Vasquez, Aurelio, Verousis, Thanos, Verwijmeren, Patrick, Vilhelmsson, Anders, Vilkov, Grigory, Vladimirov, Vladimir, Vogel, Sebastian, Voigt, Stefan, Wagner, Wolf, Walther, Thomas, Weiss, Patrick, Wel, Michel van der, Werner, Ingrid M., Westerholm, Joakim, Westheide, Christian, Wipplinger, Evert, Wolf, Michael, Wolff, Christiaan Cornelis Petrus, Wolk, Leonard, Wong, Wing Keung, Wrampelmeyer, Jan, Xia, Shuo, Xiu, Dacheng, Xu, Ke, Xu, Caihong, Yadav, Pradeep, Yagüe, José, Yan, Cheng, Yang, Antti, Yoo, Woongsun, Yu, Wenjia, Yu, Shihao, Yueshen, Bart Zhou, Yuferova, Darya, Zamojski, Marcin, Zareei, Abalfazl, Zeisberger, Stefan, Zhang, Sarah, Zhang, Xiaoyu, Zhong, Zhuo, Zhou, Z. Ivy, Zhou, Chen, Zhu, Xingyu Sonya, Zoican, Marius, Zwinkels, Remco C. J., Chen, Jian, Duevski, Teodor, Gao, Ge, Gemayel, Roland, Gilder, Dudley, Kuhle, Paul, Pagnotta, Emiliano, Pelli, Michele, Sönksen, Jantje, Zhang, Lu, Ilczuk, Konrad, Bogoev, Dimitar, Qian, Ya, Wika, Hans C., Yu, Yihe, Zhao, Lu, Mi, Michael, Bao, Li, Vaduva, Andreea, Prokopczuk, Marcel, Avetikian, Alejandro, and Wu, Zhen-Xing
Abstract: In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Published: 2021

49. Assistant: Learning and robust decision support system for agile manufacturing environments

Author: Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, Östberg, Per-Olov, Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, and Östberg, Per-Olov
Abstract: The European project ASSISTANT will provide a set of AI-based digital twins that helps process engineers and production planners to operate collaborative mixed-model assembly lines based on the data collected from IoT devices and external data sources. Such a tool will help planners to design the assembly line, plan the production, operate the line, and improve process tuning. In addition, the system monitors the line in real-time, ensures that all required resources are available, and allows fast re-planning when necessary. ASSISTANT aims to make cost-effective decisions while ensuring product quality, safety and wellbeing of the workers, and managing the various sources of uncertainties. The resulting digital twin systems will be data-driven, agile, autonomous, collaborative and explainable, safe but reactive.
Published: 2021
Full Text: View/download PDF

50. Assistant: Learning and robust decision support system for agile manufacturing environments

Author: Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, Östberg, Per-Olov, Beldiceanu, Nicolas, Dolgui, Alexandre, Gonnermann, Clemens, Gonzalez-Castañé, Gabriel, Kousi, Niki, Meyers, Bart, Prud'homme, Julien, Thevenin, Simon, Vyhmeister, Eduardo, and Östberg, Per-Olov
Abstract: The European project ASSISTANT will provide a set of AI-based digital twins that helps process engineers and production planners to operate collaborative mixed-model assembly lines based on the data collected from IoT devices and external data sources. Such a tool will help planners to design the assembly line, plan the production, operate the line, and improve process tuning. In addition, the system monitors the line in real-time, ensures that all required resources are available, and allows fast re-planning when necessary. ASSISTANT aims to make cost-effective decisions while ensuring product quality, safety and wellbeing of the workers, and managing the various sources of uncertainties. The resulting digital twin systems will be data-driven, agile, autonomous, collaborative and explainable, safe but reactive.
Published: 2021
Full Text: View/download PDF

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