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365 articles for “experimental approaches”
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Automated Microstructure Classification with Class-Specific Segmentation for Titanium Based Composite Materials
Abstract: In engineering, characterisation of microstructure is required to determine and forecast behaviour of titanium alloys. Our proposal in this work has been a deep-learning-based framework in the automatic classification and segmentation of Titanium Based Composite Material. The framework then uses EfficientNetB0 backbone, where we have chosen the backbone to scale the performance of classification and the computational efficiency with the assistance of the transfer learning and the compound scaling. In …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 424–433 Read article
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Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Recent Developments in Structural Genomics: Uncovering Cellular Functions
Abstract: Structural genomics has become a groundbreaking field for understanding cellular functions by revealing the three-dimensional structures of proteins and other biomolecules. This field combines advanced methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and computational modeling to explore the molecular structure and behavior of cellular components. Recent advances have significantly accelerated the pace of structure determination, bolstered by high-throughput methods and artificial intelligence tools like AlphaFold. These developments …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 30–35 Read article
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High-Velocity Impact Response of CFRP and Hybrid Composites: A Comprehensive Review on Ballistic Resistance and Damage Mechanisms
Abstract: This review consolidates recent advances in the study of high-velocity impact response of carbon fiber reinforced polymer and hybrid composites. Carbon fiber reinforced polymer composites are widely applied in aerospace, automotive, and defense due to their high strength-to-weight ratio, stiffness, and durability. However, their susceptibility to impact damage such as delamination, matrix cracking, and fiber breakage limits their performance under dynamic loading. To overcome these challenges, researchers have explored reinforcement …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 100–122 Read article
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A Review of Locking Protocols for Concurrency Control in Parallel Databases
Abstract: In modern database systems, many transactions may run at the same time. When several users try to access the same data or update the data simultaneously, then it creates a problem such as inconsistency data, lost updates or misinformation and may lead to conflicts between the transactions and deadlocks. To avoid these types of issues and maintain the correctness of the database, concurrency control protocols are mainly used. This paper …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 Read article
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Experimental Analysis of Wear Characteristics in Natural Fibre Composite Materials
Abstract: In mechanical systems, energy loss and material degradation due to attrition are frequently the consequences of sliding contacts, which frequently lead to premature system failure. In this study, at 50°C, 80°C, and 110°C, the hardness was tested; the results showed that the values were 350.7, 422.5, and 455.5 HV, respectively. After conducting a high-temperature wear test, the mass loss of the as-deposited composite coatings was assessed by an electrochemical approach …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 444–450 Read article
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Performance Analysis of AES Encryption Using LFSR-Based Key Expansion in VLSI
Abstract: Secure data transmission has become increasingly important with the rapid growth of digital communication and embedded systems. Protecting sensitive information from unauthorized access requires reliable cryptographic solutions. Among the available techniques, the Advanced Encryption Standard (AES) is widely recognized for its strong security and efficient implementation in both hardware and software environments. In this work, the design and performance evaluation of an AES-based crypto processor with LFSR-driven key expansion is …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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A Comprehensive Study of Quantum Cryptography
Abstract: Quantum cryptography has emerged as one of the most promising fields in modern information security, offering innovative solutions that have the potential to transform the future of global cyber-defense. Unlike classical cryptographic systems, which depend primarily on the computational difficulty of solving complex mathematical problems, quantum cryptography is grounded in the fundamental and unbreakable laws of quantum mechanics. Core principles such as superposition, entanglement, and the uncertainty principle form the …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 12–26 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
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IoT-Based Motor Protection and Control System Using PLC and ESP8266
Abstract: Because of their straightforward design and affordable price, single-phase induction motors are frequently utilized in residential and small-scale industrial settings. However, conventional direct-on-line (DOL) control provides fixed-speed operation and offers limited protection against thermal overload and fault conditions. This article describes the design and implementation of an ESP8266 Node MCU-based PLC- based closed-loop motor control system with Internet of Things features. To increase operating flexibility and maintenance efficiency, the suggested …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 54–62 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Antidiabetic Potential of Bryophyllum pinnatum: A Study on its Pharmacological Effects and Synergistic Action with Glibenclamide
Abstract: Diabetes is a long-term metabolic disorder that profoundly impacts an individual’s overall health, social interactions, and quality of life. While significant progress has been made in diabetes management with the use of medications such as insulin and oral hypoglycemic agents, the limitations of these existing treatments highlight the need for new therapeutic alternatives. Moreover, the high cost of current diabetes medications makes them inaccessible to many, particularly in rural areas …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 3, Issue 2, 2025 · pp. 18–30 Read article
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Hybrid Additive-Subtractive Manufacturing of Multi-Material Functionally Graded Components: Integration of Laser Powder Bed Fusion with High-Speed CNC Finishing for Aerospace Applications
Abstract: The synergy involved in the merging of additive and subtractive manufacturing technologies is the game changer to generate multi-material functionally graded components to be used in the aerospace industries. The paper is an in-depth review of a proposed hybrid additive-subtractive manufacturing, which synergistically merges laser powder bed fusion (LPBF) fashioning with rapid computer numerical control finishing production processes. The multi-material deposition, thermal issues, and optimization of post-processing are the challenges …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 398–418 Read article
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Optimal Abrasive Jet Machining Parameters for Glass Fiber Reinforced Plastics
Abstract: Abrasive jet machining (AJM) is a best choice for processing of glass fiber reinforced plastics (GFRP). Inherent to the nonlinear behavior of performance characteristics during repeated experiments are inevitable variations, attributed to measurement errors and unknown influencing input variables. This study employs the Taguchi method with an orthogonal array to systematically identify optimal input variables through a limited number of experiments. The paper introduces a direct and reliable Taguchi-based multi-objective …
Published in Journal of Polymer & Composites · Vol. 11, Issue 8, 2023 · pp. 247–255 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Post-Treatment Methods in Additive Manufacturing: A Review of Mechanical, Thermal, Chemical, and Hybrid Approaches
Abstract: Additive manufacturing, particularly Fused Deposition Modeling (FDM), has become a cornerstone of rapid prototyping and functional part production due to its accessibility and material versatility. However, the inherent layer-by-layer nature of FDM introduces surface roughness, reduced mechanical strength, and anisotropic behavior, which limit its industrial applications. This literature review investigates the impact of chemical post-processing treatments such as solvent vapor smoothing, immersion, and hybrid chemical-thermal methods on the surface quality …
Published in Journal of Experimental & Applied Mechanics · Vol. 16, Issue 3, 2025 · pp. 25–34 Read article
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Data Integration and Visualization in Bioinformatics: Techniques and Challenges
Abstract: Data integration and visualization play essential roles in bioinformatics, facilitating the thorough analysis, and interpretation of intricate biological datasets. In the field of bioinformatics, vast amounts of data are generated from various experimental platforms, such as genomic sequencing, proteomics, transcriptomics, and metabolomics. However, the heterogeneity of these datasets, coupled with their large scale and complexity, presents significant challenges in terms of integration, analysis, and visualization. Data integration techniques aim to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Role of Fluid Engineering in Biomedical and Healthcare Systems: A Comprehensive Review
Abstract: Fluid engineering — the study and application of fluid behavior, transport, and interaction — has become a cornerstone of modern biomedical and healthcare systems. This review synthesizes the multifaceted roles fluid engineering plays across diagnostics, therapeutics, biomedical devices, and physiological modeling. Micro-fluidics enables precise manipulation of microliter and nanoliter volumes, facilitating rapid point-of-care diagnostics, high-throughput screening, and the fabrication of uniform nano particles for targeted drug delivery. In cardiovascular medicine, …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 1–5 Read article