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311 articles for “Network optimization”
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Cyclist Safety Enhancement: A Multi-Modal Hazard Detection System
Abstract: This study presents a multi-modal hazard detection system to enhance cyclist safety in urban environments. Lever- aging a combination of computer vision, object tracking, and predictive modeling, the system offers a comprehensive approach to identifying and mitigating potential risks. Key contributions include improved depth estimation through object size priors, multi-class tracking utilizing KCF and Brisk, and a novel recurrent neural network architecture for predicting bicycle movement. The system’s collision detection …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 1, Issue 2, 2023 · pp. 35–83 Read article
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Transforming Transportation in India: Exploring the Challenges and Opportunities of Electric Vehicles
Abstract: They also help lessen the impact of ozone-depleting substances and support the widespread adoption of renewable energy. Although significant research has focused on EV features, performance, and charging infrastructure, challenges in production and network modeling persist. This paper provides an overview of various EV technologies, including EVs, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), and evaluates their market penetration rates. It explores various …
Published in International Journal of Energy and Thermal Applications · Vol. 2, Issue 2, 2024 · pp. 17–23 Read article
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Revolutionizing Agriculture with Advanced Computer Vision Technologies
Abstract: The integration of computer vision technology in smart agriculture has marked a significant advancement in the way farming operations are conducted, leading to enhanced productivity and efficiency. This paper explores the multifaceted applications of computer vision, which include crop monitoring, disease detection, automatic harvesting, and quality inspection. By utilizing high-resolution imaging and advanced algorithms, farmers can achieve real-time insights into crop health and growth stages, enabling them to make informed …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 24–30 Read article
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Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
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Lesser-Known Metabolites Influencing Ovarian Function, Follicular Development, and Embryo Viability in Dairy Cows
Abstract: The intricate processes of ovarian function, follicular development, and embryo viability in dairy cows are tightly regulated by a complex network of metabolites. While conventional biomarkers, such as steroid hormones, amino acids, and glucose metabolites, have been extensively studied, a growing body of evidence suggests that lesser-known metabolites play pivotal roles in bovine reproductive physiology. Dairy cattle fertility is critical for maintaining optimal milk production and herd sustainability, necessitating deeper …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 15, Issue 3, 2025 · pp. 18–29 Read article
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Efficient Energy Management and Utilization Using IoT Enabled Intelligent System
Abstract: Energy is essential for economic development, and the demand for electricity is rising at an extraordinary pace. Currently, fossil fuels remain the main source of global power generation, but these resources are limited and detrimental to the environment. Therefore, there is an urgent need to broaden energy sources and transition towards cleaner, sustainable, and renewable options. This paper examines the potential of multi-source power generation and usage as a viable …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 1, 2025 · pp. 38–45 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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IOT Based Monitoring and Controlling Substation Equipment
Abstract: The project ”IoT-Based Monitoring and Controlling Substation Equipment” revolves around utilizing the Internet of Things (IoT) technology to make the substation equipment electrical monitoring and control easy. Timely monitoring of these substation equipment is utmost important in ensuring the stable and reliable operation of the power distribution system. This project will design a system whereby sensors collect real-time data on the key parameters such as voltage, current, temperature, humidity, and …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 3, Issue 2, 2025 · pp. 53–58 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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Electromagnetic and Dielectric Performance of Polymer–Ceramic Composite Substrates for Fractal-Based IoT-Antenna Fabrication
Abstract: Polymer–ceramic composite substrates play a crucial role in determining the electromagnetic performance, mechanical stability, and thermal reliability of radio-frequency devices. In this work, a polymer-based composite substrate is systematically investigated for its suitability in compact IoT and RFID antenna applications. A fractal-structured antenna is employed as a functional test platform to evaluate the dielectric behavior, impedance characteristics, and radiation efficiency of the composite substrate. Novelty of the proposed reader antenna …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1518–1534 Read article
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Monoclonal Antibodies in Next Generation Animal Nutrition: Mapping Nutrient Immune Interaction Networks in Livestock Systems
Abstract: Sustainable livestock production is increasingly constrained by disease pressure, antimicrobial resistance, and declining feed efficiency under intensifying environmental stressors. Conventional nutritional strategies, while essential, remain insufficient to precisely regulate immune function and metabolic resilience. This review explores the emerging role of Monoclonal antibodies as advanced biologics in next generation animal nutrition, with a focus on mapping nutrient immune interaction networks in livestock systems. It synthesizes current knowledge on how nutrients …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 1, 2026 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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SmartTrack : Advanced Attendence System using LR RFID
Abstract: This project presents the design and implementation of a long-range RFID attendance system aimed at transforming how educational institutions track attendance by making the process faster, more accurate, and completely contactless. Tradi- tional methods, whether manual roll calls or short-range RFID scanners, often interrupt class routines and leave room for errors or proxy attendance. To address these issues, the proposed system integrates long-range RFID readers, beam sensors, and ESP32 microcontrollers …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 1, 2026 Read article
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A study on CMOS Operational Amplifier in Sensor Development
Abstract: CMOS operational amplifiers (op-amps) have emerged as pivotal components in modern sensor development, enabling the amplification and conditioning of weak signals with high precision and efficiency. Their inherent advantages low power consumption, compact size, and seamless integration with digital circuits make them ideal for advancing miniaturized, battery-powered sensor systems in fields ranging from biomedical devices to IoT networks. By delivering precision, power efficiency, and integration, CMOS op-amps are not just …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 01–07 Read article
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Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites with Embedded Memristive Energy Routing for Adaptive Solar Energy Harvesting
Abstract: This dynamic and fast-growing intelligent renewable energy system requires photovoltaic materials that can autonomously adapt to fast-changing environmental conditions. In this study, a novel system is proposed for adaptive harvesting of solar energy based on Neuromorphic Self-Learning Polymer–MXene Photovoltaic Composites (NSPMPCs) with embedded memristive energy routing networks. To boost the charge generation and charge transport in the polymer–MXene heterostructure, the flexibility and processability of conductive polymers are integrated with the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Industry 4.0 and Smart Supply Chains: Transforming Supply Chain Processes for Enhanced Efficiency and Sustainability
Abstract: The fourth industrial revolution, or Industry 4.0, is an important transformation in how industries function via the use of cutting-edge digital technology. Supply chain management is being substantially altered by integrating technologies like blockchain, big data, automated processes, artificial intelligence, and the internet of things into typical operations of the supply chain. With the help of these technologies, corporations can design intelligent supply chains that are more effective, flexible, and …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 1, 2025 · pp. 36–41 Read article
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An Overview on Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial intelligence techniques with core operating system services is ushering in a new class of platforms—Intelligent Operating Systems (Intelligent OS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article