Dr. Jinchao Chen is an Associate Professor in School of Computer Science at Northwestern Polytechnical University, Xi’an, China. He has received his Ph.D. degree in Computer Science from the same institution in 2016. He focuses on the multi-processor scheduling, embedded and real-time systems, simulation and verification, decision-making and intelligent control of unmanned aerial vehicles, human-computer interaction systems. He has over 50 papers and 4 ESI highly-cited papers published in international conferences and journals (e.g., IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Industrial Electronics, IEEE Transactions on Cybernetics, IEEE Real-Time Systems Symposium). He is the Editor-in-Chief of ASP Transactions on Computers and ASP Transactions on Computers, and the Academic Editor of International Journal of Aerospace Engineering. He is a TCP member of many conferences and regular reviewer of IEEE Transactions on Industrial Informatics, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Transportation Electrification, IEEE Transactions on Vehicular Technology, and Concurrency and Computation Practice and Experience. He is a member of IEEE and CCF.
This study investigates the application of Internet of Things (IoT) technology in agriculture, focusing on the cultivation of patchouli, a medicinal plant known for its therapeutic properties. The research highlights the specific growth requirements and medicinal benefits of patchouli, and proposes a monitoring system based on ZigBee technology. The system's hardware design incorporates cc2530 and esp8266 chips for wireless data transmission, while communication between the OneNET cloud server and the MySQL database is managed through MQTT, TCP/IP, and HTTP protocols. This integration showcases the potential of IoT to significantly enhance agricultural efficiency by providing real-time data... More >
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Research Article
| 27 July 2024
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This study introduces a novel two-stage approach for robotic grasp detection, addressing the challenges faced by end-to-end deep learning methodologies, particularly those based on convolutional neural networks (CNNs) that require extensive and often impractical datasets. Our method first leverages a particle swarm optimizer (PSO) as a candidate estimator, followed by CNN-based verification to identify the most probable grasp points. This approach represents a significant advancement in the field, achieving an impressive accuracy of 92.8% on the Cornell Grasp Dataset. This positions it among the leading methods while maintaining real-time operational capability. Furthermore, with minor modif... More >
Graphical Abstract
Free Access
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Research Article
| 21 July 2024
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This paper explores the effectiveness of Model Predictive Control (MPC) for trajectory tracking in autonomous deep-sea tracked mining vehicles operating within polymetallic nodule mining environments, considering model uncertainties and external disturbances. Traditional applications of MPC in autonomous vehicle trajectory tracking, which typically rely on kinematic models under minimal external disturbance, often fail when faced with model inaccuracies and external disruptions. To address these challenges, we propose an MPC-based trajectory tracking algorithm that includes a speed correction controller for the drive wheel. This controller, developed through experimental data fitting, aims t... More >
This paper provides a comprehensive review of the application of computer simulation in analyzing the performance of gas turbine engines. It introduces a novel three-tiered approach to simulate jet engine performance, enhancing understanding and optimization of design parameters. Utilizing a specialized computer simulation program, the study investigates the thermodynamic cycle at the design point and assesses performance at off-design points. Results underscore the pivotal role of computer simulation techniques in refining the design and efficiency of turbofan engines, offering significant insights into the development of more advanced gas turbine systems. More >
This study explores the global advancements in Computer-Aided Design (CAD) and Computer-Aided Manufacturing (CAM), focusing particularly on their application in the development of aero engines. It outlines the objectives, implementation stages, and anticipated computer system configurations for integrating CAD/CAM technologies within China's aero engine sector. By examining the current state of these technologies in China, the paper offers a customized approach that addresses both the goals and practicalities of adopting advanced CAD/CAM systems. This paper provides valuable insights into improving precision and efficiency in aero engine design and manufacturing processes in China. More >
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