Overview
Impact in Computics (e-ISSN 3122-7341) is an international, peer-reviewed, open-access journal that publishes research in Computer Science, Information Technology, and Information Systems.
The journal welcomes both theoretical and applied studies in areas such as artificial intelligence, software engineering, data science, cybersecurity, networks, cloud computing, enterprise systems, and digital technologies.
The journal also welcomes computing applications in fields including healthcare, agriculture, education, business, government, and smart infrastructure.
Latest Articles
A Conv-Attention Seasonal Aggregation Network (CASA-Net) for PM2.5 Concentration Forecasting Using US EPA Monitoring Data
The prediction of fine particulate matter, or fine particulate (PM₂.₅), is very important for air quality management and protecting human health. Current deep-learning approaches, however, cannot capture the local time-specific interactions and spatiotempor...
Systematic Review of Machine Learning and Deep Learning Approaches for Spam Detection in Online Social Networks
Malicious activities such as phishing, disinformation, and bot attacks for spamming in online social networks (OSNs) have become an increasing problem, and online spam detection is an ongoing challenge to keep users safe and OSNs healthy. However, classical...
AI-Based Tutoring Systems for Deaf and Hard-of-Hearing Learners: A Systematic Review of Computational Architectures, Adaptive Mechanisms, and Meta-Analysis of Learning Outcomes
Children who are Deaf or hard of hearing (DHH) often experience educational challenges that may affect their academic achievement. Artificial intelligence (AI)-based tutoring systems have been proposed to address some of these challenges, but evidence regar...
An AI-Driven Game Analytics Framework for Intelligent Player Profiling in a Unity-Based Roll Ball Environment
Modern digital games generate extensive gameplay telemetry that can reveal patterns of player behavior and performance. This study proposes an AI-enabled game analytics framework for intelligent player profiling using gameplay data collected from a Unity-ba...
Towards Green AI: A Lightweight Experimental Study on Carbon-Aware Neural Network Training
Industry 5.0 places emphasis on human-centered innovation, aligning digital transformation with sustainability, resilience, and societal well-being. Smart cities serve as practical environments where advanced technologies must balance operational efficiency...
Blockchain-Based Traceability and Age Verification for Nicotine Products
Underage access to nicotine products and the circulation of counterfeit tobacco remain significant public health and regulatory challenges, largely driven by limited supply-chain visibility, centralized record manipulation, and weak enforcement of age-restr...
Language-Specific Tokenization for Assamese: Efficiency and Downstream Integration with LLMs
Tokenization is a fundamental step in NLP, influencing both computational efficiency and downstream task performance. While subword methods such as Byte-Pair Encoding (BPE), WordPiece, and Unigram have shown strong results for high-resource languages, their...
Artificial Intelligence-Driven Intrusion Detection Systems for Secure Healthcare IoT: A Comprehensive Review
The rapid proliferation of Internet of Medical Things (IoMT) devices in healthcare has introduced significant cybersecurity challenges, including data breaches, Distributed Denial-of-Service (DDoS) attacks, and unauthorized access. Intrusion Detection Syste...
Chatbots and Customer Experience: Evaluating Impact, Effectiveness, and Future Trends
With in the framework of customer experience, chatbots have proven to be a useful technology, presenting businesses with unique opportunities for customer engagement and delivering personalized services. However, despite their growing prevalence, understand...
An Improved Framework for Prediction of COVID-19 Cases Using a Deep Learning Approach in a Dynamic Health Management System
The COVID-19 pandemic has highlighted the urgent need for predictive models that can guide effective public health strategies. While machine learning approaches have been widely applied, shallow networks such as SSLPNN are limited in capturing the non-linea...