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1147 articles for “system optimization”
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Smart Ways to Manage Waste with AI and IOT: A Review
Abstract: Rapid urban growth and population have led to exponential growth in municipal solid waste over traditional inefficient waste management systems (collection / segregation / disposal). This paper reviews the convergence of Internet-of- Things (IoT) and artificial intelligence (AI), seen as two potential smart techniques to launch smarter waste management. The research reports important applications for AI and IoT in waste classification, waste collection optimization, waste-to-energy as well as smart bin …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 2, 2025 · pp. 26–31 Read article
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Farm Robotics: The Future of Autonomous Harvesting and Planting Systems
Abstract: The integration of ranch robotics, particularly independent systems for planting and harvesting, is transubstantiating the agrarian geography by perfecting effectiveness, sustainability, and resource operation. This study examines the current advancements in independent robotic systems designed to automate crucial agrarian tasks, including planting, weeding, and harvesting. These systems influence technologies similar as artificial intelligence (AI), machine literacy, and robotics to optimize husbandry processes, reduce labor costs, and enhance productivity. The benefits …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 07–13 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Reinforcement Learning for Adaptive Sensing with Shape Memory Polymer-Based IoT Nodes
Abstract: The rapid expansion of intelligent sensing in the Internet of Things (IoT) has revealed the pressing need for materials and algorithms capable of self-adaptation in volatile environments. Conventional polymer-based sensors and static control strategies often fail to capture nonlinear thermo-mechanical dynamics, leaving them unsuitable for unpredictable operating conditions. Although prior studies have improved polymer composites or introduced algorithmic optimization independently, few attempts have coupled the adaptability of smart materials with …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 370–391 Read article
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Mood Mate: A Solid-State Edge-AI System for Real-Time Facial Emotion Recognition
Abstract: Recent progress in solid-state electronics and embedded vision systems has enabled real-time emotion-aware applications at the edge. This paper presents MoodMate, a solid-state edge-AI framework for real-time facial emotion recognition using camera-based sensing and embedded processing. The proposed system integrates a solid-state image sensor with an AI- driven emotion classification pipeline optimized for low-latency and resource-constrained environments. Intelligent, emotion-aware apps can now be deployed right at the network edge thanks …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 24–30 Read article
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Analysis of a New Approach to Admission Call Control
Abstract: This study presents a new method of managing call admission in wireless networks using a resource reservation technique. The system under study comprises a defined number of operating devices, standby units, and technicians assigned to repair failed devices. In this method, the failure and repair of devices are assumed to follow an exponential distribution. Whenever a device fails, a standby unit replaces it to maintain seamless functionality, and the failed …
Published in International Journal of Mobile Computing Technology · Vol. 3, Issue 2, 2025 · pp. 01–06 Read article
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Electroconvulsive Therapy in the Management of Schizophrenia: A Systematic Review in Emergency Nursing Practice
Abstract: Electroconvulsive therapy (ECT) is a well-established treatment for various psychiatric disorders, including schizophrenia, particularly in cases where patients are resistant to conventional treatments. Schizophrenia, a chronic and severe psychiatric disorder, often presents with a combination of positive symptoms (such as hallucinations and delusions), negative symptoms (such as social withdrawal and emotional blunting), and cognitive impairments. While antipsychotic medications are the primary treatment, approximately 20–30% of individuals with schizophrenia do not …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 43–48 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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Performance Assessment of External Source-Driven Binary Vapor Cycles with Ammonia-Water and Trans-critical CO2: The Impact of Reheating and Pressure Variations
Abstract: This paper investigates the thermodynamic performance of binary vapor cycles, focusing on two working fluid combinations—ammonia-water mixtures and trans-critical carbon dioxide (CO2). The analysis evaluates how system performance is influenced by incorporating reheating processes and varying operating pressures, which are key parameters in optimizing cycle efficiency and energy recovery. By leveraging external heat sources and exploring these configurations, the research aims to provide insights into improving the efficiency of industrial …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 23–29 Read article
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A Smart Framework that Combines Data Mining and Optimization for Different Applications
Abstract: Blending predictive data mining with metaheuristic optimization has become essential for tackling tough, real-world problems across all kinds of fields. Most existing methods stick to fixed algorithms, each focused on a tiny slice of the puzzle, barely budging when new variables or unpredictability show up—especially with messy, human-generated data. So, here’s the idea: a Unified Metaheuristic and Predictive Data Mining (UMPDM) framework that finally connects adaptive search methods with powerful …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Optimized Hardware Realization of AES for High-Throughput FPGA Platforms
Abstract: The Advanced Encryption Standard (AES) is the predominant symmetric-key cryptographic algorithm used for securing digital communication across embedded systems, IoT devices, cloud infrastructures, and defense networks. Although software-based AES implementations offer flexibility, they often fail to meet the high-speed, low-latency, and energy-efficient requirements of modern real-time applications. Reconfigurable hardware platforms such as Field-Programmable Gate Arrays (FPGAs) provide a powerful alternative by enabling architectural customization, intrinsic parallelism, and optimized hardware acceleration. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 11–22 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Finite Element Modelling of Contact Stresses in Helical Gear Systems
Abstract: Helical gears are widely used in modern power‐transmission systems because of their high load‐carrying capacity, smooth meshing action, and increased overlapping of gear teeth. However, the design of helical gear pairs is constrained by contact stresses generated at the mating tooth surfaces, which can lead to surface fatigue (pitting), micro-cracking, and ultimately gear failure. Traditional analytical methods, such as those of the American Gear Manufacturers Association (AGMA) or International Organization …
Published in Trends in Machine design · Vol. 12, Issue 3, 2025 · pp. 35–39 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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Analyzing Barriers to Digital Procurement in Polymer Composites Supply Chain Using ISM for Sustainable Transformation
Abstract: The adoption of e-procurement in the polymer and composites industry presents a transformative opportunity to enhance supply chain efficiency, reduce material waste, and support sustainable engineering practices. However, industries face significant barriers in transitioning from traditional procurement to digital systems, particularly in sourcing specialized materials such as epoxy resins, bio-based polymers, and hybrid composites. This study employs Interpretive Structural Modeling (ISM) to identify, analyze, and prioritize eleven critical barriers affecting …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 512–521 Read article
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Energy-Efficient Thermal Management: Advanced Cooling Techniques for Electronics, Automotive, and Aerospace Applications
Abstract: The growing demand for energy-efficient systems across diverse industrial sectors, including electronics, automotive, aerospace, and renewable energy, has elevated the importance of advanced thermal management techniques. Effective heat dissipation is critical not only for maintaining optimal operating conditions in electronic devices but also for enhancing the performance and reliability of broader energy and mechanical systems. Inadequate thermal management can compromise energy efficiency, reduce component lifespan, and increase environmental impact. This …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article
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Emerging Trends in Fruit and Vegetable Science: Advances in Cultivation, Postharvest Management, and Value Addition
Abstract: Fruit and vegetable industries are undergoing a radical restructuring as a result of technological development, sustained focus on sustainable development, and rising customer preferences. This review focuses on the latest changes and developments in cultivation, postharvest, value-addition, and management in the global landscape of horticulture. With a global cultivation of 367.72 million tons and a combined market value of greater than 800 billion USD, the sector grapples with significant challenges; …
Published in International Journal of Trends in Horticulture · Vol. 3, Issue 1, 2026 · pp. 42–55 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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A Critique of Advanced Instrumentation for Supervising and Regulating Renewable Energy Systems
Abstract: The integration of renewable strength property into the power grid necessitates modern-day tracking and manipulate systems to ensure highest best average overall performance, reliability, and performance. This paper offers a comprehensive analysis of advanced instrumentation applied for monitoring and controlling renewable strength systems. Beginning with an outline of renewable energy assets and their importance in addressing environmental worries and electricity sustainability, the compare delves into the challenges inherent in monitoring …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–12 Read article
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Nutrient–Xenobiotic Crosstalk in Dairy Cattle: Implications for Metabolism, Immunity, Health, and Productivity in Resilient Dairy Development
Abstract: Dairy cattle are routinely exposed to a wide range of xenobiotics, including mycotoxins, heavy metals, pesticides, residues from veterinary drugs, and plant secondary metabolites, through feed, water, and environmental sources. These xenobiotics, being foreign to biological systems, can interfere with the absorption, metabolism, and utilization of essential nutrients, while also compromising immune function, organ health, and overall physiological performance. Chronic or subclinical exposure can reduce feed efficiency, disrupt energy and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 37–46 Read article