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435 articles for “sub-modeling”
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Modeling Deformation Mechanisms of Horseshoe Tunnel Excavation In Layered Ground Using Flac 3D
Abstract: In the modern era of civilization, the transportation sector plays a pivotal role in a nation's development. Efficient transportation networks are essential for economic progress, and tunnels are particularly valuable in this regard, as they help reduce travel time and fuel consumption. With growing interest in underground infrastructure, researchers are increasingly focusing on tunnel-related studies. This paper examines the deformational behavior of a horseshoe-shaped tunnel constructed in layered soil, subjected …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 3, 2025 · pp. 46–61 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Evaluation of Agro-based Adsorbents for Oil Spill Remediation in Freshwater and Saltwater Environments: Kinetic and Adsorption Model Analysis
Abstract: Environmental pollution caused by oil spills poses significant risks to both human health and ecosystems, particularly in regions like Nigeria’s Niger Delta, where oil spills are frequent. Conventional methods for oil spill cleanup have limitations, which has prompted research into alternative, more effective techniques. This study investigates the use of agro-based materials, specifically plantain and banana species, combined with clay soil as adsorbents for oil removal in freshwater and saltwater …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–32 Read article
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Optimized Utilization of Kota Stone Slurry Waste in Fly Ash–Based Geopolymer Mortar: A Taguchi-Driven Approach
Abstract: The large-scale generation of stone-processing wastes presents a critical sustainability challenge and an opportunity for value-added reuse in construction materials. This study develops a high-performance fly ash geopolymer mortar by partially replacing Class F fly ash with Kota stone slurry waste (KSSW) and optimizing the key mix parameters using a Taguchi design framework. Five governing factors—binder replacement level, NaOH molarity, sodium silicate–to–sodium hydroxide ratio (SS/SH), curing temperature, and alkaline solution-to-binder …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 426–445 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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DFT/Data Guided Predictive Modelling of Absorption Maxima in the OLED Rubrene Derivatives
Abstract: This study investigates the optical properties of rubrene derivatives to develop an accurate predictive model for absorption maxima using computational chemistry and chemoinformatic techniques. We benchmarked various quantum chemical methods, identifying that the M06-2X/aug-cc-pVDZ method in dichloromethane (DCM) provided the strongest correlation with experimental data. Key molecular descriptors such as band gap, ionization potential, and electrophilicity index were calculated and analyzed using principal component analysis (PCA) to identify significant factors …
Published in International Journal of Cheminformatics · Vol. 4, Issue 1, 2026 · pp. 41–56 Read article
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Role of Machine Learning Principles for Efficient Nuclear Fuel Management and Design
Abstract: The introduction of machine learning (ML) and evolutionary computation methods in addressing complex nuclear fuel management challenges has brought a significant positive change in the domain of nuclear fuel management. Key applications include fuel assembly design optimization, core loading pattern determination, burnup calculation acceleration, fuel performance prediction, and spent fuel characterization. The analysis reveals significant improvements in computational efficiency, prediction accuracy, and optimization capabilities when ML techniques are properly integrated …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–33 Read article
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Bacteria on Salt Water Medium Evaluation: The Conceptual Impacts of Temperature
Abstract: The potential impact of temperature on bacteria on salt water medium for crude oil degradation in an aerated lagoon system was simulated using MATLAB Simulation software. The specific rate of bacteria obtained revealed maximum at temperature of less than 35oC with the order of 90 o C (11 cfu/ml) > 60 o C (40 cfu/ml) > 45 o C (35 cfu/ml) > 30 o C (28 cfu/ml). Most of the …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 1, 2026 Read article
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A Comparative Analysis of Factors Contributing to Relapse in Alcohol and Opioid Dependence Among Patients Admitted to Selected Hospitals in Ludhiana, Punjab.
Abstract: Introduction: Substance abuse involves the dangerous or detrimental use of psychoactive substances, such as alcohol and illegal drugs. The use of these substances can result in dependence syndrome, which encompasses a range of behavioral, cognitive, and physiological effects that arise from ongoing substance use. Objectives: This study was carried out to examine the factors linked to relapse in alcohol and opioid dependence among patients admitted to selected hospitals in Ludhiana, …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Debris Flow Kinetics in Planetary Environments: A Systems Perspective
Abstract: Debris flow kinetics in planetary environments represent a critical intersection of geomorphology, fluid mechanics, and planetary science. These gravity-driven flow mixtures of solids, liquids, and gases play a key role in shaping planetary surfaces and recording environmental histories. This study adopts a systems perspective to analyze debris flow behavior across different planetary contexts, emphasizing the interconnected roles of material properties, energy transformations, and environmental forcing. By integrating rheological models with …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 08–17 Read article
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Impact of Hypoxia on Cardiopulmonary Adaptation in Canines: A Comprehensive Review
Abstract: Hypoxia triggers a series of cardiopulmonary responses that play an important role in oxygen delivery and the continuation of physiological activity in mammals. Canines are also a useful translational model of study to examine these adaptive responses because of their anatomical, physiological, and cardiopulmonary differences with humans. This review summarizes the experimental data of acute, subacute and chronic hypoxia in dogs with particular focus on the variations in cardiac functioning, …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 15, Issue 1, 2026 · pp. 13–24 Read article
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Impact of AI Tools in Software Engineering: Boon or a Bane
Abstract: Artificial Intelligence (AI) has become a transformative force, revolutionizing diverse sectors by integrating intelligent systems into everyday processes. Natural Language Processing (NLP) plays a crucial role, enabling machines to understand and produce human language, marking a significant advancement in technology. This innovation has various applications, including chatbots, language translation, and sentiment analysis, thereby improving interactions between humans and computers and facilitating information processing. Generative AI, a subset of AI, takes …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 1, 2024 · pp. 14–23 Read article
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Phisherman: A Phishing Email Detection Browser Extension
Abstract: Phishing attacks continue to pose significant security risks, exploiting email as a primary vector to deceive users and compromise sensitive information. To counter these threats, Phisherman presents a sophisticated, real-time phishing detection system that integrates both rule-based methods and deep learning for heightened accuracy. Built as a cross-browser extension, compatible with Chrome, Firefox, and Edge through the WebExtension API, Phisherman combines traditional verification checks, such as DNS blacklisting, SPF, DKIM, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 99–105 Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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Enhancing Crop Health: A Review of Image Processing Methods for Leaf Disease Identification
Abstract: This research presents an overview of different image processing techniques for the identification of leaf disease. Many algorithms can be used to identify and categorize leaf diseases in plants, and digital image processing provides a quick, dependable, and accurate method of disease detection. This paper presents various techniques used on multiple crops and the achieved accuracy for each model. Leaf disease detection is a critical task in agriculture to ensure …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 10–14 Read article
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LLM-based Chatbot for Course-based Question Answering
Abstract: The “LLM-based Chatbot for Course-Based Question Answering” project addresses the pressing need for tailored and efficient learning tools in education. By using a state-of-the-art Large Language Model (LLM) with a diverse dataset, including textbooks, professor slides, and web scraping data, the chatbot offers accurate and contextually enriched responses to students' course-related queries. Using recent advances in language modeling, this work presents a Longformer-based Language Model (LLM) for constructing a smart …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 30–41 Read article
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Hybrid Additive-Subtractive Manufacturing of Multi-Material Functionally Graded Components: Integration of Laser Powder Bed Fusion with High-Speed CNC Finishing for Aerospace Applications
Abstract: The synergy involved in the merging of additive and subtractive manufacturing technologies is the game changer to generate multi-material functionally graded components to be used in the aerospace industries. The paper is an in-depth review of a proposed hybrid additive-subtractive manufacturing, which synergistically merges laser powder bed fusion (LPBF) fashioning with rapid computer numerical control finishing production processes. The multi-material deposition, thermal issues, and optimization of post-processing are the challenges …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 398–418 Read article
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Metamaterial-Based Thermal Shielding Structures for Reusable Hypersonic Space Transportation Systems
Abstract: The rapid development of reusable hypersonic space transportation systems has intensified the need for advanced thermal protection technologies capable of withstanding extreme aerodynamic heating conditions encountered during atmospheric re-entry and sustained hypersonic flight. Conventional thermal shielding materials often suffer from high structural weight, limited adaptability, thermal fatigue, and degradation under repeated thermal cycling. This study proposes a novel Metamaterial-Based Thermal Shielding Structure for Reusable Hypersonic Space Transportation Systems, integrating engineered …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Secure Framework for Government Tender Allocation
Abstract: Governments and public sector entities worldwide are actively seeking innovative strategies to adapt to rapid technological progress, aiming to enhance governance effectiveness, streamline work processes, and optimize expenditure. Blockchain technology stands out as a prime example, captivating the interest of governments globally in recent years. Its ability to offer heightened security, enhanced traceability, and cost-efficient infrastructure positions blockchain as a versatile solution applicable across diverse sectors. Typically, governments engage third-party …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 23–27 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article