James C. Chen

dblp:14/3198 · DBLP profile ↗
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16ranked-venue papers
4as first author
5since 2021 · last 2026
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 7 · 2 since 2021Artificial intelligence and machine learning · 5 · 3 first-authorDatabases, data management, data science and information retrieval · 3 · 1 first-author · 3 since 2021Systems, architecture and hardware · 1
YearPublicationVenuePosition
2026 Application of GAN-based data augmentation and filtering methods for imbalanced grinding wheel specification classification
Tzu-Li Chen, James C. Chen, Yi-Jing Lin, Kuo-Ching Yao, Ping-Chen Chang
Adv. Eng. Informatics2
2024 Grinding wheel specification cybernetic recommendation with multi-task multi-imbalanced learning in smart manufacturing system
Kuo-Ching Yao, Tzu-Li Chen, James C. Chen, Chia-Ruei Li
Adv. Eng. Informatics3
2022 Imbalanced prediction of emergency department admission using natural language processing and deep neural network
Tzu-Li Chen, James C. Chen, Wen-Han Chang, Weide Tsai, Mei-Chuan Shih, Achmad Wildan Nabila
J. Biomed. Informatics2
2021 Combining empirical mode decomposition and deep recurrent neural networks for predictive maintenance of lithium-ion battery
James C. Chen, Tzu-Li Chen, Wei-Jun Liu, C. C. Cheng, Meng-Gung Li
Adv. Eng. Informatics1
2021 Reliability Evaluation of Production System With In-Line Stockers
abstract
A reliability evaluation method is proposed for production systems by applying the capacitated-flow production network (CFPN) model. In particular, this article considers in-line stockers to monitor and to avoid blockage and starvation in the CFPN. First, the minimal capacity that all cells (group of machines) should provide to meet demand is generated. Second, status of stocker is monitored via the proposed “stocker volume check table” to calculate the volume usage of a stocker, and the stocker nonutilization is then obtained. Finally, the system reliability is derived in terms of the minimal capacity vector and stocker nonutilization. An important contribution of this article is to avoid complicated dependency calculation when multiple stockers are considered. A practical case of printed circuit board production is further studied to illustrate the applicability of the proposed method.
Ping-Chen Chang, Yi-Kuei Lin, James C. Chen
IEEE Trans. Reliab.3
2020 Utilizing online stochastic optimization on scheduling of intensity-modulate radiotherapy therapy (IMRT)
W. H. Chang, Sonia M. Lo, Tzu-Li Chen, James C. Chen
J. Biomed. Informatics4
2017 Hybrid genetic algorithm to solve resource constrained assembly line balancing problem in footwear manufacturing
Thi Phuong Quyen Nguyen, James C. Chen, Chao-Lung Yang
Soft Comput.2
2015 DIGGIT: a Bioconductor package to infer genetic variants driving cellular phenotypes
abstract
UNLABELLED: Identification of driver mutations in human diseases is often limited by cohort size and availability of appropriate statistical models. We propose a method for the systematic discovery of genetic alterations that are causal determinants of disease, by prioritizing genes upstream of functional disease drivers, within regulatory networks inferred de novo from experimental data. Here we present the implementation of Driver-gene Inference by Genetical-Genomic Information Theory as an R-system package. AVAILABILITY AND IMPLEMENTATION: The diggit package is freely available under the GPL-2 license from Bioconductor (http://www.bioconductor.org).
Mariano J. Alvarez, James C. Chen, Andrea Califano
Bioinform.2
2013 Supply chain management with lean production and RFID application: A case study
James C. Chen, Chen-Huan Cheng, Potsang B. Huang
Expert Syst. Appl.1
2012 Developing A New Variables Sampling Scheme for Product Acceptance Determination
Chien-Wei Wu, James C. Chen
ICINCO (2)2
2012 Assembly line balancing in garment industry
James C. Chen, Chun-Chieh Chen, Ling-Huey Su, Han-Bin Wu, Cheng-Ju Sun
Expert Syst. Appl.1
2012 Flexible job shop scheduling with parallel machines using Genetic Algorithm and Grouping Genetic Algorithm
James C. Chen, Cheng-Chun Wu, Chia-Wen Chen, Kou-Huang Chen
Expert Syst. Appl.1
2005 Developing and Pilot Evaluating a Smartphone-and-Palm-based Evaluation Support System in Home Care
Mu-Jung Chen, James C. Chen, Ying-Ling Kuo, Chung-Fu Lan, Polun Chang
AMIA2
2005 An Economic Capacity Planning Model Considering Inventory and Capital Time Value
S. Michael Wang, Kung-Jeng Wang, Hui-Ming Wee, James C. Chen
ICCSA (4)4
1998 A Statistical Performance Simulation Methodology for VLSI Circuits
abstract
A statistical performance simulation (SPS) methodology for VLSI circuits is presented. Traditional methods of worst-case corner analysis lack accuracy and Monte-Carlo simulations cannot be applied to VLSI circuits because of their complexity. SPS methodology is accurate because no statistical information about the device parameter variation is lost. It achieves efficiency by analyzing the smaller circuit blocks and generating the performance distribution for the entire circuit. Circuit evaluation at any specified performance level is possible.
Michael Orshansky, James C. Chen, Chenming Hu
DAC2
1991 Multifunction W-band MMIC receiver technology
abstract
The development of a W-band (75-110 GHz) monolithic receiver, culminating in a three-chip multifunctional monolithic microwave integrated circuit (MMIC) receiver front-end, is described. The heart of the receiver is a four-channel multiplexer, with each channel possessing its own single balanced mixer and low-noise IF amplifier, all integrated onto a single GaAs chip. Two dual-channel monolithic Gunn oscillators with the drive level and spectral parity to meet system requirements have been developed. The key to the development of the monolithic front-end has been to ensure process compatibility between individual components and the careful partitioning of the chip architecture.>
Martin I. Herman, Guey-Liou Lan, James C. Chen, Cheng-Keng Pao
Proc. IEEE3