Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Areg Karapetyan"'
Autor:
Rashid Alyassi, Majid Khonji, Areg Karapetyan, Sid Chi-Kin Chau, Khaled Elbassioni, Chien-Ming Tseng
Publikováno v:
IEEE Transactions on Automation Science and Engineering. 20:1034-1046
Unmanned aerial vehicles (UAVs), commonly known as drones, are being increasingly deployed throughout the globe as a means to streamline monitoring, inspection, mapping, and logistic routines. When dispatched on autonomous missions, drones require an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71e22a186c25773193700eda7b263988
https://doi.org/10.1109/tase.2022.3175565
https://doi.org/10.1109/tase.2022.3175565
Publikováno v:
2022 IEEE International Symposium on Robotic and Sensors Environments (ROSE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d6438357b82a56297774901062e724f7
https://doi.org/10.1109/rose56499.2022.9977432
https://doi.org/10.1109/rose56499.2022.9977432
Autor:
Hatem H. Zeineldin, Areg Karapetyan, Ahmed Al-Durra, Majid Khonji, Tarek H. M. EL-Fouly, Chi-Kin Chau, Khaled Elbassioni
Publikováno v:
IEEE Transactions on Power Systems. 36:3430-3440
A routine task faced by Microgrid (MG) operators is to optimally allocate incoming power demand requests while accounting for the underlying power distribution network and the associated constraints. Typically, this has been formulated as an offline
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f98d595d1215d2a647142880355e3e5
https://doi.org/10.1109/tpwrs.2020.3046144
https://doi.org/10.1109/tpwrs.2020.3046144
Autor:
Kristin E. Porter, Malte Möser, Flora Wang, Bingyu Zhao, Wei Lee Woon, Yoshihiko Suhara, Adaner Usmani, Erik H. Wang, Kun Jin, Samantha Weissman, William Eggert, Hamidreza Omidvar, Andrew Or, Lisa M Hummel, Gregory Faletto, Ben Sender, Qiankun Niu, Viola Mocz, Antje Kirchner, Catherine Wu, Karen Ouyang, Ian Lundberg, Allison C. Morgan, Abdulla Alhajri, Arvind Narayanan, Khaled AlGhoneim, Louis Raes, Ilana M. Horwitz, Barbara E. Engelhardt, Ben Leizman, Crystal Qian, Drew Altschul, Guanhua He, Jeanne Brooks-Gunn, Ridhi Kashyap, Eaman Jahani, Ryan James Compton, Anna Filippova, Sara McLanahan, Tejomay Gadgil, Claudia V. Roberts, Muna Adem, Julia Wang, Jeremy Freese, Alexander T. Kindel, Daniel E Rigobon, Naijia Liu, Lisa P. Argyle, Mayank Mahajan, Jonathan D Tang, Moritz Hardt, Ethan Porter, Diana Mercado-Garcia, Andrew Halpern-Manners, Anahit Sargsyan, Duncan J. Watts, Alex Pentland, Sonia P Hashim, Dean Knox, Onur Varol, Ryan Amos, James M. Wu, Thomas Davidson, Emma Tsurkov, Bernie Hogan, Areg Karapetyan, William Nowak, Jingwen Yin, Livia Baer-Bositis, Landon Schnabel, Chenyun Zhu, Noah Mandell, Ahmed Musse, Yue Gao, Josh Gagné, Stephen McKay, Jennie E. Brand, Abdullah Almaatouq, Katy M. Pinto, Andrew E Mack, Austin van Loon, Bedoor K. AlShebli, Helge Marahrens, Xiafei Wang, Bryan Schonfeld, Sonia Hausen, Kengran Yang, Maria Wolters, Brandon M. Stewart, Naman Jain, Moritz Büchi, Nicole Bohme Carnegie, Redwane Amin, Caitlin Ahearn, Kirstie Whitaker, Bo-Ryehn Chung, Diana Stanescu, Thomas Schaffner, Patrick Kaminski, David Jurgens, Kivan Polimis, Kimberly Higuera, Zhilin Fan, Matthew J. Salganik, Debanjan Datta, Connor Gilroy, E H Kim, Katariina Mueller-Gastell, Karen Levy, Brian J. Goode, Zhi Wang, Tamkinat Rauf
Publikováno v:
PNAS
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 117(15), 8398-8403. NATL ACAD SCIENCES
Proc Natl Acad Sci U S A
Salganik, M J, Lundberg, I, Kindel, A T, Ahearn, C E, Al-ghoneim, K, Almaatouq, A, Altschul, D M, Brand, J E, Carnegie, N B, Compton, R J, Datta, D, Davidson, T, Filippova, A, Gilroy, C, Goode, B J, Jahani, E, Kashyap, R, Kirchner, A, Mckay, S, Morgan, A C, Pentland, A, Polimis, K, Raes, L, Rigobon, D E, Roberts, C V, Stanescu, D M, Suhara, Y, Usmani, A, Wang, E H, Adem, M, Alhajri, A, Alshebli, B, Amin, R, Amos, R B, Argyle, L P, Baer-bositis, L, Büchi, M, Chung, B, Eggert, W, Faletto, G, Fan, Z, Freese, J, Gadgil, T, Gagné, J, Gao, Y, Halpern-manners, A, Hashim, S P, Hausen, S, He, G, Higuera, K, Hogan, B, Horwitz, I M, Hummel, L M, Jain, N, Jin, K, Jurgens, D, Kaminski, P, Karapetyan, A, Kim, E H, Leizman, B, Liu, N, Möser, M, Mack, A E, Mahajan, M, Mandell, N, Marahrens, H, Mercado-garcia, D, Mocz, V, Mueller-gastell, K, Musse, A, Niu, Q, Nowak, W, Omidvar, H, Or, A, Ouyang, K, Pinto, K M, Porter, E, Porter, K E, Qian, C, Rauf, T, Sargsyan, A, Schaffner, T, Schnabel, L, Schonfeld, B, Sender, B, Tang, J D, Tsurkov, E, Van Loon, A, Varol, O, Wang, X, Wang, Z, Wang, J, Wang, F, Weissman, S, Whitaker, K, Wolters, M K, Woon, W L, Wu, J, Wu, C, Yang, K, Yin, J, Zhao, B, Zhu, C, Brooks-gunn, J, Engelhardt, B E, Hardt, M, Knox, D, Levy, K, Narayanan, A, Stewart, B M, Watts, D J & Mclanahan, S 2020, ' Measuring the predictability of life outcomes with a scientific mass collaboration ', Proceedings of the National Academy of Sciences, vol. 117, no. 15, pp. 8398-8403 . https://doi.org/10.1073/pnas.1915006117
Proceedings of the National Academy of Sciences of the United States of America (PNAS), 117(15), 8398-8403. NATL ACAD SCIENCES
Proc Natl Acad Sci U S A
Salganik, M J, Lundberg, I, Kindel, A T, Ahearn, C E, Al-ghoneim, K, Almaatouq, A, Altschul, D M, Brand, J E, Carnegie, N B, Compton, R J, Datta, D, Davidson, T, Filippova, A, Gilroy, C, Goode, B J, Jahani, E, Kashyap, R, Kirchner, A, Mckay, S, Morgan, A C, Pentland, A, Polimis, K, Raes, L, Rigobon, D E, Roberts, C V, Stanescu, D M, Suhara, Y, Usmani, A, Wang, E H, Adem, M, Alhajri, A, Alshebli, B, Amin, R, Amos, R B, Argyle, L P, Baer-bositis, L, Büchi, M, Chung, B, Eggert, W, Faletto, G, Fan, Z, Freese, J, Gadgil, T, Gagné, J, Gao, Y, Halpern-manners, A, Hashim, S P, Hausen, S, He, G, Higuera, K, Hogan, B, Horwitz, I M, Hummel, L M, Jain, N, Jin, K, Jurgens, D, Kaminski, P, Karapetyan, A, Kim, E H, Leizman, B, Liu, N, Möser, M, Mack, A E, Mahajan, M, Mandell, N, Marahrens, H, Mercado-garcia, D, Mocz, V, Mueller-gastell, K, Musse, A, Niu, Q, Nowak, W, Omidvar, H, Or, A, Ouyang, K, Pinto, K M, Porter, E, Porter, K E, Qian, C, Rauf, T, Sargsyan, A, Schaffner, T, Schnabel, L, Schonfeld, B, Sender, B, Tang, J D, Tsurkov, E, Van Loon, A, Varol, O, Wang, X, Wang, Z, Wang, J, Wang, F, Weissman, S, Whitaker, K, Wolters, M K, Woon, W L, Wu, J, Wu, C, Yang, K, Yin, J, Zhao, B, Zhu, C, Brooks-gunn, J, Engelhardt, B E, Hardt, M, Knox, D, Levy, K, Narayanan, A, Stewart, B M, Watts, D J & Mclanahan, S 2020, ' Measuring the predictability of life outcomes with a scientific mass collaboration ', Proceedings of the National Academy of Sciences, vol. 117, no. 15, pp. 8398-8403 . https://doi.org/10.1073/pnas.1915006117
© This open access article is distributed under Creative Commons Attribution-NonCommercialNoDerivatives License 4.0 (CC BY-NC-ND). How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e79e5a0edeb2b5d23585b10ea4b178d
https://doi.org/10.1073/pnas.1915006117
https://doi.org/10.1073/pnas.1915006117
Publikováno v:
Annals of Operations Research. 279:367-386
Stimulated by salient applications arising from power systems, this paper studies a class of non-linear Knapsack problems with non-separable quadratic constrains, formulated in either binary or integer form. These problems resemble the duals of the c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27ddc0224f344c5eae059e661be8ec7a
https://doi.org/10.1007/s10479-018-3111-9
https://doi.org/10.1007/s10479-018-3111-9
Publikováno v:
Machine Learning, Optimization, and Data Science ISBN: 9783030645823
LOD (1)
LOD (1)
Academic performance is perceived as a product of complex interactions between students’ overall experience, personal characteristics and upbringing. Data science techniques, most commonly involving regression analysis and related approaches, serve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b6eb20e575553b6ac415739ecb9d398
https://doi.org/10.1007/978-3-030-64583-0_24
https://doi.org/10.1007/978-3-030-64583-0_24
Publikováno v:
IEEE Transactions on Smart Grid. 9:2714-2725
Demand response management has become one of the key enabling technologies for smart grids. Motivated by the increasing demand response incentives offered by service operators, more customers are subscribing to various demand response programs. Howev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::518aceae495adc65e1bf432c5fd7bf9b
https://doi.org/10.1109/tsg.2016.2616945
https://doi.org/10.1109/tsg.2016.2616945
The Unsplittable Flow on a Path (UFP) problem has garnered considerable attention as a challenging combinatorial optimization problem with notable practical implications. Steered by its pivotal applications in power engineering, the present work form
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ca85f854c2c0915948b3e7098bdab29
http://arxiv.org/abs/1709.05876
http://arxiv.org/abs/1709.05876
Publikováno v:
TrustCom/BigDataSE/ICESS
Demand response (DR) programs have emerged as a potential key enabling ingredient in the context of smart grid (SG). Nevertheless, the rising concerns over privacy issues raised by customers subscribed to these programs constitute a formidable hurdle
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7b283d171e13b707e3b5007efa182ab
https://doi.org/10.1109/trustcom/bigdatase/icess.2017.276
https://doi.org/10.1109/trustcom/bigdatase/icess.2017.276
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319426334
COCOON
COCOON
We consider the problem of scheduling complex-valued demands over a discretized time horizon. Given a set of users, each user is associated with a set of demands representing different user’s preferences. A demand is represented by a complex number
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff7cfd48e9b68b88d6e0d340d0d0af91
https://doi.org/10.1007/978-3-319-42634-1_40
https://doi.org/10.1007/978-3-319-42634-1_40