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503 articles for “predictive analysis”
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Computational Investigation of Phytochemicals Targeting AKT1 for Major Depressive Disorder: A Molecular Docking and ADMET Study
Abstract: Major depressive disorder (MDD) is a prevalent neuropsychiatric condition affecting approximately 280 million individuals worldwide, with women exhibiting a 50% higher likelihood of diagnosis than men. Despite significant advancements in treatment, MDD remains a chronic and relapsing disorder, necessitating the exploration of novel therapeutic interventions. This study focuses on the AKT1 gene, a key player in neuropsychiatric disorders, and investigates its interactions with natural phytochemicals as potential alternatives to conventional …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
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In Silico Molecular Docking Studies of Phytocompounds from Melissa officinalis Against MPXV Poxin Target
Abstract: Objectives: This study aimed to evaluate the inhibitory potential of phytocompounds of Melissa officinalis against the MPXV poxin protein target, a key virulence factor in monkeypox infection. Methods: Molecular docking performed using PyRx, a virtual screening software, was conducted to predict the binding affinities of the compounds to MPXV poxin. Prior to docking, the compounds were subjected to comprehensive analysis, including Lipinski's rule of five, evaluation of physicochemical properties, pharmacological …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 25–38 Read article
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Demonstrative Research of Group VII Elements of the Periodic Table: Characteristics and Properties of Chemical Behavior
Abstract: The elements in Group VII, commonly referred to as halogens, are non-metals that exhibit similar chemical characteristics and a high level of reactivity, which can be attributed to their electron configuration. This paper seeks to provide an overview of the relationship between the electron structure and chemical behavior of the Group VII elements found in the periodic table. The primary goals include elucidating how the electron configuration influences the physical …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 2, 2025 · pp. 18–26 Read article
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Seismic-Resilient Structural Systems: Geotechnical Engineering
Abstract: Earthquakes represent one of the most destructive natural hazards, capable of causing severe structural damage, loss of life, and substantial economic disruption. Seismic waves propagating through the ground can induce excessive forces and deformations in buildings, often leading to partial or complete collapse. Statistical records indicate that thousands of earthquakes occur globally each year, including several major events that result in significant damage. Past earthquake disasters have repeatedly demonstrated that …
Published in Journal of Geotechnical Engineering · Vol. 13, Issue 1, 2026 · pp. 55–63 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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Mechanical Characterization and Machinability Optimization of Stir-Cast Al6061–SiC Metal Matrix Composites
Abstract: This study presents the fabrication, mechanical characterization, metallurgical analysis, and machinability optimization of Aluminum 6061 reinforced with Silicon Carbide (SiC) metal matrix composites (MMCs) at three weight fractions: 5%, 7.5%, and 10%. Composites were manufactured using the stir casting technique, followed by comprehensive mechanical testing (tensile, hardness, and impact), optical microscopy, and scanning electron microscopy (SEM). Machinability was assessed through turning experiments on a lathe using an L9 Taguchi orthogonal …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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A Combined ECG and PPG Signal Powered Artificial Intelligence-Based Prediction Model for Stroke
Abstract: Stroke is one of the most common causes of morbidity and mortality around the world, and emphasis on prevention and early detection strategies cannot be overstated. This review aims to integrate techniques of artificial intelligence with electrocardiogram and photoplethysmogram signals to enhance stroke prediction and monitoring of cardiovascular health. All in all, the application of artificial intelligence that incorporates machine learning, deep learning, or hybrid models gives robust tools toward …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 18–26 Read article
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Evaluating Advancements and Identifying Research Gaps in Automotive Spare Parts Demand Forecasting
Abstract: The automotive industry, a key driver of global economic activity, relies heavily on the effective management of spare parts to ensure vehicle longevity and reliability. Accurate prediction of demand for these components is imperative to uphold ideal stock levels, minimize expenditures, and elevate customer contentment. This review of literature assesses recent progressions in demand prediction methodologies for automotive spare parts, with a specific emphasis on conventional statistical methods and contemporary …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 47–58 Read article
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Design and Simulation of Forging Die Towards Improving Life of Closed Die
Abstract: Forging is the metal forming process which is used for forming complex shaped component with geometrical accuracy. More than fifty percent of the forgings are processed through this way. Forged components required in many engineering sectors, most of them in the automotive sector. The majority of the safety critical component and load bearing structural components are process through it. By using forging process production of complex component is faster with …
Published in Journal of VLSI Design Tools and Technology Read article
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Hybrid Polymer Nanocomposites with Enhanced Dielectric and Optical Properties for Wireless Communication Systems
Abstract: The incorporation of nanofillers into polymer matrices offers a promising approach to enhancing the multifunctional properties of composite materials. This study examines the effect of nanofiller concentration on the dielectric performance, mechanical strength, thermal stability, optical absorbance, and electromagnetic interference (EMI) shielding effectiveness of polyvinylidene fluoride (PVDF)-based nanocomposites. Titanium dioxide (TiO₂) and zinc oxide (ZnO) nanofillers were incorporated at varying concentrations to assess their influence on material properties. EMI shielding …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 518–549 Read article
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Machine Learning-Assisted Design and Optimization of Lightweight Polymer Composites for IoT-Enabled Automotive Applications
Abstract: This study aims to develop an integrated machine learning and optimization framework for the intelligent design of lightweight polymer composites suited for IoT-enabled automotive applications. The goal is to enhance material performance while satisfying multiple design constraints such as mechanical strength, thermal stability, and process compatibility. A curated dataset of polymer composite formulations was used to train a Random Forest Regression (RFR) model capable of predicting tensile strength, thermal conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 12–27 Read article
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Thermal Effects in High-Power Laser Systems: Modeling and Mitigation
Abstract: High-power laser systems are increasingly employed in industrial manufacturing, defense, medical procedures, and scientific research due to their ability to deliver high energy density with excellent spatial coherence. However, the performance and reliability of these systems are significantly influenced by thermal effects arising from optical absorption, non-radiative recombination, and inefficient heat dissipation within laser gain media and optical components. These thermal phenomena lead to adverse effects such as thermal lensing, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 9–13 Read article
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ML-Based Predictive Modeling of Mechanical Properties in 3D-Printed Polymer Composites for IoT Applications
Abstract: This study aims to develop an interpretable and high-accuracy machine learning framework for predicting the mechanical properties of 3D-printed fiber-reinforced polymer composites, with a focus on structure–property correlations relevant to polymer processing and functional performance. Composite specimens based on PLA and ABS matrices were fabricated using FDM with varying weight fractions (5–20 wt%) of carbon and glass fibers. Standardized mechanical testing (ASTM D638, D256, D790) was performed to evaluate tensile …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 61–78 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Integrated, Geospatial Risk Assessment of Air, Water, and Soil Pollution Impacts on Agricultural Sustainability using Advanced Digital Technologies
Abstract: The systemic threat posed by the convergence of air, water, and soil contaminants represents a critical challenge to global agricultural resilience and food security. Traditional, site-specific pollutant monitoring methods are insufficient for capturing the dynamic, diffuse, and often nonlinear nature of environmental risk pathways that permeate agrarian landscapes. This study presents a robust framework for comprehensive risk assessment utilizing a synergistic suite of modern tools designed for spatial, temporal, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 28–37 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Integrated Optimization of Solar Photovoltaic Systems Using Taguchi Method and Computational Fluid Dynamics for Enhanced Efficiency
Abstract: The transition to renewable energy demands efficient and reliable photovoltaic (PV) systems to meet rising global energy needs. This study presents an integrated optimization framework combining the Taguchi method and Computational Fluid Dynamics (CFD) to improve the thermal and electrical performance of solar PV systems. A structured experimental design using an L9 orthogonal array evaluates the influence of three key parameters—material type, panel thickness, and cooling mechanism—on system efficiency. Analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 10–25 Read article
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A Review on Predicting Wear and Friction of PTFE Composites - Fillers to Machine Learning Models
Abstract: Polytetrafluoroethylene (PTFE) composites, a self-lubricating material with low friction, became an indispensable material in engineering applications where load carrying capacity and wear are crucial. The pure PTFE has poor mechanical strength and wear resistance which can be enhanced by the addition of fillers in appropriate volume fraction. The wear performance is dependent on various factors such as fillers, operating parameters, environmental conditions as well as manufacturing attributes. This makes the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 114–128 Read article
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Evaluation on Bioremediation Kinetics of Petroleum- Contaminated Soils Using Plant-Based Amendments
Abstract: The effectiveness of bioremediation processes is strongly influenced by environmental conditions, reactor design parameters, microbial characteristics, and pollutant properties. This study investigates the combined effects of environmental-related factors, reactor design considerations, organism- related characteristics, and pollutant properties on the degradation of total petroleum hydrocarbons (TPH) in swampy and clay soils amended. Laboratory-scale remediation experiments were conducted over an 84-day period using amendment dosages ranging from 20 to 100 g. The …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 1, 2026 · pp. 24–30 Read article
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Research Paper A Review of Symmetry in Mechanical Systems: Theoretical Systems Foundations and Engineering Applications
Abstract: In mechanical system analysis and design, symmetry is of mechanical systems. This article examines the idea of symmetry in mechanical systems, exploring its mathematical foundations (such as Lie algebras and group theory) and how these ideas help explain the behavior, stability, and control of the system. We explore the applications of symmetry in a range of mechanical systems, from basic mechanical connections to intricate multi-body dynamics, emphasizing the benefits of …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 1, 2025 · pp. 15–19 Read article