JCISE Editorial Board—Year 2024
Notice bibliographique
Résumé
The Journal of Computing and Information Science in Engineering (JCISE) publishes articles related to scientific computing methods (e.g., modeling, simulation, representation, and algorithm) and computational tools (e.g., high-performance computing, virtual and augmented reality) that aim to improve engineering products and systems for their complete lifecycle (e.g., design, manufacturing, operation, maintenance, disposal, and recycling). The interest areas include computer-aided design and manufacturing, computational geometry and geometry processing, cyber-physical-social systems, data analytics and machine learning, engineering optimization, human–computer interface and human modeling, intelligent manufacturing, machine intelligence and robotics system, modeling and simulation and scientific computing, precision engineering and reverse engineering, sustainability and product lifecycle management, and systems engineering and engineering informatics.Yan Wang, Georgia Institute of Technology, USAGaurav Ameta, Siemens Corporate Technology, USANabil Anwer, Ecole Normale Superieure Paris-Sarclay, FranceStephen Baek, University of Virginia, USAWilliam Bernstein, Air Force Research Laboratory, USALinkan Bian, Mississippi State University, USASeung-Kyum Choi, Georgia Institute of Technology, USAChih-Hsing Chu, National Tsing Hua University, TaiwanJonathan Roy Corney, University of Edinburgh, UKKaushal Desai, Indian Institute of Technology Jodhpur, IndiaEhsan Esfahani, State University of New York at Buffalo, USAFrancesco Ferrise, Politecnico di Milano, ItalyAmir H. Gandomi, University of Technology Sydney, AustraliaJohann Guilleminot, Duke University, USAB. Gurumoorthy, Indian Institute of Science, IndiaBin He, Shanghai University, ChinaAjay Joneja, Hong Kong University of Science and Technology, Hong KongKrishnanand Kaipa, Old Dominion University, USATsz-Ho Kwok, Concordia University, CanadaVinayak Raman Krishnamurthy, Texas A&M University, USAGuang Lin, Purdue University, USAYusheng Liu, Zhejiang University, ChinaYan Lu, National Institute of Standards and Technology, USAJianxi Luo, City University of Hong Kong, Hong Kong, ChinaYongsheng Ma, Southern University of Science and Technology, ChinaSamy Missoum, University of Arizona, USAJohn G. Michopoulos, Naval Research Laboratory, USADuhwan Mun, Korea University, South KoreaAlison Olechowski, University of Toronto, CanadaYayue Pan, University of Illinois at Chicago, USAAnurag Purwar, Stony Brook University, USAP. V. M. Rao, Indian Institute of Technology Delhi, IndiaCaterina Rizzi, University of Bergamo, ItalyKazuhiro Saitou, University of Michigan, USAShana Smith, National Taiwan University, TaiwanYu Song, Delft University of Technology, The NetherlandsKrishnan Suresh, University of Wisconsin, Madison, USAAtul Thakur, Indian Institute of Technology Patna, IndiaWenmeng Tian, Mississippi State University, USACameron Turner, Clemson University, USADouglas Van Bossuyt, Naval Postgraduate School, USAJun Wang, Nanjing University of Aeronautics and Astronautics, ChinaKristina Wärmefjord, Chalmers University of Technology, SwedenHui Yang, Pennsylvania State University, USAXiaowei Yue, Tsinghua University, ChinaZhinan Zhang, Shanghai Jiao Tong University, ChinaVinayak Raman Krishnamurthy, Texas A&M University, USADouglas Van Bossuyt, Naval Postgraduate School, USAJami J. Shah (Founding Editor-in-Chief), Ohio State University, USABahram Ravani (Former Editor-in-Chief), University of California, Davis, USASatyandra K. Gupta (Former Editor-in-Chief), University of Southern California, USAJanet Allen, University of Oklahoma, USAImre Horváth, Delft University of Technology, The NetherlandsRam D. Sriram, National Institute of Standards and Technology, USAJianrong Tan, Zhejiang University, ChinaAnindya Bhaduri, General Electric Research, USABopaya Bidanda, University of Pittsburgh, USASatish Bukkapatnam, Texas A&M University, USAQing (Cindy) Chang, University of Virginia, USAFrancisco Chinesta, ENSAM Institute of Technology, FranceBianca Maria Colosimo, Politecnico di Milano, ItalyElias Cueto, University of Zaragoza, SpainTonya Custis, Autodesk, USALiang Gao, Huazhong University of Science and Technology, ChinaAkhil Garg, Huazhong University of Science and Technology, ChinaZhaohui Geng, Ohio University, USABabak Heydari, Northeastern University, USAChen Kan, University of Texas at Arlington, USAMegan Konar, University of Illinois at Urbana-Champaign, USAAstrid Layton, Texas A&M University, USADan Li, Clemson University, USAChenang Liu, Oklahoma State University, USADehao Liu, Binghamton University, USAJie Liu, Carleton University, CanadaJunfeng Ma, Mississippi State University, USAZhenguo Nie, Tsinghua University, ChinaEvangelos Niforatos, Delft University of Technology, The NetherlandsZhou Quan, University of Birmingham, UKSandipp Krishnan Ravi, General Electric Research, USARahul Rai, Clemson University, USAZhenghui Sha, University of Texas at Austin, USAZiyou Song, National University of Singapore, SingaporeJohn Steuben, Naval Research Laboratory, USAGregory Vogl, National Institute of Standards and Technology, USAJian-Xun Wang, University of Notre Dame, USAXiaozhi Wang, ABS, USAYinan Wang, Rensselaer Polytechnic Institute, USARobert Wendrich, Rawshaping Technology, The NetherlandsPaul Witherell, National Institute of Standards and Technology, USAMark Yampolskiy, Auburn University, USAFan Zhang, Georgia Institute of Technology, USAPai Zheng, Hong Kong Polytechnic University, ChinaYunbo Zhang, Rochester Institute of Technology, USAFiona Zhao, McGill University, CanadaRegina Neequaye
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,004 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».