المؤلفون: Aamir, M., Acar, B., Adamov, G., Adams, T., Adloff, C., Afanasiev, S., Agrawal, C., Ahmad, A., Ahmed, H. A., Akbar, S., Akchurin, N., Akgul, B., Akgun, B., Akpinar, R. O., Aktas, E., AlKadhim, A., Alexakhin, V., Alimena, J., Alison, J., Alpana, A., Alshehri, W., Dominguez, P. Alvarez, Alyari, M., Amendola, C., Amir, R. B., Andersen, S. B., Andreev, Y., Antoszczuk, P. D., Aras, U., Ardila, L., Aspell, P., Avila, M., Awad, I., Aydilek, O., Azimi, Z., Pretel, A. Aznar, Bach, O. A., Bainbridge, R., Bakshi, A., Bam, B., Banerjee, S., Barney, D., Bayraktar, O., Beaudette, F., Beaujean, F., Becheva, E., Behera, P. K., Belloni, A., Bergauer, T., Besancon, M., Bylund, O. Bessidskaia, Bhatt, L., Bhowmil, D., Blekman, F., Blinov, P., Bloch, P., Bodek, A., Boger, a., Bonnemaison, A., Bouyjou, F., Brennan, L., Brondolin, E., Brusamolino, A., Bubanja, I., Perraguin, A. Buchot, Bunin, P., Misura, A. Burazin, Butler-nalin, A., Cakir, A., Callier, S., Campbell, S., Canderan, K., Cankocak, K., Cappati, A., Caregari, S., Carron, S., Carty, C., Cauchois, A., Ceard, L., Cerci, S., Chang, P. J., Chatterjee, R. M., Chatterjee, S., Chattopadhyay, P., Chatzistavrou, T., Chaudhary, M. S., Chauhan, A., Chen, J. A., Chen, J., Chen, Y., Cheng, K., Cheung, H., Chhikara, J., Chiron, A., Chiusi, M., Chokheli, D., Chudasama, R., Clement, E., Mendez, S. Coco, Coko, D., Coskun, K., Couderc, F., Crossman, B., Cui, Z., Cuisset, T., Cummings, G., Curtis, E. M., D'Alfonso, M., D-hler-ball, J., Dadazhanova, O., Damgov, J., Das, I., DasGupta, S., Dauncey, P., Mendes, A. David Tinoco, Davies, G., Davignon, O., DeLa, P. deBarbaroC., DeSilva, M., DeWit, A., Debbins, P., Defranchis, M. M., Delagnes, E., Devouge, P., Dewangan, C., DiGuglielmo, G., Diehl, L., Dilsiz, K., Dincer, G. G., Dittmann, J., Dragicevic, M., Du, D., Dubinchik, B., Dugad, S., Dulucq, F., Dumanoglu, I., Duran, B., Dutta, S., Dutta, V., Dychkant, A., Dünser, M., Edberg, T., Ehle, I. T., Berni, A. El, Elias, F., Eno, S. C., Erdogan, E. N., Erkmen, B., Ershov, Y., Ertorer, E. Y., Extier, S., Eychenne, L., Fedar, Y. E., Fedi, G., De Almeida, J. P. Figueiredo De De Sá Sousa, Alves, B. A. Fontana Santos Santos, Frahm, E., Francis, K., Freeman, J., French, T., Gaede, F., Gandhi, P. K., Ganjour, S., Garcia-Bellido, A., Gastaldi, F., Gazi, L., Gecse, Z., Gerwig, H., Gevin, O., Ghosh, S., Gill, K., Gleyzer, S., Godinovic, N., Goek, M., Goettlicher, P., Goff, R., Golunov, A., Gonultas, B., Martínez, J. D. González, Gorbounov, N., Gouskos, L., Gray, A., Gray, L., Grieco, C., Groenroos, S., Groner, D., Gruber, A., Grummer, A., Grönroos, S., Guilloux, F., Guler, Y., Gungordu, A. D., Guo, J., Guo, K., Guler, E. Gurpinar, Gutti, H. K., Guvenli, A. A., Gülmez, E., Hacisahinoglu, B., Halkin, Y., Machado, G. Hamilton Ilha, Hare, H. S., Hatakeyama, K., Heering, A. H., Hegde, V., Heintz, U., Hinton, N., Hinzmann, A., Hirschauer, J., Hitlin, D., Hos, İ., Hou, B., Hou, X., Howard, A., Howe, C., Hsieh, H., Hsu, T., Hua, H., Hummer, F., Imran, M., Incandela, J., Iren, E., Isildak, B., Jackson, P. S., Jackson, W. J., Jain, S., Jana, P., Jaroslavceva, J., Jena, S., Jige, A., Jordano, P. P., Joshi, U., Kaadze, K., Kafizov, A., Kalipoliti, L., Tharayil, A. Kallil, Kaluzinska, O., Kamble, S., Kaminskiy, A., Kanemura, M., Kanso, H., Kao, Y., Kapic, A., Kapsiak, C., Karjavine, V., Karmakar, S., Karneyeu, A., Kaya, M., Topaksu, A. Kayis, Kaynak, B., Kazhykarim, Y., Khan, F. A., Khudiakov, A., Kieseler, J., Kim, R. S., Klijnsma, T., Kloiber, E. G., Klute, M., Kocak, Z., Kodali, K. R., Koetz, K., Kolberg, T., Kolcu, O. B., Komaragiri, J. R., Komm, M., Kopsalis, I., Krause, H. A., Krawczyk, M. A., Vinayakam, T. R. Krishnaswamy, Kristiansen, K., Kristic, A., Krohn, M., Kronheim, B., Krüger, K., Kudtarkar, C., Kulis, S., Kumar, M., Kumar, N., Kumar, S., Verma, R. Kumar, Kunori, S., Kunts, A., Kuo, C., Kurenkov, A., Kuryatkov, V., Kyre, S., Ladenson, J., Lamichhane, K., Landsberg, G., Langford, J., Laudrain, A., Laughlin, R., Lawhorn, J., Dortz, O. Le, Lee, S. W., Lektauers, A., Lelas, D., Leon, M., Levchuk, L., Li, A. J., Li, J., Li, Y., Liang, Z., Liao, H., Lin, K., Lin, W., Lin, Z., Lincoln, D., Linssen, L., Litomin, A., Liu, G., Liu, Y., Lobanov, A., Lohezic, V., Loiseau, T., Lu, C., Lu, R., Lu, S. Y., Lukens, P., Mackenzie, M., Magnan, A., Magniette, F., Mahjoub, A., Mahon, D., Majumder, G., Makarenko, V., Malakhov, A., Malgeri, L., Mallios, S., Mandloi, C., Mankel, A., Mannelli, M., Mans, J., Mantilla, C., Martinez, G., Massa, C., Masterson, P., Matthewman, M., Matveev, V., Mayekar, S., Mazlov, I., Mehta, A., Mestvirishvili, A., Miao, Y., Milella, G., Mirza, I. R., Mitra, P., Moccia, S., Mohanty, G. B., Monti, F., Moortgat, F., Murthy, S., Music, J., Musienko, Y., Nabili, S., Nayak, S., Nelson, J. W., Nema, A., Neutelings, I., Niedziela, J., Nikitenko, A., Noonan, D., Noy, M., Nurdan, K., Obraztsov, S., Ochando, C., Ogul, H., Olsson, J., Onel, Y., Ozkorucuklu, S., Paganis, E., Palit, P., Pan, R., Pandey, S., Pantaleo, F., Papageorgakis, C., Paramesvaran, S., Paranjpe, M. M., Parolia, S., Parsons, A. G., Parygin, P., Paulini, M., Paus, C., Peñaló, K., Pedro, K., Pekic, V., Peltola, T., Peng, B., Perego, A., Perini, D., Petrilli, A., Pham, H., Pierre-Emile, T., Podem, S. K., Popov, V., Portales, L., Potok, O., Pradeep, P. B., Pramanik, R., Prosper, H., Prvan, M., Qasim, S. R., Qu, H., Quast, T., Trivino, A. Quiroga, Rabour, L., Raicevic, N., Rajpoot, H., Rao, M. A., Rapacz, K., Redjeb, W., Reinecke, M., Revering, M., Roberts, A., Rohlf, J., Rosado, P., Rose, A., Rothman, S., Rout, P. K., Rovere, M., Rumerio, P., Rusack, R., Rygaard, L., Ryjov, V., Sadivnycha, S., Sahin, M. Ö., Sakarya, U., Salerno, R., Saradhy, R., Saraf, M., Sarbandi, K., Sarkisla, M. A., Satyshev, I., Saud, N., Sauvan, J., Schindler, G., Schmidt, A., Schmidt, I., Schmitt, M. H., Sculac, A., Sculac, T., Sedelnikov, A., Seez, C., Sefkow, F., Selivanova, D., Selvaggi, M., Sergeychik, V., Sert, H., Shahid, M., Sharma, P., Sharma, R., Sharma, S., Shelake, M., Shenai, A., Shih, C. W., Shinde, R., Shmygol, D., Shukla, R., Sicking, E., Silva, P., Simsek, C., Simsek, E., Sirasva, B. K., Sirois, Y., Song, S., Song, Y., Soudais, G., Sriram, S., StJacques, R. R., StahlLeiton, A. G., Steen, A., Stein, J., Strait, J., Strobbe, N., Su, X., Sukhov, E., Suleiman, A., Cerci, D. Sunar, Suryadevara, P., Swain, K., Syal, C., Tali, B., Tanay, K., Tang, W., Tanvir, A., Tao, J., Tarabini, A., Tatli, T., Taylor, R., Taysi, Z. C., Teafoe, G., Tee, C. Z., Terrill, W., Thienpont, D., Thomas, R., Titov, M., Todd, C., Todd, E., Toms, M., Tosun, A., Troska, J., Tsai, L., Tsamalaidze, Z., Tsionou, D., Tsipolitis, G., Tsirigoti, M., Tu, R., Polat, S. N. Tural, Undleeb, S., Usai, E., Uslan, E., Ustinov, V., Vernazza, E., Viahin, O., Viazlo, O., Vichoudis, P., Vijay, A., Virdee, T., Voirin, E., Vojinovic, M., Voytishin, N., Vámi, T. Á., Wade, A., Walter, D., Wang, C., Wang, F., Wang, J., Wang, K., Wang, X., Wang, Y., Wang, Z., Wanlin, E., Wayne, M., Wetzel, J., Whitbeck, A., Wickwire, R., Wilmot, D., Wilson, J., Wu, H., Xiao, M., Yang, J., Yazici, B., Ye, Y., Yetkin, T., Yi, R., Yohay, R., Yu, T., Yuan, C., Yuan, X., Yuksel, O., YushmanoV, I., Yusuff, I., Zabi, A., Zareckis, D., Zarubin, A., Zehetner, P., Zghiche, A., Zhang, C., Zhang, D., Zhang, H., Zhang, J., Zhang, Z., Zhao, X., Zhong, J., Zhou, Y., Zorbilmez, Ç.

مصطلحات موضوعية: Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability

الوصف: A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated.
Comment: Prepared for submission to JINST

الوصول الحر: http://arxiv.org/abs/2406.11937Test

المؤلفون: Gardner, WM, Razo, C, McHugh, TA, Hagins, H, Vilchis-Tella, VM, Hennessy, C, Taylor, HJ, Perumal, N, Fuller, K, Cercy, KM, Zoeckler, LZ, Chen, CS, Lim, SS, Aali, A, Abate, KH, Abd-Elsalam, S, Abdurehman, AM, Abebe, G, Abidi, H, Aboagye, RG, Abolhassani, H, Aboye, GB, Abtew, YD, Accrombessi, MMK, Adane, DE, Adane, TD, Addo, IY, Adesina, MA, Adeyinka, DA, Adnani, QES, Afzal, MS, Afzal, S, Agustina, R, Ahinkorah, BO, Ahmad, A, Ahmad, S, Ahmadi, S, Ahmed, A, Rashid, TA, Aiman, W, Ajami, M, Akbarialiabad, H, Alahdab, F, Al-Aly, Z, Alam, N, Alemayehu, A, Alhassan, RK, Ali, MA, Almustanyir, S, Al-Raddadi, RM, Al-Rifai, RH, Altirkawi, KA, Alvand, S, Alvis-Guzman, N, Amer, YSAD, Ameyaw, EK, Amu, H, Anagaw, TF, Ancuceanu, R, Anoushirvani, AA, Antwi, MH, Anvari, D, Arabloo, J, Aravkin, AY, Ariffin, H, Aripov, T, Arja, A, Arndt, MB, Arulappan, J, Aruleba, RT, Ashraf, T, Asresie, MB, Athari, SS, Atlaw, D, Aujayeb, A, Awoke, AA, Awoke, MA, Azadnajafabad, S, Azangou-Khyavy, M, Darshan, BB, Badawi, A, Badiye, AD, Baghcheghi, N, Bagheri, N, Bagherieh, S, Baig, AA, Banach, M, Banik, PC, Bantie, AT, Barr, RD, Barrow, A, Bashiri, A, Basu, S, Batiha, AMM, Begum, T, Belete, MA, Belo, L, Bensenor, IM, Berhie, AY, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhat, AN, Bhutta, ZA, Bikbov, B, Billah, SM, Birara, S, Bishai, JD, Bitaraf, S, Boloor, A, Botelho, JS, Burkart, K, Calina, D, Cembranel, F, Chakraborty, PA, Chanie, GS, Chattu, VK, Chien, JH, Chukwu, IS, Chung, E, Criqui, MH, Cruz-Martins, N, Dadras, O, Dagnew, GW, Dai, XC, Danawi, HA, Dandona, L, Dandona, R, Darwesh, AM, Das, JK, Das, S, De la Cruz-Gongora, V, Demisse, FW, Demissie, S, Demsie, DG, Desai, HD, Desalegn, M, Dessalegn, FN, Dessie, G, Dharmaratne, SD, Dhimal, M, Dhingra, S, Diaz, D, Didehdar, M, Dirac, MA, Diress, M, Doaei, S, Dodangeh, M, Doku, PN, Dongarwar, D, Dora, BT, Dsouza, HL, Edinur, HA, Ekholuenetale, M, Elagali, AEM, Elbahnasawy, MA, Elbarazi, I, ElGohary, GMT, Elhadi, M, El-Huneidi, W, Elmonem, MA, Enyew, DB, Eshetu, HB, Ewald, SB, Ezzeddini, R, Fagbamigbe, AF, Fasanmi, AO, Fatehizadeh, A, Fekadu, G, Feyisa, BR, Fischer, F, Fitzgerald, R, Foroutan, M, Fowobaje, KR, Gadanya, MA, Gaidhane, AM, Gaihre, S, Gaipov, A, Galali, Y, Galehdar, N, Garg, P, Garg, T, Gebremariam, YH, Gebremedhin, KB, Gebremichael, B, Gela, YY, Gerema, U, Getacher, L, Ghaffari, K, Ghafourifard, M, Ghamari, SH, Nour, MG, Ghashghaee, A, Gholamalizadeh, M, Ghozy, S, Gizaw, ATT, Glasbey, JC, Golechha, M, Goleij, P, Golitaleb, M, Goulart, AC, Goyomsa, GG, Guadie, HA, Gubari, MIM, Gudisa, Z, Gunawardane, DA, Gupta, R, Das Gupta, R, Gupta, S, Gupta, VK, Guta, A, Habibzadeh, P, Hamidi, S, Handal, AJ, Hanif, A, Hannan, MA, Harapan, H, Harorani, M, Hasaballah, AI, Hasan, MM, Hasani, H, Hassankhani, H, Hassen, MB, Hayat, K, Heidari, G, Hess, SY, Heyi, DZ, Hezam, K, Hiraike, Y, Holla, R, Hossain, SJ, Hosseini, K, Hosseini, MS, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Huang, JJ, Hussain, S, Hussien, FM, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Immurana, M, Inbaraj, LR, Islam, SMS, Ismail, NE, Merin, JL, Jamshidi, E, Janodia, MD, Jayarajah, U, Jayaram, S, Jebai, R, Jemal, B, Jeyakumar, A, Jha, RP, Jonas, JB, Joseph, N, Jozwiak, JJ, Kabir, A, Kalankesh, LR, Kalhor, R, Kamal, VK, Kandel, H, Kanko, TK, Karaye, IM, Kashoo, FZ, Katoto, PDMC, Kauppila, JH, Kaur, H, Kayode, GA, Kebede, AD, Keshri, VR, Keykhaei, M, Khader, YS, Khajuria, H, Khalid, N, Khammarnia, M, Khan, IA, Khan, MAB, Khatab, K, Khazaei, Z, Khubchandani, J, Kim, YJ, Kimokoti, RW, Kisa, S, Kompani, F, Kosen, S, Laxminarayana, SLK, Krishan, K, Defo, BK, Kuddus, M, Kumar, GA, Kumar, N, Kurmi, OP, Kuti, O, Lal, DK, Landires, I, Larsson, AO, Lassi, ZS, Latief, K, Laxmaiah, A, Ledda, C, Lee, SW, Legesse, SM, Liu, XF, Lorenzovici, L, Machado, VS, Mahajan, PB, Mahjoub, S, Mahmoodpoor, A, Mahmoudi, E, Rad, EM, Mallhi, TH, Malta, DC, Masoudi, S, Masoumi, SZ, Medina, JRC, Mejia-Rodriguez, F, Mendes, JJ, Mendoza, W, Mendoza-Cano, O, Mentis, AFA, Meresa, HA, Mestrovic, T, Miazgowski, T, Mirghafourvand, M, Mirica, A, Mirza, M, Misganaw, A, Misra, S, Mohammad, DK, Mohammadi, S, Mohammed, S, Mohan, S, Moka, N, Mokdad, AH, Momtazmanesh, S, Monasta, L, Moni, MA, Moosavi, D, Moradi, M, Mosapour, A, Mostafavi, E, Muche, T, Mulita, F, Mulu, GB, Musina, AM, Mustafa, G, Nagarajan, AJ, Nair, TS, Swamy, SN, Nassereldine, H, Natto, ZS, Nayak, BP, Naz, S, Negoi, I, Negoi, RI, Nguefack-Tsague, G, Ngunjiri, JW, Niazi, RK, Noori, M, Nowroozi, A, Nurrika, D, Nuruzzaman, KM, Nzoputam, OJ, Oancea, B, Obaidur, RM, Obsa, MS, Odhiambo, JN, Ogunsakin, RE, Okati-Aliabad, H, Okonji, OC, Oladunjoye, AO, Oladunjoye, OO, Olagunju, AT, Olufadewa, II, Bali, AO, Omonisi, AEE, Ortiz, A, Owolabi, MO, Padubidri, JR, Pakzad, R, Palicz, T, Pandey, A, Pandya, AK, Papadopoulou, P, Pardhan, S, Patel, J, Pathak, A, Pathan, AR, Paudel, R, Paudel, U, Pawar, S, Pereira, G, Perico, N, Perna, S, Perumalsamy, N, Petcu, IR, Pickering, BV, Piracha, ZZ, Pollok, RCG, Pradhan, PMS, Prashant, A, Qattea, I, Syed, ZQ, Rahim, F, Rahimi, M, Rahman, A, Rahman, MHU, Rahman, M, Rahmani, AM, Rahmani, S, Rai, RK, Raimondo, I, Rajaa, S, Ram, P, Rana, J, Ranjha, MMAN, Rao, CR, Rao, SJ, Rashedi, S, Rashidi, MM, Rawaf, S, Rawal, L, Raza, RZ, Redwan, EMM, Remuzzi, G, Rezaei, M, Rezaei, N, Richards, T, Rickard, J, Rodriguez, JAB, Roever, L, Roshandel, G, Roy, B, Rwegerera, GM, Saad, AMA, Sabour, S, Saddik, B, Sadeghi, M, Sadeghian, S, Saeed, U, Sahebkar, A, Sahoo, H, Salem, MR, Samy, AM, Sankararaman, S, Santoro, R, Santos, IS, Satpathy, M, Saya, GK, Seboka, BT, Senbeta, AM, Senthilkumaran, S, Seylani, A, Shafeghat, M, Shah, PA, Shaikh, MA, Shanawaz, M, Shannawaz, M, Sharew, MM, Sharma, P, Sheikhi, RA, Shenoy, SM, Shetty, A, Shetty, BSK, Shetty, JK, Shetty, PH, Shin, JI, Shivalli, S, Shivarov, V, Shobeiri, P, Shorofi, SA, Sikder, MK, Sima, AR, Simegn, W, Singh, JA, Singh, NP, Singh, P, Singh, S, Siraj, MS, Sisay, Y, Skryabina, AA, Solomon, Y, Song, Y, Sorensen, RJD, Stanaway, JD, Suchdev, PS, Sufiyan, MB, Sultana, S, Szeto, MD, Tabaeian, SP, Tahamtan, A, Taheri, M, Soodejani, MT, Tamir, Z, Tan, KK, Tariqujjaman, M, Tarkang, EE, Tat, NY, Tefera, YM, Temsah, MH, Thapar, R, Thiyagarajan, A, Ticoalu, JHV, Tigabu, BM, Tiyuri, A, Tobe-Gai, R, Tovani-Palone, MR, Tran, MTN, Tusa, BS, Ullah, I, Umer, AA, Unnikrishnan, B, Vacante, M, Tahbaz, SV, Valdez, PR, Vart, P, Varthya, SB, Vaziri, S, Verma, M, Veroux, M, Vervoort, D, Vu, LG, Wagaye, B, Weldegebreal, F, Wickramasinghe, ND, Woldemariam, M, Wonde, TE, Wubetie, GA, Xu, XY, Yari, K, Yazdanpanah, F, Yehualashet, SS, Yigit, A, Yigit, V, Yisihak, E, Yon, DK, Yonemoto, N, Young, MF, Yu, CH, Yunusa, I, Zahir, M, Zaki, L, Zaman, BA, Zamora, N, Zare, I, Zareshahrabadi, Z, Zenebe, GA, Zhang, ZJ, Zheng, P, Zoladl, M, Hay, SI, Murray, CJL, Kassebaum, NJ

المصدر: The Lancet. Haematology. 10(9):e713-e734

مصطلحات موضوعية: Medicin och hälsovetenskap

الوصول الحر: http://kipublications.ki.se/Default.aspx?queryparsed=id:154129224Test

المؤلفون: Thomson, AM, McHugh, TA, Oron, AP, Teply, C, Lonberg, N, Tella, VMV, Wilner, LB, Fuller, K, Hagins, H, Aboagye, RG, Aboye, MB, Abu-Gharbieh, E, Abu-Zaid, A, Addo, IY, Ahinkorah, BO, Ahmad, A, AlRyalat, SAS, Amu, H, Aravkin, AY, Arulappan, J, Atout, MMW, Badiye, AD, Bagherieh, S, Banach, M, Banakar, M, Bardhan, M, Barrow, A, Bedane, DA, Bensenor, IM, Bhagavathula, AS, Bhardwaj, P, Bhat, AN, Bhutta, ZA, Bilalaga, MM, Bishai, JD, Bitaraf, S, Boloor, A, Butt, MH, Chattu, VK, Chu, DT, Dadras, O, Dai, XC, Danaei, B, Dang, AK, Demisse, FW, Dhimal, M, Diaz, D, Djalalinia, S, Dongarwar, D, Elhadi, M, Elmonem, MA, Esezobor, CI, Etaee, F, Eyawo, O, Fagbamigbe, AF, Fatehizadeh, A, Force, LM, Gardner, WM, Ghaffari, K, Gill, PS, Golechha, M, Goleij, P, Gupta, VK, Hasani, H, Hassan, TS, Hassen, MB, Ibitoye, SE, Ikiroma, AI, Iwu, CCD, James, PB, Jayaram, S, Jebai, R, Jha, RP, Joseph, N, Kalantar, F, Kandel, H, Karaye, IM, Kassahun, WD, Khan, IA, Khanmohammadi, S, Kisa, A, Kompani, F, Krishan, K, Landires, I, Lim, SS, Mahajan, PB, Mahjoub, S, Majeed, A, Marasini, BP, Meresa, HA, Mestrovic, T, Minhas, S, Misganaw, A, Mokdad, AH, Monasta, L, Mustafa, G, Nair, TS, Swamy, SN, Nassereldine, H, Natto, ZS, Naveed, M, Nayak, BP, Noubiap, JJ, Noyes, T, Nri-ezedi, CA, Nwatah, VE, Nzoputam, CI, Nzoputam, OJ, Okonji, OC, Onikan, AO, Owolabi, MO, Patel, J, Pati, S, Pawar, S, Petcu, IR, Piel, FB, Qattea, I, Rahimi, M, Rahman, M, Rawaf, S, Redwan, EMM, Rezaei, N, Saddik, B, Saeed, U, Sharif-Askari, FS, Samy, AM, Schumacher, AE, Shaker, E, Shetty, A, Sibhat, MM, Singh, JA, Suleman, M, Sunuwar, DR, Szeto, MD, Tamuzi, JJL, Tat, NY, Taye, BT, Temsah, MH, Umair, M, Tahbaz, SV, Wang, C, Wickramasinghe, ND, Yigit, A, Yigit, V, Yunusa, I, Zaman, BA, Zangiabadian, M, Zheng, P, Hay, S, Naghavi, M, Murray, CJL, Kassebaum, NJ

المصدر: The Lancet. Haematology. 10(8):E585-E599

مصطلحات موضوعية: Medicin och hälsovetenskap

الوصول الحر: http://kipublications.ki.se/Default.aspx?queryparsed=id:153938784Test

المؤلفون: Ong, KL, Stafford, LK, Mclaughlin, SA, Boyko, EJ, Vollset, SE, Smith, AE, Dalton, BE, Duprey, J, Cruz, JA, Hagins, H, Lindstedt, PA, Aali, A, Abate, YH, Abate, MD, Abbasian, M, Abbasi-Kangevari, Z, Abbasi-Kangevari, M, Abd ElHafeez, S, Abd-Rabu, R, Abdulah, DM, Abdullah, AM, Abedi, V, Abidi, H, Aboagye, RG, Abolhassani, H, Abu-Gharbieh, E, Abu-Zaid, A, Adane, TD, Adane, DE, Addo, IY, Adegboye, OA, Adekanmbi, V, Adepoju, AV, Adnani, QES, Afolabi, RF, Agarwal, G, Aghdam, ZB, Agudelo-Botero, M, Arriagada, CEA, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, D, Ahmad, R, Ahmad, S, Ahmad, A, Ahmadi, A, Ahmadi, K, Ahmed, A, Ahmed, LA, Ahmed, SA, Ajami, M, Akinyemi, RO, Al Hamad, H, Hasan, SMA, AL-Ahdal, TMA, Alalwan, TA, Al-Aly, Z, Albataineh, M, Alcalde-Rabanal, JE, Alemi, S, Ali, H, Alinia, T, Aljunid, SM, Almustanyir, S, Al-Raddadi, RM, Alvis-Guzman, N, Amare, F, Ameyaw, EK, Amiri, S, Amusa, GA, Andrei, CL, Anjana, RM, Ansar, A, Ansari, G, Ansari-Moghaddam, A, Anyasodor, AE, Arabloo, J, Aravkin, AY, Areda, D, Arifin, H, Arkew, M, Armocida, B, Aernloev, J, Artamonov, AA, Arulappan, J, Aruleba, RT, Arumugam, A, Aryan, Z, Asemu, MT, Asghari-Jafarabadi, M, Askari, E, Asmelash, D, Astell-Burt, T, Athar, M, Athari, SS, Atout, MMW, Avila-Burgos, L, Awaisu, A, Azadnajafabad, S, Darshan, BB, Babamohamadi, H, Badar, M, Badawi, A, Badiye, A, Baghcheghi, N, Bagheri, N, Bagherieh, S, Bah, S, Bahadory, S, Bai, RH, Baig, AA, Baltatu, OC, Baradaran, HR, Barchitta, M, Bardhan, M, Barengo, NC, Baernighausen, TW, Barone, MTU, Barone-Adesi, F, Barrow, A, Bashiri, H, Basiru, A, Basu, S, Batiha, AMM, Batra, K, Bayih, MT, Bayileyegn, NS, Behnoush, AH, Bekele, AB, Belete, MA, Belgaumi, UI, Belo, L, Bennett, DA, Bensenor, IM, Berhe, K, Berhie, AY, Bhaskar, S, Bhat, AN, Bhatti, JS, Bikbov, B, Bilal, F, Bintoro, BS, Bitaraf, S, Bitra, VR, Bjegovic-Mikanovic, V, Bodolica, V, Boloor, A, Brauer, M, Brazo-Sayavera, J, Brenner, H, Butt, ZA, Calina, D, Campos, LA, Campos-Nonato, IR, Cao, Y, Cao, C, Car, J, Carvalho, M, Castaneda-Orjuela, CA, Catala-Lopez, F, Cerin, E, Chadwick, J, Chandrasekar, EK, Chanie, GS, Charan, J, Chattu, VK, Chauhan, K, Cheema, HA, Abebe, EC, Chen, SM, Cherbuin, N, Chichagi, F, Chidambaram, SB, Cho, WCS, Choudhari, SG, Chowdhury, R, Chowdhury, EK, Chu, DT, Chukwu, IS, Chung, SC, Coberly, K, Columbus, A, Contreras, D, Cousin, E, Criqui, MH, Cruz-Martins, N, Cuschieri, S, Dabo, B, Dadras, O, Dai, XC, Damasceno, AAM, Dandona, R, Dandona, L, Das, S, Dascalu, AM, Dash, NR, Dashti, M, Davila-Cervantes, CA, Cruz-Gongora, VD, Debele, GR, Delpasand, K, Demisse, FW, Demissie, GD, Deng, XL, Denova-Gutierrez, E, Deo, S, Dervisevic, E, Desai, HD, Desale, AT, Dessie, AM, Desta, F, Dewan, SMR, Dey, S, Dhama, K, Dhimal, M, Diao, NY, Diaz, D, Dinu, M, Diress, M, Djalalinia, S, Doan, LP, Dongarwar, D, Figueiredo, FWD, Duncan, BB, Dutta, S, Dziedzic, AM, Edinur, HA, Ekholuenetale, M, Ekundayo, TC, Elgendy, IY, Elhadi, M, El-Huneidi, W, Elmeligy, OAA, Elmonem, MA, Endeshaw, D, Esayas, HL, Eshetu, HB, Etaee, F, Fadhil, I, Fagbamigbe, AF, Fahim, A, Falahi, S, Faris, MEM, Farrokhpour, H, Farzadfar, F, Fatehizadeh, A, Fazli, G, Feng, XQ, Ferede, TY, Fischer, F, Flood, D, Forouhari, A, Foroumadi, R, Koudehi, MF, Gaidhane, AM, Gaihre, S, Gaipov, A, Galali, Y, Ganesan, B, Garcia-Gordillo, MA, Gautam, RK, Gebrehiwot, M, Gebrekidan, KG, Gebremeskel, TG, Getacher, L, Ghadirian, F, Ghamari, SH, Nour, MG, Ghassemi, F, Golechha, M, Goleij, P, Golinelli, D, Gopalani, SV, Guadie, HA, Guan, SY, Gudayu, TW, Guimaraes, RA, Guled, RA, Gupta, R, Gupta, K, Gupta, VB, Gupta, VK, Gyawali, B, Haddadi, R, Hadi, NR, Haile, TG, Hajibeygi, R, Haj-Mirzaian, A, Halwani, R, Hamidi, S, Hankey, GJ, Hannan, MA, Haque, S, Harandi, H, Harlianto, N, Hasan, SMM, Hasan, S, Hasani, H, Hassanipour, S, Hassen, MB, Haubold, J, Hayat, K, Heidari, G, Heidari, M, Hessami, K, Hiraike, Y, Holla, R, Hossain, S, Hossain, MS, Hosseini, MS, Hosseinzadeh, M, Hosseinzadeh, H, Huang, JJ, Huda, N, Hussain, S, Huynh, HH, Hwang, BF, Ibitoye, SE, Ikeda, N, Ilic, IM, Ilic, M, Inbaraj, LR, Iqbal, A, Islam, SMS, Islam, RM, Ismail, NE, Iso, H, Isola, G, Itumalla, R, Iwagami, M, Iwu, CCD, Iyamu, IO, Iyasu, AN, Jacob, L, Jafarzadeh, A, Jahrami, H, Jain, R, Jaja, C, Jamalpoor, Z, Jamshidi, E, Janakiraman, B, Jayanna, K, Jayapal, SK, Jayaram, S, Jayawardena, R, Jebai, R, Jeong, W, Jin, YZ, Jokar, M, Jonas, JB, Joseph, N, Joseph, A, Joshua, CE, Joukar, F, Jozwiak, JJ, Kaambwa, B, Kabir, A, Kabthymer, RH, Kadashetti, V, Kahe, F, Kalhor, R, Kandel, H, Karanth, S, Karaye, IM, Karkhah, S, Katoto, PD, Kaur, N, Kazemian, S, Kebede, SA, Khader, YS, Khajuria, H, Khalaji, A, AB Khan, M, Khan, M, Khan, A, Khanal, S, Khatatbeh, MM, Khater, AM, Khateri, S, Khorashadizadeh, F, Khubchandani, J, Kibret, BG, Kim, MS, Kimokoti, RW, Kisa, A, Kivimaki, M, Kolahi, AA, Komaki, S, Kompani, F, Koohestani, HR, Korzh, O, Kostev, K, Kothari, N, Koyanagi, A, Krishan, K, Krishnamoorthy, Y, Defo, BK, Kuddus, M, Kuddus, MA, Kumar, R, Kumar, H, Kundu, S, Kurniasari, MD, Kuttikkattu, A, La Vecchia, C, Lallukka, T, Larijani, B, Larsson, AO, Latief, K, Lawal, BK, Le, TTT, Le, TTB, Lee, SWH, Lee, M, Lee, WC, Lee, PH, Lee, SW, Legesse, SM, Lenzi, J, Li, YZ, Li, MC, Lim, SS, Lim, LL, Liu, XF, Liu, CJ, Lo, CH, Lopes, G, Lorkowski, S, Lozano, R, Lucchetti, G, Maghazachi, AA, Mahasha, PW, Mahjoub, S, Mahmoud, MA, Mahmoudi, R, Mahmoudimanesh, M, Mai, AT, Majeed, A, Sanaye, PM, Makris, KC, Malhotra, K, Malik, AA, Malik, I, Mallhi, TH, Malta, DC, Mamun, AA, Mansouri, B, Marateb, HR, Mardi, P, Martini, S, Martorell, M, Marzo, RR, Masoudi, R, Masoudi, S, Mathews, E, Maugeri, A, Mazzaglia, G, Mekonnen, T, Meshkat, M, Mestrovic, T, Jonasson, JM, Miazgowski, T, Michalek, IM, Minh, LHN, Mini, GK, Miranda, JJ, Mirfakhraie, R, Mirrakhimov, EM, Mirza-Aghazadeh-Attari, M, Misganaw, A, Misgina, KH, Mishra, M, Moazen, B, Mohamed, NS, Mohammadi, E, Mohammadi, M, Mohammadian-Hafshejani, A, Mohammadshahi, M, Mohseni, A, Mojiri-Forushani, H, Mokdad, AH, Momtazmanesh, S, Monasta, L, Moniruzzaman, M, Mons, U, Montazeri, F, Ghalibaf, AM, Moradi, Y, Moradi, M, Sarabi, MM, Morovatdar, N, Morrison, SD, Morze, J, Mossialos, E, Mostafavi, E, Mueller, UO, Mulita, F, Mulita, A, Murillo-Zamora, E, Musa, KI, Mwita, JC, Nagaraju, SP, Naghavi, M, Nainu, F, Nair, TS, Najmuldeen, HHR, Nangia, V, Nargus, S, Naser, AY, Nassereldine, H, Natto, ZS, Nauman, J, Nayak, BP, Ndejjo, R, Negash, H, Negoi, RI, Nguyen, HTH, Nguyen, DH, Nguyen, PT, Nguyen, VT, Nguyen, HQ, Niazi, RK, Nigatu, YT, Ningrum, DNA, Nizam, MA, Nnyanzi, LA, Noreen, M, Noubiap, JJ, Nzoputam, OJ, Nzoputam, CI, Oancea, B, Odogwu, NM, Odukoya, OO, Ojha, VA, Okati-Aliabad, H, Okekunle, AP, Okonji, OC, Okwute, PG, Olufadewa, II, Onwujekwe, OE, Ordak, M, Ortiz, A, Osuagwu, UL, Oulhaj, A, Owolabi, MO, Padron-Monedero, A, Padubidri, JR, Palladino, R, Panagiotakos, D, Panda-Jonas, S, Pandey, A, Pandi-Perumal, SR, Stoian, AMP, Pardhan, S, Parekh, T, Parekh, U, Pasovic, M, Patel, J, Patel, JR, Paudel, U, Pepito, VCF, Pereira, M, Perico, N, Perna, S, Petcu, IR, Petermann-Rocha, FE, Podder, V, Postma, MJ, Pourali, G, Pourtaheri, N, Prates, EJS, Qadir, MMF, Qattea, I, Raee, P, Rafique, I, Rahimi, M, Rahimifard, M, Rahimi-Movaghar, V, Rahman, MO, Rahman, MA, Rahman, MHU, Rahman, M, Rahman, MM, Rahmani, M, Rahmani, S, Rahmanian, V, Rahmawaty, S, Rahnavard, N, Rajbhandari, B, Ram, P, Ramazanu, S, Rana, J, Rancic, N, Ranjha, MMAN, Rao, CR, Rapaka, D, Rasali, DP, Rashedi, S, Rashedi, V, Rashid, AM, Rashidi, MM, Ratan, ZA, Rawaf, S, Rawal, L, Redwan, EMM, Remuzzi, G, Rengasamy, KRR, Renzaho, AMN, Reyes, LF, Rezaei, N, Rezaeian, M, Rezazadeh, H, Riahi, SM, Rias, YA, Riaz, M, Ribeiro, D, Rodrigues, M, Rodriguez, JAB, Roever, L, Rohloff, P, Roshandel, G, Roustazadeh, A, Rwegerera, GM, Saad, AMA, Saber-Ayad, MM, Sabour, S, Sabzmakan, L, Saddik, B, Sadeghi, E, Saeed, U, Moghaddam, SS, Safi, S, Safi, SZ, Saghazadeh, A, Sharif-Askari, NS, Sharif-Askari, FS, Sahebkar, A, Sahoo, SS, Sahoo, H, Saif-Ur-Rahman, KM, Sajid, MR, Salahi, S, Saleh, MA, Salehi, MA, Salomon, JA, Sanabria, J, Sanjeev, RK, Sanmarchi, F, Santric-Milicevic, MM, Sarasmita, MA, Sargazi, S, Sathian, B, Sathish, T, Sawhney, M, Schlaich, MP, Schmidt, MI, Schuermans, A, Seidu, AA, Kumar, NS, Sepanlou, SG, Sethi, Y, Seylani, A, Shabany, M, Shafaghat, T, Shafeghat, M, Shafie, M, Shah, NS, Shahid, S, Shaikh, MA, Shanawaz, M, Shannawaz, M, Sharfaei, S, Shashamo, BB, Shiri, R, Shittu, A, Shivakumar, KM, Shivalli, S, Shobeiri, P, Shokri, F, Shuval, K, Sibhat, MM, Silva, LMLR, Simpson, CR, Singh, JA, Singh, P, Singh, S, Siraj, MS, Skryabina, AA, Sohag, AA, Soleimani, H, Solikhah, S, Soltani-Zangbar, MS, Somayaji, R, Sorensen, RJD, Starodubova, AV, Sujata, S, Suleman, M, Sun, J, Sundstrom, J, Tabares-Seisdedos, R, Tabatabaei, SM, Tabatabaeizadeh, SA, Tabish, M, Taheri, M, Taheri, E, Taki, E, Tamuzi, JJLL, Tan, KK, Tat, NY, Taye, BT, Temesgen, WA, Temsah, MH, Tesler, R, Thangaraju, P, Thankappan, KR, Thapa, R, Tharwat, S, Thomas, N, Ticoalu, JHV, Tiyuri, A, Tonelli, M, Tovani-Palone, MR, Trico, D, Trihandini, I, Tripathy, JP, Tromans, SJ, Tsegay, GM, Tualeka, AR, Tufa, DG, Tyrovolas, S, Ullah, S, Upadhyay, E, Vahabi, SM, Vaithinathan, AG, Valizadeh, R, van Daalen, KR, Vart, P, Varthya, SB, Vasankari, TJ, Vaziri, S, Verma, MV, Verras, GI, Vo, DC, Wagaye, B, Waheed, Y, Wang, ZY, Wang, YQ, Wang, C, Wang, F, Wassie, GT, Wei, MYW, Weldemariam, AH, Westerman, R, Wickramasinghe, ND, Wu, YF, Wulandari, RDWI, Xia, J, Xiao, H, Xu, SW, Xu, XY, Yada, DY, Yang, L, Yatsuya, H, Yesiltepe, M, Yi, SY, Yohannis, HK, Yonemoto, N, You, YY, Bin Zaman, S, Zamora, N, Zare, I, Zarea, K, Zarrintan, A, Zastrozhin, MS, Zeru, NG, Zhang, ZJ, Zhong, CW, Zhou, JJ, Zielinska, M, Zikarg, YT, Zodpey, S, Zoladl, M, Zou, ZY, Zumla, A, Zuniga, YMH, Magliano, DJ, Murray, CJL, Hay, SI, Vos, T

المصدر: Lancet (London, England). 402(10397):203-234

مصطلحات موضوعية: Medicin och hälsovetenskap

الوصول الحر: http://kipublications.ki.se/Default.aspx?queryparsed=id:153970094Test

المؤلفون: Azzopardi, PS, Kerr, JA, Francis, KL, Sawyer, SM, Kennedy, EC, Steer, AC, Graham, SM, Viner, RM, Ward, JL, Hennegan, J, Pham, M, Habito, CMD, Kurji, J, Cini, K, Beeson, JG, Brown, A, Murray, CJL, Abbasi-Kangevari, M, Abolhassani, H, Adekanmbi, V, Agampodi, SB, Ahmed, MB, Ajami, M, Akbarialiabad, H, Akbarzadeh-Khiavi, M, AL-Ahdal, TMA, Ali, MM, Samakkhah, SA, Alimohamadi, Y, Alipour, V, Al-Jumaily, A, Amiri, S, Amirzade-Iranaq, MH, Anoushiravani, A, Anvari, D, Arabloo, J, Arab-Zozani, M, Arkew, M, Armocida, B, Asadi-Pooya, AA, Asemi, Z, Asgary, S, Athari, SS, Azami, H, Azangou-Khyavy, M, Azizi, H, Bagheri, N, Bagherieh, S, Barone-Adesi, F, Barteit, S, Basu, S, Belete, MA, Belo, L, Berhie, AY, Bijani, A, Bikbov, B, Burkart, K, Carreras, G, Charalampous, P, Abebe, EC, Cruz-Martins, N, Dai, XC, Dandona, L, Dandona, R, Degualem, SM, Demetriades, AK, Demlash, AA, Desta, AA, Dianatinasab, M, Doaei, S, Dorostkar, F, Effendi, DE, Emami, A, Bain, LE, Eskandarieh, S, Esmaeilzadeh, F, Faramarzi, A, Fatehizadeh, A, Ferrara, P, Fetensa, G, Fischer, F, Flor, LS, Forouhari, A, Foroutan, M, Gaihre, S, Galehdar, N, Gallus, S, Gautam, RK, Gebrehiwot, M, Gebremeskel, TG, Getacher, L, Getachew, ME, Ghamari, SH, Nour, MG, Goleij, P, Golitaleb, M, Gorini, G, Gupta, VK, Hashemian, M, Hassankhani, H, Heidari, M, Heyi, DZ, Isola, G, Jaafari, J, Javanmardi, F, Jonas, JB, Jozwiak, JJ, Juerisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kalhor, R, Kauppila, JH, Kaur, H, Kayode, GA, Keikavoosi-Arani, L, Khammarnia, M, AB Khan, M, Khatab, K, Kashani, HRK, Kolahi, AA, Koohestani, HR, Koyanagi, A, Kumar, GA, Kurmi, OP, Kyu, HH, La Vecchia, C, Lallukka, T, Lim, SS, Loureiro, JA, Mahjoub, S, Mahmoudi, R, Majeed, A, Rad, EM, Maleki, A, Mansour-Ghanaei, F, Marjani, A, Mathioudakis, AG, Mehri, F, Mentis, AFA, Mestrovic, T, Mirica, A, Misganaw, A, Mohammadian-Hafshejani, A, Mohammed, H, Mohammed, S, Mokdad, AH, Mokhtarzadehazar, P, Monasta, L, Moradi, M, Moradzadeh, M, Morovatdar, N, Mueller, UO, Mulita, F, Mulu, GBB, Muthupandian, S, Naik, GR, Nashwan, AJJ, Nejadghaderi, SA, Netsere, HB, Noor, NM, Noori, M, Oancea, B, Oguntade, AS, Okati-Aliabad, H, Otoiu, A, Padron-Monedero, A, Pakzad, R, Pandey, A, Pardhan, S, Parikh, RR, Patel, J, Pensato, U, Peprah, P, Perico, N, Poddighe, D, Postma, MJ, Rahim, F, Rahimi-Movaghar, V, Rahmani, S, Rahmanian, V, Rawaf, S, Razeghian-Jahromi, I, Regasa, MT, Remuzzi, G, Rezaeian, M, Riad, A, Romero-Rodriguez, E, Ronfani, L, Pramanik, KR, Sabour, S, Sadeghian, S, Saeb, MR, Safary, A, Sahebkar, A, Sahiledengle, B, Samadzadeh, S, Sarveazad, A, Sethi, Y, Shahabi, S, Shahraki-Sanavi, F, Shams-Beyranvand, M, Sharafi, K, Sharew, NT, Sheikh, A, Sheikhi, RA, Shiri, R, Socea, B, Soltani-Zangbar, MS, Tabares-Seisdedos, R, Tabatabai, S, Soodejani, MT, Oliaee, RT, Tiyuri, A, Tovani-Palone, MR, Tualeka, AR, Valizadeh, R, Van den Eynde, J, Vasankari, TJ, Vos, T, Walde, MT, Wang, YZ, Wei, FL, Westerman, R, Yadav, V, Yaya, S, Zare, I, Zhu, B, Zoladl, M, Zumla, A, Hay, S, Patton, GC

المصدر: Lancet (London, England). 402(10398):313-335

مصطلحات موضوعية: Medicin och hälsovetenskap

الوصول الحر: http://kipublications.ki.se/Default.aspx?queryparsed=id:153625994Test

المؤلفون: Holley, Dustin, Dsa, Jovin, Mahjoub, Hossein Nourkhiz, Ali, Gibran, Naes, Tyler, Moradi-Pari, Ehsan, Kallepalli, Pawan Sai

مصطلحات موضوعية: Computer Science - Robotics, Electrical Engineering and Systems Science - Systems and Control

الوصف: Enhancing simulation environments to replicate real-world driver behavior is essential for developing Autonomous Vehicle technology. While some previous works have studied the yielding reaction of lag vehicles in response to a merging car at highway on-ramps, the possible lane-change reaction of the lag car has not been widely studied. In this work we aim to improve the simulation of the highway merge scenario by including the lane-change reaction in addition to yielding behavior of main-lane lag vehicles, and we evaluate two different models for their ability to capture this reactive lane-change behavior. To tune the payoff functions of these models, a novel naturalistic dataset was collected on U.S. highways that provided several hours of merge-specific data to learn the lane change behavior of U.S. drivers. To make sure that we are collecting a representative set of different U.S. highway geometries in our data, we surveyed 50,000 U.S. highway on-ramps and then selected eight representative sites. The data were collected using roadside-mounted lidar sensors to capture various merge driver interactions. The models were demonstrated to be configurable for both keep-straight and lane-change behavior. The models were finally integrated into a high-fidelity simulation environment and confirmed to have adequate computation time efficiency for use in large-scale simulations to support autonomous vehicle development.
Comment: 10 pages, 7 figures, submitted to IEEE Intelligent Vehicles Symposium (IV) 2024

الوصول الحر: http://arxiv.org/abs/2404.09851Test

المؤلفون: Khlifi, Wiem, Singh, Siddarth, Mahjoub, Omayma, de Kock, Ruan, Vall, Abidine, Gorsane, Rihab, Pretorius, Arnu

مصطلحات موضوعية: Computer Science - Artificial Intelligence, I.2.11, I.2.0, A.0

الوصف: Cooperative multi-agent reinforcement learning (MARL) has made substantial strides in addressing the distributed decision-making challenges. However, as multi-agent systems grow in complexity, gaining a comprehensive understanding of their behaviour becomes increasingly challenging. Conventionally, tracking team rewards over time has served as a pragmatic measure to gauge the effectiveness of agents in learning optimal policies. Nevertheless, we argue that relying solely on the empirical returns may obscure crucial insights into agent behaviour. In this paper, we explore the application of explainable AI (XAI) tools to gain profound insights into agent behaviour. We employ these diagnostics tools within the context of Level-Based Foraging and Multi-Robot Warehouse environments and apply them to a diverse array of MARL algorithms. We demonstrate how our diagnostics can enhance the interpretability and explainability of MARL systems, providing a better understanding of agent behaviour.
Comment: 4 pages, AAAI XAI4DRL workshop 2023

الوصول الحر: http://arxiv.org/abs/2312.08468Test

المؤلفون: Mahjoub, Omayma, de Kock, Ruan, Singh, Siddarth, Khlifi, Wiem, Vall, Abidine, Tessera, Kale-ab, Pretorius, Arnu

مصطلحات موضوعية: Computer Science - Artificial Intelligence, I.2.11, I.2.0, A.0

الوصف: Measuring the contribution of individual agents is challenging in cooperative multi-agent reinforcement learning (MARL). In cooperative MARL, team performance is typically inferred from a single shared global reward. Arguably, among the best current approaches to effectively measure individual agent contributions is to use Shapley values. However, calculating these values is expensive as the computational complexity grows exponentially with respect to the number of agents. In this paper, we adapt difference rewards into an efficient method for quantifying the contribution of individual agents, referred to as Agent Importance, offering a linear computational complexity relative to the number of agents. We show empirically that the computed values are strongly correlated with the true Shapley values, as well as the true underlying individual agent rewards, used as the ground truth in environments where these are available. We demonstrate how Agent Importance can be used to help study MARL systems by diagnosing algorithmic failures discovered in prior MARL benchmarking work. Our analysis illustrates Agent Importance as a valuable explainability component for future MARL benchmarks.
Comment: 8 pages, AAAI XAI4DRL workshop 2023; references updated, figure 8 style updated, typos

الوصول الحر: http://arxiv.org/abs/2312.08466Test

المؤلفون: Singh, Siddarth, Mahjoub, Omayma, de Kock, Ruan, Khlifi, Wiem, Vall, Abidine, Tessera, Kale-ab, Pretorius, Arnu

مصطلحات موضوعية: Computer Science - Artificial Intelligence, I.2.11, I.2.0, A.0

الوصف: Establishing sound experimental standards and rigour is important in any growing field of research. Deep Multi-Agent Reinforcement Learning (MARL) is one such nascent field. Although exciting progress has been made, MARL has recently come under scrutiny for replicability issues and a lack of standardised evaluation methodology, specifically in the cooperative setting. Although protocols have been proposed to help alleviate the issue, it remains important to actively monitor the health of the field. In this work, we extend the database of evaluation methodology previously published by containing meta-data on MARL publications from top-rated conferences and compare the findings extracted from this updated database to the trends identified in their work. Our analysis shows that many of the worrying trends in performance reporting remain. This includes the omission of uncertainty quantification, not reporting all relevant evaluation details and a narrowing of algorithmic development classes. Promisingly, we do observe a trend towards more difficult scenarios in SMAC-v1, which if continued into SMAC-v2 will encourage novel algorithmic development. Our data indicate that replicability needs to be approached more proactively by the MARL community to ensure trust in the field as we move towards exciting new frontiers.
Comment: 6 pages, AAAI XAI4DRL workshop 2023; typos corrected, images updated, page count updated

الوصول الحر: http://arxiv.org/abs/2312.08463Test

المؤلفون: Tessera, Kale-ab, Tilbury, Callum Rhys, Abramowitz, Sasha, de Kock, Ruan, Mahjoub, Omayma, Rosman, Benjamin, Hooker, Sara, Pretorius, Arnu

مصطلحات موضوعية: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Computer Science - Multiagent Systems

الوصف: Optimising deep neural networks is a challenging task due to complex training dynamics, high computational requirements, and long training times. To address this difficulty, we propose the framework of Generalisable Agents for Neural Network Optimisation (GANNO) -- a multi-agent reinforcement learning (MARL) approach that learns to improve neural network optimisation by dynamically and responsively scheduling hyperparameters during training. GANNO utilises an agent per layer that observes localised network dynamics and accordingly takes actions to adjust these dynamics at a layerwise level to collectively improve global performance. In this paper, we use GANNO to control the layerwise learning rate and show that the framework can yield useful and responsive schedules that are competitive with handcrafted heuristics. Furthermore, GANNO is shown to perform robustly across a wide variety of unseen initial conditions, and can successfully generalise to harder problems than it was trained on. Our work presents an overview of the opportunities that this paradigm offers for training neural networks, along with key challenges that remain to be overcome.
Comment: Accepted at the Workshop on Advanced Neural Network Training (WANT) and Optimization for Machine Learning (OPT) at NeurIPS 2023

الوصول الحر: http://arxiv.org/abs/2311.18598Test