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232 articles for “analytical modelling”
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The Role of Mathematical Reasoning in Legal Analysis: Bridging Two Disciplines
Abstract: This research paper explores the integration of mathematical reasoning into legal analysis, emphasizing the inherent similarities between the two disciplines. Both fields rely on logical structures, such as deductive reasoning, inductive reasoning, and other formal methods of thought. By examining these parallels, the paper reveals the nascent but growing interaction between mathematics and law, uncovering how the organizational schemes that underpin mathematical principles can enhance legal argumentation, decision-making, and analysis. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
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Thermo–Electrical Performance Enhancement of a Lightweight Polymer–Metal Hybrid Electrostatic Precipitator Using Epoxy-Based Composite Housing for Industrial Particulate Control
Abstract: Airborne particulate emissions, particularly PM₁₀ and PM₂.₅ produced by industrial activities and combustion processes, they continue to pose a significant threat to both the environment and public health. Electrostatic precipitators (ESPs) are widely recognized for their ability to achieve high collection efficiencies; however, conventional metallic constructions often lead to increased system weight, higher fabrication costs, and long-term corrosion-related challenges. In this study, a lightweight hybrid material approach is proposed by …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 652–668 Read article
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SoloRider: An Autonomous Self-Balancing Electric Bike for Sustainable Urban Mobility
Abstract: Rapid urbanization has intensified challenges such as traffic congestion, parking inefficiency, and environmental degradation. While autonomous vehicle research predominantly focuses on four-wheel platforms, lightweight two-wheelers remain comparatively underexplored. Two-wheelers are a great option for sustainable urban transportation because of their many benefits, including their small size, lower energy consumption, better manoeuvrability, and lesser infrastructure requirements. This paper presents SoloRider, a conceptual autonomous self- balancing electric two-wheeler de- signed for sustainable …
Published in International Journal of Electronics Automation · Vol. 4, Issue 1, 2026 Read article
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Multi-Objective Optimization of Polymer-Based Functionally Graded Composites for Lightweight Structures
Abstract: Functionally graded composites (FGCs) improve lightweight structural performance by allowing material properties to change smoothly across a component. Polymer-based FGCs (P-FGCs), in particular, are gaining prominence in aerospace, automotive, and biomedical industries due to their excellent strength-to-weight ratio, tunability, and ease of processing. However, optimizing these materials for lightweight structural applications requires addressing conflicting design objectives, such as maximizing stiffness while minimizing weight or enhancing thermal resistance while maintaining manufacturability. …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 961–973 Read article
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Comparative Performance Assessment of Shear Wall and Diagrid Systems in an Octagonal Tall High-Rise Building under Seismic and Wind Loads
Abstract: The increasing demand for high-rise structures due to rapid urbanization necessitates the adoption of efficient lateral load-resisting systems to ensure structural safety, stability, and serviceability. This study presents a comparative evaluation of the seismic and wind performance of a Ground plus Fiftystorey high-rise building with an octagonal plan, incorporating different structural configurations such as shear wall arrangements and a diagrid system. A total of six analytical models, including a conventional …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Performance Evaluation of Kevlar-Sisal-S-Glass Hybrid Composites with Ceramic Fillers for Structural Applications
Abstract: This study examines the mechanical properties of hybrid composite laminates reinforced with Kevlar, sisal, and S-glass fibers, and incorporating ceramic fillers—silicon carbide (SiC) and aluminum oxide (Al2O3)—within an epoxy matrix. The hand lay-up method was utilized to produce the laminates, ensuring a uniform fiber stacking sequence and including 10% filler material. Two composite variations were synthesized: one incorporating SiC and the other Al₂O₃, and both underwent tensile, flexural, hardness, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article
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Digital Enablers of Nanomedicine: Pharmaceutical Software Across the Lifecycle of Nanotechnology‑Based Drug Products
Abstract: Nanotechnology‑based drug products have rapidly evolved from laboratory concepts to clinically relevant therapies, yet their development is constrained by complex design variables, stringent quality requirements, and emerging regulatory expectations specific to nanomaterials. Pharmaceutical software now plays a central role in the nanomedicine lifecycle, enabling in silico design of nano‑carriers, simulation of nano–bio interactions, control of nanoscale quality attributes during manufacturing, and systematic tracking of safety signals in real‑world use. Integrated …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 11–16 Read article
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AI-Based Threat Detection in Cloud Platforms
Abstract: This research work delves into the transformative role AI has come to assume for enhanced threat detection in the cloud ecosystem. The conventional security frameworks, which form the basis for many architectures, are several steps behind actualizing the rapidly evolving cyber threat landscape, exposing critical weaknesses in the areas of accuracy, adaptability, and speed of response. Initially, the study sets forth the problems with the old-school approaches to threat detection …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 01–10 Read article
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Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
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Modelling and Analysis of Morphing Wing Structure for Variable Camber
Abstract: This study explores the modelling and analysis of a morphing wing with variable camber configurations to observe its aerodynamic characteristics compared to conventional form. The morphing wing is the concept where the shape of the wing is altered mid-flight based on different phases of flight to improve its aerodynamic characteristics. Morphing wing structure designs such as the corrugated and FISHBAC designs were considered for this analysis. The NACA 2412 airfoil …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 209–224 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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Dynamic Cost Projection: Enhancing BIM-Integrated Estimation and Budgeting in Construction Projects
Abstract: In the realm of construction project management, the integration of Building Information Modeling (BIM) with dynamic cost projection tools represents a pivotal advancement. This paper explores the synergy between BIM and cost estimation, emphasizing their collective potential to revolutionize project budgeting. By harnessing real-time data and predictive analytics, BIM facilitates accurate and proactive cost projections throughout the project lifecycle. This integration not only enhances cost estimation precision but also fosters …
Published in Journal of Construction Engineering, Technology & Management · Vol. 14, Issue 2, 2024 · pp. 1–10 Read article
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AI and ML-Driven Immersive Technologies: A New Era in Education
Abstract: The very fast adoption of Artificial Intelligence (AI) and Machine Learning (ML) in education has transformed contemporary teaching and learning ecosystems driven by advances in immersive technologies and the growing engagement of global technology leaders with virtual environments. AI-powered educational platforms enable adaptive and personalized learning pathways by dynamically adjusting content, pace and instructional strategies to learners’ preferences, abilities and learning styles by improving engagement, retention and academic outcomes. Deep …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 116–123 Read article
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Improving Indoor Room Air Conditioning Using PID Control
Abstract: Energy use in building air conditioning contributes significantly to power demand; therefore, in this work, we propose an improved methodology to achieve comfort conditions through PID control assistance. The project develops a mathematical model based on analytical heat transfer equations for comfort conditions by fulfilling the Fanger equation, considering environmental parameters (ambient temperature), metabolic rate, and people’s physical activity (internal heat generation) to reduce power consumption and improve energy efficiency. …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 1–21 Read article
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AI-Powered Approaches to Environmental Challenges: Trends, Benefits, and Limitations
Abstract: Dynamic and unpredictable characteristics of environmental processes create challenges in their management and regulation. Artificial intelligence (AI) offers a powerful solution for addressing these complexities.AI tools have become more and more popular across a range of fields and research domains due to their efficient development and rapid growth. We analyse key trends in AI applications, including predictive analytics for climate modelling, automated monitoring of biodiversity, and smart resource management. The …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article
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The Role of Digital Detox in Improving Mental Health
Abstract: This study examines digital detox—the deliberate limitation of screen exposure—and its influence on mental health. A survey of 30 participants indicated that reducing screen time by at least two hours daily resulted in a 30% improvement in sleep quality, a 25% decrease in stress levels, and a 20% enhancement in overall mood stability. Statistical analysis (p < 0.05) confirmed these results. Additionally, participants following a structured digital detox plan reported …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article