Journal of Computer Science and Artificial Intelligence

ISSN: 3078-8242 (Print) ISSN: 3078-2309 (Online) DOI Prefix: 10.54097 Publisher: Darcy & Roy Press

Journal of Computer Science and Artificial Intelligence (JCSAI) is a peer-reviewed journal published by Darcy & Roy Press. The mission of the journal is to provide an academic forum for discussing the issues of computer science and artificial intelligence across the world. All articles published are rigorously and fast reviewed meeting the Journal Quality standards.

Scope: Computer science is the study of computation, information, and automation. The journal spans theoretical disciplines (such as algorithms, theory of computation) to applied disciplines, including artificial intelligence, machine learning, software engineering, and computer architecture.

Indexing & Abstracting: Web of Science - Research Commons, Crossref, Google Scholar, ResearchGate, Scilit, Semantic Scholar, Mendeley, etc.

Latest Articles

Transformer-Based Multi-Behavior Sequential Recommendation Method

Weining Bai, Bo He, Xia Yu, Yunfei Chen

Vol. 8, No. 3, pp. 49-54, 2026 DOI: 10.54097/06t11748 September 28, 2026

Abstract.Multi-Behavior Sequential Recommendation (MBSR) is an important research direction in sequential recommendation. It aims to exploit auxiliary behaviors in users’ historical interactions to improve item prediction under a target behavior. In recent years, Transformer architectures have provided an effective foundation for MBSR because self-attention can model long-range sequential dependencies and interactions among heterogeneous behaviors. This paper reviews recent advances in Transformer-based MBSR. We first introduce the task formulation, research background, and representative application … Read more →

The Current Status and Prospects of Reinforcement Learning in the Field of Automation Control

Yiwei Zhang

Vol. 8, No. 3, pp. 21-24, 2026 DOI: 10.54097/w7ptd039 September 28, 2026

Abstract.The implementation of Industry 4.0 and Intelligent Manufacturing 2035 plan promotes the transformation of the automation control field from traditional fixed strategies to autonomous and adaptive control. Reinforcement learning relies on the core advantages of trial and error learning and online adaptation to address the control challenges of nonlinear and uncertain systems, becoming a key support for technological upgrades in this field. This article combines authoritative industry data and practical application cases to systematically summarize its application status, analyze the … Read more →

Research on the Evolution Analysis Framework of Keywords for Intelligent Agents Oriented to Monitoring the Frontiers of Disciplines

Yicun Zhou

Vol. 8, No. 3, pp. 55-58, 2026 DOI: 10.54097/e8q82083 September 28, 2026

Abstract.Promptly identify and study new-generation disciplines to provide support for technological strategy and resource allocation. Research has shown that large language models can be used to study literature on intelligent agents to some extent. The problems of keyword evolution analysis, multi-source data integration and automation have not been solved by the current methods. A framework for the evolution analysis of keywords is put forward in this paper to track the leading edge of disciplines based on the evolution analysis of keywords and the technological progress of intelligent agents. The … Read more →

Research on Robot Path Planning Based on Improved A* Algorithm

Shaowei Hao

Vol. 8, No. 3, pp. 25-29, 2026 DOI: 10.54097/k1kxpc97 September 28, 2026

Abstract.Robot path planning is a key core technology for realizing autonomous navigation of robots. Among them, the A* algorithm has been widely used due to its good balance between path optimality and search efficiency. However, the traditional A* algorithm faces problems such as excessive expansion nodes, numerous path inflection points, poor smoothness, and insufficient adaptability caused by fixed heuristic functions in complex environments, which limits its performance in scenarios with high real-time requirements. To solve the above problems, this study aims to systematically improve the … Read more →

Reflections on the Impact Brought by Large Language Models to Software Engineering Maintenance Modes Under the Wave of Artificial Intelligence

Wenqian Zhang

Vol. 8, No. 3, pp. 59-62, 2026 DOI: 10.54097/17k6jb17 September 28, 2026

Abstract.Software maintenance occurs throughout the life cycle of the system and is relatively expensive. The Introduction of large language models is changing how software maintenance is conducted. The five areas this paper investigates for the practical applications of large language models in software maintenance are: maintenance process, collaborative verification, legacy system transformation, maintenance cognition, and security governance. According to a survey of almost 5,000 technical professionals in 2025 by the DORA report, 90% of the practitioners have already used AI tools in their work, … Read more →

Generative AI and Classical Chinese Moon Imagery in Translation

Zixuan Xu

Vol. 8, No. 3, pp. 30-34, 2026 DOI: 10.54097/advtk584 September 28, 2026

Abstract.Generative artificial intelligence has created new possibilities for literary translation and for the international circulation of classical Chinese poetry. However, AI translation becomes problematic when poetic meaning depends on culturally dense imagery rather than direct explanation. This paper investigates how generative AI reconstructs the moon image in English translation, using Chat GPT and ERNIE Bot as two representative systems. A small experimental dataset of six classical moon-image cases is constructed, and four evaluation indicators are used: literal accuracy, cultural retention, … Read more →

Employees’ Adaptation to AI Technologies: The Effects of Perceived Organizational Support and Learning Climate on AI Self-Efficacy and Adaptive Performance

Siyuan Shao

Vol. 8, No. 3, pp. 35-43, 2026 DOI: 10.54097/cv4y2t08 September 28, 2026

Abstract.The large-scale deployment of generative AI, intelligent automation and industrial AI systems has reshaped job workflows, skill requirements and employee work experiences across manufacturing, finance, medical, digital service and consulting industries. Poor employee adaptation to AI leads to technostress, passive resistance, low task efficiency and failed digital transformation, while effective AI adaptation drives adaptive performance, innovation output and sustainable human-AI collaboration. Prior literature has separately explored perceived organizational support (POS), organizational … Read more →

Design of Periodic Signal Measurement and Analysis Device Based on Analog Preprocessing and FPGA Parallel Processing

Shaoyi Sun, Yichun Li, Weimin She

Vol. 8, No. 3, pp. 7-11, 2026 DOI: 10.54097/nzbnae27 September 28, 2026

Abstract.Combining analog preprocessing with FPGA parallel signal analysis, this paper implements a device for time domain and frequency domain measurement of periodic signals. The system consists of amplifying circuits, a 7 order Butterworth low pass filter, a 14 bit ADC chip Zynq 7020 and a serial port screen, and adopts analog digital joint filtering to improve anti interference performance. Through front end signal conditioning and digital calibration, the peak to peak input range reaches 0 500 mV with measurement error controlled within 5 mV. A 121 order FIR filter equalizes the analog passband, … Read more →

Condition Assessment of Circuit Breaker Mechanical Performance During Opening and Closing Operations Using Adaptive Machine Learning

Junyuan Cao

Vol. 8, No. 3, pp. 1-6, 2026 DOI: 10.54097/wnqtd326 September 28, 2026

Abstract.The mechanical performance of circuit breakers during opening and closing operations directly affects the safety and stability of power systems. However, conventional threshold-based methods cannot adequately represent nonlinear relationships among multiple mechanical parameters and have limited adaptability to equipment differences and changing operating conditions. This study proposes an adaptive machine learning method for circuit breaker mechanical condition assessment. Opening and closing times, operating velocities, contact travel, overtravel, three-phase asynchronism, and the cumulative … Read more →

AIGC Reshaping Social Media: Technological Convergence, Content Production, and Ethical Governance

Jianqi Kong

Vol. 8, No. 3, pp. 44-48, 2026 DOI: 10.54097/1985k650 September 28, 2026

Abstract.Background: Generative Artificial Intelligence (AIGC) has emerged as a transformative force in social media ecosystems, reshaping content production, algorithmic distribution, and platform governance. From large language models to multimodal generation systems, AIGC technologies have rapidly penetrated diverse social media functions, raising urgent questions about their societal implications. Purpose: This review aims to systematically synthesize recent scholarship (2024-2026) on AIGC's integration into social media, identify research gaps across disciplinary boundaries, and propose actionable … Read more →