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
Artificial intelligence (AI) possesses the capacity to transform numerous facets of our existence; however, it concomitantly engenders considerable risks associated with bias and discrimination. This article explores eme…
Artificial intelligence (AI) integration into environ-mental analysis has revolutionized various fields. Including the construction and application of gardens, by enabling precise classification and decision-making for s…
This research investigates the performance of machine learning and deep learning models in detecting heart murmurs from audio recordings. Using the PhysioNet Challenge 2016 dataset, we compare several traditional machine…
This study explores the transformative potential of machine learning (ML) algorithms in optimizing the Routing Protocol for Low-Power and Lossy Networks (RPL), addressing critical challenges in Internet of Things (IoT) n…
Explainable Artificial Intelligence (XAI) enhances interpretability in data-driven models, providing valuable insights into complex decision-making processes. By ensuring transparency, XAI bridges the gap between advance…
Social media has changed the world by providing the facility to common person to share their views and generate their own content, known as Users Generated Content (UGC). Due to huge volume of UGC data being created at g…
In current era of globalization, English language learning is important as it has become a global language and helps people to communicate from various regions and languages. For vocational students whose main aim is to…
Reinforcement Learning (RL) has become a rapidly advancing field inside Artificial Intelligence (AI) and self-sufficient structures, revolutionizing the manner in which machines analyze and make selections. Over the past…
This study introduces a novel approach to traffic congestion detection using Reinforcement Learning (RL) of machine learning classifiers enhanced by Explainable Artificial Intelligence (XAI) techniques in Smart City (SC)…
Art serves as a profound medium for humans to express and present their thoughts, emotions, and experiences in aesthetically and captivating means. It is like a universal language transcending the limitations of language…
