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52 articles for “Linear Regression”
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Monitoring of Ship Deployment Through Emerging Technologies
Abstract: The mission for naval vessels encompasses defining combat tasks, deployment statuses, and timing requirements to optimize combat patrol effectiveness and daily ship management. This involves inheriting, developing, and optimizing ship deployment strategies while establishing new deployment categories with distinct names, connotations, personnel, and equipment needs to ensure organic integration and synergy. Emphasis is placed on maintaining continuity, stability, and forward-thinking to meet the demands of warship combat operations, facilitate management …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 59–66 Read article
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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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Advances in Non-Invasive NIR-Techniques for Gout Detection and Measurement
Abstract: Recent advancements in non-invasive near-infrared (NIR) spectroscopy techniques have significantly improved the detection and measurement of gout, a common form of inflammatory arthritis. Traditional diagnostic methods for gout, such as joint aspiration and crystal analysis, are invasive and can be uncomfortable for patients. In contrast, NIR spectroscopy offers a promising alternative by enabling real-time, non-invasive assessment of uric acid levels and related biomarkers associated with gout. The integration of portable …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 1, 2025 · pp. 1–8 Read article
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Mathematical Modeling Analysis of India's Accident &Use of Fly Ash and Polymers in Road Safety
Abstract: Accident predicting models (APMs) are exceptionally strong tools for adaptation and mitigation strategies because they have the ability to predict both the severity and frequency of crashes. Road accidents are a major problem all throughout the world, especially in developing countries. Understanding the key variables that contribute can assist in reducing the frequency of traffic collisions. This study also discovered recent developments on fly ash, green composites, other polymer materials …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 488–499 Read article
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Evaluation of AGO Adsorption Rate Isotherms Using Adsorbent Formulation of Plantain Agbagba1 and Clay of Different Mix Ratio in Pollutant Remediation in Salt Water
Abstract: The application of some agro-based materials in combination with day soil, for the production of adsorbents were investigated in relationship to their performance in AGO (Diesel) treatment in a batch process unit. The research allows the model concept of Langmuir isotherm, Frundlich isotherm and Temkin Isotherm for the determination of the adsorption rate of the various isotherms with respect to the effect of the particle size and the mixed ratios …
Published in International Journal of Pollution: Prevention & Control · Vol. 2, Issue 2, 2024 · pp. 31–42 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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The Impact of Climate Change on Jute Production in Gaibandha District, Bangladesh
Abstract: Jute plays a crucial role in Bangladesh’s agricultural economy, especially in Gaibandha District, where it is a key crop for rural livelihoods. However, climate change, characterized by rising temperatures and unpredictable rainfall, poses significant threats to jute production. While numerous studies have explored the broader impact of climate change on agriculture, there is a gap in understanding how localized climate conditions specifically affect jute farming in Gaibandha, with many existing …
Published in International Journal of Climate Conditions · Vol. 2, Issue 1, 2025 · pp. 1–17 Read article
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Environmental and Health Impacts of Rice Milling: A Case Study of Dinajpur Sadar Upazila, Bangladesh
Abstract: Rice milling plays a crucial role in Bangladesh's agricultural economy but contributes significantly to environmental pollution, affecting air, water, and soil quality, which in turn impacts public health and agricultural productivity. While prior studies have focused on immediate health effects like respiratory problems and reduced crop yields, they often overlook long-term consequences such as chronic diseases, soil degradation, and socio-economic impacts. Additionally, there is limited comparison between traditional and automated …
Published in International Journal of Climate Conditions · Vol. 2, Issue 1, 2025 · pp. 18–28 Read article
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Utilizing Machine Learning to Evaluate the Connection between Poisson's Ratio and the Petrophysical Properties of Reservoir Rocks
Abstract: The Poisson's ratio is a crucial cornerstone, illuminating our understanding of geomechanical behaviour in wells during the dynamic drilling process and the inspiring recovery journey. This research rigorously employs machine learning methods to analyse the significant impact of geophysical parameters on the Poisson ratio in hydrocarbon reservoirs found in oil fields. The analysis utilized data from multiple oil and gas fields, highlighting the crucial relationships between the Poisson ratio, the …
Published in Journal of Petroleum Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 33–43 Read article
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Machine Learning Approach to Predict the Performability and Emissions of Diesel Engine Fueled with Doped Biodiesel Blend
Abstract: Enhancing the performability and emission characteristics of diesel engines has been a difficult task in light of growing concerns about global warming and other negative effects, as diesel accounts for 70% of global energy demand. In this study, engine performance and exhaust emissions for various fuel blends were thoroughly evaluated using machine learning techniques to predict engine emission and performance behavior. We focused on biodiesel blend and nanoparticle additive concentration …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 1–12 Read article
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Examining the Relationship Between Academic Stress, Maladaptive Perfectionism and Trauma-Related Responses Among University Students
Abstract: Academic stress is a significant concern among university students, frequently contributing to maladaptive perfectionism and trauma-like responses. While perfectionism can enhance performance, its maladaptive variant may be exacerbated by academic stress which can induce trauma-like responses. This study investigates the correlation between academic stress, maladaptive perfectionism and trauma-like responses. Validated self-report measures were used in a quantitative, correlational study involving 101 university students. Linear regression analysis and Kendall’s Tau-B correlation …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 145–154 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Graph Theoretic Analysis of Cyclodextrin Polymers
Abstract: Topological indicators in chemical graph theory are essential tools in cheminformatics, providing valuable insights into molecular structure and properties to make more accurate predictions about the behavior and efficacy of novel compounds in drug design. The macro molecules are correlated with certain derivatives. The derivatives are growing structures which depends on the cyclic structures. The Cyclodextrin is one of the cyclic structures which depends on the carbon atoms. The polymer …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 997–1006 Read article
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An Integrated Simulation Framework for Predicting Dielectric Breakdown and Electrical Aging in Epoxy-Silica Composite Insulation Systems
Abstract: This paper provides a combined computation approach in forecasting the dielectric breakdown and electrical aging within epoxy-silica composite of insulation system. The approach will consist of a three-complementary methodology (a combination of computing electric field using the finite element analysis, estimation of the probability of failures or breakdowns using Weibull statistics, and prediction of degradation tendencies using artificial neural networks). The epoxy-silica composites are of 10-40 volumes fillers. The simulations …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 339–376 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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The Awareness–Behaviour Paradox: Media Literacy and Social Media Risk Behaviour Among Nigerian Undergraduates
Abstract: Background: The proliferation of internet-capable devices and social media platforms has created an intricate web of risks for Nigerian undergraduates, including cyberbullying, addiction, misinformation, and exposure to indecent content. While media literacy has been widely proposed in Western scholarship as a sustainable intervention for responsible online behaviour, its protective mechanisms remain insufficiently understood in non-Western contexts, particularly with respect to the psychological pathways through which literacy operates. Objectives: This study …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 121–126 Read article
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Machine-Learning-Assisted Development of Polymer-Biochar Composite Adsorbents for the Removal of Heavy Metals from Gomti River Water
Abstract: Rapid urbanization, industrial discharge, and agricultural runoff pose a significant threat to freshwater sustainability and public health. Within these ecosystems, polymer pollutants—such as microplastics, nanoplastics, synthetic fibres, and additive residues—have emerged as persistent vectors capable of adsorbing and transporting toxic heavy metals. Because these polymeric contaminants dynamically interact with conventional aquatic parameters to alter pollutant mobility and ecological risk profiles, there is an urgent need to transition from passive environmental …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 72–95 Read article
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Evaluating UX Design Factors Affecting Efficiency of Composite Material Design and Analysis Platforms
Abstract: Within engineering software platforms that involve the design, simulation and characterization of composite materials, user experience (UX) design has become a key determinant for efficient use. This research aims to quantify how user experience design parameters relate to productivity in composite engineering workflows by analyzing the relationship between usability, learnability, accessibility, complexity of the UI, navigation efficiency and users engineering results satisfaction. Computational techniques in python were used in the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 341–366 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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Psychological Profile of Patients Undergoing Hemodialysis and Its Association with Physiological Parameters
Abstract: Background: End-stage renal disease (ESRD) is a chronic, progressive condition requiring maintenance hemodialysis, which imposes substantial physiological, psychological, and social burdens on patients. While physiological indicators are routinely monitored during treatment, the influence of psychological factors on these indicators and patients' quality of life remains inadequately explored, particularly in the Indian context. Objective: To investigate the relationship between psychological variables (depression, anxiety, illness intrusiveness, and quality of life) and physiological …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 Read article