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154 articles for “Statistical models”
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Quantitative Structure-activity Relationship in Computer-aided Drug Design: A Review
Abstract: Quantitative Structure-Activity Relationship stands at the forefront of Computer-Aided Drug Design, providing a systematic framework for understanding the relationship between the chemical structure of molecules and their biological activity. The present review delves into the multifaceted realm of quantitative structure-activity relationship methodologies within the landscape of drug discovery. Through an exploration of diverse quantitative structure-activity relationship models, molecular descriptors, validation techniques, and recent advancements, the present article aims to elucidate …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 55–63 Read article
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Interfacial and Tribo-Mechanical Performance of a TiO₂–Castor Oil Polymeric Nanofluid During Sustainable Machining of AISI 316L Stainless Steel Under MQL Conditions
Abstract: This research examines the tribo-mechanical performance and interfacial film characteristics of a TiO₂-reinforced castor-oil polymeric nanofluid during the turning of AISI 316L stainless steel under minimum-quantity lubrication (MQL). A Taguchi L9 orthogonal array was utilized to assess the synergistic effects of cutting speed, depth of cut, and coolant composition on surface integrity, while machining experiments were performed under dry, conventional, and TiO₂-nanofluid lubrication techniques. ANOVA and multiple-regression modeling were used …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 901–914 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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The Impact of Environmental Changes on Indian Agriculture: Strategies for Resilience
Abstract: With more than 61 years of independence, the portion of agriculture in the whole national revenue has been come down from 50 percent in the year 1950 to 18 percent in the year 2007-08. But, as sup above specified, more than 60 percent of workforce in the country are involved in the agricultural activity. But the economy in general depends to a great extent on the performance of agriculture. For …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 13, Issue 3, 2024 · pp. 01–08 Read article
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Comparison of Models of Machine Learning and Hyperparameter optimization methods on various datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameters tuning step. The traditional exhaustive methods of search (Grid Search and others) ensure that the search space is covered, but are computationally very inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian Optimization, Tree-structured Parzen Estimator (TPE), Genetic Algorithms) are thought to …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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Additive Manufacturing of Polymer-Based Advanced Composites: Mechanical Properties and Performance Evaluation
Abstract: Fabrication of large-scale and geometrically complex polymer-based advanced composites via fused deposition modelling (FDM) has been shown to be a promising technology for the production of such materials, however there are challenges in using short carbon fibre-reinforced polylactic acid (CF-PLA) which include obtaining high mechanical performance and maintaining dimensional accuracy with dynamic robot motion and complex interactions occurring between process parameters. The conventional approaches are mostly static feed rates or …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1335 Read article
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The Impact of Nutrition on Sports Performance and Academic Success: A Study Among University Athletes – Eastern Technical University of Sierra Leone
Abstract: University athletes operate within dual-performance environments that require simultaneous academic and athletic excellence. Nutrition plays a critical role in supporting both physiological performance and cognitive functioning; however, limited empirical work has examined its combined influence on athletic and academic outcomes within university athlete populations, particularly in low-resource contexts. This study aimed to investigate the relationship between nutritional practices, sports performance, and academic achievement among university athletes at the Eastern Technical …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 16–27 Read article
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Analysis of Gold Price Trend Using the Hidden Markov Model
Abstract: This study aims to analyze the behavior of gold prices in India through a two-state Hidden Markov Model (HMM). We first formulated crucial parameters, such as the Transition Probability Matrix (TPM), Initial Probability Vector (IPV), and Emission Probability Matrix (EPM). Subsequently, we constructed a hidden Markov probability distribution and evaluated Pearson’s coefficients to gauge the correlations separately for each state. The goodness of fit of the developed model was assessed …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 7–16 Read article
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Identification and Prioritization of Critical Erosion Prone and Water Potential Areas of Manandragarh Watershed Using HEC-HMS for Management
Abstract: This study was carried out at Indira Gandhi Krishi Vishwavidyalaya, Raipur (CG) on hydrological modelling and development of soil and water conservation plan for critical erosion prone and water potential sub-watersheds of Manendragarh watershed of upper Hasdeo subbasin in Chhattisgarh using Hydrological Engineering Centre-Hydrological Modelling System (HEC-HMS). The Hydrological Engineering Centre-Geo Hydrological Modelling System (HEC-Geo HMS) was utilized for developing the model setup, while the HEC-HMS model was employed to …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 1, 2025 · pp. 26–44 Read article
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Prediction of Mechanical Properties for Advanced Engineering Applications utilizing Polymer Composite Materials by Machine Learning
Abstract: Polymer composites show great promise as engineering materials because of their mechanical performance, resistance to corrosion, lightweight nature, and adaptability in design. Aerospace, automotive, biomedical, maritime, and civil engineers all rely on mechanical property prediction to cut down on trial expenses, expedite product development, and optimize material selection. Speedy design optimization is not possible using traditional numerical and experimental methods due to the high costs associated with material characterisation, computational …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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QSAR Modeling of a Novel Series of Methoxylated Chalcones as Antioxidant Agents Against Gram-Positive Bacteria Staphylococcus aureus
Abstract: Background: Chalcones are aromatic ketones belonging to the flavonoid family. They are plant-based compounds and are widely found in nature. For centuries, these bioactive molecules have been utilized in various traditional medicines for the treatment of several ailments. Chalcones have antibacterial, antiviral, antimalarial, antifungal, antioxidant, and antileishmanial properties. They are also used to treat inflammation and cancer. Chalcones act as angiogenesis inhibitors, an important factor in cancer progression and metastasis. …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 3, Issue 1, 2025 · pp. 28–34 Read article
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Adoption of Major Improved Crop Varieties in Selected Districts of the Southwest Ethiopia Region
Abstract: Agriculture forms the backbone of the Ethiopian economy and significantly contributes to the livelihoods of the majority of the population. It remains a central pillar of food security, employment, and rural development across the country.The present study aims to examine the adoption of improved major crop varieties and to identify the key factors influencing their uptake in the southwest Ethiopia region. The research was carried out in the districts of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 18–31 Read article
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Structure–Property Modeling of Cement-Based Multi-Component Composites Using Ensemble Machine Learning and Explainable Feature Attribution
Abstract: Accurate prediction of compressive strength is central to structure–property optimization, quality control, and sustainability-driven design in cement-based composite materials. Cementitious systems represent heterogeneous multi-phase composites composed of reactive binder matrices and dispersed aggregate phases, whose macroscopic mechanical performance emerges from complex nonlinear interactions among constituents and curing-dependent microstructural evolution. This study develops a data-driven structure–property modeling framework to quantify the nonlinear dependence of compressive strength on multi-component composite composition and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 112–131 Read article
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Unveiling Patterns in Complexity: The Role of Simple Statistics and Fuzzy Mathematics in Data Analysis
Abstract: In this study, statistical methods must be integrated with fuzzy mathematics to solve complex data. Statistical methods offer clear, unbiased, and computationally feasible tools for analysing numerical data. whereas fuzzy mathematics excels in describing the vagueness and ambiguity of human feeling by way of linguistic variables, membership functions, and inference systems. Giving it an apparent advantage when modelling complex conditions. Hybrid frameworks offer fine-grained decision-making and resilient adaptability to real-world …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 1, 2025 · pp. 01–10 Read article
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Review on Machine Learning Techniques for Heart Failure Analysis in Health Industries
Abstract: There are few bodily components as crucial as the heart. It aids in the filtration and distribution of blood to every area of a body. The world's biggest cause of death is heart disease. It has been reported that symptoms include breathing difficulties, fast heartbeat, and chest discomfort. They analyze this data on a regular basis. This review begins with a brief introduction of cardiac disease and the present methods …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 29–43 Read article
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Signal Feature Extraction and Machine Learning Techniques for Human Activity Recognition
Abstract: Human Activity Recognition (HAR) has emerged as a critical field of study with diverse applications in healthcare, fitness tracking, smart homes, and human-computer interaction. The aim of this research is to create an efficient HAR system through advanced techniques characterized by signal feature extraction and machine learning algorithms. The MEMS sensors are used appropriately during data mining to extract time-domain, frequency-domain, and statistical features, which are subsequently passed to the …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 24–41 Read article
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Dielectric Breakdown and Electrical Aging of Insulating Polymer Materials in High Voltage Systems
Abstract: In this paper, a detailed analysis of dielectric breakdown and electrical aging behavior of high-voltage insulating polymer material has been proposed through sophisticated MATLAB simulation. The research involves electric field modeling, aging life prediction, partial discharge (PD) behavior and uncertainty modeling using Monte Carlo analysis. Electric field hotspots causing critical behavior, sensitivity of the lifespan to electric stress, and the stochastic PD build-up allow predictive diagnostics of the health of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 173–187 Read article
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Influence of SlS Parameters on Strength and Fatigue Durability of Polyamide-12
Abstract: Selective Laser Sintering (SLS), a laser-based polymer powder bed fusion process, has gained prominence in the fabrication of high-performance thermoplastics such as Polyamide-12 (PA12). This paper provides an extensive review of how key SLS process parameters—such as laser power, scan speed, hatch spacing, and energy density—affect the mechanical properties of PA12 components, with a specific focus on tensile strength and fatigue resistance. Studies demonstrate that increasing energy input enhances particle …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 178–191 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 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