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503 articles for “predictive analysis”
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 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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Statistical Modeling of Heat Transfer and Fluid Dynamics: Application in Mechanical Engineering Design
Abstract: Understanding and optimizing the intricate processes involved in heat transfer and fluid dynamics—two concepts essential to mechanical engineering design—require statistical modeling. Engineers can forecast, regulate, and enhance the performance of systems including heat exchangers, turbines, cooling mechanisms, and different fluid machinery by using statistical approaches. In order to address uncertainties, variability in material properties, boundary conditions, and operational parameters, this work investigates the integration of statistical modeling tools in the …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 2, 2024 · pp. 18–22 Read article
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Incorporating Material Fatigue Parameter Determine in The Rolling & Sliding Contact Fatigue Analysis of Gears
Abstract: As the material's intricate stresses and strains are always shifting during phases of loading, determining the predicted equipment working under rolling-sliding contact loads and their fatigue lives (wheels, bearings, and gears) is particularly difficult. Another difficulty is not knowing the precise characteristics of the material used to make the components, which is particularly noticeable. when it comes to heat-treated components, where the material characteristics' values can differ greatly among the …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 1–5 Read article
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Reactive Strength Index as a Predictor of Jump Height and Agility in Basketball Athletes
Abstract: This study examines the relationship between the Reactive Strength Index (RSI) and specific performance metrics, namely jump height and agility, in youth basketball players. The RSI, a measure derived from drop jump testing, provides insight into an athlete’s explosive strength and reactive capabilities—essential qualities for success in basketball, where quick directional changes and reactive power are integral to performance. A cohort of forty youth athletes, comprising 20 males and 20 …
Published in Recent Trends in Sports · Vol. 1, Issue 2, 2024 · pp. 8–13 Read article
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Enhancing Energy Efficiency in Air Handling Units Through AI Driven Optimization
Abstract: This research explores the implementation of artificial intelligence (AI) in enhancing the energy efficiency of Air Handling Units (AHUs) in manufacturing facilities. The study proposes a comprehensive solution architecture that incorporates temperature and humidity sensors within AHUs, utilizing RS485 for data communication. The collected data undergoes exploratory analysis, which informs the training of a decision tree algorithm, chosen for its accuracy and compatibility with edge gateways. The algorithm's predictions enable …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 2, 2024 · pp. 19–28 Read article
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Quasi-Static Thermal Stress Analysis in a Thin Circular Cylinder Due To Internal Heat Generation Under Transient Temperature Conditions
Abstract: This paper is concerned with inverse quasi-static thermal stress analysis in a thin circular cylinder due to internal heat generation under transient temperature conditions. The internal heat generation is modeled as a cylindrical surface heat source located in the annular region along the axial length of the cylinder. This source is placed concentrically inside the cylinder and begins releasing heat spontaneously at a specific point in time. The thin circular …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 17–28 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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Impact of Friendship Quality on Self-Esteem and Resilience among Adolescents
Abstract: Adolescence is an integral developmental stage of change in social, emotional and psychological aspects of an individual's life. Friendship is an essential component of this period that helps to provide social support and emotional comfort. The present research gaps are not fully addressed by the existing literature on friendship quality, self-esteem, and resilience among adolescents. Hence, the present study sought to establish whether friendship quality and its sub-dimensions of safety, …
Published in Recent Trends in Social Studies · Vol. 2, Issue 2, 2025 · pp. 39–49 Read article
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Investigate an Implementation Study of TI-6AL-4V Lattice-based Scaffold Design Using Finite Element Analysis
Abstract: Implementation studies are advised to determine the effectiveness and performance of bone scaffolding in morphology, which has been demonstrated scientifically. The rehabilitation of bone defects, which is still a complex problem in orthopedic surgery, was the subject of an implementation study we provided. Biomaterial scaffolding porosity and pore size are essential in both in vivo and in vitro bone development. However, it has been linked to various drawbacks, including poor …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 1, Issue 1, 2023 · pp. 28–35 Read article
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Semantics Analysis of Expected Goals in Soccer Data Using Machine Learning
Abstract: In recent years, the increasing availability of soccer data has greatly enhanced the accuracy and depth of player performance evaluation. Soccer, being one of the most popular sports worldwide, attracts millions of fans due to its simple rules, minimal equipment requirements, and high entertainment value. However, analyzing an entire match manually can be time-consuming, leading to a growing demand for automated methods that can summarize and interpret game data efficiently. …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 31–47 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Seismic Hazard Evaluation through Attenuation Law Derivation and Response Spectrum Design: Bangladesh Case Study
Abstract: Bangladesh, positioned at the confluence of the Indian, Eurasian, and Burma tectonic plates, faces significant seismic hazards due to its complex geological setting. This research focuses on formulating empirical attenuation relationships and Creating a design response spectrum for assessing seismic risks in Bangladesh, using data from ten large earthquakes with magnitudes ranging from 6. 7 to 7. 9. The study creates Ground Motion Prediction Equations (GMPEs) for various structural periods …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 54–63 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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A Study to Find the Relation Between School Bag Weight and Musculoskeletal Discomfort in School Going Children
Abstract: Background: School bags are one of the several forms of manual load carriage used by school children. Carrying school bags that exceed 10% of body weight can lead to heightened energy expenditure, causing increased forward lean of the neck and trunk, reduced lung capacity, and elevated cardio-respiratory measures. Musculoskeletal disorders (MSDs) are characterized by injuries or disorders affecting muscles, tendons, ligaments, cartilage, or spinal discs, as diagnosed by healthcare providers, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 49–58 Read article
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Harnessing Shell Scripting for Autonomous System Management: A Vision for the Future
Abstract: As IT systems become increasingly complex, the demand for efficient and automated management solutions is more critical than ever. This paper investigates the pivotal role of shell scripting in the development of autonomous systems that can self-manage and optimize their operations. Shell scripting, with its powerful automation capabilities, serves as a foundational tool for orchestrating various tasks, including system monitoring, data analysis, and deployment processes. We begin by examining current …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 3, 2024 · pp. 17–31 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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A Review of Recent Advancements in Machine Learning and Deep Learning Approaches for Pet Diseases Prediction
Abstract: This systematic study assesses recent developments in Machine Learning (ML) and Deep Learning (DL) approaches to predict pet diseases. With the increasing role of Artificial Intelligence (AI) in pet healthcare, this study identifies recent research trends, limitations, and future directions. A comprehensive search was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines in selecting 20 relevant studies from over 300 articles published between 2020 and …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 1–6 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article