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Your search keyword '"A. Spiridon"' showing total 254 results
Start Over Author "A. Spiridon" Publisher elsevier b.v.
254 results on '"A. Spiridon"'

2. Review of Solar Energetic Particle Prediction Models

Author

Whitman, Kathryn, Egeland, Ricky, Richardson, Ian G., Allison, Clayton, Quinn, Philip, Barzilla, Janet, Kitiashvili, Irina, Sadykov, Viacheslav, Bain, Hazel M., Dierckxsens, Mark, Mays, M. Leila, Tadesse, Tilaye, Lee, Kerry T., Semones, Edward, Luhmann, Janet G., Núñez, Marlon, White, Stephen M., Kahler, Stephen W., Ling, Alan G., Smart, Don F., Shea, Margaret A., Tenishev, Valeriy, Boubrahimi, Soukaina F., Aydin, Berkay, Martens, Petrus, Angryk, Rafal, Marsh, Michael S., Dalla, Silvia, Crosby, Norma, Schwadron, Nathan A., Kozarev, Kamen, Gorby, Matthew, Young, Matthew A., Laurenza, Monica, Cliver, Edward W., Alberti, Tommaso, Stumpo, Mirko, Benella, Simone, Papaioannou, Athanasios, Anastasiadis, Anastasios, Sandberg, Ingmar, Georgoulis, Manolis K., Ji, Anli, Kempton, Dustin, Pandey, Chetraj, Li, Gang, Hu, Junxiang, Zank, Gary P., Lavasa, Eleni, Giannopoulos, Giorgos, Falconer, David, Kadadi, Yash, Fernandes, Ian, Dayeh, Maher A., Muñoz-Jaramillo, Andrés, Chatterjee, Subhamoy, Moreland, Kimberly D., Sokolov, Igor V., Roussev, Ilia I., Taktakishvili, Aleksandre, Effenberger, Frederic, Gombosi, Tamas, Huang, Zhenguang, Zhao, Lulu, Wijsen, Nicolas, Aran, Angels, Poedts, Stefaan, Kouloumvakos, Athanasios, Paassilta, Miikka, Vainio, Rami, Belov, Anatoly, Eroshenko, Eugenia A., Abunina, Maria A., Abunin, Artem A., Balch, Christopher C., Malandraki, Olga, Karavolos, Michalis, Heber, Bernd, Labrenz, Johannes, Kühl, Patrick, Kosovichev, Alexander G., Oria, Vincent, Nita, Gelu M., Illarionov, Egor, O’Keefe, Patrick M., Jiang, Yucheng, Fereira, Sheldon H., Ali, Aatiya, Paouris, Evangelos, Aminalragia-Giamini, Sigiava, Jiggens, Piers, Jin, Meng, Lee, Christina O., Palmerio, Erika, Bruno, Alessandro, Kasapis, Spiridon, Wang, Xiantong, Chen, Yang, Sanahuja, Blai, Lario, David, Jacobs, Carla, Strauss, Du Toit, Steyn, Ruhann, van den Berg, Jabus, Swalwell, Bill, Waterfall, Charlotte, Nedal, Mohamed, Miteva, Rositsa, Dechev, Momchil, Zucca, Pietro, Engell, Alec, Maze, Brianna, Farmer, Harold, Kerber, Thuha, Barnett, Ben, Loomis, Jeremy, Grey, Nathan, Thompson, Barbara J., Linker, Jon A., Caplan, Ronald M., Downs, Cooper, Török, Tibor, Lionello, Roberto, Titov, Viacheslav, Zhang, Ming, and Hosseinzadeh, Pouya

Published
2023
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6. The association between genetically elevated polyunsaturated fatty acids and risk of cancer

Author

Tintle, Nathan, Rice, Terri, Cheng, Iona, Jenkins, Mark, Gallinger, Steve, Cornish, Alex J., Sud, Amit, Vijayakrishnan, Jayaram, Wrensch, Margaret, Johansson, Mattias, Norman, Aaron D., Klein, Alison, Clay-Gilmour, Alyssa, Franke, Andre, Ardisson Korat, Andres V., Wheeler, Bill, Nilsson, Björn, Smith, Caren, Heng, Chew-Kiat, Song, Ci, Riadi, David, Claus, Elizabeth B., Ellinghaus, Eva, Ostroumova, Evgenia, Hosnijeh, de Vathaire, Florent, Cugliari, Giovanni, Matullo, Giuseppe, Oi-Lin Ng, Irene, Passow, Jeanette E., Foo, Jia Nee, Han, Jiali, Liu, Jianjun, Barnholtz-Sloan, Jill, Schildkraut, Joellen M., Maris, John, Wiemels, Joseph L., Hemminki, Kari, Yang, Keming, Kiemeney, Lambertus A., Wu, Lang, Amundadottir, Laufey, Stern, Marc-Henri, Boutron, Marie-Christine, Iles, Mark Martin, Purdue, Mark P., Stanulla, Martin, Bondy, Melissa, Gaudet, Mia, Mobuchon, Lenha, Camp, Nicola J., Sham, Pak Chung, Guénel, Pascal, Brennan, Paul, Taylor, Philip R., Ostrom, Quinn, Stolzenberg-Solomon, Rachael, Dorajoo, Rajkumar, Houlston, Richard, Jenkins, Robert B., Diskin, Sharon, Berndt, Sonja I., Tsavachidis, Spiridon, Channock, Stephen J., Harrison, Tabitha, Galesloot, Tessel, Gyllensten, Ulf, Joseph, Vijai, Shi, Y., Yang, Wenjian, Lin, Yi, Van Den Eeden, Stephen K., Haycock, Philip C., Borges, Maria Carolina, Burrows, Kimberley, Lemaitre, Rozenn N., Burgess, Stephen, Khankari, Nikhil K., Tsilidis, Konstantinos K., Gaunt, Tom R., Hemani, Gibran, Zheng, Jie, Truong, Therese, Birmann, Brenda M., OMara, Tracy, Spurdle, Amanda B., Iles, Mark M., Law, Matthew H., Slager, Susan L., Saberi Hosnijeh, Fatemeh, Mariosa, Daniela, Cotterchio, Michelle, Cerhan, James R., Peters, Ulrike, Enroth, Stefan, Gharahkhani, Puya, Le Marchand, Loic, Williams, Ann C., Block, Robert C., Amos, Christopher I., Hung, Rayjean J., Zheng, Wei, Gunter, Marc J., Smith, George Davey, Relton, Caroline, and Martin, Richard M.

Published
2023
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12. Study of spin-isospin responses of radioactive nuclei with the background-reduced neutron spectrometer, PANDORA

Author

Stuhl, L., Sasano, M., Gao, J., Hirai, Y., Yako, K., Wakasa, T., Ahn, D.S., Baba, H., Chilug, A.I., Franchoo, S., Fujino, Y., Fukuda, N., Gibelin, J., Hahn, I.S., Halász, Z., Harada, T., Harakeh, M.N., Inomoto, D., Isobe, T., Kasahara, H., Kim, D., Kiss, G.G., Kobayashi, T., Kondo, Y., Korkulu, Z., Koyama, S., Kubota, Y., Kurihara, A., Liu, H.N., Matsumoto, M., Michimasa, S., Miki, H., Miwa, M., Motobayashi, T., Nakamura, T., Nishimura, M., Otsu, H., Panin, V., Park, S., Saito, A.T., Sakai, H., Sato, H., Shimada, T., Shimizu, Y., Shimoura, S., Spiridon, A., Stefanescu, I.C., Sun, X., Sun, Y.L., Suzuki, H., Takada, E., Togano, Y., Tomai, T., Trache, L., Tudor, D., Uesaka, T., Yamada, H., Yang, Z., Yasuda, M., Yoneda, K., Yoshida, K., Zenihiro, J., and Zhang, N.

Published
2020
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38. Audio-deepfake detection: Adversarial attacks and countermeasures.

Author

Rabhi, Mouna, Bakiras, Spiridon, and Di Pietro, Roberto

Subjects
*GENERATIVE adversarial networks, *ARTIFICIAL intelligence, *SENSOR networks, *BIOMETRIC identification, *SOUND systems
Abstract

Audio has always been a powerful resource for biometric authentication: thus, numerous AI-based audio authentication systems (classifiers) have been proposed. While these classifiers are effective in identifying legitimate human-generated input their security, to the best of our knowledge, has not been explored thoroughly when confronted with advanced attacks that leverage AI-generated deepfake audio. This issue presents a serious concern regarding the security of these classifiers because, e.g. , samples generated using adversarial attacks might fool such classifiers, resulting in incorrect classification. In this study, we prove the point: we demonstrate that state-of-the-art audio deepfake classifiers are vulnerable to adversarial attacks. In particular, we design two adversarial attacks on a state-of-the-art audio-deepfake classifier, i.e. , the Deep4SNet classification model, which achieves 98.5% accuracy in detecting fake audio samples. The designed adversarial attacks 1 1 The code of the attacks will be released open-source in the camera ready. leverage a generative adversarial network architecture and reduce the detector's accuracy to nearly 0%. In particular, under graybox attack scenarios, we demonstrate that when starting from random noise, we can reduce the accuracy of the state-of-the-art detector from 98.5% to only 0.08%. To mitigate the effect of adversarial attacks on audio-deepfake detectors, we propose a highly generalizable, lightweight, simple, and effective add-on defense mechanism that can be implemented in any audio-deepfake detector. Finally, we discuss promising research directions. • Expose weakness of Deep4SNet, state-of-the-art deepfake audio detection. • Reveal limitations of relying on audio histograms for deepfake detection. • Present powerful GAN-based attacks on audio-deepfake classifier. • Propose viable, lightweight, general defense to counter deepfake audio. [ABSTRACT FROM AUTHOR]

Published
2024
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49. New composites based on starch/Ecoflex®/biomass wastes: Mechanical, thermal, morphological and antimicrobial properties.

Author

Spiridon, Iuliana, Anghel, Narcis Catalin, Darie-Nita, Raluca Nicoleta, Iwańczuk, Andrzej, Ursu, Ramona Gabriela, and Spiridon, Irene Alexandra

Subjects
*LIGNINS, *IMPACT strength, *PACKAGING materials, *DRUG resistance in microorganisms, *STARCH, *STRENGTH of materials, *TENSILE strength, *POLYETHYLENE terephthalate
Abstract

Different biomass wastes were successfully blended with starch and Ecoflex® viz. poly(butylene adipate- co -terephthalate), without glycerol addition, to obtain biocomposite materials. The mechanical properties, as well as thermal and surface properties, of the developed composites were evaluated. It was found that the tensile strength and impact strength improved upon the addition of lignin, while the water uptake capacity decreased. The presence of 5% lignin determined an increase in tensile strength of 125.4% for materials comprising celery (CEL), 109.6% for materials comprising poplar seed hair fibers (PSH), 92.9% for materials comprising pomace (POM) and 127.7% for materials comprising Asclepias syriaca fibers (ASF), compared with a reference sample. The addition of lignin to all the formulations conferred good antimicrobial properties against different microorganisms, S. aureus and especially E. coli. The good mechanical properties, water resistance and antimicrobial activity against pathogens recommend these composites to be used in the manufacture of packaging materials. [ABSTRACT FROM AUTHOR]

Published
2020
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