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1. Spintronic Physical Reservoir for Autonomous Prediction and Long-Term Household Energy Load Forecasting

Author

Misba, Walid Al, Mavikumbure, Harindra S., Rajib, Md Mahadi, Marino, Daniel L., Cobilean, Victor, Manic, Milos, and Atulasimha, Jayasimha

Subjects
Computer Science - Machine Learning
Abstract

In this study, we have shown autonomous long-term prediction with a spintronic physical reservoir. Due to the short-term memory property of the magnetization dynamics, non-linearity arises in the reservoir states which could be used for long-term prediction tasks using simple linear regression for online training. During the prediction stage, the output is directly fed to the input of the reservoir for autonomous prediction. We employ our proposed reservoir for the modeling of the chaotic time series such as Mackey-Glass and dynamic time-series data, such as household building energy loads. Since only the last layer of a RC needs to be trained with linear regression, it is well suited for learning in real time on edge devices. Here we show that a skyrmion based magnetic tunnel junction can potentially be used as a prototypical RC but any nanomagnetic magnetic tunnel junction with nonlinear magnetization behavior can implement such a RC. By comparing our spintronic physical RC approach with energy load forecasting algorithms, such as LSTMs and RNNs, we conclude that the proposed framework presents good performance in achieving high predictions accuracy, while also requiring low memory and energy both of which are at a premium in hardware resource and power constrained edge applications. Further, the proposed approach is shown to require very small training datasets and at the same time being at least 16X energy efficient compared to the sequence to sequence LSTM for accurate household load predictions.

Published
2023
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2. RX-ADS: Interpretable Anomaly Detection using Adversarial ML for Electric Vehicle CAN data

Author

Wickramasinghe, Chathurika S., Marino, Daniel L., Mavikumbure, Harindra S., Cobilean, Victor, Pennington, Timothy D., Varghese, Benny J., Rieger, Craig, and Manic, Milos

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Cryptography and Security
Abstract

Recent year has brought considerable advancements in Electric Vehicles (EVs) and associated infrastructures/communications. Intrusion Detection Systems (IDS) are widely deployed for anomaly detection in such critical infrastructures. This paper presents an Interpretable Anomaly Detection System (RX-ADS) for intrusion detection in CAN protocol communication in EVs. Contributions include: 1) window based feature extraction method; 2) deep Autoencoder based anomaly detection method; and 3) adversarial machine learning based explanation generation methodology. The presented approach was tested on two benchmark CAN datasets: OTIDS and Car Hacking. The anomaly detection performance of RX-ADS was compared against the state-of-the-art approaches on these datasets: HIDS and GIDS. The RX-ADS approach presented performance comparable to the HIDS approach (OTIDS dataset) and has outperformed HIDS and GIDS approaches (Car Hacking dataset). Further, the proposed approach was able to generate explanations for detected abnormal behaviors arising from various intrusions. These explanations were later validated by information used by domain experts to detect anomalies. Other advantages of RX-ADS include: 1) the method can be trained on unlabeled data; 2) explanations help experts in understanding anomalies and root course analysis, and also help with AI model debugging and diagnostics, ultimately improving user trust in AI systems.

Published
2022

3. Self-Supervised and Interpretable Anomaly Detection using Network Transformers

Author

Marino, Daniel L., Wickramasinghe, Chathurika S., Rieger, Craig, and Manic, Milos

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Cryptography and Security
Abstract

Monitoring traffic in computer networks is one of the core approaches for defending critical infrastructure against cyber attacks. Machine Learning (ML) and Deep Neural Networks (DNNs) have been proposed in the past as a tool to identify anomalies in computer networks. Although detecting these anomalies provides an indication of an attack, just detecting an anomaly is not enough information for a user to understand the anomaly. The black-box nature of off-the-shelf ML models prevents extracting important information that is fundamental to isolate the source of the fault/attack and take corrective measures. In this paper, we introduce the Network Transformer (NeT), a DNN model for anomaly detection that incorporates the graph structure of the communication network in order to improve interpretability. The presented approach has the following advantages: 1) enhanced interpretability by incorporating the graph structure of computer networks; 2) provides a hierarchical set of features that enables analysis at different levels of granularity; 3) self-supervised training that does not require labeled data. The presented approach was tested by evaluating the successful detection of anomalies in an Industrial Control System (ICS). The presented approach successfully identified anomalies, the devices affected, and the specific connections causing the anomalies, providing a data-driven hierarchical approach to analyze the behavior of a cyber network.

Published
2022

6. Stroke in critically ill patients with respiratory failure due to COVID-19: Disparities between low-middle and high-income countries

Author

Al-Dabbous, Tala, Alfoudri, Huda, Shamsah, Mohammed, Alfroukh, Khadeejeh, Bairmani, Zinah Aqeel Abdulzahra, Khalid, Khalid Jehad, Abukhalaf, Salsabeel M.A., Hadhoud, Mohammed Maher, Abdrabo, Mohamed Fouad, Fathi, Mohamed, Alhouri, Hasan, Shahla, Dr Hamza, Alhadad, Qamrah, Hanan, Matly, Elapavaluru, Subbarao, Berg, Ashley, Horn, Christina, Abdelhalim, Ahmed Reda Mohamed Elsayed, Amer, Amro Essam, Elnaggar, Cinderella Omar Rageh, Hassan, Ahmed Ayman, Abdelaziz, Ali, Abdelhalim, Mohamed, Orabi, Yehia Samir Shaaban Aly, Alaraji, Zinah A., Muhaisen, Mo'nes R., Almasri, Lana, Mustafa, Dana, Hamdan, Shaher, Al-Saba'a, Yousef, Dalloul, Zaina, Alkahlout, Mohammed, Jaber, Hamza, Aldabbourosama, Osama, Abdalhadi, Alaa Abdalfattah, Hussein, Aliae AR Mohamed, Emad, Zarief Kamel, Khaled, Sarah, Mohamed, Nouralsabah, Hassanin, Ebtisam, Hamdi, Abdelhafeez, Gamal, May, Emad, Ahmed, Ragab, Abdelrahman, Azizeldin, Mohammed G, Hamza, Almthani, Omer, Alsarrah Ali Mohammed, Fadl alla, Asgad Osman Abdalla, Abdallahrs, Asia Atif Abdelrahman, Eltayeb, Aml Ahmed, Alhasan, Maali khalid mohamed abdalla, Abdelgaum, Esraa Hassan, Ahmed, Aya Mustafa, Abdulbaqi, Lamees Adil, Mohammedelhassan, Omer Abdullah, Ahmed, Musaab Mohammed Mohammed, Ali, Maha TagElser Mohammed, Mayasi, Yunis, Schroll, Stephan, Meyer, Dan, Velazco, Jorge, Ploskanych, Ludmyla, Fikes, Wanda, Bagewadi, Rohini, Dao, Marvin, White, Haley, Laviena, Alondra Berrios, Ehlers, Ashley, Shalabi-McGuire, Maysoon, Witt, Trent, Grazioli, Lorenzo, Lorini, Luca, Grandin, E. Wilson, Nunez, Jose, Reyes, Tiago, O'Briain, Diarmuid, Hunter, Stephanie, Ramanan, Mahesh, Affleck, Julia, Veerendra, Hemanth Hurkadli, Rai, Sumeet, Russell-Brown, Josie, Nourse, Mary, Joseph, Mark, Mitchell, Brook, Tenzer, Martha, Abe, Ryuzo, Cho, Hwa Jin, Jeong, In Seok, Rahman, Nadeem, Kakar, Vivek, Tamimi, Ahmed, Zabalawi, Diala, Elhennawi, Mohamed, Ghisulal, Praveen, Malik, Sadaf, Brozzi, Nicolas, Mehkri, Omar, Krishnan, Sudhir, Duggal, Abhijit, Houltham, Stuart, Graf, Jerónimo, Diaz, Roderigo, Orrego, Roderigo, Delgado, Camila, González, Joyce, Sanchez, Maria Soledad, Piagnerelli, Michael, Sarrazin, Josefa Valenzuela, Zabert, Prof. Gustavo, Espinosa, Lucio, Delgado, Paulo, Delgado, Victoria, Rincón, Diego Fernando Bautista, Yanten, Angela Maria Marulanda, Duque, Melissa Bustamante, Brodie, Daniel, Abouelmagd, Khaled, Elhazmi, Alyaa, Al-Hudaib, Abdullah, Javidfar, Jeff, Callahan, Maria, Dong, Andy, D'Orleans, Charles Crepy, Taufik, M. Azhari, Wardoyo, Elizabeth Yasmin, Gunawan, Margaretha, Trisnaningrum, Nurindah S, Irawany, Vera, Rayhan, Muhammad, Panigada, Mauro, Pesenti, Antonio, Zanella, Alberto, Grasselli, Giacomo, Colombo, Sebastiano, Martinet, Chiara, Florio, Gaetano, Antonelli, Massimo, Carelli, Simone, Grieco, Domenico L., Asaki, Motohiro, Hoshino, Kota, Salazar, Leonardo, Monsalve, Mary Alejandra Mendoza, Laffey, John, McNicholas, Bairbre, Cosgrave, David, Atif, Minha, Qutishat, Fadi, Laffey, Caoimhe, Van Der Walt, Michaeal, McCaffrey, Joseph, Bone, Allison, Trickey, Jemma, Horton, Michelle, Pearce, Stephanie, Salerno, Tania, Mohamed, Akram, Alhaddad, Salem, Bakeer, Baliad, Haitam, Shames, Shalabi, Laila, Ahmed, Mohammed Abodina, Hakeem, Yusuff, Winearls, James, Tallott, Mandy, Thomson, David, Joubert, Ivan, Arnold-Day, Christel, Piercy, Jenna, Smit, Richard van Zyl, Miller, Malcom, Seymour, Lisa, van Heyningen, Francois, Teyangesikayi, Gilbert, Fredericks, David, Hssain, Ali Ait, Aliudin, Jeffrey, Alqahtani, Al-Reem, Mohamed, Khoulod, Mohamed, Ahmed, Tan, Darwin, Villanueva, Joy, Zaqout, Ahmed, Labib, Ahmed, Kurtzman, Ethan, Ademi, Arben, Dobrita, Ana, Aoudi, Khadija El, Segura, Juliet, Giwangkancana, Gezy, Ohshimo, Shinichiro, Osatnik, Javier, Joosten, Anne, Torres, Antoni, Yang, Minlan, Motos, Ana, Luna, Carlos, Arancibia, Francisco, Williams, Virginie, Noel, Alexandre, Luque, Nestor, Fantini, Marina, García, Ruth Noemi Jorge, Alvarez, Enrique Chicote, Greti, Anna, Ceccato, Adrian, Sanchez, Angel, Vazquez, Ana Loza, Roche-Campo, Ferran, Franch-Llasat, Diego, Tuazon, Divina, Amato, Marcelo, Cassimiro, Luciana, Pola, Flavio, Ribeiro, Francis, Fonseca, Guilherme, Dalton, Heidi, Desai, Mehul, Osborn, Erik, Deeb, Hala, Arcadipane, Antonio, Martucci, Gennaro, Panarello, Giovanna, Vitiello, Stefano, Bianco, Claudia, Occhipinti, Giovanna, Rossetti, Matteo, Cuffaro, Raffaele, Siddig, Nidhal, Cho, Sung-Min, Whitman, Glenn, Sayed, Marwan El, Mokhtar, Walaa, El-Shenawy, Eslam, Shimizu, Hiroaki, Moriyama, Naoki, Kim, Jae-Burm, Kitamura, Nobuya, Gebauer, Johannes, Yokoyama, Toshiki, Al-Fares, Abdulrahman, Buabbas, Sarah, Alamad, Esam, Alawadhi, Fatma, Alawadi, Kalthoum, Khalefa, Mohamed Ahmed, Ajeel, Nourah Ahmad Abdulaziz Al, Aly, Mohammad Fathy, Al-Saleh, Abdullah, Naanouh, Abdullah, Elshourbgy, Alaa Mohammed, Gad, Mohamed Yousef, ElRazaz, Rania Mohamed, Khadadah, Ibrahim, Almumin, Ahmed Mohammed, Altarakma, Hala, Albannay, Hasan, Alsaleh, Mohammed Kh, Radwan, Mahmoud Saad Abdallah, Saadallah, Islam Ahmed, Tanaka, Hiro, Hashimoto, Satoru, Yamazaki, Masaki, Oh, Tak-Hyuck, Epler, Mark, Forney, Cathleen, Kruse, Louise, Feister, Jared, Williamson, Joelle, Grobengieser, Katherine, Gnall, Eric, Golden, Sasha, Caroline, Mara, Shapiro, Timothy, Karaj, Colleen, Thome, Lisa, Sher, Lynn, Vanderland, Mark, Welch, Mary, McDermott, Sherry, Brain, Matthew, Mineall, Sarah, Unwin, Maria, Chen, Lixian, Trezise, Tarnya, McKeon, Laurie, Kimura, Dai, Brazzi, Luca, Sales, Gabriele, Montrucchio, Giorgia, Ogston, Tawnya, Nagpal, Dave, Fischer, Karlee, Lorusso, Roberto, van Bussell, Bas, De Piero, Maria Elena, Mariani, Silvia, Rangappa, Dr Rajavardhan, Shetty, Dr Rajesh Mohan, P, Sujin Rai, Ganesan, Argin, Tharwat, Samar, Esperatti, Mariano, Fuentes, Nora Angélica, Gonzalez, Maria Eugenia, Carton, Edmund G., Sen, Ayan, Palacios, Amanda, Rainey, Deborah, Samoukoviv, Gordan, Campisi, Josie, Durham, Lucia, Neumann, Emily, Seefeldt, Cassandra, Falcucci, Octavio, Emmrich, Amanda, Guy, Jennifer, Johns, Carling, Potzner, Kelly, Zimmermann, Catherine, Espinal, Angelia, Buchtele, Nina, Schwameis, Michael, Korhnfehl, Andrea, Brock, Roman, Staudinger, Thomas, Stecher, Stephanie-Susanne, Barnikel, Michaela, Antón, Sófia, Pawlikowski, Alexandra, Zaaqoq, Akram, Galloway, Lan Anh, Merley, Caitlin, Muftah, Mohamed, Nichol, Alistair, Csete, Marc, Quesada, Luisa, Saba, Isabela, Kasugai, Daisuke, Hiraiwa, Hiroaki, Tanaka, Taku, Marwali, Eva, Purnama, Yoel, Dewayanti, Santi Rahayu, Ardiyan, Juzar, Dafsah Arifa, Siagian, Debby, Chen, Yih-Sharng, Aldhalia, Amer, Ogino, Mark, Nasa, Prashant, Matthew, Christina, Majeed, Nimisha Abdul, Hafez, Wael, Ratsep, Indrek, Post, Andra-Maris, Sillaots, Piret, Krund, Anneli, Lehiste, Merili-Helen, Lepik, Tanel, Manetta, Frank, Mihelis, Effe, Sarmiento, Iam Claire, Narasimhan, Mangala, Varrone, Michael, Komats, Mamoru, Garcia-Diaz, Julia, Harmon, Catherine, Satyapriya, S. Veena, Bhatt, Amar, Mokadam, Nahush A., Uribe, Alberto, Gonzalez, Alicia, Shi, Haixia, McKeown, Johnny, Pasek, Joshua, Fiorda, Juan, Echeverria, Marco, Moreno, Rita, Zakhary, Bishoy, Cavana, Marco, Cucino, Alberto, Foti, Giuseppe, Giani, Marco, Fumagalli, Benedetta, Chiumello, Davide, Castagna, Valentina, Dell'Amore, Andrea, Navalesi, Paolo, Shum, Hoi-Ping, Vuysteke, Alain, Usman, Asad, Acker, Andrew, Smood, Benjamin, Mergler, Blake, Sertic, Federico, Subramanian, Madhu, Sperry, Alexandra, Rizer, Nicolas, Burhan, Erlina, Rasmin, Menaldi, Akmal, Ernita, Sitompul, Faya, Lolong, Navy, Naivedh, Bhat, Erickson, Simon, Barrett, Peter, Dean, David, Daugherty, Julia, Loforte, Antonio, Khan, Irfan, Quraishi, Mohammed Abraar, DeSantis, Olivia, Nasrallah, Ahmad, So, Dominic, Kandamby, Darshana, Mandei, Jose M., Natanael, Hans, YudhaLantang, Eka, Lantang, Anastasia, Wijaya, Surya Oto, Jung, Anna, Ng, George, Ng, Wing Yiu, Ng, Pauline Yeung, Fang, Shu, Tabah, Alexis, Ratcliffe, Megan, Duroux, Maree, Alajeeli, Ahmed, Tarhabat, Ali, Adachi, Shingo, Nakao, Shota, Blanco, Pablo, Prieto, Ana, Sánchez, Jesús, Nicholson, Meghan, Butt, Warwick, Serratore, Alyssa, Delzoppo, Carmel, Janin, Pierre, Yarad, Elizabeth, Totaro, Richard, Coles, Jennifer, Pujo, Bambang, Balk, Robert, Vissing, Andy, Kapania, Esha, Hays, James, Fox, Samuel, Yantosh, Garrett, Mishin, Pavel, Adem, Safia, Yuliarto, Saptadi, Santoso, Kohar Hari, Djajalaksana, Susanthy, Fatoni, Arie Zainul, Fukuda, Masahiro, Liu, Keibun, Pelosi, Paolo, Battaglini, Denise, Robba, Chiara, Jiménez, Juan Fernando Masa, Bastos, Diego, Gaião, Sérgio, Rusmawatiningtyas, Desy, Cho, Young-Jae, Lee, Su Hwan, Kawasaki, Tatsuya, Munshi, Laveena, Sakiyalak, Pranya, Nitayavardhana, Prompak, Elagili, Mohamed Bashir, Salem, Talat Ahmed Abu, Seitz, Tamara, Arora, Rakesh, Kent, David, Marino, Daniel, Parwar, Swapnil, Cheng, Andrew, Miller, Jennene, Fujitani, Shigeki, Shimizu, Naoki, Madhok, Jai, Owyang, Clark, Buscher, Hergen, Reynolds, Claire, Abdurraouf, Abusalama, Kredan, Ali Abdulnasir, Haddud, Abdurrahman, Moharam, Saad, Maasikas, Olavi, Beljantsev, Aleksan, Mihnovits, Vladislav, Akimoto, Takako, Aizawa, Mariko, Horibe, Kanako, Onodera, Ryota, Hodgson, Carol, Burrell, Aidan, Young, Meredith, George, Timothy, Shekar, Kiran, McGuinness, Niki, Irvine, Lacey, Flynn, Brigid, Almjersah, Abdulrahman, Bakri, Ashraf, Endo, Tomoyuki, Sugiyama, Kazuhiro, Shimizu, Keiki, Fan, Eddy, Exconde, Kathleen, Ichiba, Shingo, Binnawara, Muhannud, Embarek, Hussein, Lussier, Leslie, Lotz, Gösta, Malfertheiner, Maximilian, Maier, Lars, Dreier, Esther, Kusumastuti, Neurinda Permata, McCloskey, Colin, Dabaliz, Al-Awwab, Elshazly, Tarek B, Smith, Josiah, Szuldrzynski, Konstanty S., Bielański, Piotr, Wille, Keith, Murthy, Srinivas, Parhar, Ken Kuljit S., Fiest, Kirsten M., Codan, Cassidy, Shahid, Anmol, Fayed, Mohamed, Evans, Timothy, Garcia, Rebekah, Gutierrez, Ashley, Song, Tae, Rose, Rebecca, Bennett, Suzanne, Richardson, Denise, Peek, Giles, Arora, Lovkesh, Rappapport, Kristina, Rudolph, Kristina, Sibenaller, Zita, Stout, Lori, Walter, Alicia, Herr, Daniel, Vedadi, Nazli, Bartlett, Robert, Thompson, Shaun, Hoffman, Julie, Ying, Xiaonan, Williams, Bailey, Sanchez, Emely, Akwani, Chika, Kennedy, Ryan, Elhadi, Muhammed, Griffee, Matthew, Mone, Mary, Ciullo, Anna, Kida, Yuri, Roca, Ricard Ferrer, Riera, JordI, Contreras, Sofia, Alegre, Cynthia, Kay, Christy, Fischer, Irene, Renner, Elizabeth, Taniguci, Hayato, Lee, James, Plotkin, Daniel, Citarella, Barbara Wanjiru, Merson, Laura, Hartley, Emma, Lubis, Bastian, Ikeyama, Takanari, Mortada, Alshaymaa, Alhamad, Ameen, Mechi, Ahmed, Nadar, Islam Mohsen Ali Mohamed Hassan, Alyasiri, Mohammed Saleh, Elsaid, Muhammed Zainab Alghali, Bhaskar, Balu, Jung, Jae-Seung, McGuinness, Shay, Eastwood, Glenn, Marta, Sandra Rossi, Guarracino, Fabio, Gerle, Stacy, Coxon, Emily, Claro, Bruno, Aldressi, Wafa, Eleisawy, Mahmoud, Osama, Hasnaa, Loverde, Daniel, Patil, Namrata, Parrini, Vieri, McBride, Angela, Negaard, Kathryn, Ratsch, Angela, Abdelaziz, Ahmad, Uribe, Juan David, Peris, Adriano, Sanders, Mark, Emerson, Dominic, Kamal, Muhammad, Faida, Hamza, Povoa, Pedro, Francis, Roland, Cherif, Ali, Joseph, Sunimol, Nardo, Matteo Di, Heard, Micheal, Kyle, Kimberly, Blackwell, Ray A, OUYAHIA, Amel, Biston, Patrick, Jeong, Hye Won, Smith, Reanna, Prawira, Yogi, Garcia, Arturo Huerta, Salterain, Nahikari, Meyns, Bart, Elnasser, Muhammed, Moreno, Marsha, Walia, Rajat, Mehta, Amit, Schweda, Annette, Williams, Melissa, Amkhatirah, Emad, Kim, Kyung Hoon, Assad, Alexandra, Giraldo, Estefania, Karolak, Wojtek, Balik, Martin, Pocock, Elizabeth, Gajkowski, Evan, Bedair, Mohamed, Masafumi, Kanamoto, Barrett, Nicholas, Takeyama, Yoshihiro, Park, Sunghoon, Amin, Faizan, Andriyani, Fina Meilyana, Sudakevych, Serhii, Schnur, Janos, Vera, Magdalena, Cornejo, Rodrigo, Schwarz, Patrícia, Mardini, Ana Carolina, de Paula, Thais, Neto, Ary Serpa, Villoldo, Andrea, Colafranceschi, Alexandre Siciliano, Iglesias, Alejandro Ubeda, Granjean, Juan, Melro, Lívia Maria Garcia, Romualdo, Giovana Fioravante, Gaia, Diego, Souza, Helmgton, Galas, Filomena, Mendiluce, Rafael Máñez, Sosa, Alejandra, Martinez, Ignacio, Kurosawa, Hiroshi, Almoshantaf, Mohammad Badr, Salgado, Juan, Hugi-Mayr, Beate, Charbonneau, Eric, Barzilai, Vitor Salvatore, Monteiro, Veronica, de Souza, Rodrigo Ribeiro, Harper, Michael, Suzuki, Hiroyuki, Adams, Celina, Brieva, Jorge, Khamees, Almu'atasim, Graige, Fadi, Supriatna, Moh, Nyale, George, Eltatar, Faisal Saleem, Fatani, Jihan, Baeissa, Husam, Masri, Ayman AL, Rabie, Ahmed, Hui, Mok Yee, Yamane, Masahiro, Jung, Hanna, Margaret, Ayorinde Mojisola, Nacpil, Newell, Ruck, Katja, Bakken, Rhonda, Jara, Claire, Felton, Tim, Berra, Lorenzo, Shah, Bobby, Chakraborty, Arpan, Cardona, Monika, Capatos, Gerry, Akkanti, Bindu, Orija, Abiodun, Jain, Harsh, Ito, Asami, Housni, Brahim, Low, Sennen, Iihara, Koji, Chavez, Joselito, Ramanathan, Kollengode, Zabert, Gustavo, Naidoo, Krubin, Seppelt, Ian, VanDyk, Marlice, MacDonald, Sarah, McGregor, Randy, Siebenaler, Teka, Flynn, Hannah, Lofton, Kristi, Aokage, Toshiyuki, Kvirkvelia, Bakar, Shigemitsu, Kazuaki, Moscatelli, Andrea, Fiorentino, Giuseppe, Baumgaertel, Matthias, Mba, Serge Eddy, Assy, Jana, Hutahaean, Amelya, Roush, Holly, Sichting, Kay A, Alessandri, Francesco, Burns, Debra, Alkhubouli, Taha Husayn, Salt, Gavin, Garabedian, Carl P., Millar, Jonathan, Sim, Malcolm, Mattke, Adrian, McAuley, Danny, Tadili, Jawad, Frenzel, Tim, Abuleil, Amro, Bar-Lavie, Yaron, Ortiz, Aaron Blandino, Stone, Jackie, Attokaran, Antony, Farquharson, Michael, Patel, Brij, Gunning, Derek, Baillie, Kenneth, Watson, Pia, Tamai, Kenji, Saaid, Ayoub, Anania, Pasquale, Sajinadiyasa, Gede Ketut, Kanyawati, Dyah, Salgado, Marcello, Sassine, Assad, Yudo, Bhirowo, McCaul, Scott, Lee, Bongjin, Lee, Sang Min, Afek, Arnon, Fattouh, Shimaa E, Iwashita, Yoshiaki, Fadlalmola, Hammad, Semedi, Bambang Pujo, Mansour, Noureldin Mohamed, Metiva, Jack, Van Belle, Nicole, Martin-Loeches, Ignacio, Al-Sadawi, Dr Mohammed, Kirakli, Cenk, Shimaa, Al-Touny, Ivatt, Lenny, Woon, Chia Yew, Kang, Hyun Mi, Smith, Timothy, James, Erskine, Al-Rawas, Nawar, Iwasaki, Yudai, Ashour, Hamza, King-Chung, Kenny Chan, Gudzenko, Vadim, Taccone, Fabio, Perdhana, Fajar, Lamarche, Yoan, Ribeiro, Joao Miguel, Bradic, Nikola, Van den Bossche, Klaartje, Lansink, Oude, Singh, Gurmeet, Debeuckelaere, Gerdy, Stelfox, Henry T., Yi, Cassia, Elia, Jennifer, Tribble, Thomas, Shankar, Shyam, Padmanabhan, Raj, Hallinan, Bill, Paoletti, Luca, Leyva, Yolanda, Fykuda, Tatuma, Badulak, Jenelle, Koch, Jillian, Janowaik, Lisa, Hackman, Amy, Hernandez, Deb, Osofsky, Jennifer, Donadello, Katia, Lawang, Aizah, Fine, Josh, Davidson, Benjamin, Vazquez, Andres Oswaldo Razo, Abdehaleem, Ibrahim, Kelly, Thu-Lan, Fanning, Jonathon, Premraj, Lavienraj, Porto, Diego Bastos, White, Nicole M., Bassi, Gianluigi Li, Suen, Jacky, and Fraser, John F.

Published
2024
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9. 8 healthcare trends for 2024: A guide for health system leaders and their boards: Healthcare providers faced many transformational challenges in 2023, including the continued advancement of payers into the provider space and the challenge of managing merger and acquisition activity

Author

Marino, Daniel J.

Subjects
Acquisitions and mergers
Abstract

As health systems progress through 2024, they will require effective governance to successfully navigate the rising headwinds. As they plan and execute initiatives, their leaders and boards should remain informed [...]

Published
2024

10. Physics Enhanced Data-Driven Models with Variational Gaussian Processes

Author

Marino, Daniel L. and Manic, Milos

Subjects
Computer Science - Machine Learning, Computer Science - Robotics, Physics - Computational Physics, Statistics - Machine Learning
Abstract

Centuries of development in natural sciences and mathematical modeling provide valuable domain expert knowledge that has yet to be explored for the development of machine learning models. When modeling complex physical systems, both domain knowledge and data provide necessary information about the system. In this paper, we present a data-driven model that takes advantage of partial domain knowledge in order to improve generalization and interpretability. The presented approach, which we call EVGP (Explicit Variational GaussianProcess), has the following advantages: 1) using available domain knowledge to improve the assumptions(inductive bias) of the model, 2) scalability to large datasets, 3) improved interpretability. We show how the EVGP model can be used to learn system dynamics using basic Newtonian mechanics as prior knowledge. We demonstrate how the addition of prior domain-knowledge to data-driven models outperforms purely data-driven models.

Published
2019

11. An Adversarial Approach for Explainable AI in Intrusion Detection Systems

Author

Marino, Daniel L., Wickramasinghe, Chathurika S., and Manic, Milos

Subjects
Computer Science - Machine Learning, Computer Science - Cryptography and Security, Statistics - Machine Learning
Abstract

Despite the growing popularity of modern machine learning techniques (e.g. Deep Neural Networks) in cyber-security applications, most of these models are perceived as a black-box for the user. Adversarial machine learning offers an approach to increase our understanding of these models. In this paper we present an approach to generate explanations for incorrect classifications made by data-driven Intrusion Detection Systems (IDSs). An adversarial approach is used to find the minimum modifications (of the input features) required to correctly classify a given set of misclassified samples. The magnitude of such modifications is used to visualize the most relevant features that explain the reason for the misclassification. The presented methodology generated satisfactory explanations that describe the reasoning behind the mis-classifications, with descriptions that match expert knowledge. The advantages of the presented methodology are: 1) applicable to any classifier with defined gradients. 2) does not require any modification of the classifier model. 3) can be extended to perform further diagnosis (e.g. vulnerability assessment) and gain further understanding of the system. Experimental evaluation was conducted on the NSL-KDD99 benchmark dataset using Linear and Multilayer perceptron classifiers. The results are shown using intuitive visualizations in order to improve the interpretability of the results.

Published
2018

13. Predictive Factors of Inactive Patient Participation in an Inflammatory Bowel Disease Learning Health System: A Longitudinal Cohort Study

Author

Dang, Nhu, primary, Kumar, Soryan, additional, Kwon, Michelle, additional, Cradeur, Michael, additional, Zeven, Katherine, additional, Khunte, Mihir, additional, Marino, Daniel, additional, Tse, Chung Sang, additional, van Deen, Welmoed K, additional, Lee, Adrian, additional, Kamp, Kendra, additional, Oberai, Ridhima, additional, Melmed, Gil Y, additional, Siegel, Corey A, additional, Weaver, S Alandra, additional, and Shah, Samir A, additional

Published
2024
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15. Hemorrhage, Disseminated Intravascular Coagulopathy, and Thrombosis Complications Among Critically Ill Patients with COVID-19: An International COVID-19 Critical Care Consortium Study

Author

Fanning, Jonathon P., Weaver, Natasha, Fanning, Robert B., Griffee, Matthew J., Cho, Sung-Min, Panigada, Mauro, Obonyo, Nchafatso G., Zaaqoq, Akram M., Rando, Hannah, Chia, Yew Woon, Fan, Bingwen Eugene, Sela, Declan, Chiumello, Davide, Coppola, Silvia, Labib, Ahmed, Whitman, Glenn J. R., Arora, Rakesh C., Kim, Bo S., Motos, Anna, Torres, Antoni, Barbé, Ferran, Grasselli, Giacomo, Zanella, Alberto, Etchill, Eric, Usman, Asad Ali, Feth, Maximilian, White, Nicole M., Suen, Jacky Y., Li Bassi, Gianluigi, Peek, Giles J., Fraser, John F., Dalton, Heidi, Al-Dabbous, Tala, Alfoudri, Huda, Shamsah, Mohammed, Elapavaluru, Subbarao, Berg, Ashley, Horn, Christina, Mayasi, Yunis, Schroll, Stephan, Meyer, Dan, Velazco, Jorge, Ploskanych, Ludmyla, Fikes, Wanda, Bagewadi, Rohini, Dao, Marvin, White, Haley, Berrios Laviena, Alondra, Ehlers, Ashley, Shalabi-McGuire, Maysoon, Witt, Trent, Grazioli, Lorenzo, Lorini, Luca, Wilson Grandin, E., Nunez, Jose, Reyes, Tiago, O’Briain, Diarmuid, Hunter, Stephanie, Ramanan, Mahesh, Affleck, Julia, Hurkadli Veerendra, Hemanth, Rai, Sumeet, Russell-Brown, Josie, Nourse, Mary, Joseph, Mark, Mitchell, Brook, Tenzer, Martha, Abe, Ryuzo, Jin Cho, Hwa, Seok Jeong, In, Rahman, Nadeem, Kakar, Vivek, Brozzi, Nicolas, Mehkri, Omar, Krishnan, Sudhir, Duggal, Abhijit, Houltham, Stuart, Graf, Jerónimo, Diaz, Roderigo, Orrego, Roderigo, Delgado, Camila, González, Joyce, Soledad Sanchez, Maria, Piagnerelli, Michael, Valenzuela Sarrazin, Josefa, Zabert, Gustavo, Espinosa, Lucio, Delgado, Paulo, Delgado, Victoria, Rincón, Diego Fernando Bautista, Yanten, Angela Maria Marulanda, Bustamante Duque, Melissa, Brodie, Daniel, Elhazmi, Alyaa, Al-Hudaib, Abdullah, Callahan, Maria, Azhari Taufik, M., Yasmin Wardoyo, Elizabeth, Gunawan, Margaretha, Trisnaningrum, Nurindah S, Irawany, Vera, Rayhan, Muhammad, Panigada, Mauro, Pesenti, Antonio, Zanella, Alberto, Grasselli, Giacomo, Colombo, Sebastiano, Martinet, Chiara, Florio, Gaetano, Antonelli, Massimo, Carelli, Simone, Grieco, Domenico L., Asaki, Motohiro, Hoshino, Kota, Salazar, Leonardo, Monsalve, Mary Alejandra Mendoza, Laffey, John, McNicholas, Bairbre, Cosgrave, David, McCaffrey, Joseph, Bone, Allison, Hakeem, Yusuff, Winearls, James, Tallott, Mandy, Thomson, David, Arnold-Day, Christel, Cupido, Jerome, Fanie, Zainap, Miller, Malcom, Seymore, Lisa, van Straaten, Dawid, Ait Hssain, Ali, Aliudin, Jeffrey, Alqahtani, Al-Reem, Mohamed, Khoulod, Mohamed, Ahmed, Tan, Darwin, Villanueva, Joy, Zaqout, Ahmed, Kurtzman, Ethan, Ademi, Arben, Dobrita, Ana, El Aoudi, Khadija, Segura, Juliet, Giwangkancana, Gezy, Ohshimo, Shinichiro, Osatnik, Javier, Joosten, Anne, Torres, Antoni, Yang, Minlan, Motos, Ana, Luna, Carlos, Arancibia, Francisco, Williams, Virginie, Noel, Alexandre, Luque, Nestor, Fantini, Marina, García, Ruth Noemi Jorge, Chicote Alvarez, Enrique, Greti, Anna, Ceccato, Adrian, Sanchez, Angel, Loza Vazquez, Ana, Roche-Campo, Ferran, Franch-Llasat, Diego, Tuazon, Divina, Amato, Marcelo, Cassimiro, Luciana, Pola, Flavio, Ribeiro, Francis, Fonseca, Guilherme, Dalton, Heidi, Desai, Mehul, Osborn, Erik, Deeb, Hala, Arcadipane, Antonio, Martucci, Gennaro, Panarello, Giovanna, Vitiello, Chiara, Bianco, Claudia, Occhipinti, Giovanna, Rossetti, Matteo, Cuffaro, Raffaele, Cho, Sung-Min, Whitman, Glenn, Shimizu, Hiroaki, Moriyama, Naoki, Kim, Jae-Burm, Kitamura, Nobuya, Gebauer, Johannes, Yokoyama, Toshiki, Al-Fares, Abdulrahman, Buabbas, Sarah, Alamad, Esam, Alawadhi, Fatma, Alawadi, Kalthoum, Tanaka, Hiro, Hashimoto, Satoru, Yamazaki, Masaki, Oh, Tak-Hyuck, Epler, Mark, Forney, Cathleen, Kruse, Louise, Feister, Jared, Williamson, Joelle, Grobengieser, Katherine, Gnall, Eric, Golden, Sasha, Caroline, Mara, Shapiro, Timothy, Karaj, Colleen, Thome, Lisa, Sher, Lynn, Vanderland, Mark, Welch, Mary, McDermott, Sherry, Brain, Matthew, Mineall, Sarah, Kimura, Dai, Brazzi, Luca, Sales, Gabriele, Montrucchio, Giorgia, Ogston, Tawnya, Nagpal, Dave, Fischer, Karlee, Lorusso, Roberto, Rangappa, Rajavardhan, Rai, Sujin, Appu, Argin, Esperatti, Mariano, Angélica Fuentes, Nora, Eugenia Gonzalez, Maria, O’Briain, Diarmuid, Carton, Edmund G., Sen, Ayan, Palacios, Amanda, Rainey, Deborah, Samoukoviv, Gordan, Campisi, Josie, Durham, Lucia, Neumann, Emily, Seefeldt, Cassandra, Falcucci, Octavio, Emmrich, Amanda, Guy, Jennifer, Johns, Carling, Potzner, Kelly, Zimmermann, Catherine, Espinal, Angelia, Buchtele, Nina, Schwameis, Michael, Korhnfehl, Andrea, Brock, Roman, Staudinger, Thomas, Stecher, Stephanie-Susanne, Barnikel, Michaela, Antón, Sófia, Pawlikowski, Alexandra, Zaaqoq, Akram, Anh Galloway, Lan, Merley, Caitlin, Nichol, Alistair, Csete, Marc, Quesada, Luisa, Saba, Isabela, Kasugai, Daisuke, Hiraiwa, Hiroaki, Tanaka, Taku, Marwali, Eva, Purnama, Yoel, Rahayu Dewayanti, Santi, Ardiyan, Arifa Juzar, Dafsah, Siagian, Debby, Chen, Yih-Sharng, Ogino, Mark, Ratsep, Indrek, Post, Andra-Maris, Sillaots, Piret, Krund, Anneli, Lehiste, Merili-Helen, Lepik, Tanel, Manetta, Frank, Mihelis, Effe, Claire Sarmiento, Iam, Narasimhan, Mangala, Varrone, Michael, Komats, Mamoru, Garcia-Diaz, Julia, Harmon, Catherine, Veena Satyapriya, S., Bhatt, Amar, Mokadam, Nahush A., Uribe, Alberto, Gonzalez, Alicia, Shi, Haixia, McKeown, Johnny, Pasek, Joshua, Fiorda, Juan, Echeverria, Marco, Moreno, Rita, Zakhary, Bishoy, Cavana, Marco, Cucino, Alberto, Foti, Giuseppe, Giani, Marco, Fumagalli, Benedetta, Chiumello, Davide, Castagna, Valentina, Dell’Amore, Andrea, Navalesi, Paolo, Shum, Hoi-Ping, Vuysteke, Alain, Usman, Asad, Acker, Andrew, Smood, Benjamin, Mergler, Blake, Sertic, Federico, Subramanian, Madhu, Sperry, Alexandra, Rizer, Nicolas, Burhan, Erlina, Rasmin, Menaldi, Akmal, Ernita, Sitompul, Faya, Lolong, Navy, Naivedh, Bhat, Erickson, Simon, Barrett, Peter, Dean, David, Daugherty, Julia, Loforte, Antonio, Khan, Irfan, Abraar Quraishi, Mohammed, DeSantis, Olivia, So, Dominic, Kandamby, Darshana, Mandei, Jose M., Natanael, Hans, YudhaLantang, Eka, Lantang, Anastasia, Oto Wijaya, Surya, Jung, Anna, Ng, George, Yiu Ng, Wing, Yeung Ng, Pauline, Fang, Shu, Tabah, Alexis, Ratcliffe, Megan, Duroux, Maree, Adachi, Shingo, Nakao, Shota, Blanco, Pablo, Prieto, Ana, Sánchez, Jesús, Nicholson, Meghan, Butt, Warwick, Serratore, Alyssa, Delzoppo, Carmel, Janin, Pierre, Yarad, Elizabeth, Totaro, Richard, Coles, Jennifer, Pujo, Bambang, Balk, Robert, Vissing, Andy, Kapania, Esha, Hays, James, Fox, Samuel, Yantosh, Garrett, Mishin, Pavel, Yuliarto, Saptadi, Hari Santoso, Kohar, Djajalaksana, Susanthy, Zainul Fatoni, Arie, Fukuda, Masahiro, Liu, Keibun, Pelosi, Paolo, Battaglini, Denise, Masa Jiménez, Juan Fernando, Bastos, Diego, Gaião, Sérgio, Rusmawatiningtyas, Desy, Cho, Young-Jae, Hwan Lee, Su, Kawasaki, Tatsuya, Munshi, Laveena, Sakiyalak, Pranya, Nitayavardhana, Prompak, Seitz, Tamara, Arora, Rakesh, Kent, David, Marino, Daniel, Parwar, Swapnil, Cheng, Andrew, Miller, Jennene, Fujitani, Shigeki, Shimizu, Naoki, Madhok, Jai, Owyang, Clark, Buscher, Hergen, Reynolds, Claire, Maasikas, Olavi, Beljantsev, Aleksan, Mihnovits, Vladislav, Akimoto, Takako, Aizawa, Mariko, Horibe, Kanako, Onodera, Ryota, Hodgson, Carol, Burrell, Aidan, Young, Meredith, George, Timothy, Shekar, Kiran, McGuinness, Niki, Irvine, Lacey, Flynn, Brigid, Endo, Tomoyuki, Sugiyama, Kazuhiro, Shimizu, Keiki, Fan, Eddy, Exconde, Kathleen, Ichiba, Shingo, Lussier, Leslie, Lotz, Gösta, Malfertheiner, Maximilian, Maier, Lars, Dreier, Esther, Permata Kusumastuti, Neurinda, McCloskey, Colin, Dabaliz, Al-Awwab, Elshazly, Tarek B, Smith, Josiah, Szuldrzynski, Konstanty S., Bielański, Piotr, Hakeem, Yusuff, Wille, Keith, Murthy, Srinivas, Parhar, Ken Kuljit S., Fiest, Kirsten M., Codan, Cassidy, Shahid, Anmol, Fayed, Mohamed, Evans, Timothy, Garcia, Rebekah, Gutierrez, Ashley, Shimizu, Hiroaki, Song, Tae, Rose, Rebecca, Bennett, Suzanne, Richardson, Denise, Peek, Giles, Arora, Lovkesh, Rappapport, Kristina, Rudolph, Kristina, Sibenaller, Zita, Stout, Lori, Walter, Alicia, Herr, Daniel, Vedadi, Nazli, Bartlett, Robert, Pesenti, Antonio, Thompson, Shaun, Hoffman, Julie, Ying, Xiaonan, Kennedy, Ryan, Elhadi, Muhammed, Griffee, Matthew, Ciullo, Anna, Kida, Yuri, Ferrer Roca, Ricard, Riera, JordI, Contreras, Sofia, Alegre, Cynthia, Kay, Christy, Fischer, Irene, Renner, Elizabeth, Taniguci, Hayato, Fraser, John, Li Bassi, Gianluigi, Suen, Jacky, Barnett, Adrian, White, Nicole, Gibbons, Kristen, Forsyth, Simon, Corley, Amanda, Pearse, India, Hinton, Samuel, Abbate, Gabriella, Hassan, Halah, Heinsar, Silver, Karnik, Varun A, Ki, Katrina, O’Neill, Hollier F., Obonyo, Nchafatso, Pretti Pimenta, Leticia, Reid, Janice D., Sato, Kei, Shekar, Kiran, Vuorinen, Aapeli, Wildi, Karin S., Wilson, Emily S., Yerkovich, Stephanie, Lee, James, Plotkin, Daniel, Wanjiru Citarella, Barbara, Merson, Laura, Hartley, Emma, Lubis, Bastian, Ikeyama, Takanari, Bhaskar, Balu, Jung, Jae-Seung, McGuinness, Shay, Eastwood, Glenn, Rossi Marta, Sandra, Guarracino, Fabio, Gerle, Stacy, Coxon, Emily, Claro, Bruno, Loverde, Daniel, Patil, Namrata, Parrini, Vieri, McBride, Angela, Negaard, Kathryn, Ratsch, Angela, Abdelaziz, Ahmad, David Uribe, Juan, Peris, Adriano, Sanders, Mark, Emerson, Dominic, Kamal, Muhammad, Povoa, Pedro, Francis, Roland, Cherif, Ali, Joseph, Sunimol, Di Nardo, Matteo, Heard, Micheal, Kyle, Kimberly, Blackwell, Ray A, Piagnerelli, Michael, Biston, Patrick, Won Jeong, Hye, Smith, Reanna, Prawira, Yogi, Montrucchio, Giorgia, Huerta Garcia, Arturo, Salterain, Nahikari, Meyns, Bart, Moreno, Marsha, Walia, Rajat, Mehta, Amit, Schweda, Annette, Supriatna, Moh, Kirakli, Cenk, Williams, Melissa, Hoon Kim, Kyung, Assad, Alexandra, Giraldo, Estefania, Karolak, Wojtek, Balik, Martin, Pocock, Elizabeth, Gajkowski, Evan, Masafumi, Kanamoto, Barrett, Nicholas, Takeyama, Yoshihiro, Park, Sunghoon, Amin, Faizan, Meilyana Andriyani, Fina, Sudakevych, Serhii, Ratsch, Angela, Vera, Magdalena, Cornejo, Rodrigo, Schwarz, Patrícia, Carolina Mardini, Ana, de Paula, Thais, Serpa Neto, Ary, Villoldo, Andrea, Siciliano Colafranceschi, Alexandre, Ubeda Iglesias, Alejandro, Granjean, Juan, Melro, Lívia Maria Garcia, Fioravante Romualdo, Giovana, Gaia, Diego, Souza, Helmgton, Galas, Filomena, Máñez Mendiluce, Rafael, Sosa, Alejandra, Martinez, Ignacio, Kurosawa, Hiroshi, Salgado, Juan, Hugi-Mayr, Beate, Charbonneau, Eric, Salvatore Barzilai, Vitor, Monteiro, Veronica, Ribeiro de Souza, Rodrigo, Harper, Michael, Suzuki, Hiroyuki, Adams, Celina, Brieva, Jorge, Nyale, George, Saleem Eltatar, Faisal, Fatani, Jihan, Baeissa, Husam, Masri, Ayman AL, Rabie, Ahmed, Yee Hui, Mok, Yamane, Masahiro, Jung, Hanna, Mojisola Margaret, Ayorinde, Nacpil, Newell, Ruck, Katja, Bakken, Rhonda, Jara, Claire, Felton, Tim, Berra, Lorenzo, Shah, Bobby, Chakraborty, Arpan, Cardona, Monika, Capatos, Gerry, Akkanti, Bindu, Orija, Abiodun, Jain, Harsh, Ito, Asami, Housni, Brahim, Low, Sennen, Iihara, Koji, Chavez, Joselito, Ramanathan, Kollengode, Zabert, Gustavo, Naidoo, Krubin, Seppelt, Ian, VanDyk, Marlice, MacDonald, Sarah, Ichiba, Shingo, McGregor, Randy, Siebenaler, Teka, Flynn, Hannah, Lofton, Kristi, Aokage, Toshiyuki, Shigemitsu, Kazuaki, Moscatelli, Andrea, Fiorentino, Giuseppe, Baumgaertel, Matthias, Eddy, Serge, Assy, Jana, Hutahaean, Amelya, Roush, Holly, Sichting, Kay A, Alessandri, Francesco, Burns, Debra, Rabie, Ahmed, Salt, Gavin, Garabedian, Carl P., Millar, Jonathan, Sim, Malcolm, Mattke, Adrian, McAuley, Danny, Tadili, Jawad, Frenzel, Tim, Bar-Lavie, Yaron, Blandino Ortiz, Aaron, Stone, Jackie, Tabah, Alexis, Attokaran, Antony, Farquharson, Michael, Patel, Brij, Gunning, Derek, Baillie, Kenneth, Watson, Pia, Tamai, Kenji, Ketut Sajinadiyasa, Gede, Kanyawati, Dyah, Salgado, Marcello, Sassine, Assad, Yudo, Bhirowo, McCaul, Scott, Lee, Bongjin, Min Lee, Sang, Afek, Arnon, Iwashita, Yoshiaki, Pujo Semedi, Bambang, Permata Kusumastuti, Neurinda, Metiva, Jack, Van Belle, Nicole, Martin-Loeches, Ignacio, Ivatt, Lenny, Yew Woon, Chia, Mi Kang, Hyun, Smith, Timothy, James, Erskine, Al-Rawas, Nawar, Iwasaki, Yudai, Chan King-Chung, Kenny, Gudzenko, Vadim, Hugi-Mayr, Beate, Taccone, Fabio, Perdhana, Fajar, Lamarche, Yoan, Miguel Ribeiro, Joao, Bradic, Nikola, Van den Bossche, Klaartje, Lansink, Oude, Singh, Gurmeet, Debeuckelaere, Gerdy, Stelfox, Henry T., Yi, Cassia, Elia, Jennifer, Tribble, Thomas, Shankar, Shyam, Padmanabhan, Raj, Hallinan, Bill, Paoletti, Luca, Leyva, Yolanda, Fykuda, Tatuma, Badulak, Jenelle, Koch, Jillian, Hackman, Amy, Janowaik, Lisa, Hernandez, Deb, Osofsky, Jennifer, Donadello, Katia, Lawang, Aizah, Fine, Josh, Davidson, Benjamin, and Vazquez, Andres Oswaldo Razo

Published
2023
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18. Building Energy Load Forecasting using Deep Neural Networks

Author

Marino, Daniel L., Amarasinghe, Kasun, and Manic, Milos

Subjects
Computer Science - Neural and Evolutionary Computing
Abstract

Ensuring sustainability demands more efficient energy management with minimized energy wastage. Therefore, the power grid of the future should provide an unprecedented level of flexibility in energy management. To that end, intelligent decision making requires accurate predictions of future energy demand/load, both at aggregate and individual site level. Thus, energy load forecasting have received increased attention in the recent past, however has proven to be a difficult problem. This paper presents a novel energy load forecasting methodology based on Deep Neural Networks, specifically Long Short Term Memory (LSTM) algorithms. The presented work investigates two variants of the LSTM: 1) standard LSTM and 2) LSTM-based Sequence to Sequence (S2S) architecture. Both methods were implemented on a benchmark data set of electricity consumption data from one residential customer. Both architectures where trained and tested on one hour and one-minute time-step resolution datasets. Experimental results showed that the standard LSTM failed at one-minute resolution data while performing well in one-hour resolution data. It was shown that S2S architecture performed well on both datasets. Further, it was shown that the presented methods produced comparable results with the other deep learning methods for energy forecasting in literature.

Published
2016
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19. Fast Trajectory Simplification Algorithm for Natural User Interfaces in Robot Programming by Demonstration

Author

Marino, Daniel L. and Manic, Milos

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Trajectory simplification is a problem encountered in areas like Robot programming by demonstration, CAD/CAM, computer vision, and in GPS-based applications like traffic analysis. This problem entails reduction of the points in a given trajectory while keeping the relevant points which preserve important information. The benefits include storage reduction, computational expense, while making data more manageable. Common techniques formulate a minimization problem to be solved, where the solution is found iteratively under some error metric, which causes the algorithms to work in super-linear time. We present an algorithm called FastSTray, which selects the relevant points in the trajectory in linear time by following an open loop heuristic approach. While most current trajectory simplification algorithms are tailored for GPS trajectories, our approach focuses on smooth trajectories for robot programming by demonstration recorded using motion capture systems.Two variations of the algorithm are presented: 1. aims to preserve shape and temporal information; 2. preserves only shape information. Using the points in the simplified trajectory we use cubic splines to interpolate between these points and recreate the original trajectory. The presented algorithm was tested on trajectories recorded from a hand-tracking system. It was able to eliminate about 90% of the points in the original trajectories while maintaining errors between 0.78-2cm which corresponds to 1%-2.4% relative error with respect to the bounding box of the trajectories.

Published
2016

20. Root phosphoenolpyruvate carboxylase activity is essential for Sorghum bicolor tolerance to ammonium nutrition

Author

Universidad de Sevilla. Departamento de Biología Vegetal y Ecología, Gobierno Vasco, Junta de Andalucía, European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER), Ministerio de Ciencia e Innovación (MICIN). España, Agencia Estatal de Investigación. España, Marín Peña, A. J., Vega Mas, Izargi, Busturia, I., Osa Fernández, Clara de la, González Moro, María Begoña, Monreal Hermoso, José Antonio, Marino, Daniel, Universidad de Sevilla. Departamento de Biología Vegetal y Ecología, Gobierno Vasco, Junta de Andalucía, European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER), Ministerio de Ciencia e Innovación (MICIN). España, Agencia Estatal de Investigación. España, Marín Peña, A. J., Vega Mas, Izargi, Busturia, I., Osa Fernández, Clara de la, González Moro, María Begoña, Monreal Hermoso, José Antonio, and Marino, Daniel

Abstract

Phosphoenolpyruvate carboxylase (PEPC; EC 4.1.1.31) is an enzyme family with pivotal roles in plant carbon and nitrogen metabolism. A main role for non-photosynthetic PEPC is as anaplerotic enzyme to load tricarboxylic acid (TCA) cycle with carbon skeletons that compensate the intermediates diverted for biomolecule synthesis such as amino acids. When plants are grown under ammonium (NH4 +) nutrition, the excessive uptake of NH4 + often provokes a stress situation. When plants face NH4 + stress, N assimilation is greatly induced and thus, requires the supply of carbon skeletons coming from TCA cycle. In this work, we addressed the importance of root PEPC and TCA cycle for sorghum (Sorghum bicolor L. Moench), a C4 cereal crop, grown under ammonium nutrition. To do so, we used RNAi sorghum lines that display a decrease expression of SbPPC3 (Ppc3 lines), the main root PEPC isoform, and reduced root PEPC activity. SbPPC3 silencing provoked ammonium hypersensitivity, meaning lower biomass accumulation in Ppc3 respect to WT plants when growing under ammonium nutrition. The silenced plants presented a deregulation of primary metabolism as highlighted by the accumulation of NH4 + in the root and the alteration of normal TCA functioning, which was evidenced by the accumulation of organic acids in the root under ammonium nutrition. Altogether, our work evidences the importance of non-photosynthetic PEPC, and root TCA cycle, in sorghum to deal with high external NH4 + availability.

Published
2024

22. DRF x : An Understandable, High Performance, and Flexible Memory Model for Concurrent Languages

Author

Marino, Daniel, Singh, Abhayendra, Millstein, Todd, Musuvathi, Madanlal, and Narayanasamy, Satish

Subjects
Sequential consistency, memory models, DRFx, Computer Software, Information Systems, Software Engineering
Abstract

The most intuitive memory model for shared-memory multi-threaded programming is sequential consistency (SC), but it disallows the use of many compiler and hardware optimizations and thus affects performance. Data-race-free (DRF) models, such as the C++11 memory model, guarantee SC execution for data-race-free programs. But these models provide no guarantee at all for racy programs, compromising the safety and debuggability of such programs. To address the safety issue, the Java memory model, which is also based on the DRF model, provides a weak semantics for racy executions. However, this semantics is subtle and complex, making it difficult for programmers to reason about their programs and for compiler writers to ensure the correctness of compiler optimizations. We present the drf x memory model, which is simple for programmers to understand and use while still supporting many common optimizations. We introduce a memory model (MM) exception that can be signaled to halt execution. If a program executes without throwing this exception, then drf x guarantees that the execution is SC. If a program throws an MM exception during an execution, then drf x guarantees that the program has a data race. We observe that SC violations can be detected in hardware through a lightweight form of conflict detection. Furthermore, our model safely allows aggressive compiler and hardware optimizations within compiler-designated program regions. We formalize our memory model, prove several properties of this model, describe a compiler and hardware design suitable for drf x , and evaluate the performance overhead due to our compiler and hardware requirements.

Published
2016

27. Dye Chromoendoscopy Outperforms High-Definition White Light Endoscopy in Dysplasia Detection for Patients With Inflammatory Bowel Disease: An Updated Meta-Analysis of Randomized Controlled Trials.

Author

Mohamed, Mouhand F. H., Marino, Daniel, Elfert, Khaled, Beran, Azizullah, Nayfeh, Tarek, Abdallah, Mohamed A., Sultan, Shahnaz, and Shah, Samir A.

Subjects
*INFLAMMATORY bowel diseases, *RANDOMIZED controlled trials, *VIRTUAL colonoscopy, *DYSPLASIA, *CONTRAST-enhanced magnetic resonance imaging, *ENDOSCOPY
Abstract

INTRODUCTION: Whether dye spray chromoendoscopy (DCE) adds value in surveillance colonoscopy with high-definition (HD) scopes remains controversial. This updated meta-analysis compares dysplasia detection using DCE and high-definition white light endoscopy (HD-WLE) in patients with inflammatory bowel disease (IBD) undergoing surveillance colonoscopy. METHODS: A comprehensive search was performed for randomized controlled trials (RCT) comparing HD-WLE and DCE in patients with IBD. The primary outcome was to compare the proportion of patients with at least 1 dysplastic lesion detected by DCE vs HD-WLE. Odds ratios (OR) and95%confidence intervals (CI) were pooled using the random-effects model, with I² > 60% indicating substantial heterogeneity. The Grading of Recommendations, Assessment, Development, and Evaluation approach was used to assess the certainty of evidence (CoE). RESULTS: Six RCT involving 978 patients were analyzed (DCE5479 vs HD-WLE5499 patients). DCE detected significantlymore patients with dysplasia thanHD-WLE (18.8%vs9.4%), OR1.94 (95%CI1.21-3.11, I²=28%, P50.006, highCoE). This remained significant after excluding2 RCTpublished as abstracts. A sensitivity analysis excluding a noninferiority RCT with a single experienced operator eliminated the results' heterogeneity, OR 2.46 (95%CI 1.56-3.90, I²=0%). Although high-grade dysplasia detection was numerically higher in the DCE group (2.8% vs 1.1%), the difference was statistically insignificant, OR 2.21 (95% CI 0.64-7.62, I² = 0%, low CoE). DISCUSSION: Our updated meta-analysis supports DCE as a superior strategy in overall dysplasia detection in IBD, even with HD scopes. When expertise is available, DCE should be considered for surveillance colonoscopy in patients with high-risk IBD, with the acknowledgment that virtual chromoendoscopy shows equivalence in recent studies. Further multicenter trials with multiple endoscopists with varying expertise levels and longer-term outcome data showing a reduction in cancer or cancer-related death are needed. [ABSTRACT FROM AUTHOR]

Published
2024
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33. How to leverage the telemedicine surge to create a profitable telehealth model

Author

Zielinski, Lucy and Marino, Daniel J.

Subjects
Physicians -- Technology application, Telemedicine -- Usage, Epidemics -- Influence -- United States, COVID-19 -- Influence, Technology application, Business, Health care industry
Abstract

Some things are always changing. Other things stay the same for years, even decades, until a catalyst event leads to rapid transformation and reveals an opportunity. Case in point--the dramatic [...]

Published
2020

42. Some Vulnerabilities Are Different Than Others : Studying Vulnerabilities and Attack Surfaces in the Wild

Author

Nayak, Kartik, Marino, Daniel, Efstathopoulos, Petros, Dumitraş, Tudor, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Stavrou, Angelos, editor, Bos, Herbert, editor, and Portokalidis, Georgios, editor

Published
2014
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43. RX-ADS: Interpretable Anomaly Detection Using Adversarial ML for Electric Vehicle CAN Data

Author

Wickramasinghe, Chathurika S., Marino, Daniel L., Mavikumbure, Harindra S., Cobilean, Victor, Pennington, Timothy D., Varghese, Benny J., Rieger, Craig, and Manic, Milos

Abstract

Recent year has brought considerable advancements in Electric Vehicles (EVs) and associated infrastructures/communications. Intrusion Detection Systems (IDS) are widely deployed for anomaly detection in such critical infrastructures. This paper presents an Interpretable Anomaly Detection System (RX-ADS) for intrusion detection in CAN protocol communication in EVs. Contributions include: 1) Feature Extractor; 2) Anomaly Detection System; and 3) Explanation Generator for detected anomalies. The presented approach was tested on two benchmark CAN datasets: OTIDS and Car Hacking. The anomaly detection performance of RX-ADS was compared against the state-of-the-art approaches on these datasets: HIDS and GIDS. The RX-ADS approach showed comparable performance to the HIDS approach on OTIDS dataset and outperformed HIDS and GIDS approaches on Car Hacking dataset. Further, the proposed approach was able to generate explanations for detected abnormal behaviors arising from various intrusions. These explanations were later validated by information used by domain experts to detect anomalies. Other advantages of RX-ADS include: 1) the method can be trained on unlabeled data; 2) explanations help experts in understanding anomalies and root course analysis, and also help with AI model debugging and diagnostics, ultimately improving user trust in AI systems.

Published
2023
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47. ENGAGING PATIENTS IN INFLAMMATORY BOWEL DISEASE CARE — WHAT DETERMINES ACTIVE PARTICIPATION?

Author

Dang, Nhu, primary, Kwon, Michelle, additional, Kumar, Soryan, additional, Cradeur, Michael, additional, Zeven, Katherine, additional, Khunte, Mihir, additional, Marino, Daniel, additional, Tse, Chung Sang, additional, van Deen, Welmoed, additional, Lee, Adrian, additional, Kamp, Kendra, additional, Oberai, Ridhima, additional, Melmed, Gil, additional, Siegel, Corey, additional, Weaver, Alandra, additional, and Shah, Samir, additional

Published
2023
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48. INVESTIGATING THE USE OF THE SOCIAL VULNERABILITY INDEX TO PREDICT HEALTHCARE UTILIZATION AMONG PATIENTS WITH INFLAMMATORY BOWEL DISEASE

Author

Dang, Nhu, primary, Cradeur, Michael, additional, Zeven, Katherine, additional, Khunte, Mihir, additional, Kumar, Soryan, additional, Marino, Daniel, additional, Kwon, Michelle, additional, Kamp, Kendra, additional, Oberai, Ridhima, additional, van Deen, Welmoed, additional, Tse, Chung Sang, additional, Melmed, Gil, additional, Siegel, Corey, additional, Weaver, Alandra, additional, and Shah, Samir, additional

Published
2023
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49. EFFECTS OF ACTIVE PATIENT PARTICIPATION IN AN INFLAMMATORY BOWEL DISEASE QUALITY IMPROVEMENT PROGRAM ON HEALTHCARE UTILIZATION OUTCOMES

Author

Dang, Nhu, primary, Kumar, Soryan, additional, Kwon, Michelle, additional, Cradeur, Michael, additional, Zeven, Katherine, additional, Khunte, Mihir, additional, Marino, Daniel, additional, Tse, Chung Sang, additional, van Deen, Welmoed, additional, Kamp, Kendra, additional, Oberai, Ridhima, additional, Melmed, Gil, additional, Siegel, Corey, additional, Weaver, Alandra, additional, and Shah, Samir, additional

Published
2023
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