Academic Editor
Author
Contributions by role
Author 1
Reviewer 12
Editor 33
Membership
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 Contributions

Free Access | Research Article | 12 January 2025
Design and Implementation of an STM32-Based Smart Medicine Box Reminder System with Multiple Functionalities
IECE Transactions on Computer Science | Volume 2, Issue 1: 26-34, 2025 | DOI:10.62762/TCS.2024.657367
Abstract
Since the 21st century, with the acceleration of people's life rhythm and the increasing number of patients with chronic diseases, taking medicine has become a part of their daily life. This system is based on the design of the smart pill box reminder system based on the single-chip microcomputer, using STM32F103C8T6 as the core of the smart pill box reminder system, which is composed of a button module, an OLED display module, an infrared detection module, a servo module, a clock module and a Wi-Fi module. As a setting module, the user can set the reminder time and dosage of the three pill boxes according to their needs. When the set time for taking medicine is reached, the user will be rem... More >

Graphical Abstract
Design and Implementation of an STM32-Based Smart Medicine Box Reminder System with Multiple Functionalities

Free Access | Research Article | 12 January 2025
Development and Implementation of ’Fresh House Grocery’ Fresh Food E-commerce System Based on Django Framework
IECE Transactions on Computer Science | Volume 2, Issue 1: 18-25, 2025 | DOI:10.62762/TCS.2024.931558
Abstract
With the rapid development of Internet technology, people's shopping methods are gradually shifting from offline to online. As an important branch of this, fresh food e-commerce has gradually become a part of people's daily lives. Traditional offline fresh food markets require a large amount of manpower and material resources for operation and maintenance, which is inefficient and has serious waste of resources. Therefore, it is particularly important to develop an efficient and convenient online fresh food shopping platform. This article introduces a 'Fresh House Grocery' fresh food e-commerce system based on the Django framework. This system aims to provide consumers with a convenient and... More >

Graphical Abstract
Development and Implementation of ’Fresh House Grocery’ Fresh Food E-commerce System Based on Django Framework

Free Access | Research Article | 11 December 2024
Surface Area Measurement of Irregular Objects Based on 3D Laser Scanning Technology
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
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
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
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