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464 articles for “model transformation”
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Covariance based Clustering for Digital Image Compression
Abstract: Traditionally clustering is done based on distance between the data points and the cluster centroids. A new type of clustering based on distance between the covariance matrices of the clustered data points was recently introduced. This allows clustering data points according to their spatial distribution model. This paper presents an improved algorithm for the computation of covariance based clustering with application to digital image compression. Karhunen-Loeve Transform is an optimal …
Published in Current Trends in Information Technology · Vol. 8, Issue 1, 2018 · pp. 16–21 Read article
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Processing of Deepfake Images Using Deep Learning
Abstract: Face identification has been a significant exploration subject in the mid 2000s. Right around twenty years after the fact, this issue is essentially settled and face recognition is accessible as a library in most programming dialects. Indeed, even face-trade innovation is the same old thing and has been around for a couple of years. Such an advancement depends on neural organizations whole computational models that are inexactly roused by the …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 2, 2022 · pp. 24–29 Read article
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Vibration Characteristics of Copper-Aluminium Composite under Different Boundary Conditions: Experiment and Simulation
Abstract: The utilization of vibration analysis on the tapered beam significantly enhances the engineering investigation and design process. It is notable that the width of the tapered beam exhibits variation along its length, while the height remains constant. Experimental modal testing aims to determine modal factors such as natural frequency, damping, and mode shapes. A comparative study is presented in this paper, examining the vibrational characteristics of tapered beams composed of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 190–203 Read article
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Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
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Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
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Algebraic Foundations of Generalized Signal Processing: A Unified Approach Across Domains
Abstract: Using the techniques of algebra, notably polynomial algebras and modules, algebraic signal processing (ASP) is a contemporary, abstract framework that generalizes conventional signal processing— including Fourier analysis, filtering, and convolution. The notion is to use algebraic structures to explain signals, systems, and transformations such that ideas may be understood and generalized across many domains, including time, space, graph, or group. A unifying theoretical framework called ASP generalizes classical signal processing …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 33–44 Read article
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Detecting Winding Movement by Fuzzy Logic for Frequency Response of Power Transformer
Abstract: Power transformers are basically one of the most efficient devices that are used in Power Plant or in any substation. Its maintenance is bit some tedious but has to be done to diagnose any severe fault that may damage the transformer. Sweep Frequency Response Analysis (SFRA) is used to detect any winding or core deformation in transformer that would arise during transportation, due to severe short circuits or due to …
Published in Journal of Power Electronics and Power Systems · Vol. 5, Issue 3, 2015 · pp. 25–34 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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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 · pp. 22–36 Read article
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Study and Performance Analysis of Orthogonal Frequency Division Multiplexing with Different Modulation for Rayleigh Channel Model
Abstract: AbstractFor the advancement of wireless communication systems, methods such as MIMO, OFDM and integrating them together as MIMO-OFDM are very useful. OFDM is used in numerous wireless transmission standards nowadays. In OFDM, high rate data stream is divided into low-rate streams which are transmitted together over a number of subcarriers. A broadband and frequency-selective channel are transformed into a multiplicity of parallel narrow-band single channels by the OFDM modulation. By …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 76–80 Read article
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AI-Assisted Kinetic Modeling of PLA Hydrolysis Under Subcritical Water Conditions for Sustainable Polymer Recycling
Abstract: The accumulation of poly (lactic acid) (PLA) in terrestrial and marine ecosystems has intensified the demand for closed-loop, green recycling technologies. Subcritical water (SCW) hydrolysis offers a promising, catalyst-free pathway for the rapid depolymerization of PLA into its constituent monomer, lactic acid. However, the complex, highly non-linear kinetics governing macro-molecular degradation under variable hydrothermal conditions limit real-time process optimization and industrial scalability. This study develops a novel artificial intelligence (AI)-assisted …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 2, 2026 · pp. 65–74 Read article
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Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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A Systematic Review on The Role of Artificial Intelligence in Assisted Reproductive Technology
Abstract: Artificial Intelligence (AI) has significantly transformed Assisted Reproductive Technology (ART) over the past five years, enhancing diagnostic accuracy, treatment personalization, and overall success rates. AI-driven algorithms and machine learning models have been integrated into various aspects of ART, including sperm selection, embryo grading, and predicting implantation success. Deep learning techniques have improved image-based embryo assessment, reduced human subjectivity and increased efficiency. Additionally, AI-powered predictive analytics have helped optimize ovarian stimulation …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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USING DIFFERENT END CONDITIONS EXPERIMENTAL AND THEORETICAL ANALYSIS FOR VIBRATIONAL PROPERTIES OF NATURAL FIBER COMPOSITES BEAM
Abstract: The today’s research trend in composite is for the development of composite with natural fibre instead of synthetic fibre. It is because of properties like low cost, light weight, bio-degradability, ease to manufacture and low impact on environment. It becomes necessary to study the vibrational behaviour of composite in addition to mechanical strength and chemical properties for effective utilization in real world applications as they subjected to many types of …
Published in Trends in Machine design · Vol. 5, Issue 2, 2018 · pp. 34–41 Read article
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Transforming Transportation in India: Exploring the Challenges and Opportunities of Electric Vehicles
Abstract: They also help lessen the impact of ozone-depleting substances and support the widespread adoption of renewable energy. Although significant research has focused on EV features, performance, and charging infrastructure, challenges in production and network modeling persist. This paper provides an overview of various EV technologies, including EVs, hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), and evaluates their market penetration rates. It explores various …
Published in International Journal of Energy and Thermal Applications · Vol. 2, Issue 2, 2024 · pp. 17–23 Read article
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HFSS-Based Helix Antenna Design Optimization and Simulation
Abstract: This project uses HFSS (High-Frequency Structure Simulator) to simulate, develop, and analyze the performance of a helix antenna for (a particular purpose, such as broadband wireless or satellite communication). Because of their distinctive structural characteristics, helix antennas are well-suited for a variety of high-frequency applications by balancing compactness, high gain, and wide bandwidth. In this work, we parametrically analyze important design parameters including pitch, radius, number of turns, and wire …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 29–35 Read article
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Real-Time IR Intensity Measurement and Computation for Systems
Abstract: In contemporary defense mechanisms, infrared (IR) sensing has become a fundamental technology for identifying and neutralizing heat-seeking threats, especially concerning aircraft protection. Conventional IR detection systems, such as single-channel radiometers and basic thermal sensors, frequently face restrictions due to low spatial resolution, sluggish data processing, and inadequate user engagement. These constraints can impede the prompt identification of dangers like missile launches or flare activations, potentially endangering mission safety. Additionally, numerous …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 8–13 Read article
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Automation and Robotics for Quality Control in Manufacturing: A Review of Technologies and Applications
Abstract: Automation and robotics technologies have rapidly evolved, transforming modern manufacturing processes by improving productivity, quality, and operational efficiency. This review examines key advancements such as cloud robotics, machine vision, Industry 4.0 robotics, Building Information Modeling (BIM) combined with Computer Numerical Control (CNC), joystick-controlled automation, and intelligent manufacturing systems. These technologies utilize artificial intelligence (AI), machine learning (ML), digital twins, collaborative robots, programmable logic controllers (PLCs), and cyber-physical systems (CPS) to …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 3, 2025 · pp. 36–48 Read article
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A Review Study on CPU-Optimized Parameter-Efficient Fine-Tuning for Large Language Models to Increase Accuracy Using LoRA
Abstract: The fast proliferation of large language models (LLMs) has increased the need to optimize the process of fine-tuning, but the existing workflows that require a graphics processing unit (GPU) are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of parameter-efficient fine-tuning (PEFT) based on low-rank adaptation (LoRA). The major purpose …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article