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1261 articles for “advanced applications”
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Analyzing Cavitation in Marine Propeller: A Computational Approach with Consideration for Polymer Applications
Abstract: A major source of noise and blade damage in marine propellers is because of the phenomenon of hydrodynamic cavitation. The Computational Fluid Dynamics (CFD) analysis approach is employed for the prediction of the cavitating propeller’s performance characteristics under various conditions of operation with the advance coefficient (J) ranging from 0.55 to 0.91 and cavitation number (σ) in the range of 0.80 to 4.50. The numerical simulation is performed on INSEAN …
Published in Journal of Polymer & Composites · Vol. 12, Issue 8, 2024 · pp. 29–44 Read article
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Material Selection for Optimized Antenna Performance: A Comprehensive Analysis
Abstract: The performance of antennas is heavily influenced by the choice of materials used in their design. This work presents a comprehensive analysis of various materials and their properties relevant to antenna applications, focusing on parameters such as dielectric constant, conductivity, magnetic permeability, and thermal stability. The interplay between these properties significantly affects the efficiency, bandwidth, gain, and impedance matching of the antenna. This study explores materials such as metals, ceramics, …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 1–10 Read article
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AI Voice Detection Tool
Abstract: In today’s digital era, distinguishing between AI-generated and human voices is more important than ever. This project introduces an AI-based voice detection system designed to accurately identify synthetic voices, ensuring security and authenticity across various applications like cybersecurity, media verification, and fraud prevention.Our system works by analyzing incoming audio samples and comparing them against a diverse database of both AI-generated and real human voices. Using advanced machine learning and signal …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 1–8 Read article
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Enzyme Stability Prediction using BERT and CNN-A Deep Learning Approach for Enhanced Biocatalysis
Abstract: An important factor in determining the efficacy of industrial enzymes used in various biotechnological applications is their stability. The goal of this study is to develop a predictive model for industrial enzyme stability, which is essential to the efficiency of these enzymes in biotechnological applications. The research takes a comprehensive strategy to comprehend the parameters affecting enzyme stability by combining statistical analysis, deep learning algorithms (BERT and CNN), and molecular …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 19–35 Read article
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Current Trends and Future Trajectories: Polymer-Modified Concrete in the Context of Bangladesh
Abstract: Polymer-modified concrete (PMC) presents itself as a novel way to improve the characteristics of conventional concrete, tackling a variety of issues in the building industry. This paper explores the present dynamics and future potential of PMC, with a focus on Bangladesh, a fast-expanding country with unique environmental, economic, and infrastructure needs that call for the use of cutting-edge building materials. The benefits of polymer modification, such as increased durability, flexural …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 285–294 Read article
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Exploring the Future of Operating Systems: Architectural Innovations and Kernel Development Trends
Abstract: Modern applications and the rapid evolution of hardware technologies are challenging operating system (OS) design. This paper speculates the future of OS based on revolutionary architecture advancements and emerging possibilities in kernel construction. The growth of multi-core processors, spread-bound processing, and edge architectures have challenged traditional OS paradigms. The paper provides an analysis of the progress in microkernel and monolithic kernel structures, discussing the bandwidth capacity as well as security …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 38–47 Read article
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Harnessing Ethylene and Brassinosteroids for Enhanced Agricultural Productivity and Food Quality
Abstract: This study provides a comprehensive review of the roles of ethylene and brassinosteroids, two vital hormonal regulators in plants, focusing on their impact on fruit ripening, stress responses, and overall plant growth. Ethylene, a gaseous plant hormone, is recognized as a key regulator in various physiological processes, particularly in the maturation of fruits. Its involvement in the ripening process has profound implications for agricultural practices, as it directly influences the …
Published in International Journal of Trends in Horticulture · Vol. 1, Issue 2, 2024 · pp. 29–32 Read article
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Understanding the Corrosion Behaviour of Graphite in Peat Environment for Environmental and Sustainability Applications
Abstract: Graphite, which is one of the most remarkable carbon materials for industrial applications, is a heat exchanger component material in the phosphoric acid industry, bipolar layer or electrode material in vanadium redox flow batteries, electrode material for advanced oxidation processes, electrode material for lead-acid batteries, electrode material in fuel cells and microbial fuel cells, and more interesting, as moderator or core material in nuclear reactors used. Corrosion, one of the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 728–737 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Key Generation Algorithms Using Difference Equations with Multi-Precision Arithmetic: A Review
Abstract: Modern cryptographic systems rely on robust key generation to secure data and communication. This review explores the integration of difference equations and multi-precision arithmetic for cryptographic key generation, addressing limitations in traditional methods like pseudorandom number generators and chaotic systems. Difference equations produce deterministic yet chaotic sequences ideal for cryptography due to their sensitivity to initial conditions and nonlinearity. However, finite precision arithmetic can lead to periodicity and loss of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 23–36 Read article
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Investigations of Mechanical Testing and its Effects on Lithium Ion Battery and Battery Pack for Electric Vehicle Application
Abstract: This research delves into the comprehensive study of mechanical testing methodologies and their consequential impact on the structural integrity, safety, and performance of Lithium-Ion batteries (Li-ion) and battery packs designed for electric vehicle (EV) applications. The investigation aims to enhance the understanding of mechanical stressors' influence on the reliability and safety of energy storage systems crucial for the sustainable advancement of electric mobility. The paper opens with mechanical testing protocols …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 2, 2024 · pp. 35–49 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
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Transforming Digital Health Card Healthcare in India: An Integrated IT Solution
Abstract: India's healthcare sector faces critical challenges, including fragmented medical records, limited access to quality care in rural areas, and inefficiencies in patient engagement and insurance processes. This study proposes an innovative IT-driven healthcare model integrating a digital health card, web application, and NFC-enabled mobile platform. The system aims to streamline medical record management, enable telemedicine consultations, and provide seamless prescription and insurance integration. Advanced digital capabilities ranging from AI-driven recommendations …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 11–15 Read article
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Leveraging Large Language Models for Personalized Document Summarization and Question Answering: An Architecture for Stoner-Friendly Chatbots
Abstract: This study presents a detailed framework for developing personalized chatbots that utilize large language models (LLMs) to process and extract information from extensive documents while effectively responding to user inquiries. The proposed system is designed to mitigate information overload by employing advanced natural language processing techniques, leveraging technologies such as OpenAI, LangChain, and Streamlit. By integrating these tools, the framework enhances knowledge retrieval, simplifies document comprehension, and improves overall productivity. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 88–93 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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Polyurethane: Chemistry, Production, Applications, and Future Prospects—An Overview
Abstract: Polyurethane (PU), a class of versatile polymers, has emerged as one of the most significant materials in modern industry owing to its remarkable mechanical strength, elasticity, durability, and resistance to abrasion, chemicals, and environmental degradation. Its wide range of tunable properties has made PU indispensable across multiple sectors, including fashion, automotive, manufacturing, biomedical, coatings, and construction. This review emphasizes the diverse applications of polyurethane and explores how its unique chemistry …
Published in Journal of Thin Films, Coating Science Technology & Application · Vol. 12, Issue 3, 2025 · pp. 17–25 Read article
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Applications of Nanotechnology in Crop Improvement: New Era of Agriculture
Abstract: It represents a transformative force in agriculture, promising to improve the productivity, yield, sustainability, and food security. This review paper focused on the certain advantages of nanoscience and nanotechnology in enhancing the agricultural productivity, disease management, and food safety. By manipulating different materials and objects at the nanoscale, researchers can develop advanced tools such as smart sensors and targeted delivery systems that improve nutrient absorption and combat plant pathogens. By …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 3, 2025 · pp. 46–54 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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Gene Therapy in Modern Medicine: Promises and Challenge in Treating Genetic Diseases
Abstract: Gene therapy is a medical approach that focuses on altering or adjusting an individual’s genes to treat or prevent illnesses. The aim is to repair faulty genes or insert new ones into the body to combat diseases. Gene therapy can involve directly introducing modified or new genes into a patient’s cells or altering the genes already present in the patient’s body. This approach shows potential for treating a range of …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 2, 2024 · pp. 27–32 Read article
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Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article