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464 articles for “model transformation”
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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A MODEL DRIVEN APPROCH FOR REQUIREMENTS ENGINEERING OF INDUSTRIAL AUTOMATION SYSTEM
Abstract: A model-driven approach to developing multiple, consistent user interfaces for your application. An Abstract UI (AUI) model constrained to dialogue flow maintains the fundamental similarities of different user interfaces.. In particular, we will consider how to customize the User Interface at his AUI level by deriving and customizing dialog structures that take into account the limitations imposed by the front-end platform or novice user. The generated user interface is integrated …
Published in Journal of Mechatronics and Automation · Vol. 9, Issue 3, 2022 · pp. 1–4 Read article
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Analysis of Natural Frequency for Three-Dimensional Model of Transformer Winding Using FEA
Abstract: AbstractPower transfer winding is prone to a number of events of a short circuit. However, over a period of time, capabilities of winding to withstand forces generated during such events decrease. In order to understand the behavior of winding at excitation, study of natural frequency is an important parameter. In this paper, winding’s radial and axial modes are studied with the help of finite element approach. Three-dimensional (3D) and two-dimensional …
Published in Journal of Instrumentation Technology & Innovations · Vol. 8, Issue 1, 2018 · pp. 8–12 Read article
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Modeling of Transformer Windings having Non-uniform Inductance Distribution
Abstract: A direct analytical procedure for analyzing power transformer windings with location-dependent series inductance is presented. This dependence is typically introduced in order to take the inter-turn mutual inductive coupling into consideration. The paper addresses the frequency domain analysis conducted in the complex s- or the jω-domains. Results for the frequency-dependent winding’s input impedance with different treatments of the transformer’s neutral point will be available. The frequency characteristics including the resonance …
Published in Journal of Power Electronics and Power Systems · Vol. 4, Issue 3, 2014 · pp. 12–25 Read article
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Exploring Technologies for Extractive Text Summarization: A Review of Transformer and Reinforcement Learning Models
Abstract: In recent years, the size of information on the Internet has increased exponentially. Therefore, a solution is needed to transform large amounts of raw data into useful information the human brain can understand. Automatic Text Summarization (ATS) is a part of Natural Language Processing (NLP) that aims to take long texts and shorten them, keeping the most important information in a clear and easy-to-understand way. This research report explores methods …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
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Online Change Detection Algorithm Based on the Continuous Wavelet Transform, the CUSUM Algorithm and an Autoregressive Model
Abstract: In this article, we present a change point detection algorithm based on the continuous wavelet transform, the CUSUM algorithm and an autoregressive model. At the beginning of the article, we describe a necessary transformation of a signal which has to be made for the purpose of change detection. Then case study related to iron ore sinter production which can be solved using our proposed technique is discussed. After that, we …
Published in Current Trends in Signal Processing · Vol. 1, Issue 1-3, 2025 · pp. 17–29 Read article
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A Review of Recent Advancements in Machine Learning and Deep Learning Approaches for Pet Diseases Prediction
Abstract: This systematic study assesses recent developments in Machine Learning (ML) and Deep Learning (DL) approaches to predict pet diseases. With the increasing role of Artificial Intelligence (AI) in pet healthcare, this study identifies recent research trends, limitations, and future directions. A comprehensive search was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines in selecting 20 relevant studies from over 300 articles published between 2020 and …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 1–6 Read article
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Encoder-Decoder Based Fine-Tuned Model for Code Doubt Solver
Abstract: As we are growing in technology, more technologically skilled persons are needed in industry. They all often rely on programming in their daily work, and when some doubts arise, they seek help from teachers to LLMs like GPT to Deepseek. However, when errors arise, then comes hectic part to troubleshoot and resolve the error. Usually, people seek help from some LLMs like GPT, or Deepseek for the solution; they give …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 35–42 Read article
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Comparison of RSM and ANN Modeling Approaches in Predicting the Laser Phase Transformation Hardening Parameters on the Heat Input and Hardened-Bead Profile Quality of Unalloyed Titanium
Abstract: In the present work, laser transformation hardening (LTH) of unalloyed titanium, nearer to ASTM Grade 3 of chemical composition was investigated using CW 2kW, Nd: YAG laser. The laser process variables such as laser power, scanning speed, and focused position play a major role in deciding the laser hardened bead quality. Two methods, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used to predict the heat input and …
Published in Journal of Materials & Metallurgical Engineering · Vol. 5, Issue 1, 2015 · pp. 36–59 Read article
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Prediction Of Compression Index For Lateritic Soil Using Transformed Variable
Abstract: The information on the compression index of a soil is vital in geotechnical design, but its determination is expensive and time consuming. Most models relating compression index and basic soil properties are usually based on soil types. This work seeks to develop a model relationship between compression index and basic soil properties for lateritic soils. Selective transformation method which involves testing some general functional forms, to choose the model that …
Published in Journal of Geotechnical Engineering · Vol. 5, Issue 3, 2018 · pp. 14–23 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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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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From Quantum Chemistry to Bioprocess Intensification: Advanced Computational Modeling and Enzyme-Based Catalytic Platforms for Green Chemical Transformations
Abstract: Green chemistry requires the development of sustainable catalytic systems that minimize waste generation, reduce energy consumption, and improve process efficiency. Computational chemistry and biocatalysis have emerged as complementary approaches for environmentally responsible chemical manufacturing. Computational techniques such as quantum chemistry, density functional theory (DFT), molecular dynamics, and machine learning provide mechanistic insights into catalytic reactions and support the rational design of efficient catalysts. These approaches enable the prediction of reaction …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 45–52 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Bridging the Gap and Unlocking Health Literacy: A Guide to Medical Report Clarity
Abstract: This research highlights the significant challenges faced by the general population in interpreting laboratory reports, medical charts, and other health-related documents. Studies show that approximately 9 out of 10 individuals struggle to understand such medical information, primarily due to low health literacy levels. This lack of understanding has become a hidden epidemic, affecting the way people engage with and respond to their own healthcare. While medical tests are essential for …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 31–36 Read article
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Intelligent Failure Detection in Biomedical Composite Materials Using Machine Vision
Abstract: The biomedical composite materials are intelligent failure-detecting, which is necessary to ensure the reliability, safety, and durability of the current healthcare equipment. This paper describes a machine vision design, which incorporates convolutional neural networks, transformer models, and ensemble learning to correctly detect and localize material defects. The proposed system takes advantage of the capabilities of high-resolution imaging, advanced preprocessing software, and deep feature learning in the identification of the intricate …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 55–66 Read article
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T-π Network Simulation and Thevenin- Norton Equivalent Circuit Values From Laplace Description Using Pspice Software
Abstract: From the conversion methods of T-π (star-delta) for impedances circuits, the behavioral modeling of Pspice simulation program is used to obtain equivalent circuits using LAPLACE option. The conversions are verified for two types of circuits by obtaining AC values of voltages and currents at various nodes and branches using Pspice computer simulations. There are many ways of expressing Thevenin/Norton equivalent circuit parameters such as (a) as real numbers for pure …
Published in Journal of Semiconductor Devices and Circuits · Vol. 9, Issue 2, 2022 · pp. 43–58 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Algebraic Foundations of AES (Advanced Encryption Standard): Group Theory and Finite Field Applications in Symmetric Cryptography
Abstract: This paper presents a mathematical study of symmetric cryptographic algorithms, with a particular emphasis on the Advanced Encryption Standard (AES), which is one of the most widely used encryption schemes in modern security applications. The study highlights how abstract mathematical frameworks such as group theory, finite fields, and vector space concepts provide the foundation for the design, implementation, and analysis of AES. By approaching the algorithm from a mathematical perspective, …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 12–16 Read article