IECE - Institute of Emerging and Computer Engineers

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    Academic Editor
    Author
    Contributions by role
    Author 1
    Reviewer 13
    Editor 31
    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
    31
    Free Access | Research Article | 11 December 2024
    Surface Area Measurement of Irregular Objects Based on 3D Laser Scanning Technology
    by
    Quan Qi
    ,
    Yuhua Wang
    ,
    Xingdong Wang
    ,
    Lulu Shi
    IECE Transactions on Intelligent Unmanned Systems | Volume 1, Issue 2: 63-72, 2024 | DOI:10.62762/TIUS.2024.725258
    Abstract
    Calculating surface area is quite common in daily life; however, due to the irregular shapes of objects, traditional feature point data collection methods are not suitable for complex surfaces. Therefore, this study employs 3D laser scanning technology, using the Ligrip H120 handheld rotating laser scanner for data collection of the artificial stone. Based on four algorithms, we performed 3D reconstruction of the obtained point cloud data. Subsequently, we developed a program for surface area calculation using the Python interface of CloudCompare software and the Open3D library. The results indicate that the surface area measured with this technology has an accuracy improvement of 1.03 perce... More >
    Graphical Abstract
    Surface Area Measurement of Irregular Objects Based on 3D Laser Scanning Technology
    Free Access | Research Article | 11 December 2024
    Dialogflow-based Robot Customer Service in Online Shopping Malls
    by
    Kunhao Zhang
    ,
    Xingdong Wang
    ,
    Yuhua Wang
    IECE Transactions on Intelligent Unmanned Systems | Volume 1, Issue 2: 55-62, 2024 | DOI:10.62762/TIUS.2024.257761
    Abstract
    With the rapid development of e-commerce, consumers encounter more and more frequent customer service problems in the shopping process, especially during peak periods, the burden of manual customer service is heavy, and it is difficult to provide timely and effective service. In addition, enterprises are faced with high labor costs and low service efficiency. However, existing customer service systems are still deficient in user experience and intelligence level. In order to solve these problems, I designed a mall system and integrated Google's Dialogflow robot service in it, which realizes intelligent customer service functions through natural language processing technology to help users ge... More >
    Graphical Abstract
    Dialogflow-based Robot Customer Service in Online Shopping Malls
    Free Access | Research Article | 08 December 2024
    Optimized CNNs for Rapid 3D Point Cloud Object Recognition
    by
    Tianyi Lyu
    ,
    Dian Gu
    ,
    Peiyuan Chen
    ,
    Yaoting Jiang
    ,
    Zhenhong Zhang
    ,
    Huadong Pang
    ,
    Li Zhou
    ,
    Yiping Dong
    IECE Transactions on Internet of Things | Volume 2, Issue 4: 83-94, 2024 | DOI:10.62762/TIOT.2024.758153
    Abstract
    This study introduces a method for efficiently detecting objects within 3D point clouds using convolutional neural networks (CNNs). Our approach adopts a unique feature-centric voting mechanism to construct convolutional layers that capitalize on the typical sparsity observed in input data. We explore the trade-off between accuracy and speed across diverse network architectures and advocate for integrating an L1 penalty on filter activations to augment sparsity within intermediate layers. This research pioneers the proposal of sparse convolutional layers combined with L1 regularization to effectively handle large-scale 3D data processing. Our method’s efficacy is demonstrated on the MVTec... More >
    Graphical Abstract
    Optimized CNNs for Rapid 3D Point Cloud Object Recognition
    Free Access | Review Article | 07 December 2024
    An Overview of Data Persistence Approaches for Enterprise Web Applications
    by
    Zhiwei Xu
    ,
    Ming Lei
    IECE Transactions on Computer Science | Volume 2, Issue 1: 10-17, 2024 | DOI:10.62762/TCS.2024.529749
    Abstract
    In the era of digital transformation, enterprise web applications have become indispensable tools for business operations, necessitating the efficient and reliable management of vast amounts of data. Data persistence is critical to ensure consistency, security, and scalability, especially in complex environments involving high concurrency and sensitive information. This paper reviews the key requirements for data persistence in enterprise-level web applications, such as reliability, security, scalability, and high availability, while addressing the challenges posed by modern business needs. Various persistence solutions, including relational databases, NoSQL databases, and distributed storag... More >
    Graphical Abstract
    An Overview of Data Persistence Approaches for Enterprise Web Applications
    Free Access | Research Article | 07 December 2024
    Predictive Analysis for Road Safety Enhancement in Chicago County
    by
    Reshma Shaik
    ,
    Kislay Raj
    ,
    Aditya Singh
    ,
    Teerath Kumar
    IECE Transactions on Computer Science | Volume 2, Issue 1: 1-9, 2024 | DOI:10.62762/TCS.2024.766854
    Abstract
    With the increasing incidents of fatal road injuries, there is an urgent need for developing effective road safety management systems. The study aims to develop predictive models based on machine learning to forecast the likelihood of road collisions depending on factors like weather, road condition, time, and driver behaviour in Chicago, USA. A machine learning approach has been applied to the crash dataset to evaluate the factors affecting the prevalence of road accidents. Python programming and the Jupyter Notebook platform have been used for performing descriptive statistics, correlation and three classification algorithms (Random Forest, KNN, Decision Tree and MLP Classification). Obtai... More >
    Graphical Abstract
    Predictive Analysis for Road Safety Enhancement in Chicago County
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