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432 articles for “algorithm efficiency”
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Revolutionizing oncology - role of artificial intelligence in early cancer detection and diagnostic advances-A comprehensive review
Abstract: Oncology has experienced a remarkable transformation with the adoption of artificial intelligence (AI), which has greatly enhanced cancer detection and diagnosis. As one of the leading causes of death worldwide, cancer highlights the importance of early detection in improving patient outcomes and survival rates. AI’s ability to analyze vast and complex datasets has enabled groundbreaking innovations in imaging, pathology, biomarker discovery, and predictive analytics. This review highlights key AI-driven advancements …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 18–22 Read article
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Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
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An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System
Abstract: This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 33–39 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Adaptive Task Scheduling And Resource Optimization Using Ai Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Harnessing Bacteria for Next-Generation Data Storage Technologies – A Review
Abstract: The exponential increase in global digital information has created a pressing need for storage technologies that are more durable, compact, and sustainable than conventional electronic media. While hard drives, solid-state drives, and cloud-based systems have transformed information management, they face severe limitations related to storage density, energy consumption, maintenance costs, and long-term preservation. Researchers have, therefore, begun exploring biological systems as alternative information storage platforms. Among these, bacteria have emerged …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article
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PCM with Multiple Node Injections
Abstract: Phase-Changing Materials (PCM) are currently being investigated for use as heat storage in solar energy applications. To analyze the temperature profile, morphing tree structures are used to simulate the melting algorithm of Phase Changing Material with increasing branch numbers. The melting behavior is simulated for invading lines of heat, which range from single-lined, zero branch insertions, to insertions with two branched lines. The research aims to address the growing demand …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 1, 2024 · pp. 2–7 Read article
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Swarm Intelligence: Nature-Inspired Problem Solving
Abstract: Swarm Intelligence (SI) is a computational paradigm inspired by the collective behavior of natural systems, such as flocks of birds, schools of fish, and colonies of ants. It involves decentralized, self- organized systems where simple agents follow simple rules, yet their interactions lead to complex global behaviors. SI has gained significant attention in recent years due to its potential applications in solving optimization problems, routing, scheduling, and artificial intelligence tasks. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 Read article
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Design and Implementation of a Four-Port DC to DC Converter for a Hybrid Energy System
Abstract: A four-port DC-DC converter has been developed for integrating a hybrid energy from renewable sources system into an AC microgrid. This converter is particularly suitable for AC microgrid applications that require system-level power management. It boasts a straightforward design, making it effective for interfacing sources with varying voltage and current characteristics. The converter is created to connect a battery bank, a photovoltaic (PV) panel, a wind turbine, and an inverter, …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 47–60 Read article
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Enhancing LAN Security Using Machine Learning
Abstract: The modern Local Area Network (LAN) is a critical component of any organization's infrastructure, facilitating communication, resource sharing, and access to the wider internet. However, this connectivity also brings inherent security risks. Traditional security measures, relying on signature-based detection and rule-based systems, are increasingly struggling to keep pace with the evolving sophistication of cyberattacks. This is where Machine Learning (ML) offers a powerful alternative, enabling proactive threat detection and enhanced …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 07–16 Read article
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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The Future of Robotics: A Review of AI-Enabled Robotics Research, Development, and Applications
Abstract: Robotics powered by artificial intelligence (AI) is transforming contemporary industries by empowering machines to learn, adapt, and operate on their own in intricate, changing contexts. The breadth and capabilities of automation have been greatly expanded by the convergence of AI technologies with robots, including machine learning, deep learning, computer vision, and natural language processing (NLP). With an emphasis on technological advancements, application areas, and research advances, this study examines current …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 33–38 Read article
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Analyzing the Cognitive Proficiencies of Artificial Intelligence Within the Legal Paradigm: Prospects Within the Jurisdiction of India
Abstract: The swift progress of artificial intelligence (AI) has become a pivotal factor in various industries, notably affecting the legal sector. This study extensively investigates the substantial effects of AI on legal research and case analysis, mapping out the progression of AI technology within the legal domain. The exploration goes beyond mere acknowledgment of AI‘s presence, delving into a nuanced analysis of its potential advantages and the formidable challenges it poses …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 84–112 Read article
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Automated Math Solver Assist with LLM RAG
Abstract: The challenges of solving complex mathematical problems often hinder efficiency in various scientific and engineering domains. This project proposes an innovative solution to these challenges by integrating automated math solvers with large language model (LLM) retrieval-augmented generation (RAG). The proposed system aims to streamline mathematical problem-solving processes, offering a robust and precise tool for real-time recognition, classification, and solution generation. This work provides a novel method of automating the solution …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 25–30 Read article
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Multi-directional Wind Turbine System Optimisation and Mathematical Modelling for India’s Sustainable Wind Energy Development
Abstract: The global trend towards green energy usage is expanding. Wind power is clean and sustainable and may compete with fossil fuels in the electricity market. This project's manufacturing cost must match fossil fuels or other energy sources to be competitive. The main investment in wind generation is in machinery and infrastructure. Wind power becomes competitive by lowering energy costs through turbine design, building, and operation. Understanding wind turbine activity over …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 1, 2023 · pp. 32–42 Read article
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Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture
Abstract: Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture" explores the convergence of cutting-edge technologies in revolutionizing traditional farming practices towards sustainability. This study investigates the integration of Internet of Things (IoT), Artificial Intelligence (AI), and Image Processing techniques in agricultural contexts, aiming to enhance efficiency, productivity, and environmental stewardship. Through a comprehensive review of recent advancements and case studies, this research elucidates the transformative potential of IoT-enabled …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 52–69 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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A Study on Leveraging Sensors and AI in Insect-Inspired Robotics for Unstructured Environments: Bio-Inspired Autonomy
Abstract: Insects, with their unparalleled agility, resilience, and highly efficient sensory-motor control in complex, unstructured environments, offer a rich blueprint for the next generation of autonomous robots. This study explores the design, implementation, and potential of insect-inspired robots, focusing on the synergistic integration of miniaturized sensor arrays and advanced Artificial Intelligence (AI) algorithms. We delve into bio-mimetic sensing, drawing inspiration from compound eyes, olfactory systems, and tactile hairs, to equip robots …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 7–21 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article