Journal of Computer Technology & Applications

Latest articles

• Published Subscription Review Article 20 Feb 2026

  Skin Disease prediction and classification from dermoscopy images using Neural Network

  By Prasanna Kumar Mishra, Lalit Kumar Behera, Jitendra Kumar Mishra

  Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article →

• Published Subscription Review Article 20 Feb 2026

  Automated Intelligence, Machine Learning, and Big Data in Education: A Practical Framework, Synthetic Demonstration, and Deployment Guidance

  By Ravindra P. Purohit

  Abstract: Artificial intelligence (AI), machine learning (ML), and big-data methods are increasingly used to improve educational decision making through personalization, early-warning systems, scalable feedback, and operational analytics. This manuscript proposes a practical end-to-end framework for educational AI/ML projects, covering problem definition, data engineering, modeling, evaluation, intervention design, and responsible governance. To provide a complete and reproducible template without exposing sensitive student data, we present a synthetic demonstration study that mirrors typical …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article →

• Published Subscription Original Research 20 Feb 2026

  A SHAP - Enhanced Voice-Based Conversational Agent for Agriculture Using BERT

  By Sirapani D, Revathi J, Ramadevi C

  Abstract: The integration of advanced artificial intelligence technologies into modern agriculture has become increasingly important for narrowing the persistent knowledge gap faced by farmers, especially in regions with limited access to expert advisory services. While state-of-the-art language models such as BERT (Bidirectional Encoder Representations from Transformers) demonstrate exceptional performance in understanding and generating natural language, their opaque “black-box” nature often limits user confidence, trust, and widespread adoption. Farmers may hesitate to …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article →

• Published Subscription Original Research 20 Feb 2026

  An Automated Smart Contract Repair Framework for Reentrancy, Integer Overflow, and Denial- of-Service Vulnerabilities

  By Lipi Begam, Ranjit Haldar, Devmalya Mondal, Sabyasachi Chakroborty

  Abstract: This paper introduces a novel static analysis framework designed to bridge a long-standing gap in Ethereum smart contract security: the disconnect between vulnerability detection and automated remediation. Although widely adopted tools such as Slither and Oyente are highly effective at identifying security weaknesses, they stop short of providing actionable fixes. As a result, developers manually patch vulnerabilities, a process that is not only time-consuming but also susceptible to human error …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 31–41 Read article →

• Published Subscription Original Research 20 Feb 2026

  Comparative Analysis of Supervised Learning Algorithms

  By Kalpesh U. Gundigara, Jeet S. Pandya

  Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article →

• Published Subscription Original Research 20 Feb 2026

  Log Identification and Monitoring System Using Generative AI

  By Nikhil Santosh Shinde, Ajay Shiketod, Swati Andhale

  Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article →

• Published Subscription Original Research 20 Feb 2026

  Green and Edge-Aware Computing: Rethinking Cloud Infrastructure for Sustainability

  By Dipankar Barui, Raghunath Maji, Subhankar Roy, Satyajit Maiti, Subhadip Goswami

  Abstract: Cloud computing has transformed the way organizations access and manage information technology resources, providing flexible, scalable, and cost-efficient services that support today’s data-driven world. Despite these advantages, the rapid expansion of large-scale cloud infrastructures has resulted in rising energy consumption, significant heat generation, and a growing environmental footprint. This research focuses on advancing green cloud computing by examining methods that reduce power usage while maintaining high performance. Key strategies include …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 17–24 Read article →

• Published Subscription Review Article 10 Feb 2026

  AI-Based Machine Learning Web Application Firewall (ML-WAF)

  By M. Fatima, Ritik Lodhi, Ashika Bajpai, Keshav Pachlaniya, Ruchika Nagle, Sourabh Kumar

  Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …

  Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article →