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464 articles for “model transformation”
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Virtual Assistant: JarvisAI Using Natural Language Processing
Abstract: This research presents the development of a voice-interactive virtual assistant built upon the JarvisAI framework, integrating advanced technologies such as Natural Language Processing (NLP), Machine Learning (ML), and Speech Recognition. The goal is to enable seamless and intuitive human-computer interaction by allowing users to communicate through natural spoken and written language. The assistant is designed to understand, interpret, and respond to various user commands, aiding in tasks such as information …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 26–39 Read article
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Immunological Mechanisms Underlying Autoimmune Disorders: Recent Advances and Therapeutic Implications
Abstract: A diverse range of illnesses known as autoimmune disorders are typified by dysregulated immune responses against self-antigens, which result in tissue damage and persistent inflammation. Understanding the genetic, epigenetic, and environmental variables that contribute to autoimmune pathogenesis has advanced significantly during the last ten years. Current disease models have been transformed by new understandings of immunological tolerance mechanisms such as the functions of regulatory T cells, cytokine networks, and the …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 1, 2026 · pp. 21–25 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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Entomo-Analytics: Insect Behavioral Intelligence for Climate-Smart Environmental Monitoring Systems
Abstract: Rapid environmental change driven by climate variability, urbanization, and ecological degradation has intensified the need for innovative monitoring systems capable of providing real-time ecological intelligence. Traditional environmental monitoring methods often rely on satellite imaging and stationary sensors, which may lack fine-scale biological sensitivity. In contrast, insects—due to their abundance, ecological diversity, and rapid responsiveness to environmental shifts—offer a powerful yet underutilized source of bio-sensing data. This paper introduces the concept …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 17–26 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Generative AI for VR: Creating Physically Realistic Models
Abstract: Virtual Reality has revolutionized the traditional learning system by creating and interactive and engaging environment. However, its ability to show precise real-world experiences is limited due to lack of physical realism. This study investigates the potential of Generative Adversarial Network (GAN) in creating physically realistic 3D models. Proposed system incorporates deep learning techniques along with physics-based constraints to enhance model’s accuracy and usability. To achieve this, experiments were conducted on …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 14–22 Read article
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Monsoon Flood Forecasting in Gandak River Using Discreet Wavelet Transform
Abstract: The Gandak River in North Bihar carries huge flood during the monsoon period. The daily variation in its flow during this period is so significant that conventional methods find it difficult to model the flow. In this paper, new models employing discreet wavelet transform (DWT) have been developed to forecast daily flows in a large river like Gandak. DWT decomposes the flow series into constituent wavelet components of ``approximations’’ and …
Published in Recent Trends in Civil Engineering & Technology · Vol. 2, Issue 1-3, 2012 · pp. 93–101 Read article
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Comparative of Encryption-Decryption Performance of (Binary, Gray- Scale, Color) Images Using Discrete Fractional Fourier Transform (DFRFT)
Abstract: The Discrete Fractional Fourier transform (DFRFT) provides an effective model of image encryption by further developing the classic Fourier transform by adding fractional orders, which increase the degrees of freedom. Owing to the omnipresence of digital media in many industries like education, healthcare, and entertainment, the mobility of visual data has become a significant issue to keep confidential. Images form one of the main ways of exchanging information and, therefore, …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 54–65 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Composition of Ideal Fluid Flows Around Cylinder Using Bilinear Transformation
Abstract: Advent of conformal mapping eases to model a flow in sought-after domain without trade- off between laws of fluid mechanics and the theory of complex valued-functions. The far-reaching properties manifested by conformal mapping discern and facilitate solution of large class of two-dimensional flow problems. Bilinear transformation is amidst the conformal mappings. The properties, mapping a circular boundary onto horizontal line and composition of bilinear transformations is again a bilinear transformation …
Published in Recent Trends in Fluid Mechanics · Vol. 10, Issue 1, 2023 · pp. 31–38 Read article
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Identification and Evaluation of Safety Factors in Construction Industry Using Fuzzy Reasoning Technique
Abstract: Modern construction projects, characterized by their complexity and uniqueness, are inherently susceptible to various risks. These risks represent uncertain events that may arise during the project's life cycle, potentially influencing its objectives either positively or negatively. Positive risks are referred to as opportunities, while negative risks are identified as threats. To effectively harness these opportunities and mitigate threats, the implementation of Risk Management is essential. A novel theoretical framework known …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 7–12 Read article
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Quantitative Structure-activity Relationship in Computer-aided Drug Design: A Review
Abstract: Quantitative Structure-Activity Relationship stands at the forefront of Computer-Aided Drug Design, providing a systematic framework for understanding the relationship between the chemical structure of molecules and their biological activity. The present review delves into the multifaceted realm of quantitative structure-activity relationship methodologies within the landscape of drug discovery. Through an exploration of diverse quantitative structure-activity relationship models, molecular descriptors, validation techniques, and recent advancements, the present article aims to elucidate …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 55–63 Read article
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Development of Slip Power Recovery Scheme sing Buck-Boost Chopper for Performance enhancement of Wound Rotor IM Drive
Abstract: This paper presents the mathematical modeling and testing of wound rotor induction motor drive (WRIMD) to develop the slip power recovery scheme (SPRS) using buck-boost chopper control techniques improving the performance of drive. The main focus of this research work is on the understanding of methodological development of Simulink model of SPRS. Various mathematical equations describing performance characteristics of WRIMD using SPRS with buck-boost chopper are derived. The performance parameters …
Published in Journal of Power Electronics and Power Systems · Vol. 12, Issue 2, 2022 · pp. 44–63 Read article
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The Role of Smart Grids in Enhancing Energy Efficiency and Sustainability
Abstract: The rapid adoption of smart grid technologies is reshaping the energy sector, prompting significant changes in the traditional utility business model. This survey paper provides a comprehensive analysis of the impact of smart grids on utility revenue streams, focusing on the transition from conventional electricity sales to new, service-oriented business models. By examining key innovations such as energy-as-a-service, virtual power plants, and peer-to-peer energy trading, this study highlights how utilities …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 2, 2024 · pp. 10–18 Read article
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Unified Mass–Energy Dissolution Cosmology (UMEDC): A Staged Framework for Cosmic Energy Transformation and Late-Time Acceleration
Abstract: The ΛCDM model successfully describes the universe’s expansion but remains fundamentally descriptive: it assigns fixed densities to matter, dark matter, and dark energy without providing a unifying physical mechanism behind their coexistence or evolution. In this work, we introduce the Unified Mass–Energy Dissolution Cosmology (UMEDC), a novel framework based on the staged transformation M → DM → DE, where ordinary matter gradually dissolves into a dark-matter-like reservoir, which subsequently transforms …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 18–34 Read article
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Revolutionizing Knee Osteoarthritis Diagnosis: Unleashing the Potential of Vision Transformers
Abstract: Osteoarthritis (OA) is the most common kind of arthritis. By analysing data from both sides of the knee joints, radiologists use the Kellgren–Lawrence (KL) grading system to determine the severity of osteoarthritis (OA). The need for knee arthroplasties has increased as a result of this. Recently, there have been proposals for computer-assisted techniques to improve the precision of OA diagnosis. Choosing between conservative and surgical treatment options for knee osteoarthritis …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 1, 2024 · pp. 24–31 Read article
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Leveraging Deep Learning and Cloud Computing for Water Usage Optimization in Agriculture: A Study
Abstract: Water scarcity and inefficient irrigation practices are significant challenges in modern agriculture. This research investigates how deep learning and cloud computing can be combined to enhance water efficiency in agricultural practices. Leveraging advancements in deep learning and cloud computing, researchers have developed innovative solutions for optimizing water usage. This review examines the state-of-the-art methodologies, technologies, and applications in smart irrigation systems. It explores how deep learning models and cloud platforms …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 83–91 Read article
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Swarm Intelligence in Software Engineering: A Systematic Review of Crowd-Based Development Models
Abstract: The crowd-based software production model has emerged as a transformative paradigm, leveraging global collaboration, decentralized governance, and artificial intelligence (AI)-driven automation to develop software efficiently. Traditional software development models, characterized by centralized control and in-house teams, are increasingly giving way to distributed, community-driven efforts. Key advancements such as blockchain-based decentralized autonomous organizations (DAOs), AI-assisted coding and debugging, and edge computing applications are reshaping the landscape of software engineering. DAOs provide …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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Serverless Computing in Personal Internet of Things (PIoT): Current Trends & Future Perspectives
Abstract: Serverless computing has played a great role in the deployment of the various services and applications including the Personal Internet of Things (PIoT). It illustrates the transformation of cloud programming models, their platforms, and the hiding of inessential details. It is proof of capability and immense endorsement of cloud technologies. In the following study, we analyze the concept of Serverless Computing in the Personal Internet of Things (PIoT), the current …
Published in Current Trends in Information Technology · Vol. 11, Issue 2, 2021 · pp. 1–7 Read article