The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Artificial intelligence (AI) is the branch of computer science concerned with building systems that perform tasks normally requiring human intelligence, such as reasoning, planning, perception, and language understanding. The field spans symbolic approaches (rule-based expert systems, knowledge graphs, automated planning) and statistical approaches (machine learning, deep neural networks, probabilistic reasoning), increasingly combined to improve interpretability and reliability. AI research addresses search and optimization, multi-agent coordination, knowledge representation, and generalization from limited data. Applications range from recommendation engines and autonomous vehicles to fraud detection, scientific discovery, and decision-support systems in medicine, finance, and manufacturing. Agentic AI, systems that plan and act across multi-step tasks, has become a leading research focus; Stanford's 2026 AI Index Report finds most organizations are still experimenting with AI agents rather than deploying them at scale. As a peer-reviewed, open-access artificial intelligence journal, IJACSA (an AI journal indexed in Scopus) publishes research spanning foundational algorithms to applied AI systems evaluated on real-world datasets.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
Estimating crowd size in dense environments re-mains a complex problem, yet it holds critical value for safety monitoring, city infrastructure design, and large-scale gathering coordination. Leveraging contemporary devel…
Academic stress represents a significant challenge in higher education, especially for students navigating unfamiliar academic environments. In such contexts, difficulties in understanding expectations, feedback, and per…
Robust inspection of aeroengine turbine blades remains a critical challenge in safety-critical industrial environments, where limited data availability, class imbalance, optimisation bias, and imaging degradation can red…
This research examines the challenges of AI adoption in Saudi Arabia healthcare sector in terms of the framework defined by the Vision 2030 healthcare transformation agenda. We utilized the Analytic Hierarchy Process (AH…
With the widespread adoption of the Internet of Medical Things (IoMT), hospitals have become prime targets for cyberattacks. To overcome the limitations of traditional defenses and computationally heavy deep learning mod…
Iterative Magnitude Pruning (IMP) is a widely used technique for compressing neural networks by progressively removing low-magnitude weights while maintaining predictive accuracy. Despite its widespread application and s…
Software bugs remain one of the most costly chal-lenge in software engineering, consuming significant development time and resources. Recent advances in Artificial Intelligence (AI), particularly deep learning and large…
A shift from deterministic testing to artificial intelligence (AI) driven quality ecosystems is necessitated by the rapid evolution of software architectures, and research from 2016 to the present year is combined by thi…
Career transition into digital professions is a strategic lever for addressing youth unemployment in Sub-Saharan Africa. However, existing training programs lack objective career guidance tools. This study presents two c…
This study conducted an Artificial Intelligence-assisted community needs assessment of partner-community respondents of Wesleyan University-Philippines, with emphasis on the Tricycle Operators and Drivers Association. Us…
