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Record W2001695553 · doi:10.1115/1.4029962

Acknowledging JMD's Associate and Guest Editors

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

Bibliographic record

VenueJournal of Mechanical Design · 2015
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsEditorial boardAssociate editorDiligenceLibrary scienceEngineeringComputer scienceEngineering managementManagementPsychology

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.230
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2015
Admission routes1
Has abstractyes

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