IECE - Institute of Emerging and Computer Engineers

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    Academic Editor
    Author
    Contributions by role
    Author 1
    Reviewer 21
    Editor 23
    Membership
    ORCID
    0000-0001-6234-1001
    Jinchao Chen
    School of Computer Science, Northwestern Polytechnical University, Xi’an 710072, China
    Summary
    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.
    Edited Journals
    IECE Transactions on Internet of Things
    IECE Transactions on Intelligent Unmanned Systems
    IECE Transactions on Computer Science
    IECE Contributions
    Articles
    1
    Edited
    23
    Research Article | 27 July 2024
    Enhancing Robotic Grasp Detection with a Novel Two-Stage Approach: From Conceptualization to Implementation
    by
    Zhe Chu
    ,
    Mengkai Hung
    ,
    Xiangyu Chen
    IECE Transactions on Intelligent Unmanned Systems | Volume 1, Issue 1: 44-54, 2024 | DOI:10.62762/TIUS.2024.777385
    Abstract
    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
    Enhancing Robotic Grasp Detection with a Novel Two-Stage Approach: From Conceptualization to Implementation
    Research Article | 21 July 2024
    Model Predictive Control for Enhanced Trajectory Tracking of Autonomous Deep-Sea Tracked Mining Vehicles
    by
    Hongyun Wu
    ,
    Yuheng Chen
    ,
    Hongmao Qin
    IECE Transactions on Intelligent Unmanned Systems | Volume 1, Issue 1: 31-43, 2024 | DOI:10.62762/TIUS.2024.557673
    Abstract
    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 >
    Graphical Abstract
    Model Predictive Control for Enhanced Trajectory Tracking of Autonomous Deep-Sea Tracked Mining Vehicles
    Research Article | 17 July 2024
    Enhancing Aero Engine Design Through Advanced Computer Simulation Techniques
    by
    Luo Zhe
    IECE Transactions on Intelligent Unmanned Systems | Volume 1, Issue 1: 24-30, 2024 | DOI:10.62762/TIUS.2024.424921
    Abstract
    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 >
    Review Article | 10 July 2024
    Advancements in Aero Engine Design and Manufacturing through the Integration of Electronic Computing Technologies: A Comprehensive Analysis
    by
    Zhe Luo
    IECE Transactions on Intelligent Unmanned Systems | Volume 1, Issue 1: 16-23, 2024 | DOI:10.62762/TIUS.2024.970930
    Abstract
    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 >
    Graphical Abstract
    Advancements in Aero Engine Design and Manufacturing through the Integration of Electronic Computing Technologies: A Comprehensive Analysis
    Review Article | 07 July 2024
    Advancements and Perspectives in Fatigue Driving Detection: A Comprehensive Review
    by
    Xiao Yan
    ,
    Ashardi bin Abas
    IECE Transactions on Intelligent Unmanned Systems | Volume 1, Issue 1: 4-15, 2024 | DOI:10.62762/TIUS.2024.767724
    Abstract
    Driver fatigue is a significant contributor to road accidents worldwide. Timely detection and alert systems for driver fatigue can substantially enhance driving safety and reduce traffic-related casualties. This article presents a comprehensive review of the recent advancements in driver fatigue detection technologies. It categorizes and evaluates detection methods based on physiological signals, behavioral characteristics, vehicle dynamics, and information fusion techniques. Additionally, it scrutinizes the prevalent datasets and methodologies employed in fatigue detection, offering valuable insights for future research directions. Our analysis emphasizes the importance of integrating multi... More >
    Graphical Abstract
    Advancements and Perspectives in Fatigue Driving Detection: A Comprehensive Review
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