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102 articles for “Algorithm Performance”
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 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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An Investigative Study on Cache-Oblivious Data Structures
Abstract: Cache-oblivious data structures and data management systems have emerged as critical components in modern computing environments, aiming to optimize memory access patterns across different levels of the memory hierarchy without explicit knowledge of cache sizes or configurations. This study presents an overview of cache-oblivious techniques, including adaptive data structures, compression, parallel processing, and security considerations. The workexplores future directions in cache-oblivious systems, such as non-volatile memory support, graph processing, edge …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 33–37 Read article
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A Study on Automatic Feedback Control by Image Processing for Mixing Solutions in a Microfluidic Device
Abstract: Precise and rapid mixing of chemical and biological reagents is a critical yet challenging aspect of microfluidic systems, often limited by laminar flow conditions and the need for manual or pre- programmed interventions. Existing mixing strategies frequently lack real-time adaptability and closed-loop control, hindering reproducibility and the execution of complex reaction protocols. This work presents an innovative automatic feedback control system utilizing the study on real- time image processing to …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 32–41 Read article
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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Predictive Learning Powered by AI and Sophisticated Student Engagement Techniques
Abstract: The contemporary landscape of education has witnessed a paradigm shift in integrating advanced technologies that have revolutionized the learning experience. Innovative methodologies have emerged to address longstanding challenges, such as enhancing student engagement, accurately predicting academic performance, and personalizing the learning journey. However, despite the numerous benefits that technology brings to education, there remains a crucial hurdle - sustaining student motivation and engagement. Traditional teaching methodologies often struggle to generate …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 127–140 Read article
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Modelling and Control of Grid-Connected PV–Battery Hybrid System Using Dynamic Voltage Restorer for Enhanced Power Quality
Abstract: The integration of large-scale photovoltaic (PV) systems into modern power grids introduces significant challenges in maintaining power quality, including voltage sags, swells, and harmonics. To address these issues, this study presents a comprehensive modelling and control framework for a grid-connected PV–Battery hybrid system equipped with a Dynamic Voltage Restorer (DVR). The PV array is modelled using detailed mathematical equations, while the DC–DC converter incorporates advanced Maximum Power Point Tracking (MPPT) …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 43–58 Read article
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Sensors-Based Electric Machine Design for Industry
Abstract: The integration of advanced sensors is fundamentally changing the economics and reliability of electric machines. It moves design focus from minimizing material cost and adhering to conservative standards toward maximizing operational availability and energy efficiency. In the industry of tomorrow, the electric motor will not be a passive collection of coils and steel, but a self-diagnosing, self-optimizing, and perhaps even self-healing asset—a sentient motor—driven by its highly refined sixth sense, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
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Literature Review and Research Gaps in Power Quality Enhancement: From Conventional Methods to Intelligent Solutions
Abstract: Power quality (PQ) has become a critical concern in modern electrical power systems due to the rapid integration of renewable energy sources, proliferation of power electronic devices, and increasing sensitivity of loads. This paper presents a comprehensive literature review and research gap analysis of power quality enhancement techniques, ranging from conventional approaches to emerging intelligent solutions. Traditional methods, including passive filters, capacitor banks, and synchronous condensers, have been widely employed …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 38–80 Read article
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DDoS Detection Using Cascade Correlation for Improving Network Resources in Cloud Environment
Abstract: Intrusion detection is critical for protecting network security from emerging cyber threats. This study describes a unique intrusion detection system (IDS) based on the Random Forest algorithm. Random Forests are used as an effective classifier to identify patterns linked with malevolent behaviour. This technique uses Random Forests to improve the accuracy and efficiency of intrusion detection systems. The suggested methodology's value is shown by its performance on the benchmark KDD …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 17–22 Read article
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Neural Network Based Fractional Order PID Controller for Harmonic Mitigation of Induction Motor Drive System
Abstract: Torque produced in IM (induction Motor) is collected fundamental torque, however, due to core saturation, air gap irregularity, and winding distribution; stator and rotor slotting harmonics torque are produced. This reduces the quality of the power system, life span, and performance of the motor and the controller device. In this paper, a neural network, based fractional order proportional integral derivative (NNFOPID) controller is designed to compensate the harmonics of the …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 23–41 Read article
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Smart Shuttle System: An IoT and Machine Learning Based Approach
Abstract: The Smart Shuttle System is an IoT-based system designed to provide a hassle-free, cashless payment experience for students using the shuttle service. The system utilizes RFID (Radio Frequency Identification) technology to identify students and deduct the fare amount from their account. Radio Frequency Identification (RFID) technology is being considered as an alternative to traditional money and Unified Payments Interface (UPI) for making payments due to several advantages it provides over …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 9–22 Read article
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Analytical Study on DNA-based Modern Cryptographic Techniques
Abstract: Today, as the amount of information being stored and shared continues to grow rapidly, ensuring the security of that information has become more important than ever.To ensure information security, a variety of techniques are employed, including traditional cryptographic methods such as substitution and transposition techniques, hashing functions, and encryption algorithms like DES, RSA, AES, IDEA, and ECC. DNA cryptography is also new emerging technique for providing security to data and …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Reconfigurable AES Based AEAD For Multi-Mode Operation with Lightweight Compatibility
Abstract: The proposal is for a lightweight, multi-mode, reconfigurable authenticated encryption system with associated data (AEADs) based on AES. It is challenging to effectively integrate different AEADs in hardware because each one has its own mode of operation and/or subfunctions, even though some major AEADs share several basic components (such as the XOR-Encryption-XOR (XEX) scheme, block chaining, and advanced encryption standard (AES). This paper proposes hardware that effectively combines the basic …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 1, 2025 · pp. 54–68 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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Offloading Computation to the Cloud
Abstract: Mobile devices are increasingly relied upon for complex and resource-intensive applications such as real-time video processing, augmented reality, and machine learning. However, their limited computational power, storage capacity, and battery life pose significant challenges. Computation offloading to the cloud has emerged as a promising solution to overcome these limitations by transferring demanding tasks from mobile devices to remote cloud servers. This approach enables improved performance, reduced energy consumption, and enhanced …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 27–37 Read article
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Evaluating AI-Driven Adaptive Learning Models in Mathematics: A Contemporary Perspective
Abstract: Artificial Intelligence (AI) continues to transform mathematics education through data-driven personalization and adaptive learning technologies. This study investigates how AI-enabled adaptive platforms influence student performance and engagement in mathematics classrooms. Using a quantitative approach across two institutions, pre- and post-assessment results were compared between students using AI-assisted adaptive learning tools and those receiving conventional instruction. The findings reveal that AI-driven learners demonstrated significantly higher gains in conceptual understanding and engagement …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 8–12 Read article