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80 articles for “interpretive structural modeling”
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 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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Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 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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ML-Enhanced Smart Sensing Framework for IoT- Based Structural Health Monitoring Using Conductive Polymer Composites
Abstract: The growing demand for intelligent structural health monitoring (SHM) in dynamic infrastructures necessitates flexible sensing systems that are not only mechanically robust but also capable of real-time interpretation. Conventional SHM frameworks often rely on brittle sensor configurations and cloud-dependent processing pipelines, which suffer from latency, limited durability, and poor adaptability under variable loading conditions. Despite recent advances in composite materials and machine learning, current approaches lack a unified framework that …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 348–369 Read article
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A Review Paper of Automated Driving & ADAS Technologies
Abstract: Automated driving and Advanced Driver Assistance Systems (ADAS) are transforming road mobility, promising enhanced safety, improved traffic efficiency, and greater accessibility. This review presents a comprehensive synthesis of core technologies, system architectures, sensor modalities, perception and decision-making algorithms, and evaluation methodologies underpinning contemporary ADAS and automated driving. We provide a detailed discussion of the functional components—sensors (camera, radar, LiDAR, ultrasonic), localization, perception, prediction, planning, control, and human–machine interfaces—and how these …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–7 Read article
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Artificial Intelligence in Drug Repurposing: A Short Impact Assessment
Abstract: Artificial intelligence (AI) in pharmaceutical repurposing has become a game-changing tool that opens new avenues for the application of new drugs that have already been approved. Traditional drug discovery is a lengthy and expensive process, whereas AI can rapidly analyze vast datasets of biological, chemical, and clinical information to predict drug-disease interactions. AI-driven techniques, such as machine learning, natural language processing, and deep learning, enable the identification of potential repurposing …
Published in Trends in Drug Delivery · Vol. 11, Issue 3, 2024 · pp. 42–45 Read article
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Delhi Ladli Scheme 2008: A Parental Perspective
Abstract: An exploratory study to assess the knowledge and utilization of ‘Ladli scheme 2008’ among parents of girl child who are eligible to avail the benefits of this scheme in a selected community of Delhi with a view to develop Information Guidelines was conducted. The main objectives of the study were to (i) Identify the parents of girl child who are eligible to avail the benefits of ‘Ladli scheme 2008’. (ii) …
Published in Journal of Nursing Science & Practice · Vol. 4, Issue 3, 2014 · pp. 43–48 Read article
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A Quasi Experimental Study to Assess the Effectiveness of Chewing Gum on the Bowel Motility among the Patients after Abdominal Surgery in Selected Hospital of New Delhi
Abstract: A quasi experimental study to assess the effectiveness of chewing gum on the bowel motility was conducted on the patients after abdominal surgery in selected hospital of New Delhi. The objectives of the study were to (i) To assess the bowel motility of patients after abdominal surgery in the experimental and control group (ii) To compare the bowel motility of patients after abdominal surgery in the experimental and control group …
Published in Research and Reviews : Journal of Surgery · Vol. 5, Issue 1, 2016 · pp. 1–6 Read article
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Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Comparison of Models of Machine Learning and Hyperparameter optimization methods on various datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameters tuning step. The traditional exhaustive methods of search (Grid Search and others) ensure that the search space is covered, but are computationally very inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian Optimization, Tree-structured Parzen Estimator (TPE), Genetic Algorithms) are thought to …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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Exploring Practical Applications of Artificial Neural Networks: A Review
Abstract: Computational models called artificial neural networks (ANNs) are modeled after the structure of the human brain. These models are designed to process information and learn from data. Artificial neural networks, or ANNs, are composed of interconnected artificial neurons layered to resemble the brain's neural network.. Through training, ANNs adjust the connections between neurons based on labeled data, enabling them to recognize patterns and perform specific tasks. Despite their efficacy in …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 1–11 Read article
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QSAR Modeling Techniques: A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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AI-Driven Micro-Expression Recognition for Early Mental Health Disorder
Abstract: Mental health conditions like anxiety and depression are often undiagnosed because the usual diagnostic methods based on basic regular instruments like questionnaires and clinical interviews have some limitations in them. They are not objective often and may not catch the initial signs of psychological distress. Micro-expressions have become valid measures of repressed or unconscious emotions and can provide greater insight into someone's mental condition. Also, identification and interpretation of these …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 40–49 Read article
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Developing Design Sense in First-Year Architecture Students: A Pedagogical Approach to Basic Design
Abstract: This study explores the pedagogical significance of Basic Design Studios in shaping the foundational competencies of first-year architecture students. Serving as the foundation of architectural education, these studios cultivate essential skills in spatial awareness, creative thinking, and problem-solving. The research underscores how structured studio exercises, material explorations, and conceptual modeling collectively nurture an understanding of the interrelationship between space, form, and function. By emphasizing experiential and hands-on learning, students are …
Published in International Journal of Architectural Design and Planning · Vol. 4, Issue 1, 2026 · pp. 1–6 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Bridging Traditional Ayurvedic Pedagogy and Competency-Based Education: A Contemporary Perspective
Abstract: Mentoring plays a pivotal part in education. It has deep roots in both the traditional practitioner- Shishya Parampara of Ayurveda and ultramodern faculty- grounded medical education. The National Medical Commission and the National Commission for Indian System of Medicine have stated that structured mentorship programs are essential to guide scholars from newcomers to interpreters. This composition looks at how these traditions connect. It explains the purpose and limits of mentoring. …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 15, Issue 2, 2026 Read article