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343 articles for “optimization framework”
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Microalgae Based Wastewater Treatment: A Sustainable Approach
Abstract: The global water crisis and strict environmental policies demand advanced wastewater treatment techniques that combine pollution control with resource recovery. Microalgae-based wastewater treatment has emerged as a sustainable biotechnological solution that aligns with circular economy principles by simultaneously eliminating contaminants and producing valuable biomass that can be converted into useful products. This review paper provides an in- depth assessment of the application of microalgae in treating municipal, industrial, and agricultural …
Published in International Journal of Sustainability · Vol. 3, Issue 2, 2026 · pp. 1–15 Read article
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Carbon Sequestration in Mineralogy: Potential of Ultramafic Rocks for CO₂ Storage
Abstract: The increasing concentration of atmospheric carbon dioxide (CO₂) due to anthropogenic activities has necessitated the development of effective carbon sequestration strategies. Mineral carbonation, particularly utilizing ultramafic rocks, has emerged as a promising approach for long-term CO₂ storage. This review explores the potential of ultramafic rocks in sequestering CO₂, discussing their mineral composition, reaction mechanisms, advantages, and challenges associated with their utilization in carbon capture and storage (CCS). Additionally, advancements in …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 30–35 Read article
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Smart Solar Tracking System for Maximizing Energy Output
Abstract: This paper presents the design and development of a dual-axis solar tracking system using a stepper motor and light- dependent sensors to maximize solar energy capture. The proposed system continuously aligns the photovoltaic panel perpendicular to the sun’s rays, thereby improving overall power-generation efficiency. A complete prototype was developed and experimentally tested. To assess system performance, experimental testing was carried out in a variety of lighting and environmental settings. When …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article
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Integrate AI and IoT to Develop Sustainable Polymer Structural Materials Processing Optimization: Enabled Monitoring Strategies for Performance and Lifecycle Assessment
Abstract: The need for long-lasting structural polymer materials that are both environmentally friendly and highly mechanically effective is driving demand for these materials as the industrial sector continues to grow. Optimizing processes, saving energy, detecting faults, and monitoring structures are all hindered by conventional polymer manufacture. This study suggests an AI-IoT system for environmentally friendly production of structural polymer materials to get around these problems. Tools for evaluating system performance and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 169–192 Read article
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IoT Security: Issues, Best Practices, and Open Challenges
Abstract: The internet of things (IoT) provides the facility to connect different devices and communicate and share information over the internet. IoT has emerged as a transformative and pervasive technological paradigm, revolutionizing how we interact with our environment and infusing intelligence into everyday objects and devices. This interconnected ecosystem has unleashed a wave of innovative applications across diverse domains, including healthcare, transportation, agriculture, industrial automation, and smart cities. However, as the …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 7–13 Read article
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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The Future of Farming with IoT-Operated Drones
Abstract: The integration of Internet of Things (IoT) technology with drone systems has revolutionized precision agriculture, offering innovative solutions to address the inefficiencies and environmental concerns linked to conventional pesticide application. This study explores the design, implementation, and impact of IoT-operated drones tailored for automated pesticide spraying. By leveraging real-time sensor data, AI-driven analytics, and cloud-based connectivity, these drones enable dynamic, data-informed decisions to optimize chemical application. Results indicate that IoT-enabled …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 20–26 Read article
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Optimizing Glass to Metal Composite Seal Performance: An integrated Approach with Artificial Neural Network, Multiple Regression, and Taguchi
Abstract: Composite materials, particularly glass to metal composites, are critical components in solar receiver tubes, where vacuum leakage can significantly compromise the efficiency of solar plants. This research addresses the technical barriers associated with the development of durable and high-quality glass to metal composite seals. We investigate the principles that can enhance the physical and chemical properties of these composite seals, focusing on the incorporation of TiO2 and MgO nanoparticles into …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 418–435 Read article
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Productivity Improvement Using Kaizen-Muda Elimination
Abstract: In today's fiercely competitive business environment, achieving operational excellence and sustainable growth is paramount for organizations across diverse industries. The Kaizen philosophy, rooted in Japanese principles, offers a powerful framework for driving continuous improvement by systematically identifying and eliminating waste, or "muda." This paper explores the concept of Kaizen and its application in eradicating muda, paving the way for enhanced productivity, cost reduction, and a competitive advantage. Kaizen, which translates …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 1, 2024 · pp. 1–6 Read article
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ML-Enhanced Smart Sensing Framework for IoT- Based Structural Health Monitoring Using Conductive Polymer Composites
Abstract: The growing demand for intelligent structural health monitoring (SHM) in dynamic infrastructures necessitates flexible sensing systems that are not only mechanically robust but also capable of real-time interpretation. Conventional SHM frameworks often rely on brittle sensor configurations and cloud-dependent processing pipelines, which suffer from latency, limited durability, and poor adaptability under variable loading conditions. Despite recent advances in composite materials and machine learning, current approaches lack a unified framework that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 348–369 Read article
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Structural Analysis of Heavy Vehicle Chassis Using Various Geometries and Materials
Abstract: The present research investigates the significance of the automobile chassis as a crucial section of a vehicle that provides a framework for the body and other parts to rest on. It highlights the need for the chassis to have sufficient bending stiffness for the best handling qualities, as well as enough rigidity to withstand shocks, twists, vibrations, and other loads. The draft and designing model for all the sections (I, …
Published in Journal of Polymer & Composites · Vol. 12, Issue 1, 2024 · pp. 9–33 Read article
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Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
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Alkylimidazolium Chloride Ionic Liquids as Green Additives in Rubber Composites: A Comprehensive Review
Abstract: The growing emphasis on sustainable and environmentally friendly materials has underscored the use of ionic liquids (ILs) as green additives in polymer science. Alkylimidazolium chloride ionic liquids (ACLs) have emerged as viable possibilities for improving the performance of rubber composites while minimizing the environmental impact of conventional processing aids. This research conducts a thorough examination of the function of ACls in rubber technology, focusing on their physicochemical features, interaction mechanisms …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 1–13 Read article
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The Future of Robotics: A Review of AI-Enabled Robotics Research, Development, and Applications
Abstract: Robotics powered by artificial intelligence (AI) is transforming contemporary industries by empowering machines to learn, adapt, and operate on their own in intricate, changing contexts. The breadth and capabilities of automation have been greatly expanded by the convergence of AI technologies with robots, including machine learning, deep learning, computer vision, and natural language processing (NLP). With an emphasis on technological advancements, application areas, and research advances, this study examines current …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 33–38 Read article
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Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Overview of Ionic Polarization: A Model Based Novel Approach
Abstract: This study presents a comprehensive analysis of ionic polarization through a novel model-based approach that integrates theoretical, computational, and experimental methodologies. Ionic polarization, which significantly influences the dielectric properties of materials, is examined through the lens of the Clausius-Mossotti equation and the Debye relaxation model, providing a theoretical framework for understanding the relationship between ionic displacement and dielectric behavior. To explore ionic displacement and polarization at the atomic level, advanced …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 18–25 Read article
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Using MCDM Methods in automotive industry- A Review
Abstract: In the automobile sector, choosing the best car necessitates weighing a number of factors, including cost, fuel economy, performance, safety, and environmental impact. In order to solve complicated situations that need the simultaneous evaluation of multiple conflicting aspects, Multi-Criteria Decision Making (MCDM) procedures are essential. Among the various MCDM approaches, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and MOORA are widely recognized for their straightforward structure …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 20–26 Read article
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Investigating the Influence of Process Parameters on Photochemical Machining of Phosphor Bronze Alloy Microchannels
Abstract: Microchannels are widely employed in microfluidic devices, biomedical systems, and compact heat exchangers, where their functional efficiency depends strongly on surface finish, dimensional control, and edge quality. Traditional machining techniques often face limitations in producing such features with the required precision, prompting the use of advanced micromachining methods. In the present work, photochemical machining (PCM) has been applied to fabricate serpentine-shaped microchannels in phosphor bronze. The study systematically investigates the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 837–846 Read article