A5035758757- Metaheuristic Optimization Algorithms Research
- Scheduling and Optimization Algorithms
- Advanced Manufacturing and Logistics Optimization
- Digital Transformation in Industry
- Advanced Multi-Objective Optimization Algorithms
- Advanced Algorithms and Applications
- Energy Efficient Wireless Sensor Networks
- Food Supply Chain Traceability
- Transportation Planning and Optimization
- Power Systems Fault Detection
- Functional Brain Connectivity Studies
- Complex Network Analysis Techniques
- Heart Rate Variability and Autonomic Control
- Advanced Chemical Sensor Technologies
- Image Enhancement Techniques
- Power System Reliability and Maintenance
- Advanced Image Fusion Techniques
- Robotic Path Planning Algorithms
- Collaboration in agile enterprises
- Vehicle Routing Optimization Methods
- Fire Detection and Safety Systems
- Power Systems and Renewable Energy
- IoT and GPS-based Vehicle Safety Systems
- Gait Recognition and Analysis
- RFID technology advancements
Jiangnan University
2025
Beijing University of Posts and Telecommunications
2022-2024
Wuhan University of Technology
2011-2024
Southwest Jiaotong University
2024
Zhejiang University of Technology
2024
UNSW Sydney
2019-2021
Shanghai University of Electric Power
2021
China Three Gorges University
2020
Seattle University
2014
University of Washington
2004-2014
A comprehensive learning particle swarm optimizer (CLPSO) embedded with local search (LS) is proposed to pursue higher optimization performance by taking the advantages of CLPSO's strong global capability and LS's fast convergence ability. This paper proposes an adaptive LS starting strategy utilizing our quasi-entropy index address its key issue, i.e., when start LS. The changes as proceeds are analyzed in theory via numerical tests. algorithm tested on multimodal benchmark functions....
Because of COVID-19, factories are facing many difficulties, such as shortage workers and social alienation. How to improve production performance under limited labor resources is an urgent problem for global manufacturing factories. This work studies energy-efficient job-shop scheduling with workers. Those can have multiskills. A many-objective model five objectives, that is: 1) makespan; 2) total tardiness; 3) idle time; 4) worker cost; 5) energy, built. To solve this optimization (MaOP),...
Energy-efficient production scheduling research has received much attention because of the massive energy consumption manufacturing process. In this article, we study an energy-efficient job-shop problem with sequence-dependent setup time, aiming to minimize makespan, total tardiness and simultaneously. To effectively evaluate select solutions for a multiobjective optimization nature, novel fitness evaluation mechanism (FEM) based on fuzzy relative entropy (FRE) is developed. FRE...
Pilots' brain fatigue status recognition faces two important issues. They are how to extract cognitive features and identify these characteristics. In this article, a gamma deep belief network is proposed multilayer representations of high-dimensional data. The Dirichlet distributed connection weight vector upsampled layer by in each iteration, then the hidden units distribution downsampled. An effective upper lower Gibbs sampler formed realize automatic reasoning structure. order 3-D...
We utilized contrast enhanced magnetic resonance imaging (MRI) to delineate the anatomy of female genital and pelvic organs during sexual arousal. Eleven healthy pre-menopausal women eight post-menopausal underwent MRI pelvis while watching an erotic video. A 1.5 Tesla MR system was used produce T1-weighted images following administration MS-325, a gadolinium-based blood pool agent. Selected structural dimensions enhancement were measured prior In both pre- subjects, vestibular bulb labia...
To explore relationships among low back pain knowledge, fall fear, exercise self-efficacy and kinesiophobia in pregnant women with pregnancy-related (PLBP) through a chain mediating model. This study used cross-sectional survey utilized convenience sampling from August to December 2023 at third-class hospital Wuxi, China. A total of 325 PLBP were chosen as the subjects this study. Sociodemographics information about self-efficacy, collected. Path analysis was analyze data. The results found...
Exceptional opportunities exist for researchers and practitioners to invest in conducting innovative transformative research data mining health informatics. This IEEE Intelligent Systems "Trends Controversies" (T&C) department hopes raise awareness highlight recent move toward such goals. The introduction, "Healthcare Intelligence: Turning Data into Knowledge," is written by Hui Yang Erhun Kundakcioglu. Next, "Empowering Excellence of Care Radiology Informatics" Jing Li, Teresa Wu, J. Ross...
Accurate prediction of water level in inland waterway has been an important issue for helping flood control and vessel navigation a proactive manner. In this research, deep learning approach called long short-term memory... | Find, read cite all the research you need on Tech Science Press
Optimizing the design of an airport baggage handling transport system (BHTS) with respect to minimization total costs and energy consumption is essential reduce Carbon dioxide (chemical formula CO2) emissions in operations. This paper introduces a mathematical model that comprehensively considers relevant regarding operation belt conveyors BHTS. Specifically, Capital Expenditure (CapEx) Operational (OpEx) are considered BHTS cost function. Furthermore, include impact CO2 emissions,...
A series of novel thiocyanate-based phase-change pseudo ionic liquids (PILs) with excellent renewability have been designed for ammonia absorption and storage.
In recent years, the individualized demand of customers brings small batches and diversification orders towards enterprises. The application enabling technologies in factory, such as industrial Internet things (IIoT) cloud manufacturing (CMfg), enhances ability customer requirement automatic elicitation process control. job shop scheduling problem with a random arrival time dramatically increases difficulty management. Thus, how to collaboratively schedule production logistics resources...
There have been a number of deficiencies in domestic waste source regulation, dynamic monitoring, etc‥ caused by geographical conditions, technology and other factors for long time which brought low efficiency illegal behaviors to refuse treatment. As new network technology, IOT has significant advantages its traceability, characteristics solving the problems above. This paper established brief introduction IOT, summarizing application treatment disposal. In case certain place, current...
Traffic is becoming one of important problems in our society, which possible to be resolved by the application Internet Things. Based on analysis relevant researches Things, this paper proposes architecture real-time information collecting and monitoring system. The system integrates several advanced technologies, such as RFID wireless sensor networks (WSN), realize collection transmission processing. Through design hardware software, can collect traffic monitor flow, finally help improve situation.
Material safety and traceability is of great importance in toy manufacturing because there have been tougher requirements on product imposed by new international regulations. We investigate analyze the production workflow small medium enterprises SADT simulation analysis. find out that tracking information incomplete flow material are out-sync due to lacking process collaboration current system. Thus, objective creates a need for systems collaborate enterprises. In this paper, aiming at...
The development of industrial-enabling technology, such as the industrial Internet Things and physical network system, makes it possible to use real-time information in production-logistics scheduling. Real-time an intelligent factory is random, arrival customers’ jobs, fuzzy, processing time Production-Logistics Resources. Besides, coordination production logistic resources a flexible workshop also hot issue. availability this will enhance quality making scheduling decisions. However, when...
Food instance segmentation is essential to estimate the serving size of dishes in a food image. The recent cutting-edge techniques for are deep learning networks with impressive quality and fast computation. Nonetheless, they hungry data expensive annotation. This paper proposes an incremental framework optimize model performance given limited labelling budget. power novel difficulty assessment model, which forecasts how challenging unlabelled sample latest trained model. collection...
In recent years, the individualized demand of customers brings small batches and diversification orders towards enterprises. The application enabling technologies in factory, such as Industrial Internet Things (IIoT) Cloud Manufacturing (CMfg), enhances ability customer requirement automatic elicitation manufacturing process control. job shop scheduling problem with random arrival time dramatically increases difficulty management. Thus, how to collaboratively schedule production logistics...