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343 articles for “optimization framework”
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Smart Air Filtration Systems for Cities: A Technological Approach to Reducing Urban Pollution
Abstract: Urban air pollution is considered one of the main ecologically critical issues of the 21st century since it threatens citizens' health through respiratory diseases, pathologies of the cardiovascular system, and even premature death. Regarding an extremely high level of pollution in large cities, it becomes necessary to realize technological solutions which could avoid the negative impact of this phenomenon. Smart air filtration systems have emerged as promising solutions for urban …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 2, Issue 2, 2024 · pp. 27–42 Read article
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Smart Parking Solutions: Optimizing Urban Mobility Through Real-Time Apps
Abstract: The changing nature of urban transport has made the city more complicated, with a spiking number of vehicles and a lack of parking facilities. Smart Parking Solutions provide innovative solutions to solve this problem by using real-time information, mobile apps and IoT. The present study presents the aspect of integrating smart parking systems into the urban transportation systems and the role of real-time apps in maximizing parking efficiencies in relation …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 36–61 Read article
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A Study of Fixed-Point and Best Proximity Point
Abstract: Fixed-point theory plays a fundamental role in nonlinear analysis and has significant applications in optimization, differential equations, and applied mathematics. This study investigates the existence and properties of fixed points and best proximity points for various classes of mappings defined on metric and normed spaces. While fixed-point results guarantee the existence of a point that remains invariant under a given mapping, such points may not exist when the mapping is …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 28–39 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Dynamic Analysis of Honeycomb Sandwich Laminated Composite Plate using ANSYS
Abstract: A structural sandwich is a peculiar form of a laminated composite comprising of a combination of distinct materials which are bonded together to use effectively the properties of each separate component to the structural advantage of the whole assembly. Two thin, rigid and quite strong faces in the framework are partitioned by a thick, light and weaker core. The faces are attached adhesively to the core to ensure effective load …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 4, Issue 2, 2026 Read article
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Enhanced Sunlight Intensity Measurement with Solar Tracking System
Abstract: Sunlight intensity measurement plays a crucial role in various applications, particularly in the context of solar energy utilization. However, traditional static acquisition devices often fail to provide precise measurements throughout the entire daylight period. This limitation necessitates the development of more advanced methodologies for accurate sunlight intensity assessment. In this studynn, we propose a novel approach utilizing a solar tracking system integrated with a measurement device to achieve precise sunlight …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 1, 2024 · pp. 8–15 Read article
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Exploring Robotic Arm Fabrication: An In-depth Review of Current Trends
Abstract: Robotic arms have emerged as indispensable tools across a myriad of industries, revolutionizing manufacturing processes, medical procedures, and even everyday tasks. This comprehensive review explores the recent advancements in robotic arm technology, focusing on key developments in design, control, sensing, and applications. The review begins by examining the evolution of robotic arm design, highlighting innovations in materials, actuators, and kinematic configurations that have enhanced the performance, versatility, and dexterity of …
Published in Journal of Control & Instrumentation · Vol. 15, Issue 3, 2024 · pp. 28–41 Read article
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Nutrient Sensing and Microbiota Crosstalk: Driving Determinants Shaping Metabolic Stability and Adaptive Physiology for Animal Health
Abstract: Nutrient sensing is a fundamental cellular process that enables animals to adapt to fluctuating dietary inputs while maintaining metabolic homeostasis and health. Recent advances reveal that the gut microbiota functions as an active metabolic partner, producing bioactive metabolites that directly influence host nutrient-sensing pathways and downstream cellular responses. This review synthesizes current knowledge on the integration of key signalling networks, including adenosine monophosphate activated protein kinase (AMPK), mechanistic target of …
Published in International Journal of Molecular Biotechnological Research · Vol. 4, Issue 2, 2026 Read article
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Lyapunov-Stable Adaptive Fractional-Order Interval Type-2 Fuzzy Control for Robust Anti-Lock Braking Under Uncertain Road Adhesion Conditions
Abstract: This paper proposes a Lyapunov-stable Adaptive Fractional-Order Interval Type-2 Fuzzy Logic Controller (FO-IT2FLC) for robust anti-lock braking system (ABS) control under nonlinear vehicle dynamics and uncertain road adhesion conditions. The proposed framework integrates fractional-order error dynamics to capture memory-dependent tire–road interaction, interval Type-2 fuzzy inference to model uncertainty via footprint-of-uncertainty representation, and a Lyapunov-based adaptive learning mechanism for real-time parameter tuning. A rigorous stability proof guarantees boundedness of all closed-loop …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 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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Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Integrated Frameworks for Artifical Intelligence in Radioactive Waste Characterization and Nuclear Lifecycle Safety
Abstract: The management and characterization of radioactive waste represent a pivotal challenge for the global energy sector, requiring the convergence of advanced physics, material science, and computational intelligence. As the nuclear industry undergoes a paradigm shift toward decommissioning legacy facilities and establishing deep geological repositories, the limitations of traditional, manually-intensive waste management processes have become increasingly apparent. Rigid separation from the biosphere is required for radioactive waste, which is defined by …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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An Integrated Simulation Framework for Predicting Dielectric Breakdown and Electrical Aging in Epoxy-Silica Composite Insulation Systems
Abstract: This paper provides a combined computation approach in forecasting the dielectric breakdown and electrical aging within epoxy-silica composite of insulation system. The approach will consist of a three-complementary methodology (a combination of computing electric field using the finite element analysis, estimation of the probability of failures or breakdowns using Weibull statistics, and prediction of degradation tendencies using artificial neural networks). The epoxy-silica composites are of 10-40 volumes fillers. The simulations …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 339–376 Read article
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Viscoelastic Behavior and Wrinkle Formation in Cotton- Polyester Garments: A Data-Driven Approach for Textile Care
Abstract: This study investigates the wrinkle behavior of cotton-polyester blended fabrics by analyzing data from over 1,200 store-handled garments. Integrating concepts from polymer chemistry and computer vision, it aims to establish a smart textile care framework based on fiber-specific wrinkle characteristics. The research identifies how cotton’s hydrophilic and non-elastic structure results in increased wrinkling, while polyester’s thermoplastic and crystalline properties enhance wrinkle resistance. Elastomeric fibers like Lycra contribute to wrinkle recovery …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 50–60 Read article
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Low-Grade Heat Recovery: Emerging Materials and Systems for Efficient Utilization
Abstract: Low-grade heat (LGH), generally characterized by temperatures below 200°C, constitutes a significant portion of wasted thermal energy in industrial, commercial, and even residential processes. Despite its vast availability, the efficient recovery and utilization of LGH remains underdeveloped due to its inherently low exergy content and the limitations of traditional heat recovery technologies. The creation of cutting-edge materials and creative system-level approaches for LGH recovery has accelerated significantly as companies continue …
Published in International Journal of Energy and Thermal Applications · Vol. 3, Issue 1, 2025 · pp. 24–29 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Optimizing Second Language Acquisition: A Focus on Influential Factors and Techniques
Abstract: The process through which individuals learn a language other than their mother tongue, usually after mastering their first language, is known as second language acquisition, or SLA. In this context, the second language refers to English, and this paper examines the factors influencing its acquisition. Reviews and research on SLA have been considered for a comprehensive study. The use of various tools and technologies for second language learning is highlighted, …
Published in Emerging Trends in Languages · Vol. 2, Issue 1, 2025 · pp. 18–26 Read article
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Mathematical Modeling of Tumor Growth and Immune System Interaction Incorporating Time Delays and Suppression Effects for Tumor Control
Abstract: Cancer growth is a complex biological process influenced by various factors, including the dynamic interaction between tumor cells and the host immune system. Mathematical modeling serves as a powerful tool to understand these interactions and predict the outcomes of different therapeutic strategies. This study presents a mathematical framework that captures the essential dynamics of tumor-immune interactions, specifically incorporating the effects of time delay and immune suppression mechanisms. Time delay accounts …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 3, 2025 · pp. 25–34 Read article