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Enregistrement W2001695553 · doi:10.1115/1.4029962

Acknowledging JMD's Associate and Guest Editors

2015· article· en· W2001695553 sur OpenAlexaboutno aff
Shapour Azarm

Notice bibliographique

RevueJournal of Mechanical Design · 2015
Typearticle
Langueen
DomaineEngineering
ThématiqueManufacturing Process and Optimization
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEditorial boardAssociate editorDiligenceLibrary scienceEngineeringComputer scienceEngineering managementManagementPsychology

Résumé

récupéré en direct d'OpenAlex

I would like to take this opportunity and thank all our Associate Editors (AEs) and Guest Editors (GEs) for their diligence and hard work on behalf of the journal.Once a paper is submitted to Journal of Mechanical Design (JMD), and after successfully passing an initial screening, it is assigned to one of our AEs, or GEs in the case of a special issue. Subsequently, an AE or GE takes the lead in handling review coordination for the paper. The review coordination involves identifying and inviting reviewers who are best suited to review the paper, following-up with the reviewers to obtain a timely review, and finally making a recommendation based on the reviews and the AEs or GEs own assessment of the paper. Clearly, AEs and GEs are key players in coordinating a successful peer review process.A list of current and past members of the Editorial Board including their biographies is given on the companion website of the journal.1 The journal's masthead can be found on ASME's Journal Tool website.2I am pleased to welcome several new AEs and GEs who recently joined the editorial board. They include:Dr. Dar-Zen Chen (AE) received his Ph.D. from the University of Maryland, College Park, MD in mechanical engineering. He is a Professor in the Department of Mechanical Engineering and Institute of Industrial Engineering at the National Taiwan University. In addition to robotics, kinematics, and mechanism design, his research interests cover intellectual property management, scientometrics, and competitive analysis.Dr. Massimiliano Gobbi (AE) received his Ph.D. in Applied Mechanics from the Politecnico di Milano in Italy. He is an Associate Professor of Mechanical Engineering at the Politecnico di Milano. His areas of interest include road vehicles engineering, optimization of complex systems, and advanced design.Dr. James Guest (AE) received his Ph.D. from the Princeton University in Civil Engineering. He is an Associate Professor of Civil Engineering at the Johns Hopkins University. His areas of interest include topology optimization, structural optimization, materials design, and design under uncertainty.Dr. Charles Kim (AE) received his Ph.D. in Mechanical Engineering from the University of Michigan, Ann Arbor, MI. He is an Associate Professor of Mechanical Engineering at the Bucknell University. His primary technical research interests are in methodologies for the design of compliant systems and soft robotic actuators.Dr. Nam-Ho Kim (AE) received his Ph.D. in the Department of Mechanical Engineering from the University of Iowa. He is a Professor of Mechanical and Aerospace Engineering at the University of Florida. His research areas include structural design optimization, design sensitivity analysis, design under uncertainty, structural health monitoring, nonlinear structural mechanics, and structural-acoustics.Dr. Gul Kremer (AE) received her Ph.D. from the Department of Engineering Management and Systems Engineering of the Missouri University of Science & Technology. She is a Professor of Engineering Design and Industrial Engineering at the Pennsylvania State University. Her areas of interest include design education, design decision-making, and sustainability in product design.Dr. David Myszka (AE) received his Ph.D. in mechanical engineering from the University of Dayton. He is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Dayton. He is co-director of the Design of Innovative Machines Laboratory, where he is involved in several academic and industrial projects related to machine and mechanism design, analysis, and experimentation.Dr. David Rosen (GE) received his Ph.D. at the University of Massachusetts in mechanical engineering. He is a Professor in the School of Mechanical Engineering at the Georgia Institute of Technology. He is Director of the Rapid Prototyping & Manufacturing Institute at the Georgia Tech. His research interests include computer-aided design, additive manufacturing, and design methodology.Dr. Tim Simpson (GE) received his Ph.D. in Mechanical Engineering from the Georgia Tech. He is a Professor of Mechanical and Industrial Engineering at the Pennsylvania State University. His areas of interest include product platforms, product family design, multidisciplinary design optimization, and additive manufacturing.Dr. Hai Xu (AE) received his Ph.D. in Mechanical Engineering from the Ohio State University. He is a Staff Engineer of General Motors Company serving as a Driveline Gear Technical Specialist at the GM's Global Vehicle Components and Subsystems unit. His areas of interest include gear design and manufacturing methods, gear geometry and applications, gear tribology, power loss, fatigue, and noise and vibration.Dr. Christopher Williams (GE) received his Ph.D. in Mechanical Engineering from the Georgia Tech. He is an Associate Professor and W. S. Pete White Chair for Innovation in Engineering Education at the Virginia Tech. His areas of interest include additive manufacturing (processes and materials), design for additive manufacturing, engineering design education.I would also like to take this opportunity and thank the AEs and GEs who recently completed their term. They are Drs. Jon Cagan (AE) from the CMU, Wei Chen (AE) from the Northwestern University, Mary Frecker (AE and GE) from the Penn State University, Ashok Goel (GE) from the Georgia Tech, Larry Howell (AE and GE) from the BYU, Chintien Huang (AE) from the National Cheng Kung University, Taiwan, Nancy Johnson (AE) from the GM, Michael Kokkolaras (AE) from the McGill University, Canada, Craig Lusk (AE) from the University of South Florida, Dan McAdams (GE) from the Texas A&M, Chris Paredis (AE) from the Georgia Tech, Karthik Ramani (AE) from the Purdue University, Alex Slocum (AE and GE) from the MIT, Robert Stone (GE) from the Oregon State University, Janis Terpenny (AE) from the Iowa State University, and Kwun-Lon Ting (AE) from the Tennessee Technological University.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,958
Score d'incertitude au seuil0,252

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,029
Tête enseignante GPT0,230
Écart entre enseignants0,201 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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