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232 articles for “analytical modelling”
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Mathematical Modelling of Semiconductor Device Physics: An Analytical Approach
Abstract: Semiconductor device physics forms the foundation of modern electronic and optoelectronic technologies. Mathematical modelling provides a rigorous framework for understanding, predicting, and optimizing the behavior of semiconductor devices by linking physical principles with device-level performance. This work presents an analytical approach to the mathematical modelling of semiconductor devices, emphasizing the derivation and interpretation of governing equations that describe charge transport and electrostatic behavior. The model is based on fundamental physical …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 36–42 Read article
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Management of Lead–Acid Battery System in Electric Vehicles
Abstract: To determine the lead-acid battery's state of charge in electric vehicles, a novel coulometric method is presented in this article. There are two major problems with the main state of charge algorithms that are currently in use: one defines the state of charge incorrectly for applications involving electric vehicles, and the other uses the accumulator's static performance sub-optimally to estimate its state under dynamic stresses. To address these two shortcomings, …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 18–27 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article
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The Influence of Data Analytics on Sports Performance
Abstract: Data analytics has drastically changed how we evaluate, improve, and maintain athletic performance. Coaches used to use subjective observations as well as only limited numbers of statistics to consider player performance; however, tracking technology is now advancing at a fast pace. There are now very large amounts of real-time data available on athletes in regards to speed, movement patterns, fatigue, efficiency, etc. This enables all teams to more accurately make …
Published in Recent Trends in Sports · Vol. 3, Issue 1, 2026 · pp. 15–21 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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Machine Learning Based House Price Forecasting
Abstract: This research endeavours to craft a predictive model leveraging machine learning to estimate the market value of houses in Delhi. By integrating Python and its powerful libraries, pandas for data processing, Plot for interactive visualizations, scikit-learn for implementing machine learning algorithms, XGBoost for boosting the model's prediction accuracy, and to evaluate the model's performance cross-validation techniques are used. An interactive user interface is created using a Flask web application to …
Published in Current Trends in Information Technology · Vol. 14, Issue 1, 2024 · pp. 5–11 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
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Thermal Behavior and Insulation Strategies for Li-FeS₂ Thermal Batteries: An ANSYS Simulation Study
Abstract: Thermal batteries are special electrochemical systems in which a great amount of energy is delivered during a relatively short period of time. The holding time of the thermal battery's working temperature and cell temperature define its discharge life. Thermal batteries have their advantages comparing other type of batteries, so they are used for several purposes including military field. Thermal batteries usually operate in the internal temperature range of 400 to …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 3, 2024 · pp. 45–52 Read article
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Modelling -Based Evaluation of Hybrid Natural Synthetic Fiber Polymer Composites for Sustainable Energy Applications
Abstract: The growing need of lightweight, high-performance, and green energy system materials has increased the research on hybrid polymer composites. This paper gives a modelling-based evaluation of polymer matrix composites which are reinforced using natural fibers like jute, sisal, bamboo in a combination with synthetic glass fibers to be used in sustainable energy sources. An analytical model has been used to assess the effect of hybrid fiber composition on mechanical, thermal, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 682–688 Read article
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Advancements in Electromechanical Modeling for Energy Harvesting and Actuators in Robotics and Design Engineering
Abstract: This article examines the expanding field of electromechanical modeling, highlighting the integration of energy harvesting, actuator behavior, and magnetic/electromagnetic analyses in the design and production of electromechanical systems. It discusses the application of the Galerkin method for modeling intricate vibrations and torque generation, with a particular focus on its use in actuators for robotics and induction motors. Significant advancements in energy harvesting methods, especially those utilizing mechanical vibrations, have led …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 21–25 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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A simple analytical theory for the preliminary structural design of submarine
Abstract: An Underwater Vehicle (UV) is designed to function underwater and range from an Autonomous UV to a submarine. The main difficulty that UV designers face is minimizing the weight of the pressure hull to maximize payload and propulsion velocity while reducing construction cost and time by employing appropriate material and design approaches. Herein, we examine applications geared toward submarines as well as the creation and development of an analytical model …
Published in Journal of Offshore Structure and Technology · Vol. 11, Issue 1, 2024 · pp. 1–11 Read article
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Development of a Novel Analytical Framework for Investigating Non-Symmetric Deformation Behavior in Strip Rolling
Abstract: In recent years, the asymmetrical rolling process has attracted considerable research attention due to its ability to induce non-uniform deformation characteristics within metallic workpieces. In this context, the present study introduces a novel analytical framework for asymmetrical cold rolling based on an enhanced slab method, specifically designed to overcome the inherent limitations of existing analytical models when applied to a wide range of asymmetric rolling conditions. A newly developed mathematical …
Published in Journal of Experimental & Applied Mechanics · Vol. 17, Issue 1, 2026 · pp. 1–21 Read article
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Spintronic Logic Device Modeling and Energy Optimization for Beyond-CMOS Computing Systems
Abstract: The continuous scaling limitations of conventional CMOS technology have accelerated the exploration of alternative computing paradigms for next-generation low-power and high-performance systems. Spintronic logic devices have emerged as a promising solution due to their non-volatility, ultra-low switching energy, high integration density, and compatibility with beyond-CMOS architectures. This research presents a comprehensive modeling and energy optimization framework for spintronic logic devices applied in beyond- CMOS computing systems. The proposed work investigates …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Assessment of Fire Resistance of Offshore Structures under Special Environmental Loads: Emphasizing Structural Integrity and Safety Measures for Extreme Conditions
Abstract: Offshore structures are exposed to a myriad of environmental challenges, including high temperatures and fire hazards, necessitating robust fire resistance measures to ensure structural integrity and the safety of personnel and facilities. This study aims to evaluate the fire resistance of offshore structures under special environmental loads, with a focus on the structural integrity and safety measures in place to withstand extreme conditions. The research methodology includes a comprehensive review …
Published in Journal of Offshore Structure and Technology · Vol. 11, Issue 1, 2024 · pp. 1–9 Read article
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Polymer-coated Composites: Enhancing Performance in Single Electron Transistors
Abstract: The single electron transistors (SETs) have potential for ultra-low power operation and quantum coherence, and due to this it guarantees for next-generation electronics devices and quantum computing. SETs have the ability to control movement of a single electron and this unique ability allows significant advancement in the energy efficiency and device miniaturization. There are some obstacles that need to be overcome to achieve reliable and effective operation, particularly for room …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 108–114 Read article