Results 81 to 90 of about 3,545,579 (292)
New Area Based Metrics for Automatic Gait Recognition
, 2001 Gait is a new biometric aimed to recognise a subject by the manner in which they walk. Gait has several advantages over other biometrics, most notably that it is non-invasive and perceivable at a distance when other biometrics are obscured.Foster, Jeff P., Prudel-Bennett, Adam, Nixon, Mark S., A Prugel-Bennet, J Foster, M Nixon +5 morecore +1 more sourceMucocutaneous Disease Activity and Damage Accrual in Systemic Lupus Erythematosus: Analyses From the Asia‐Pacific Lupus Collaboration Longitudinal Cohort Study
Arthritis Care &Research, EarlyView.Objective
This research article aims to describe the prevalence, associations, and health‐related quality of life (HRQoL) impact of mucocutaneous features of systemic lupus erythematosus (SLE). Methods
Data from the Asia‐Pacific Lupus Collaboration cohort were analyzed (2013–2021).Amanda M. Saracino, Yanjie Hao, Dylan Hansen, Yi‐Hsing Chen, Alberta Hoi, Vera Golder, Jiacai Cho, Aisha Lateef, Worawit Louthrenoo, Laniyati Hamijoyo, Shue Fen Luo, Yeong‐Jian Jan Wu, Sandra Navarra, Leonid Zamora, Chak Sing Lau, Shirley Chan, Zhanguo Li, Hai‐hong Yao, Sargunan Sockalingam, B. M. D. B. Basnayake, Yasuhiro Katsumata, Masayoshi Harigai, Zhuoli Zhang, Jun Kikuchi, Yuko Kaneko, Tsutomu Takeuchi, Madelynn Chan, Sang‐Cheol Bae, Fiona Goldblatt, Sean O'Neill, Geraldine Hassett, Kristine Ng, Nicola Tugnet, Mark Sapsford, Yih Jia Poh, Michael Tee, Cherica Tee, Naoaki Ohkubo, Yoshiya Tanaka, Rangi Kandane‐Rathnayake, Eric Morand, Shereen Oon, Mandana Nikpour +42 morewiley +1 more sourceImage Pattern Recognition-Based Morphological Structure and Applications
, 2008 This chapter describes a new pattern recognition method: pattern recognition-based morphological structure. First, smooth following and linearization are introduced based on difference chain codes. Second, morphological structural points are described in Yu, Donggang,, Donggang Yu, Tuan D. Pham, Pham, Tuan D, +3 morecore +1 more sourceCumulative Social Disadvantage and Disease Activity in Juvenile Idiopathic Arthritis: A Childhood Arthritis and Rheumatology Research Alliance Registry Study
Arthritis Care &Research, EarlyView.Objective
Social determinants of health (SDOH) contribute to juvenile idiopathic arthritis (JIA) disparities, but most studies have assessed SDOH independently rather than cumulatively across individual, family, and neighborhood levels. Using a socioecological framework, we investigated the relationship among cumulative social disadvantage ...William Daniel Soulsby, John Boscardin, Andrea Knight, Daniel B. Horton, Karine Toupin‐April, Emily von Scheven, on behalf of the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry Investigators and for the CARRA Health Equity Work Group, R. Aamir, K. Abulaban, A. Adams, C. Aguiar Lapsia, H. Ahmed, S. Akoghlanian, A. AlBijadi, E. Allenspach, M. Alpizar, G. Amarilyo, M. Amoruso, S. Angeles‐Han, S. Ardoin, S. Armendariz, N. Aviran Dagan, I. Balboni, S. Balevic, S. Ballinger, S. Baluta, L. Barillas‐Arias, L. Barillas‐Arias, M. Basiaga, K. Baszis, M. Becker, A. Begezda, E. Beil, H. Bell‐Brunson, H. Benham, S. Benseler, L. Bermudez‐Santiago, W. Bernal, T. Bigley, C. Bingham, B. Binstadt, C. Black, B. Blackmon, M. Blakley, J. Bohnsack, A. Boneparth, H. Bradfield, J. Bridges, E. Brooks, M. Brothers, D. Brown, H. Brunner, L. Buckley, Mary Buckley, Meredith Buckley, H. Bukulmez, D. Bullock, A. Cancino, S. Canna, L. Cannon, S. Canny, V. Cartwright, E. Chalom, Johanna Chang, Joyce Chang, M. Chang, A. Chang‐Hoftman, A. Chen, P. Chiraseveenuprapund, K. Ciaglia, M. Cidon, D. Co, E. Cohen, R. Connor, K. Cook, A. Cooper, J. Cooper, K. Corbin, C. Correll, R. Cron, M. Curry, A. Dagci, A. Dalrymple, E. Datyner, T. Davis, D. De Ranieri, J. Dean, C. DeCoste, F. Dedeoglu, M. DeGuzman, N. Delnay, E. L. DeSantis, R. Devine, M. Dhalla, A. Dhanrajani, D. Dissanayake, B. Dizon, J. Drew, K. Driest, Q. Du, E. Duncan, K. Dunnock, D. Durkee, J. Dvergsten, A. Eberhard, K. Ede, B. Edelheit, C. Edens, M. Elder, Y. Elzaki, C. Failing, D. Fair, L. Favier, B. Feldman, J. Fennell, I. Ferguson, P. Ferguson, C. Figueroa, E. Flanagan, L. Fogel, E. Fox, M. Fox, L. Franklin, R. Fuhlbrigge, J. Fuller, T. Futch‐West, S. Gagne, M. Geiszler, D. Gerstbacher, M. Gilbert, A.C. Gironella, D. Glaser, I. Goh, S. Gorry, N. Goswami, B. Gottlieb, T. Graham, S. Grevich, T. Griffin, A. Grim, A. Grom, M. Guevara, L. Guzman, T. Hahn, O. Halyabar, E. Hammelev, T. Hammond, S. Haro, J. Harris, O. Harry, J. Hausmann, A. Hay, K. Hays, K. Hayward, L. Henderson, M. Henrickson, A. Hersh, L. Hiraki, M. Hiskey, P. Hobday, C. Hoffart, M. J. Holland, M. Hollander, S. Hong, D. Horton, J. Hsu, A. Huber, J. Huggins, J. Hui‐Yuen, M. Ibarra, A. Imlay, L. Imundo, C. Inman, A. Jackson, K. James, G. Janow, Y. Jiang, L. Johnson, N. Johnson, J. Jones, D. Kafisheh, K. Kaidar, S. Kasinathan, R. Kaur, E. Kessler, B. Kienzle, S. Kim, Y. Kimura, D. Kingsbury, M. Kitcharoensakkul, J. Klauss, K. Klein, M. Klein‐Gitelman, A. Knight, L. Kovalick, D. Krajewski, C. Kremer, T. LaFlam, B. Lang, S. Lapidus, B. Lapin, A. Lasky, E. Lawson, R. Laxer, A. Lee, Patricia Lee, Pui Lee, T. Lee, E. Leisinger, L. Lentini, M. Lerman, Y. Levinsky, D. Levy, S. Li, S. Lieberman, L. Lim, E. Limenis, C. Lin, N. Ling, G. Lionetti, R. Livny, M. Lo, A. Long, M. Lopez‐Peña, D. Lovell, S. Lvovich, A. Lytch, M. Ma, A. Machado, J. MacMahon, J. Madison, M. Mannion, C. Manos, L. Mansfield, B. Marston, K. Marzan, T. Mason, S. Matossian, L. McAllister, K. McBrearty, D. McCurdy, K. McDaniels, J. McDonald, L. McIntosh, E. Meidan, E. Mellins, Z. Mian, P. Miettunen, M. Miller, D. Milojevic, R. Mitacek, R. Modica, S. Mohan, K. Moore, T. Moore, L. Moorthy, J. Moreno, E. Morgan, A. Moyer, B. Murante, A. Murphy, E. Muscal, O. Mwizerwa, A. Najafi, K. Nanda, L. Nassi, S. Nativ, M. Natter, J. Neely, L. Newhall, A. Nuyen, P. Nigrovic, J. Nocton, B. Nolan, A. Nowakowski, K. Nowicki, R. Oakes, E. Oberle, S. Ogbonnaya‐Whittesley, E. Ogbu, M. Oliver, R. Olveda, K. Onel, A. Orandi, J. Padam, N. Pan, J. Pandya, S. Panupattanapong, A. Pappo Toledano, J. Patel, P. Patel, A. Patrick, S. Patrizi, S. Paul, J. Perfetto, M. Perron, M. Peskin, C. Pinotti, L. Ponder, R. Pooni, S. Prahalad, M. Quinlan‐Waters, J. Rafko, H. Rahimi, S. Ramsey, R. Randell, L. Ray, Ann Reed, Annelle Reed, H. Reid, D. Reiff, I. Reyhan, B. Richard, M. Riebschleger, E. Rife, M. Riskalla, A. Robinson, L. Robinson, L. Rodgers, M. Rodriquez, D. Rogers, T. Ronis, A. Rosado, M. Rosenkranz, N. Rosenwasser, H. Rothermel, D. Rothman, E. Rothschild, K. Rouster ‐ Stevens, T. Rubinstein, N. Ruth, S. Sabbagh, R. Sadun, L. Santiago, V. Saper, A. Sarkissian, L. Scalzi, J. Schahn, K. Schikler, A. Schlefman, B. Schlichting, H. Schmeling, E. Schmitt, G. Schulert, C. Schutt, C. Seper, B. Shaham, R. Sheets, A. Shehab, S. Shenoi, M. Sherman, J. Shirley, M. Shishov, N. Singer, V. Sivaraman, E. Sloan, C. Smith, J. Smith, E. Smitherman, J. Soep, M. B. Son, C. Spencer, L. Spiegel, J. Spitznagle, H. Srinivasalu, H. Stapp, A. Stephens, Y. Sterba Rakovchik, S. Stern, B. Stevens, R. Stevenson, C. Stingl, M. Stoll, E. Stringer, S. Sule, J. Sullivan, R. Sundel, M. Sutter, C. Swaffar, N. Swayne, T. Symington, G. Syverson, A.M. Szymanski, S. Taber, R. Tal, A. Tambralli, A. Taneja, T. Tanner, S. Tarvin, A. Taxter, M. Tesher, T. Thakurdeen, A. Theisen, G. Thieroff, B. Thomas, L. Thomas, N. Thomas, L. Timmerman, T. Ting, C. Todd, D. Toib, K. Torok, H. Tory, M. Toth, E. Treemarcki, S. Tse, T. Tse, C. Tsin, J. Twachtman‐Bassett, M. Twilt, T. Valcarcel, R. Valdovinos, A. Vallee, H. Van Mater, S. Vandenbergen, C. Varghese, N. Vasquez, P. Vega‐Fernandez, J. Verbsky, R. Verstegen, E. von Scheven, S. Vora, L. Wagner‐Weiner, D. Wahezi, S. Wakefield, B. Walker, S. Wallgren, H. Walters, M. Waterfield, J. Weiss, P. Weiss, E. Wershba, V. Westheuser, K. Widrick, C. Williams, S. Wong, S. Wooldridge, L. Woolnough, T. Wright, E. Wu, A. Yalcindag, R. Yeung, K. Yomogida, A. Zeft, Y. J. Zhang, Y. D. Zhao, Z. Zheng, A. Zhu, C. Zic +448 morewiley +1 more sourceMid-level Deep Pattern Mining∗
, 2015 Mid-level visual element discovery aims to find clusters of image patches that are both representative and discrimi-native. In this work, we study this problem from the prospec-tive of pattern mining while relying on the recently popular-ized ...Anton Van Den Hengel, Lingqiao Liu, Van Den Hengel, A., Liu, L., Shen, C., Chunhua Shen, Li, Y., Yao Li +7 morecore +1 more sourceEmbodiment in social psychology [PDF]
, 2012 Psychologists are increasingly interested in embodiment based on the assumption that thoughts, feelings, and behaviors are grounded in bodily interaction with the environment.Simone Schnall, Schwarz, Norbert, Schnall, Simone S., John A. Bargh, Meier, Brian P., Brian P. Meier, Norbert Schwarz, Schnall, Simone, Bargh, John A. +8 morecore +3 more sourcesMachine learning and essentialism
Zagadnienia Filozoficzne w Nauce, 2022 Machine learning and essentialism have been connected in the past by various researchers, in order to state that the main paradigm in machine learning processes is equivalent to choosing the “essential” attributes for the machine to search for.Kristina Šekrst, Sandro Skansidoaj
