About the Journal

Journal of Industrial Engineering and Applied Science is peer-reviewed journal of Southern United Academy of Sciences published in the field of Engineering Technology. The journal registers independent DOI and ARK for each article. The DOI prefix is ​​10.70393 and the ARK prefix is ​​40704.

ISSN 3005-6071 (Print), ISSN 3005-608X (Online), International CODEN (CAS): JIEAAE

The journal focuses on the following fields:

  • Applied Mathematics - Computational Mathematics, Statistical Analysis, Mathematical Modeling
  • Applied Physics - Condensed Matter Physics, Applied Optics, Plasma Physics
  • Applied Chemistry - Chemical Engineering, Polymer Chemistry, Environmental Chemistry
  • Information Science - Data Management, Information Retrieval, Library Science
  • Computer Science - Software Engineering, Computer Networks, Cybersecurity
  • Mechanical Science - Thermodynamics, Fluid Mechanics, Robotics
  • Materials Science - Nanomaterials, Biomaterials, Composite Materials
  • Automation Technology - Control Systems, Industrial Automation, Process Automation
  • Artificial Intelligence Technology - Machine Learning, Natural Language Processing, Computer Vision
  • Aerospace Technology - Aerodynamics, Avionics, Spacecraft Design

All articles published by JCTAM are indexed by OpenAIRE, BASE, WorldCat and ICI.

(OpenAIRE - DataSources | BASE - Bielefeld Academic Search Engine | WorldCat - OCLC)

All articles published are rigorously reviewed meeting the Journal Quality standards.

Announcements

Current Issue

Vol. 2 No. 6 (2024)
View Vol. 2 No. 6 (2024)

All content published in this issue has undergone peer review and strict repetition rate checks have been conducted.

Number of articles in this issue: 13
Number of pages in this issue: 126

If you have any questions about the content of this issue, you can contact each author via email. For questions about the journal itself, you can directly contact SUAS Press.

Published: 2024-12-01

Articles

  • The Application of Generative AI in Virtual Reality and Augmented Reality
    Authors: Shijie Lyu
    Resource Type: Article
    Disciplines: Computer Science | Subjects: Generative AI
    Publication ID: v2n6a01
    Abstract: This study explores the historical development of Virtual Reality (VR) and Augmented Reality (AR) technologies and their applications in various fields, such as education, tourism, and consumer experiences. Through a review of relevant literature,...
    1-9
    DOI Icon Abstract views: 29 | DOI Icon PDF downloads: 10 | DOI Icon references: 47
    DOI Icon DOI: 10.70393/6a69656173.323339
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a01
  • Leveraging AI in Traffic Engineering to Enhance Bicycle Mobility in Urban Areas
    Authors: Chang Che, Junchi Tian
    Resource Type: Article
    Disciplines: Artificial Intelligence | Subjects: Traffic Engineering
    Publication ID: v2n6a02
    Abstract: More With the rise of AI-driven technologies, urban cycling is becoming more accessible and appealing to many due to benefits such as health improvement and cost efficiency. Governments worldwide are promoting cycling as a sustainable...
    10-15
    DOI Icon Abstract views: 18 | DOI Icon PDF downloads: 8 | DOI Icon references: 12
    DOI Icon DOI: 10.70393/6a69656173.323039
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a02
  • Advances in Deep Reinforcement Learning for Computer Vision Applications
    Authors: Zhengyang Li
    Resource Type: Article
    Disciplines: Computer Science | Subjects: Computer Vision
    Publication ID: v2n6a03
    Abstract: Deep Reinforcement Learning (DRL) has become very popular for computer vision (CV), solving mostly visually complex environments with decision making and dynamic adaption to different situations. This article provides an introduction to the basic...
    16-26
    DOI Icon Abstract views: 40 | DOI Icon PDF downloads: 11 | DOI Icon references: 26
    DOI Icon DOI: 10.70393/6a69656173.323234
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a03
  • Enhancing User Engagement and Behavior Change in Healthy Eating Apps: A Human-Computer Interaction Perspective
    Authors: Yuxin Zhao, Jiawei Wu
    Resource Type: Article
    Disciplines: Human-Computer Interaction | Subjects: User Engagement and Behavior
    Publication ID: v2n6a04
    Abstract: Healthy eating apps have gained popularity as tools for promoting dietary improvements and supporting behavior change. Despite their potential, maintaining user engagement and achieving sustained behavior change remain significant challenges. This...
    27-34
    DOI Icon Abstract views: 29 | DOI Icon PDF downloads: 10 | DOI Icon references: 49
    DOI Icon DOI: 10.70393/6a69656173.323330
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a04
  • Exploring Multimodal Feedback Mechanisms for Improving User Interaction in Virtual Reality Environments
    Authors: Yuxin Zhao, Zuen Cen
    Resource Type: Article
    Disciplines: Virtual Reality | Subjects: Multimodal Feedback Mechanisms
    Publication ID: v2n6a05
    Abstract: As Virtual Reality (VR) technology progresses, the need for intuitive and immersive interaction mechanisms becomes increasingly important. However, current VR systems primarily rely on visual and auditory feedback, often overlooking other sensory...
    35-41
    DOI Icon Abstract views: 24 | DOI Icon PDF downloads: 7 | DOI Icon references: 40
    DOI Icon DOI: 10.70393/6a69656173.323331
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a05
  • Adaptive Hybrid Optimized LSTM Models: A Novel Computational Framework for Algorithmic Financial Trading System
    Authors: Pei-Chiang Su
    Resource Type: Article
    Disciplines: Computational Science | Subjects: Intelligent Computing
    Publication ID: v2n6a06
    Abstract: In our modern society, with the development of Internet and information system, pre-programing algorithmic trading strategies for online automatic trading has also flourished, especially in the rapidly fluctuating trading market. Using...
    42-64
    DOI Icon Abstract views: 56 | DOI Icon PDF downloads: 22 | DOI Icon references: 53
    DOI Icon DOI: 10.70393/6a69656173.323338
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a06
  • Interpretable Machine Learning: Explainability in Algorithm Design
    Authors: Xueyi Cheng, Chang Che
    Resource Type: Article
    Disciplines: Computer Science | Subjects: Machine Learning
    Publication ID: v2n6a07
    Abstract: In recent years, there is a high demand for transparency and accountability in machine learning models, especially in domains such as healthcare, finance and etc. In this paper, we delve into deep how to make machine learning models more...
    65-70
    DOI Icon Abstract views: 15 | DOI Icon PDF downloads: 8 | DOI Icon references: 22
    DOI Icon DOI: 10.70393/6a69656173.323337
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a07
  • Automated Machine Learning: A Survey of Tools and Techniques
    Authors: Junchi Tian, Chang Che
    Resource Type: Article
    Disciplines: Computer Science | Subjects: Machine Learning
    Publication ID: v2n6a08
    Abstract: Automated Machine Learning (AutoML) has revolutionized the field of machine learning by automating complex and time-intensive tasks such as data preprocessing, model selection, and hyperparameter tuning. This study explores the capabilities,...
    71-76
    DOI Icon Abstract views: 23 | DOI Icon PDF downloads: 12 | DOI Icon references: 22
    DOI Icon DOI: 10.70393/6a69656173.323336
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a08
  • Anomaly Pattern Detection in High-Frequency Trading Using Graph Neural Networks
    Authors: Maoxi Li, Mengying Shu, Tianyu Lu
    Resource Type: Article
    Disciplines: Artificial Intelligence Technology | Subjects: Machine Learning
    Publication ID: v2n6a09
    Abstract: This paper presents a new method for detecting abnormal patterns in high-frequency trading (HFT) using graph neural networks (GNNs). The increasing sophistication of trading algorithms and the large volume of data have often created unprecedented...
    77-85
    DOI Icon Abstract views: 12 | DOI Icon PDF downloads: 7 | DOI Icon references: 20
    DOI Icon DOI: 10.70393/6a69656173.323430
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a09
  • Real-time Detection of Abnormal Financial Transactions Using Generative Adversarial Networks: An Enterprise Application
    Authors: Shuaiqi Zheng, Maoxi Li, Wenyu Bi, Yining Zhang
    Resource Type: Article
    Disciplines: Artificial Intelligence Technology | Subjects: Machine Learning
    Publication ID: v2n6a10
    Abstract: This paper presents a novel real-time financial fraud detection framework utilizing Generative Adversarial Networks (GANs) for enterprise applications. The proposed system addresses critical challenges in fraud detection, including class...
    86-96
    DOI Icon Abstract views: 16 | DOI Icon PDF downloads: 14 | DOI Icon references: 36
    DOI Icon DOI: 10.70393/6a69656173.323431
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a10
  • FSMM: Food System Monitoring Model for Re-optimization
    Authors: Wenjun Wu, Dong Liu, Lai Jiang, Kai Guo
    Resource Type: Article
    Disciplines: Applied Mathematics | Subjects: Mathematical Modeling
    Publication ID: v2n6a11
    Abstract: The unstability of global food system have aroused growing attention worldwide. Althrough there is sufficient food produced to feed every person, many people in the world are suffering from hunger. Moreover, the current food system is harmful to...
    97-110
    DOI Icon Abstract views: 48 | DOI Icon PDF downloads: 18 | DOI Icon references: 28
    DOI Icon DOI: 10.70393/6a69656173.323433
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a11
  • Multi-modal Market Manipulation Detection in High-Frequency Trading Using Graph Neural Networks
    Authors: Yuexing Chen, Maoxi Li, Mengying Shu, Wenyu Bi, Siwei Xia
    Resource Type: Article
    Disciplines: Artificial Intelligence Technology | Subjects: Machine Learning
    Publication ID: v2n6a12
    Abstract: This paper proposes a novel multi-modal graph neural network framework for detecting market manipulation in high-frequency trading environments. The framework integrates diverse data sources through sophisticated fusion mechanisms and employs...
    111-120
    DOI Icon Abstract views: 21 | DOI Icon PDF downloads: 13 | DOI Icon references: 24
    DOI Icon DOI: 10.70393/6a69656173.323432
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a12
  • Deep Reinforcement Learning-Enhanced Multi-Stage Stochastic Programming for Real-Time Decision-Making in Centralized Seed Packaging Systems
    Authors: Yuqun Zhou
    Resource Type: Article
    Disciplines: Artificial Intelligence Technology | Subjects: Machine Learning
    Publication ID: v2n6a13
    Abstract: The centralized seed packaging system faces significant challenges in dynamic decision-making due to stochastic demand fluctuations and operational constraints. This paper presents a novel hybrid approach integrating deep reinforcement learning...
    121-126
    DOI Icon Abstract views: 27 | DOI Icon PDF downloads: 13 | DOI Icon references: 5
    DOI Icon DOI: 10.70393/6a69656173.323435
    DOI Icon ARK: ark:/40704/JIEAS.v2n6a13
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