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464 articles for “model transformation”
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Pharmacodynamics and Drug–Receptor Interactions: Integrating PK/PD Modeling with Modern Drug Development
Abstract: Understanding drug action requires an integrated perspective of pharmacodynamics and pharmacokinetics, which together determine therapeutic efficacy and safety. This review provides a comprehensive overview of the mechanisms underlying drug action, with particular emphasis on drug–receptor interactions and their role in modulating physiological responses. Drugs exert their effects primarily through interactions with specific biological targets, including receptors, enzymes, ion channels, and transporters, resulting in a spectrum of desired and adverse outcomes. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 · pp. 33–47 Read article
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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 Read article
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Enhancing Customer Engagement with AI-Driven Movie Recommenders: Integrating Neural Collaborative Filtering, Sentiment Analysis, and Conversational Agents
Abstract: In today’s competitive digital landscape, user engagement is a critical factor for the success of entertainment platforms, especially those offering movie recommendations. This study introduces a comprehensive AI-driven framework designed to enhance customer interaction, satisfaction, and loyalty through the intelligent integration of multiple deep learning models. The system combines three core components: Neural Collaborative Filtering (NCF) for generating personalized movie recommendations based on user behavior and preferences, Long Short-Term Memory …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 45–54 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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A Comparison of Different Generative AI Models
Abstract: Generative models have significantly advanced the field of artificial intelligence by allowing machines to produce complex and realistic outputs such as images, text, and other forms of data. Among the leading frameworks in this domain are generative adversarial networks (GANs), variational autoencoders (VAEs), and architectures based on Transformers. Each model offers specific benefits and drawbacks concerning design structure, training demands, and range of applications. This paper provides a detailed comparison …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 16–22 Read article
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Face Aging Using Generative Adversarial Network
Abstract: This project addresses the challenge of predicting how a person may look in the future or how they appeared in the past using a single photograph. While existing methods mainly focus on altering texture, they often neglect changes in head shape that naturally occur during the aging process, limiting their effectiveness, especially when applied to images of children. To tackle this issue, a novel approach is introduced that employs a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
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AI-Powered Chatbot with Sentiment Analysis, Summarization, and Q&A for Business Automation
Abstract: Artificial Intelligence (AI) chatbots have become increasingly significant in recent years due to their ability to automate a wide range of business operations, improve user interaction, and create more efficient customer support experiences. The development of such systems goes beyond simple rule-based responses and now integrates advanced natural language processing (NLP) techniques to deliver contextually relevant and human-like interactions. This study introduces a chatbot framework that incorporates three major components: …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 01–05 Read article
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AI-Enabled Feedback Management for Enhancing Education
Abstract: Institutions are becoming more aware of the importance of student input in improving learning experiences in the current educational environment. However, the intricate and complex patterns found in this feedback are frequently missed by conventional techniques like manual reviews and simple statistics. Our proposal suggests a novel method for analyzing student input and more accurately predicting sentiment by utilizing Long Short-Term Memory (LSTM) algorithms. We can learn more about student …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 21–27 Read article
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An Analytical Method for the Analysis of Transformer Windings Having Non-Uniform Capacitance Distribution
Abstract: A direct procedure for the transient and frequency analysis of transformer windings with location-dependent inter-turn capacitance distribution is presented. This can help simulate windings with non-uniform insulation. The derived analytic solutions in the Laplace domain are based on expressing the non-uniformly-distributed series capacitance per unit length as the sum of a constant term and a variable part proportional to the square of the distance from the winding’s source terminal. The …
Published in Journal of Power Electronics and Power Systems · Vol. 5, Issue 2, 2015 · pp. 41–54 Read article
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The Frequency Characteristics of Transformer Windings Considering the Separation-Dependence of the Inter-Turn Mutual Parameters
Abstract: The paper presents a direct method for the determination of the frequency characteristics of transformer windings. The dependence of both the inter-turn mutual inductances and capacitances on the separation between these winding turns is taken into consideration. From measured data available in the literature, a formula for this dependence is derived. The voltage and current distributions along the winding will be governed by two integro-differential equations in terms of the …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 3, 2016 · pp. 72–81 Read article
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The Time and Frequency Response of Shielded Transformer Windings
Abstract: A distributed-parameter model is presented for the transient and frequency analysis of power transformers’ windings in the presence of electrostatic shielding, a technique occasionally applied for improving their initial voltage distribution. The s-domain solution takes into account the windings’ circuit parameters with special emphasis on the additional distributed capacitances between the windings’ conductors and the conducting shield which is connected to the windings’ line terminal. The closeness of the resulting …
Published in Journal of Power Electronics and Power Systems · Vol. 4, Issue 2, 2014 · pp. 33–47 Read article
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Fast Fuzzy Network Model
Abstract: Fuzzy is applied to design a network model for performing efficiently in this paper. The probability theory is applied to analyze the existed network model and the advantages transformed into the proposed fast fuzzy network model. Various analysis techniques and formulations are presented in this paper. The resultant is the fast fuzzy network with minimized error and maximized the security over the standard computational complexity.
Published in Recent Trends in Electronics Communication Systems · Vol. 6, Issue 2, 2019 · pp. 33–38 Read article
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Application of Dynamic Phasor Model as an Alternative to DFT in Phasor Measurement
Abstract: This paper presents the application of dynamic phasor based models as an alternative to the Discrete Fourier Transform (DFT) commonly used in the Phasor Measurement Units (PMU). The paper demonstrates that the computation of a phasor using DFT in discrete time domain is equivalent to the computation of phasor (Dynamic Phasor) in continuous time domain. This paper proposes the application of dynamic phasor based models to simulate a Wide Area …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 1, 2018 · pp. 46–52 Read article
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An Empirical Study of Hyperparameter Impact on Deep Learning Models for Cardamom Leaf Disease Classification
Abstract: Recent advancements in deep learning models like convolutional neural networks and self- attention mechanisms have achieved great success in the field of plant disease classification. This study investigates the efficacy of two pre-trained models, ConvNeXT-Tiny and Swin Transformer-Tiny, for leaf disease classification in cardamom using a publicly available dataset constituting three categories of leaves, namely Healthy, Colletotrichum Blight and Phyllosticta Leaf Spot. The effectiveness of the models highly depends on …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 48–60 Read article
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Blind Image Quality Assessment using NSS Approach in the DCT Domain
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment.This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are used …
Published in Recent Trends in Electronics Communication Systems · Vol. 8, Issue 3, 2021 · pp. 1–6 Read article
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Natural Language Processing in Everyday Applications: From Classrooms to Clinics
Abstract: Natural Language Processing (NLP) is transforming everyday sectors like healthcare and education by creating new opportunities for efficiency, accessibility, and early intervention. This paper investigates the function of natural language processing (NLP) in computer education. Tools like automated grading systems, intelligent tutoring assistants, and multilingual translation platforms are revolutionizing traditional teaching methods. Despite its benefits, adoption is still being slowed down by problems like data privacy, integration with education, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 Read article
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Vertical Villages: Redefining Urban Living for a Sustainable Future
Abstract: As urbanization accelerates, cities face growing challenges in balancing population growth with sustainable resource use. Traditional horizontal sprawl is increasingly unsustainable, causing habitat loss, inefficient land use, and higher carbon emissions from long commutes and overstressed infrastructure. Addressing these issues, vertical villages offer an innovative, sustainable alternative for dense urban environments. Vertical villages are multi-story, integrated communities that combine residential, commercial, and communal spaces within compact areas. By optimizing land …
Published in International Journal of Architectural Design and Planning · Vol. 3, Issue 1, 2025 · pp. 7–17 Read article
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Unravelling Modern News Classification Methods: A Systematic Review
Abstract: Nowadays, the news is being generated each second from every corner of the world, with millions of news articles generated every day. Some assume that at least 1.8 million articles are published yearly, in about 28,000 journals. It has become difficult to recognize what's fake and what's genuine due to the overflow of millions of articles every day. Not every person reads every news, so the classification of news according …
Published in Journal of Computer Technology & Applications Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Exploring the Viability and Implications of Quantum Communication in 6G Networks
Abstract: The development of telecommunication systems has brought us to the era of 6G, characterized by remarkable connectivity, speed and performance achievements. This article investigates the fusion of quantum communication into the architecture of 6G networks as a new approach to achieving security and efficiency. Using quantum mechanics principles, such as superposition and entanglement, quantum communication allows bloodless encryption and secure data transmission. The theoretical frameworks and quantum networks for 6G …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 1, 2024 · pp. 01–14 Read article