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343 articles for “optimization framework”
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Smart Monitoring and Controlling of the Battery and Motor
Abstract: The demand for effective battery and motor monitoring and management to guarantee dependability, safety, and peak performance has increased due to the quick development of electric vehicles and smart industrial systems. The smart monitoring and control methods used in battery management systems and motor control systems are thoroughly reviewed in this paper. In addition to speed, torque, efficiency, and fault situations in motors, it emphasizes important characteristics like temperature, voltage, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 11–15 Read article
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Graphene–Perovskite Hybrid Opto-Electronic Modulators for Ultra-Low Power Optical Communication
Abstract: This paper proposes a novel self-adaptive neuromorphic opto-electronic transceiver architecture designed to enhance the intelligence, adaptability, and efficiency of next-generation optical communication networks. The proposed system integrates neuromorphic computing principles with photonic signal processing to enable real-time learning, dynamic resource allocation, and autonomous compensation of channel impairments such as dispersion, nonlinearities, and noise. Unlike conventional transceivers, the developed model employs spiking neural networks embedded within opto-electronic circuits to mimic biological …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 41–52 Read article
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Circadian Regulation of Lipid Peroxidation in the Brain: Linking Ferroptosis to Neurodegenerative Vulnerability
Abstract: The human brain operates through highly coordinated physiological and biochemical processes that regulate cognition, behavior, and neural adaptability. Central to these processes are mechanisms governing brain function, neurophysiology, and neuroplasticity, which are increasingly recognized to be influenced by circadian rhythms. Recent advances in cognitive neuroscience, neuroimaging, and behavioral neuroscience have revealed that disruptions in circadian regulation can significantly impact oxidative balance within the brain, particularly through enhanced lipid peroxidation. Lipid …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 1–14 Read article
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Optimization of Supply Chain Management Cost Reduction and Delivery Time Improvement
Abstract: Management of the supply chain is vital for every company's success. Businesses can cut expenses and speed up delivery by effectively regulating the flow of goods and services. In this study, we will explore the various strategies and best practices in supply chain management that can help achieve these objectives. We will delve into the importance of efficient sourcing, inventory management, and logistics to streamline operations and optimize the supply …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 15–21 Read article
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A Comprehensive Review of Deep Compressive Sensing for Efficient IoT Data Management
Abstract: The Internet of Things has revolutionized data-driven ecosystems and offers advanced services, such as live monitoring and automation in various domains: smart cities, healthcare, and industrial automation. However, with the exponential growth of IoT devices, comes a large amount of data generation, which poses considerable problems like network congestion, latency, and energy inefficiency. Compressive sensing (CS), one of the newest signal processing methodologies, has emerged as an enabler to meet …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 Read article
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Enhancing Energy Storage and Optimization of Distributed Energy Resources Using a Hybrid SWOA-MSNN Approach
Abstract: The fast growth of Distributed Energy Resources (DERs) like solar photovoltaics, wind power, and energy storage devices requires enhanced optimization methods to manage energy efficiently and stabilize operations in contemporary smart grids. A significant challenge is the dynamic optimization of the energy storage systems (ESS) and the distribution of the energy among DERs in conditions of uncertainty of loads and generation. The conventional control and optimization methods generally find it …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Optimizing System Management: Innovative Approaches to Shell Scripting for Automation in Large-Scale Systems
Abstract: In today’s dynamically changing technology environment, effective systems management is of utmost importance for enterprises that run their applications or services on large-scale infrastructure. In this article, I detail some of these practices as applied to shell scripting, a fundamental building block for process automation in such environments. Using these advanced scripting methods, system administrators can perform routine tasks much more efficiently than they would manually and greatly reduce the …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 32–40 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Nanotechnology-Driven Drug Delivery: A Comprehensive Review of Current Trends and Future Directions
Abstract: Nanotechnology has revolutionized drug delivery systems, offering profound advancements in precision, efficiency, and targeted therapeutic interventions. This review examines the revolutionary influence of nanotechnology on medical therapies, focusing on advancements, such as precise drug delivery, improved solubility, and responsive treatment systems. These advancements have significantly improved treatment efficacy and minimize side effects, particularly in oncology and chronic disease management. The development of nanoparticles designed for specific cell targeting and environmental …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 1, 2025 · pp. 24–46 Read article
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A Sustainable EOQ Model for Declining Products Incorporating Cubic Demand, Variable Deterioration, Partial Backlogging, and Carbon Emission Optimization
Abstract: In this paper proposes a sustainable Economic Order Quantity (EOQ) model for inventory systems involving decaying items under cubic time-dependent demand, variable decaying rates, and partial backlogging while absolutely considering carbon emission costs. The model reflects practical market actions where demand initially increases and afterwards declines over time, and decay depends on the age of the item. To demonstrate the current model's applicability as well as evaluate the trade-off between …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Role of Pharmaceutical Software in Vaccine Development and Manufacturing Process Optimization
Abstract: Vaccine development and manufacturing have become increasingly complex due to the emergence of diverse vaccine platforms, stringent regulatory expectations, and global demand for safe and effective immunization. Across the vaccine lifecycle – from antigen design and preclinical evaluation to large‑scale manufacturing and post‑marketing surveillance – pharmaceutical software now plays a central role in handling data, optimizing processes, and ensuring regulatory compliance. Software tools support in silico antigen and epitope design, …
Published in International Journal of Vaccines · Vol. 3, Issue 1, 2026 · pp. 1–8 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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AI Driven IoT based Satellite remote sensing system: KSK Approach in Satellite Remote Sensing
Abstract: The convergence of the Internet of Things (IoT) and satellite remote sensing has traditionally been bottlenecked by massive data latency and limited downlink bandwidth. This paper proposes a decentralized framework for an "AI-Driven IoT-based Satellite Remote Sensing System," which shifts the paradigm from raw data transmission to onboard edge-intelligence. By integrating lightweight convolutional neural networks (CNNs) directly into satellite payloads, the system performs real-time feature extraction and anomaly detection before …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 50–57 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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Risk Management in Civil Engineering by FTA, FMEA and Risk Matrix
Abstract: Infrastructure projects, particularly in civil engineering, are fraught with uncertainties that manifest as both physical and financial risks. The project report, titled Quantifying and Managing Financial and Physical Risks in Infrastructure Projects, aims to bridge the existing gap between managing these two critical categories of risks. By integrating advanced statistical methodologies such as Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Risk Matrix, and Regression Analysis, this study …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 34–46 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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Artificial Intelligence and Edge Computing in Oil and Gas: Applications, Architectures, and Operational Realities
Abstract: Artificial intelligence has arrived in oil and gas, and unlike some previous waves of digital enthusiasm in the sector, this one is sticking. Saudi Aramco analyses approximately 10 billion data point every day and reported USD 4 billion in technology-driven operational gains in 2024. ExxonMobil uses AI to increase shale well output by more than 5 percent. Shell has deployed machine learning across more than 10,000 assets using C3.ai to …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 01–06 Read article
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Human-robot Collaboration in Manufacturing: Safety, Efficiency, and Technological Developments
Abstract: Human-robot collaboration (HRC) has emerged as a transformative force in modern manufacturing, significantly enhancing productivity, operational flexibility, and overall efficiency. This review article explores the fundamental aspects of HRC, with a particular focus on safety protocols, efficiency optimization, and technological advancements that are shaping the future of collaborative robotics. Ensuring safety in HRC environments is a primary concern, necessitating the implementation of advanced safety measures, risk assessment methodologies, and compliance …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 18–23 Read article