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641 articles for “Optimization technique”
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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Performance Comparison of Noise-Tolerant, High- Performance CMOS Domino Logic Configurations
Abstract: In high-performance VLSI chip design, domino logic configuration is often preferred over static logic due to its faster operation and smaller area footprint, especially in deep submicron (DSM) technology. However, DSM noise has become a significant challenge in domino-based circuits, leading to compromises in the reliability and signal integrity of integrated circuits (ICs). The switching threshold of domino logic, defined as the input voltage level at which the gate output …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 35–50 Read article
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AI-Based Discovery of High-Performance Energy Storage Polymer Composites: A Comprehensive Review
Abstract: The accelerating global demand for high-performance energy storage systems has stimulated significant research into advanced polymer composites as next-generation electrolytes, electrode binders, and functional membranes for batteries, supercapacitors, and photovoltaic devices. However, the vast compositional and structural design space of polymer materials presents formidable challenges for conventional trial-and-error discovery strategies, which remain slow, costly, and biased by prior expert knowledge. Machine learning (ML) and artificial intelligence (AI) have emerged as …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1083–1097 Read article
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Study and analysis of the Double Data Rate SDRAM Controller for High-speed Interfacing with Processing Device
Abstract: A real-time embedded system must now manage many programs running concurrently. Increased Data Rate Because of its burst access, speed, and pipeline features, synchronous DRAM is a typical memory-building material. DDR transfers are performed using synchronous dynamic access memory. The memory controller must be set with a pipelined design for various applications and systems to perform effectively. The purpose of this study is to design a DRAM controller that will …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 8–13 Read article
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An Adaptive Approach for Real-Time Embedded System Design, Analysis and Optimization
Abstract: Real-time embedded systems are critical components in various domains, such as automotive, aerospace, healthcare, and industrial automation. The design, analysis, and optimization of these systems are vital to ensure their reliable and efficient operation. In this paper, we propose an adaptive approach for real-time embedded systems that aims to address the challenges faced during the development process while maintaining high-quality results. Our approach leverages adaptive techniques to dynamically adjust the …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 1, 2023 · pp. 8–14 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Leveraging Digital Marketing Techniques for Newly Developed Software Using AI
Abstract: In today’s digital era, most software developers prefer using paid advertising campaigns for their newly developed software to strengthen their online visibility and attract new users; this research explores some strategies to increase and maximize the reach of newly developed software through digital marketing campaigns, particularly focusing on the use of artificial intelligence (AI) tools to optimize campaign performance and increase the reach of newly developed software. To fully assess …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 12–22 Read article
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Electroplating and Corrosion Properties of Binary and Ternary Zinc Alloys with Nickel, Cobalt and Iron
Abstract: The anti-corrosive three binary (Zn-Ni, Zn-Co, Zn-Fe) and two ternary (Zn-Ni-Co, Zn-Co-Fe) alloy coating films on mild steel from acid chloride bath using sulphanilic acid and gelatin as additives for the electroplating technique. The normal Hull cell method was used to optimize the bath compositions, temperature and pH of the bath solutions for coating performance against corrosion. The cause of current density (CD) on metal weight percentage (M = Ni, …
Published in Journal of Thin Films, Coating Science Technology & Application Read article
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Enhancing Control with Embedded Ssvep-Bci
Abstract: Brain–Computer Interface (BCI) technology establishes a direct communication link between the human brain and external devices without relying on muscular activity. Among various BCI paradigms, the Steady-State Visually Evoked Potential (SSVEP)-based approach has gained significant attention due to its high signal-to-noise ratio, minimal user training, and suitability for real-time applications. However, implementing such systems on embedded hardware presents challenges such as limited computational resources, signal noise, and latency in processing. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 3, 2025 · pp. 41–52 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Unraveling Ulcerogenesis: A Comprehensive Delve of Enteric & Nonenteric Ulcers
Abstract: Enteric ulcers present a multifaceted landscape encompassing both peptic and non-peptic varieties, demanding a thorough exploration of their manifestations, causes, and pathophysiology. At the forefront of understanding lie pivotal factors such as Helicobacter pylori infection, nonsteroidal anti-inflammatory drugs usage, lifestyle choices, and stress, each wielding significant influence over ulcer development and progression. The intricate interplay of these factors underscores the complexity of enteric ulcer etiology. Helicobacter pylori infection—a prevalent culprit—inflicts …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 1, 2024 · pp. 25–40 Read article
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Large-Scale Green Hydrogen Storage and Transportation: Advancements and Challenges for Sustainable Energy Integration
Abstract: The transition from non-renewable energy sources to renewable energy sources is a significant step in the direction of a sustainable future. Hydrogen is acknowledged as a great renewable energy source, which may help overcome the energy intermittency challenges. Hydrogen must have convenient storage and transportation to become a green hydrogen, i.e., greenhouse gas emission-free energy carrier. Large-scale green hydrogen storage and transportation are pivotal for the effective integration of renewable …
Published in Emerging Trends in Chemical Engineering · Vol. 11, Issue 3, 2024 Read article
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Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
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Advancements In Al6061 Metal Matrix Composites: The Role of SiC, Al₂O₃, and Graphite Reinforcements in Enhancing Properties and Applications
Abstract: Al6061-based metal matrix composites (MMCs) reinforced with silicon carbide (SiC), graphite (Gr), and aluminum oxide (Al₂O₃) exhibit a unique combination of mechanical, thermal, and tribological properties, making them highly suitable for advanced engineering applications. SiC enhances hardness, wear resistance, and load-bearing capacity, while Al₂O₃ improves thermal stability and mechanical strength. Graphite provides self-lubricating properties, reduces friction, and lowers the composite's density, improving fatigue resistance. The synergy of combining these reinforcements …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 90–98 Read article
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A Comparative Study of Oven, Spouted Bed, and Convective Tunnel Drying Methods of Mango for Oil Production
Abstract: Mango seeds, with a high moisture content exceeding 70% (wet basis) require effective drying methods to ensure their preservation and to enhance the quality of derivative products like mango seed oil. Proper drying is essential to inhibit enzymatic activity and microbial growth, which extends the shelf life of these seeds. This study investigates multiple drying techniques, including conventional oven drying, spouted bed drying, and convective tunnel drying, to determine their …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 1, 2025 · pp. 15–19 Read article
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Application of Grey Wolf Optimizer (GWO) strategy for Malware Analysis
Abstract: The ever-evolving landscape of cybersecurity necessitates continuous advancements in malware analysis techniques. This study explores the deployment of the Grey Wolf Optimizer (GWO) algorithm as a novel bio-inspired optimization mechanism to address the challenges posed by modern malware threats. The primary objective is to enhance various facets of malware analysis, including feature selection, parameter optimization, and the overall efficacy of malware detection models. The study begins by introducing the GWO …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 43–53 Read article
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Leveraging Deep Learning for Accurate Weed Identification
Abstract: Weed control is very important for all types of agricultural businesses. The project here revolves around the application of computer vision techniques and, more concretely, deep learning techniques, for the effective recognition and classification of weeds. The EfficientNetB4 architecture is an appropriate backbone as its scalability and performance optimization is adequate. The modifier used is Adam optimization algorithm which will serve as a pre- processor for the model. Weeds at …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 90–99 Read article
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Understanding Food Spoilage: Mechanisms, Shelf-Life Determination, and Safety Standards
Abstract: Food spoilage poses significant challenges to the global food industry, impacting both food safety and economic sustainability. The main causes of food quality deterioration are microbial and non-microbial spoiling. Microbial spoilage primarily results from the activity of bacteria, yeasts, and molds, which thrive under favorable environmental conditions. These microorganisms can lead to food poisoning and spoilage through the production of off-flavors, discoloration, slime formation, and the accumulation of harmful toxins. …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 14, Issue 1, 2025 · pp. 6–9 Read article
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Statistical Modeling of Heat Transfer and Fluid Dynamics: Application in Mechanical Engineering Design
Abstract: Understanding and optimizing the intricate processes involved in heat transfer and fluid dynamics—two concepts essential to mechanical engineering design—require statistical modeling. Engineers can forecast, regulate, and enhance the performance of systems including heat exchangers, turbines, cooling mechanisms, and different fluid machinery by using statistical approaches. In order to address uncertainties, variability in material properties, boundary conditions, and operational parameters, this work investigates the integration of statistical modeling tools in the …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 2, 2024 · pp. 18–22 Read article