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323 articles for “optimization algorithms”
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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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Emerging Trends in Interdisciplinary Perspectives and Future Frontiers in Modern Symmetry
Abstract: Symmetry, long recognized as a cornerstone of the natural sciences, has increasingly found relevance across a variety of disciplines, from physics and mathematics to economics, architecture, and systems theory. This interdisciplinary review explores the expanding role of symmetry as a conceptual and analytical tool, highlighting its applications in diverse fields. In classical and quantum physics, symmetry principles form the foundation for conservation laws, particle interactions, and field equations. In economics …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 26–30 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Intelligent Robotics using microelectronics Exploring the Future of Smart Machines
Abstract: In the past few years, robotics technology has made remarkable progress. In order to assist humans in their work, robots that can recognise and track people are required; as a result, tools like the "Human Following Load carrier" that can converse and live with people must be created. Localising the robot and its surroundings is one of the primary obstacles in enabling the robot to do different jobs in the …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 10–17 Read article
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Exploring the Development of AI Models Using Open-Source Tools to Predict Patient Outcomes and Optimize Treatment Plans
Abstract: Integrating artificial intelligence (AI) into healthcare offers a transformative opportunity to enhance patient care and clinical decision-making. Through the use of predictive analytics, AI can significantly enhance the accuracy of outcome predictions and assist in developing personalized treatment plans that cater to each patient’s specific needs. This paper delves into the development of AI models using open-source tools, which are increasingly favored for their accessibility, collaborative nature, and capacity for …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 37–49 Read article
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Advancements, Hurdles, and Applications in Quantum Computing
Abstract: Using the ideas of quantum mechanics, quantum computing has become a paradigm shift in computing, enabling computations to be completed tenfold quicker than with traditional computers. This study investigates the current status of quantum computing, looking at the notable advancements, ongoing difficulties, and potential uses that could completely change a range of industries. By utilizing the principles of superposition and entanglement, quantum computers can potentially solve complex problems that classical …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 11–29 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Arduino-Based Embedded-Software for Offline and Web-Based Attendance System
Abstract: Embedded software originally controlled hardware but algorithm and software developed determine mode of control and action expected of the hardware. Arduino hardware microcontroller board called Arduino UNO is one of the best electronics boards with coding these days while many attendance systems developed today are mostly one-way. Many developing and underdeveloped countries cannot guaranty 24/7 electricity and strong network connection or data for fully online attendance system. Based on this …
Published in Research & Reviews: A Journal of Embedded System & Applications Read article
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Intuitionistic Fuzzy Hypergraph Laplacians and Dominating Transversals for Resilient Discrete Network Design
Abstract: This manuscript develops a discrete mathematical framework for resilience analysis on networks whose interactions are polyadic, uncertain, and partially conflicting. Classical graphs compress multi-way coordination into pairwise edges, while ordinary fuzzy graphs often ignore the non-membership information that becomes critical in emergency logistics, infrastructure interdependence, and cyberphysical coordination. We therefore formulate an intuitionistic fuzzy hypergraph in which each vertex hyperedge incidence carries membership, non-membership, and hesitation, and we construct a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 15–21 Read article
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An Investigation of Model Predictive Control in Self-driving Vehicles
Abstract: Autonomous vehicles, which are often known as self-driving automobiles or driverless cars, are vehicles that can navigate and operate without human intervention. They require efficient controllers capable of handling complexities, with reduced computational costs, and should handle multiple inputs and outputs simultaneously. Model predictive control (MPC) possesses all these characteristics which means it can be utilized effectively for the same purpose. MPC for autonomous vehicles proposes various ways of achieving …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 40–50 Read article
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Next-Gen Techniques for Bottleneck Detection in High-Performance Computing
Abstract: Modern computing systems face new challenges in bottleneck detection and mitigation due to their increasing complexity which stems from multi-core architectures alongside distributed platforms and real-time processing needs. Traditional methods like hardware profiling and static analysis which used to work well now struggle to keep up with the changing conditions of dynamic system behaviors and diverse computing environments along with variable workload patterns. The current limitations restrict their capability to …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 09–14 Read article
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A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV
Abstract: This venture presents an IoT-enabled and hand gesture-managed robot arm that operates in three distinct modes: automated control, IoT-based control via the Blynk app, and gesture-based control using OpenCV. The gadget integrates a NodeMCU microcontroller for wireless verbal exchange and management, with MQTT protocol enabling real-time messaging among the devices. In automated mode, the robotic arm plays predefined tasks autonomously. In IoT mode, users can remotely manage the arm using …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 35–40 Read article
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Performance Analysis And Battery Management System Optimization In Electric Vehicles
Abstract: The rapid electrification of the automotive industry has led to an increased need for battery management systems that are not only efficient and safe but also intelligent. BMS is the device that guarantees the best use of the battery, prolongs its life, and allows its safe operation even under different environmental and load conditions. Through the synthesis of literature and industry practices, this paper acts as a tribute to the …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 Read article
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Smart HVAC Systems: The Role of IoT and AI in Energy Optimization
Abstract: Heating, ventilation, and air conditioning (HVAC) systems are crucial for maintaining interior comfort and air quality in all types of buildings. However, they also rank among the highest energy users in the built environment. Traditional HVAC systems are evolving into intelligent, networked systems through the integration of Internet of Things (IoT) and artificial intelligence (AI) technologies, as energy efficiency and sustainability become increasingly important across the globe. This review article …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 2, 2025 · pp. 38–43 Read article
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Optimized Text Extraction and E-Repository Development of Hindi and Punjabi Documents Using OCR and NLP Techniques
Abstract: Increase in digitalization of content in the form of text content necessitates powerful document and text extraction systems, particularly for Indian languages such as Hindi and Punjabi. The existing Optical Character Recognition (OCR) solutions support major scripts such as English, leaving a research opportunity for effective recognition of Devanagari and Gurmukhi scripts. This study recommends a modified text extraction algorithm based on Tesseract OCR, accompanied by preprocessing steps of conversion …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 35–43 Read article
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Future Prospects of AI in Pharmaceutical Industry and its Limitation
Abstract: The pharmaceutical industry is facing significant challenges, including prolonged drug development timelines, high costs, and low success rates in clinical trials. Traditional methods often result in inefficiencies, with new drug development taking over a decade and billions of dollars, yet most candidates fail in clinical trials due to issues like inefficacy or safety concerns. Artificial Intelligence (AI) has become a groundbreaking technology with the potential to tackle these issues effectively. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 6–13 Read article
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AI-Powered Drug Delivery: Revolutionizing Formulation Science
Abstract: Artificial Intelligence (AI) is emerging as a groundbreaking tool in revolutionizing Drug Delivery Systems (DDS), offering promising advancements in precision, efficiency, and personalized treatment strategies. The integration of AI technologies into pharmaceutical research and development is transforming how drugs are formulated, delivered, and monitored in real time. By leveraging machine learning algorithms and data analytics, researchers can design drug delivery models that are not only more effective but also tailored …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 48–61 Read article