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786 articles for “model-based approach”
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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Unleashing the Power of Mathematics in Natural Language Processing: Sentiment Analysis Perspectives
Abstract: Sentiment analysis (SA), which utilizes natural language processing (NLP), computational linguistics, text analysis, image processing, and video processing to extract and analyze subjective information from the internet, social media, and other sources, is becoming increasingly popular in both the business world and the scientific community. It is even possible to model it so that it focuses on polarity, sentiments and emotions, urgency, and even goals. It is able to distinguish …
Published in Recent Trends in Programming languages · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
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Analyzing Thermal Expansion in Polymer Composites Through Heat Transfer Simulations
Abstract: Although lightweight and strong, polymer composites require careful handling in environments where temperatures shift. Their usefulness in fields like aviation, vehicle manufacturing, and electronic devices comes from customizable heat behavior alongside favorable mechanical traits. Yet variation in size due to heating or cooling remains a concern hard to dismiss. As conditions change, expansion occurs - sometimes enough to disrupt fit, alignment, or function within complex systems. This response to warmth …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1098–1108 Read article
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A Hybrid Software Engineering Teaching Model (HSETM): Integrating Traditional and Contemporary Pedagogical Approaches
Abstract: Software engineering education faces a persistent dichotomy between traditional lecture-based instruction, which effectively delivers theoretical frameworks but inadequately develops practical competencies, and contemporary pedagogical approaches such as problem-based learning (PBL) and flipped learning, which enhance learner engagement but risk weakening theoretical foundations. This study proposes and empirically validates the Hybrid Software Engineering Teaching Model (HSETM), a systematic integration of traditional and contemporary pedagogical methods designed to overcome this dichotomy. Grounded …
Published in Current Trends in Information Technology · Vol. 16, Issue 2, 2025 · pp. 33–43 Read article
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Structure based pharmacophore Modelling of compounds against Neurodegenerative disorder – Amyotrophic Lateral sclerosis
Abstract: Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by the progressive degeneration of motor neurons, leading to muscle dysfunction, paralysis, and eventually death. These diseases are classified as ALS variations because autopsies reveal abnormalities in both upper and lower motor neurons. These disorders account for only 10% of all adult-onset motor neuron disease cases. Despite extensive research efforts, effective therapeutic interventions for ALS remain limited. Structure-based pharmacophore modeling …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 3, 2023 · pp. 1–17 Read article
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A New Approach to Hypersoft Sets and their Application in Decision Making
Abstract: An uncertainty based model, parallel to the soft set (SS) model introduced by Molodtsov, was proposed by Smarandache in the form of hypersoft sets (HSS). The basic characteristic of both these models is that these are parametrized family of sets which are induced by the parameters involved. However, Smarandache had left open the basic operation on HSS. In this paper, we first redefine HSS using the characteristic function based approach, …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 2, 2022 · pp. 1–10 Read article
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A Particle-Derived Nonlinear Dynamical Framework for Bubble Oscillations: Reduced-Order Modeling, Bifurcation Analysis, and Optimal Stabilization
Abstract: Particle-based fluid simulation has emerged as a powerful computational framework for modeling complex multiphase flows involving large deformations, moving interfaces, and nonlinear fluid interactions that challenge conventional mesh-based approaches. In this work, a nonlinear dynamical systems framework is developed for particle-resolved bubble oscillations by constructing a reduced-order model that preserves the dominant physical mechanisms governing bubble interface evolution. The formulation represents the bubble dynamics through coupled radial and shape deformation …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 2, 2026 · pp. 11–33 Read article
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Aerodynamics and Kinematics Modeling of a Double Articulated Flapping Wing System through the Rigid Body Approach
Abstract: The current model for kinematics and aerodynamics of a flapping wing system with double articulation is introduced by using strip theory approach based on blade element theory, which is complex. This research helped to formulate the model for kinematics and aerodynamics of a flapping wing system with double articulation using the rigid body approach and also use the model for the selection of motor, battery and the other electronic components …
Published in Journal of Aerospace Engineering & Technology · Vol. 7, Issue 1, 2017 · pp. 13–27 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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Research Note on the estimation of unrained bearing capacity of spud can foundation under combination loading
Abstract: This research note presents a numerical investigation into the bearing behavior of an embedded spud-can in normally consolidated soil. The numerical model is implemented with ABAQUS*TM. The different embedment depths from shallow to deep are considered in this research note. The numerical model is based upon the ‘small strain finite element (SSFE)’ approach to compute capacity of the installed spud-can. The numerical model allows a systematic estimation of the combined …
Published in Journal of Offshore Structure and Technology · Vol. 5, Issue 3, 2018 · pp. 7–26 Read article
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Blind Image Quality Assessment: An Overview
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 relies on a simple Bayesian inference model to predict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The estimated parameters of the model are …
Published in Journal of Electronic Design Technology · Vol. 12, Issue 3, 2021 · pp. 1–3 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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Machine Learning Assisted Design and Analysis of Polymer Composite Materials for Sustainable Renewable Energy Systems
Abstract: Accurate prediction and optimization of polymer composite properties is of paramount importance in the design of these lightweight, durable, and sustainable materials within renewable energy technologies. This work will provide a holistic machine learning-assisted framework that unites materials informatics with domain-specific features and state-of-the-art ML methodologies in the prediction of the mechanical properties of polymer composites, such as tensile strength. This includes embedding several ensemble models, including Random Forest and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 391–402 Read article
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Additive Manufacturing of Polymer-Based Advanced Composites: Mechanical Properties and Performance Evaluation
Abstract: Fabrication of large-scale and geometrically complex polymer-based advanced composites via fused deposition modelling (FDM) has been shown to be a promising technology for the production of such materials, however there are challenges in using short carbon fibre-reinforced polylactic acid (CF-PLA) which include obtaining high mechanical performance and maintaining dimensional accuracy with dynamic robot motion and complex interactions occurring between process parameters. The conventional approaches are mostly static feed rates or …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1335 Read article
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DRUG INDUCED IMMUNE MEDIATED NEPHRITIS: MOLECULAR MECHANISM , PATHWAYS AND CLINICAL IMPLICATIONS
Abstract: Drug-induced immune-mediated nephritis (DI-IMN) has become a more widely known cause of acute kidney injury (AKI), with the potential for development to chronic kidney disease if not detected and treated promptly. T-cell hypersensitivity to pharmaceuticals, such as antibiotics, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, and immunological drugs, are the major causes for it. Beyond clinical burden, DI-IMN reflectsintricate molecular interactions that sustain interstitial inflammation and tubular injury. These interactions include …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 13–29 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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A Quasi-Experimental Study to Assess the Effectiveness of Hot Fomentation versus Cold Compress in Reducing Infiltration among Patients Undergoing IV Infusion in a Selected Hospital of Delhi
Abstract: A quasi-experimental study to assess the effectiveness of hot fomentation versus cold compress in reducing infiltration and associated pain among patients undergoing IV infusion in a selected hospital of Delhi. The objectives of the study were (i) to assess the degree of infiltration in both the groups (ii) to assess the level of infiltration after the intervention in both the groups (iii) to compare the level of infiltration before and …
Published in Research and Reviews : Journal of Surgery · Vol. 5, Issue 1, 2016 · pp. 24–30 Read article
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Food Packaging Chemicals and Human Health: Molecular Toxicity, Exposure Pathways, and Regulatory Perspectives
Abstract: Food packaging plays a vital role in preserving food quality, extending shelf life, and ensuring safe transportation. However, increasing evidence indicates that chemicals from packaging materials can migrate into food during processing, storage, and consumption, resulting in chronic human exposure. Several food packaging chemicals, including bisphenols, phthalates, per- and polyfluoroalkyl substances (PFAS), styrene, heavy metals, and non-intentionally added substances (NIAS), have emerged as important xenobiotics due to their potential adverse …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article