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154 articles for “Statistical models”
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The Evolution and Impact of Numbers: From Ancient Tallies to Quantum Computing: Review Article on Numbers
Abstract: Numbers are among the most fundamental constructs in human civilization, serving as the backbone of mathematics, science, technology, and virtually every aspect of daily life. They represent not only quantities and measures but also relationships, structures, and patterns that underpin the fabric of human understanding. From the earliest tallies etched on bones by prehistoric humans to the sophisticated numerical systems embedded in today’s artificial intelligence and quantum computing, the evolution …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 15–19 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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Exploring Gelatin Film an Eco-Friendly Biomaterial: Synthesis, Characterization, and Environmental Applications
Abstract: This study explores the synthesis, characterization, and application of eco-friendly gelatin films, a sustainable and biodegradable biopolymer alternative to synthetic plastics. Synthesized via solution casting and characterized by UV-Vis spectroscopy, FTIR, and TGA, these films demonstrated excellent molecular integrity and thickness-dependent properties, with higher gelatin concentrations leading to thicker films and delayed solubility. The research highlights their significant potential in removing diverse environmental pollutants, including dyes (methylene blue, methyl orange), …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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The Poisson–Uma Distribution with Properties and Applications to Model Thunderstorm Events
Abstract: The discrete data available in any field of knowledge is influenced by several known and unknown factors and the factors which affect the discrete data are stochastic. The stochastic nature of discrete data is a challenge for statisticians to model and analyze with the existing discrete distributions. In the present paper, Poisson-Uma distribution, the Poisson compound of Uma distribution, has been proposed to model over-dispersed data of thunderstorm events. The …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 1, 2024 · pp. 20–30 Read article
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A Multivariate Adaptive Regression Splines Based Study of Soil Parameters and Their Impact on Onion Yield in Bhavnagar District
Abstract: Bhavnagar district is one of the prominent onion-growing areas in the Saurashtra region of Gujarat, encompassing key talukas such as Mahuva, Talaja, Ghogha, Jesar, and Palitana. Onion cultivation in the district is carried out across three distinct seasons: rabi, kharif, and late kharif with harvesting periods extending from April to May for the rabi crop and from October to March for the kharif and late kharif crops. The productivity of …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 53–64 Read article
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Data-Driven Life Prediction of Fiber-Reinforced Polymer Composites Using IoT Sensing and Machine Learning Algorithms
Abstract: The accurate prediction of fatigue life in fiber-reinforced polymer (FRP) composites remains a major challenge due to their nonlinear, multi-mechanism degradation behavior under variable loading conditions. This study presents a data-driven framework, H-LiProNet, which combines real-time IoT sensing with hybrid machine learning to estimate remaining useful life (RUL) in FRP composites. The proposed system integrates embedded Fiber Bragg Grating (FBG) and acoustic emission (AE) sensors to capture strain and damage …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 116–130 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Real-Time Air Quality Prediction Using IoT-Integrated Polymer Sensors and Recurrent Neural Networks
Abstract: Real-time air quality monitoring remains a critical challenge in urban environments, where traditional sensor infrastructures often suffer from limited responsiveness, poor scalability, and high deployment costs. The increasing prevalence of NO₂ pollution, a key contributor to respiratory and cardiovascular ailments, demands advanced sensing platforms capable of both accurate detection and predictive inference. Existing methods either rely on rigid electronic sensors lacking adaptability or on statistical forecasting models that fail to …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 332–347 Read article
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Strategic Solutions: How Mathematics Reshapes Industrial Landscapes
Abstract: One of the earliest and most fundamental fields of the physical sciences is mathematics. It has a significant impact on industrial enterprises' bottom lines and enhances their performance in the current data-driven market. One subfield of applied mathematics is industrial mathematics. It concentrates on issues that arise in the industry and seeks answers that are pertinent to the sector. The use of mathematical models and techniques to diverse industry difficulties …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 1, 2024 · pp. 16–23 Read article
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Therapeutic Potential of Plant-Derived Phytochemicals in Targeting Receptor Pathways Related to Non-Enzymatic Glycation: A Meta-Analysis
Abstract: Background: Non-enzymatic glycation, where reducing sugars react with proteins, lipids, and nucleic acids, contributes to various pathological conditions, such as diabetic complications and cardiovascular diseases. This process is facilitated by the receptor for advanced glycation end-products (RAGE), which is pivotal in driving inflammation and causing tissue damage. Objective: This meta-analysis evaluates the effects of plant-derived phytochemicals on RAGE expression and associated signaling pathways, assessing their therapeutic potential in glycation-related diseases. …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 60–73 Read article
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Machine Learning-Based Channel Estimation in 5G, Beyond-5G, and 6G Networks: Recent Advances and Future Directions
Abstract: Accurate channel estimation is one of the most fundamental challenges in modern wireless communication systems. In fifth- generation (5G) New Radio (NR) and emerging sixth-generation (6G) networks, precise knowledge of the wireless channel is essential for achieving reliable data transmission, high spectral efficiency, and low Bit Error Rate (BER). Conventional estimation techniques such as Least Squares (LS) and Minimum Mean Square Error (MMSE) rely on mathematical channel models and predefined …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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Unveiling Fairness: A Quest for Ethical Artificial Intelligence and Bias Mitigation
Abstract: Artificial intelligence (AI) systems have become ubiquitous across areas like finance, healthcare, employment, and criminal justice. However, they suffer from issues of unfair bias, lack of transparency, and broad ethical implications impacting vulnerable societal groups disproportionately. This paper reviews key challenges around AI ethics and bias while proposing data-driven guidelines mitigating such algorithmic harms through rigorous statistical testing, predictive modeling ensembles adjusting distortion vectors and AI audits by domain experts …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 2, 2023 · pp. 28–31 Read article
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Future-proofing the Mind: Fostering Robust Innovation in Soft Computing and Computational Intelligence
Abstract: This study examines the impact of Computer Science (CS) and Soft Computing (SC) on a few scholarly disciplines and way of life. The study considers points to improve calculation execution by utilizing computational intelligence (CI) techniques, progressing the steadiness of statistical classification (SC) models, and optimizing them through algorithmic upgrades. These adjustments encourage the method of altering, selecting, and creating oneself, indeed in challenging circumstances. The effect on work, protection, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article
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Factors Influencing Coffee Retail Selection Among Smallholder Producers in Gimbo District, Kaffa Zone, Southwest Ethiopia
Abstract: Coffee is Ethiopia’s most important export crop, contributing significantly to GDP and providing income for around 20% of the population. Despite its potential, farmers face marketing challenges, particularly in selecting appropriate market outlets. This study analyzes the determinants of coffee producers’ market outlet choice decisions in the Gimbo district. A purposive and two-stage random sampling technique were used to collect data from 200 coffee producers, 22 traders, and 22 consumers …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 121–133 Read article
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Determinants of Coffee Market Outlet Choices in Gimbo District, Kaffa Zone, Southwest Ethiopia.
Abstract: Coffee is Ethiopia’s most important export crop, contributing significantly to GDP and providing income for around 20% of the population. Despite its potential, farmers face marketing challenges, particularly in selecting appropriate market outlets. This study analyzes the determinants of coffee producers’ market outlet choice decisions in the Gimbo district. A purposive and two-stage random sampling technique was used to collect data from 200.00 coffee producers, 22.00 traders, and 22.00 consumers …
Published in Research & Reviews : Journal of Agricultural Science and Technology Read article
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Size-biased Sujatha Distribution with Properties and Application to Model Flood Data
Abstract: In this study, a size-biased version of the Sujatha distribution was proposed to model flood data. The descriptive statistical properties based on moments and the reliability properties of the distribution are discussed in detail along with their derivation and graphical presentation. An interesting feature of the proposed distribution is that it is a member of the exponential family of distributions. A sequential probability ratio test was performed using the proposed …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 1, 2024 · pp. 31–46 Read article
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Blind Image Quality Assessment using NSS Approach in the DCT Domain
Abstract: We have develop an efficient model for improving image quality using IQA and NSS based on blind image Quality Assessment. This algorithm does computation for the parameters which user expect at output. The certain extracted features approach depends on a simple Bayesian inference model to dipict image quality scores. The project features are based on statistic scenes of discrete cosine transform for images. The resultant parameters of the model are …
Published in Recent Trends in Electronics Communication Systems Read article
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Microvita: A New Hybrid Particle Bridging the Fermionic and Bosonic Domains in Particle Physics
Abstract: In particle physics, the established classification of particles into fermions and bosons—obeying Fermi-Dirac and Bose-Einstein statistics, respectively—has shaped theoretical and experimental frameworks for nearly a century. This study introduces 'Microvita', a novel theoretical particle that exhibits hybrid characteristics modulated by a continuous parameter α ∈ [0,1]. Through this parameter, Microvita interpolates between bosonic and fermionic behavior in terms of spin, statistical distributions, and operator algebra. We explore the foundational algebra …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 14–27 Read article
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The Role of AI-Powered Assessment Tools in Improving Educational Feedback in Nigeria
Abstract: Educational systems in Nigeria face a persistent challenge in delivering high-quality, timely, and personalized feedback, due primarily to large class sizes, heavy teacher workloads, and reliance on traditional assessment methods. This study investigates the potential of integrating Artificial Intelligence (AI)-powered assessment tools to overcome these systemic barriers and improve the quality of educational feedback within the Nigerian secondary school context. Employing a quantitative cross-sectional survey design, data was collected from …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 31–41 Read article
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Parametric Study of Laser Drilling Process Using Multi Variable Regression Analysis
Abstract: The laser drilling process is an advanced manufacturing technique extensively employed for intricate and high-value components in aerospace, automotive, and electronics industries. Laser drilling technology offers opportunities to meet the contemporary demands of industries using a broad spectrum of engineering materials. However, this process encounters several engineering challenges such as thermal damage, dimensional inaccuracies, and the formation of a recast layer in the drilled components. This study focuses on examining …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1000–1015 Read article