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464 articles for “model transformation”
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Harnessing the Magic of Regular Expressions: Transforming Citations into Harvard Referencing Style
Abstract: Current work is centred on the conversion of citations into the Harvard referencing style using regular expressions for pattern recognition. A conceptual model has been devised for this conversion process, and it has been implemented in Python. The ChatGPT API is utilized within Python to cleanse and transform the text into the desired format. Subsequently, regular expressions have been crafted to locate and convert elements such as volume numbers, issue …
Published in Current Trends in Information Technology · Vol. 13, Issue 3, 2023 · pp. 32–44 Read article
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Continuous Learning in Language Models: A Survey of Streaming Data Processing Techniques
Abstract: The integration of continual learning with Large Language Models (LLMs) and Natural Language Processing (NLP) represents a transformative step toward creating adaptive, intelligent systems capable of functioning effectively in ever-changing environments. Traditional LLMs are typically trained on large, pre-collected datasets, which limits their ability to evolve as new information emerges. Continual learning, in contrast, enables models to acquire new knowledge incrementally without the need for complete retraining, thereby supporting long-term …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 23–34 Read article
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Integrated Computational and Bio-catalytic Transformations: DFT-Guided Mechanistic Insights, Machine Learning, and Nano-biocatalyst Engineering for Sustainable Catalysis
Abstract: Computational catalysis has emerged as a transformative scientific discipline that integrates quantum chemistry, molecular modeling, machine learning, and density functional theory (DFT) to understand catalytic mechanisms and design highly efficient catalytic systems for sustainable industrial applications. The increasing global demand for environmentally responsible chemical manufacturing has accelerated research on advanced catalytic materials including transition metal catalysts, metal–organic frameworks (MOFs), homogeneous catalysts, heterogeneous systems, and bimetallic catalysts involving nickel and iron. …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 36–44 Read article
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Dependency of pure liquid pool boiling heat transfer coefficient to bubble contact angle on roughened Brass heater in new model
Abstract: Heat transfer coefficient of nucleate pool boiling Nucleation is a basic part of phase transformations, which plays an important role in understanding and describing any phase change processes. For a boiling process, nucleation appears in the initial stage, and directly affects bubble formation and boiling intensity. According to the heterophase fluctuations which induce phase transition, the phase change has two main types. Classically, phase change caused by the fluctuation with …
Published in Emerging Trends in Chemical Engineering · Vol. 9, Issue 2, 2022 · pp. 29–36 Read article
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Design and Performance Evaluation of PLA-based Umbrella Wheels for Stair-Climbing Robotic Applications
Abstract: Staircase climbing robots require a complex design capable of navigating various stair configurations. A crucial component of such robots is the wheel mechanism. This paper focuses on the umbrella wheel mechanism and its application in staircase climbing robots. In this study, a PLA–based umbrella wheel structure is developed and fabricated using fused deposition modeling (FDM) for application in stair-climbing robots. The umbrella wheel geometry enables transformation from a circular rolling …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 808–824 Read article
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Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns
Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Environmental Horticulture: Pathways to Sustainability and Climate Resilience
Abstract: Environmental horticulture represents a multidisciplinary approach that combines plant cultivation, landscape management, and sustainable practices to address pressing global environmental challenges while promoting ecological and societal well-being. This study delves into key themes such as sustainable horticulture, urban agriculture, vertical farming, hydroponics, aquaponics, and their significant contributions to biodiversity conservation, soil and water preservation, and climate change mitigation. The integration of innovative practices like green roofs, living walls, and biophilic …
Published in International Journal of Trends in Horticulture · Vol. 1, Issue 2, 2024 · pp. 33–38 Read article
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Text to Image Using Machine Learning
Abstract: In the era of digital transformation, our project addresses the convergence of computer vision and natural language processing to enhance user interaction and visual content creation. This project comprises three distinct modules: user authentication and session management, image colorization from grayscale inputs, and text-to-image generation. The login registration module provides secure access to the system, ensuring user privacy and data integrity. Once authenticated, users can utilize advanced computer vision techniques …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 35–41 Read article
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A New Paradigm in the Intersection of Science and Consciousness through the Microvita Theory
Abstract: Microvita theory, first proposed by philosopher Prabhat Ranjan Sarkar, posits the existence of subtle energy-based entities called "Microvita" that act as the missing link between consciousness and matter. This paper explores Microvita as a novel conceptual framework that bridges the gap between particle physics, consciousness studies, and environmental sustainability. Unlike traditional scientific paradigms, which often exclude the non-material dimensions of reality, Microvita theory asserts that subtle energies and conscious forces …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 2, 2025 · pp. 7–13 Read article
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The Future of Computing: Exploring the Impact of 3D Technology
Abstract: In the evolving landscape of computing, the integration of three-dimensional (3D) technology has revolutionized various industries, from entertainment to healthcare. “Computers in the 3-D World” explores the transformative impact of 3D computing, focusing on how advances in hardware and software are enabling new forms of interaction, visualization, and simulation. The study explores the key technologies behind this transformation, including virtual reality (VR), augmented reality (AR), 3D modeling, and 3D printing. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 01–19 Read article
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The Transient Response and Frequency Characteristics of Power Transformers having Non-uniform Winding Insulation
Abstract: This paper presents a Laplace-domain distributed-parameter technique for analyzing the transient and frequency response of power transformers having non-uniform winding insulation. Stronger winding insulation near the windings source side terminals is usually applied in order to mitigate the concentration of the transient voltage stresses close to these locations. This will result in a location-dependent inter-turn capacitance distribution. The suggested procedure for analyzing such windings is based on the cascade connection …
Published in Journal of Power Electronics and Power Systems · Vol. 4, Issue 1, 2014 · pp. 37–52 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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Exploring the Development of AI Models Using Open-Source Tools to Predict Patient Outcomes and Optimize Treatment Plans
Abstract: Integrating artificial intelligence (AI) into healthcare offers a transformative opportunity to enhance patient care and clinical decision-making. Through the use of predictive analytics, AI can significantly enhance the accuracy of outcome predictions and assist in developing personalized treatment plans that cater to each patient’s specific needs. This paper delves into the development of AI models using open-source tools, which are increasingly favored for their accessibility, collaborative nature, and capacity for …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 37–49 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Development of Automobile Scaled Model from CAD (Blender) Using FDM 3D Printing
Abstract: Additive manufacturing (AM), also known as 3D printing, has emerged as a disruptive technology with the potential to transform automotive manufacturing. This paper reviews the applications of AM across the automotive product development lifecycle. The paper examines case studies demonstrating the use of AM for developing computer-aided design (CAD) models from concept sketches. Overall, AM brings several benefits such as design flexibility, faster time-to-market, and distributed production. However, there are …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 2, 2024 · pp. 1–9 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article