A5086134377- Manufacturing Process and Optimization
- Energy Efficiency and Management
- Scheduling and Optimization Algorithms
- Educational Games and Gamification
- Flexible and Reconfigurable Manufacturing Systems
- Advanced Manufacturing and Logistics Optimization
- Advanced Machining and Optimization Techniques
- Intelligent Tutoring Systems and Adaptive Learning
- Advanced machining processes and optimization
- Assembly Line Balancing Optimization
- Innovative Teaching and Learning Methods
- Teaching and Learning Programming
- Online Learning and Analytics
- Product Development and Customization
- Digital Transformation in Industry
- Sustainable Supply Chain Management
- Injection Molding Process and Properties
- Optimization and Packing Problems
- Consumer Market Behavior and Pricing
- Experimental Learning in Engineering
- Reinforcement Learning in Robotics
- Artificial Intelligence in Games
- Additive Manufacturing and 3D Printing Technologies
- Innovation Diffusion and Forecasting
- Supply Chain and Inventory Management
Rowan University
2016-2025
China West Normal University
2025
Northeastern University
2015-2024
Dongguk University
2024
Bridge University
2015-2024
University of Minnesota
2024
Institute of Technology of Cambodia
2024
University of Arkansas at Fayetteville
2024
New York University
2024
New Jersey Institute of Technology
2000-2024
Recycling, reusing, and remanufacturing of end-of-life (EOL) products have been receiving increasing attention. They effectively preserve the ecological environment promote development economy. Disassembly sequencing line balancing problems are indispensable to recycling EOL products. A set subassemblies can be obtained by disassembling an product. In practice, there many different types that disassembled on a disassembly line, high-level uncertainty exists in process those Hence, this paper...
Breast cancer is the most common female in world, and it poses a huge threat to women's health. There currently promising research concerning its early diagnosis using deep learning methodologies. However, some commonly used Convolutional Neural Network (CNN) their variations, such as AlexNet, VGGNet, GoogleNet so on, are prone overfitting breast classification, due both small-scale pathology image datasets overconfident softmax-cross-entropy loss. To alleviate issue for better...
Technological advancement has given education a new definition-parallel intelligent education-resulting in fundamentally ways of teaching and learning. This article exemplifies an important component parallel education-artificial system narrative game environment to offer personalized The collects data on the player's actions while they play, assessing their concept knowledge via k-nearest-neighbor (kNN) classification, provides tailored feedback that student as play game. Based empirical...
Product disassembly is critically important in recycling end-of-life products, reducing their negative impact on environmental pollution and minimizing resource waste. Disassembly line balancing problems have attracted much attention from researchers industrial practitioners. Most of the existing studies, however, consider only human or robot alone. This work considers human-robot collaboration. It proposes an collaborative model considering stochastic task time, where AND/OR graph adopted...
Disassembly, as the process of systematic removal desirable constituent parts from an assembly, is growing importance due to increasing environmental and economic pressure. Although disassembly in practice manual labor intensive, little attention has been paid human intervention process. This paper addresses this deficiency by developing a fuzzy attributed Petri net (FAPN) model mathematically represent uncertainty large amount intervention. An algorithm based upon further proposed for...
In the context of automated manufacturing systems (AMS), Petri nets are widely adopted to solve modeling, analysis, and control problems. So far, nearly all known approaches liveness enforcing supervisory investigate AMS with either flexible routes or assembly operations, whereas little work investigates them both. this paper, we propose a novel class systems, which can well deal both features so as facilitate more complex AMS. Using structural show that their net model be attributed absence...
Selective disassembly sequence planning (SDSP) is regarded as an efficient strategy to determine optimal sequences for extracting target parts (TP) from complex end-of-life (EOL) products. Previous research assumes that all EOL products have the same structure and selective are given before removed. However, different operation states during their use stage, which results in high uncertainty of The often makes predetermined impractical minimizing time maximizing profit. This letter...
Energy consumption prediction of a CNC machining process is important for energy efficiency optimization strategies. To improve the generalization abilities, more and parameters are acquired modeling. While data collected from workshops may be incomplete because misoperation, unstable network connections, frequent transfers, etc. This work proposes framework modeling based on to address this issue. First, some necessary preliminary operations used sets. Then, missing values estimated...
Metaverse has gained increasing interest in education, with much of literature focusing on its great potential to enhance both individual and social aspects learning. However, little work been done address the systems technologies behind providing meaningful This article proposes a technical framework this research gap, where hierarchical multiagent reinforcement learning approach experience sharing is developed augment intelligence nonplayer characters for personalization. The utility...
Abstract The potential of the metaverse in field education is an area increasing interest, with many researchers exploring space to increase ease and efficacy student while reducing time labor requirements deliver effective teaching. However, there has been little work into systematic technological aspects delivering through metaverse. To fill this gap, we propose a system that takes good advantages virtual reality Web3 blockchain techologies create social learning environment. With added...