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225 articles for “linearity of data”
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The Fundamental Premises of Efficient Linear Regression and Applying Regression
Abstract: Linear regression is a statistical technique for estimating the value of a dependent variable from an independent variable. Linear regression is a way to assess how two variables are related. A dependent variable is predicted using this modelling technique based on one or more independent factors. Many analyses are based on linear regression. Sometimes the data must be changed to satisfy the needs of the analysis, or extra room must …
Published in Trends in Machine design · Vol. 9, Issue 4, 2022 Read article
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Photochemically Assisted LC–MS Method Development and Validation for Stability-Indicating Determination of Glasdegib in Rat Plasma
Abstract: A simple, precise, and cost-effective LC–MS method was successfully developed for the determination of Glasdegib in rat plasma. The method optimization was carried out by systematically varying key chromatographic parameters, including flow rate, injection volume, analyte concentration, and mobile phase composition, to achieve optimal sensitivity and resolution. A C18 Hypersil BDS column (150 mm × 4.6 mm, 3.5 µm particle size) was used for chromatographic separation, offering effective peak shape …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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House Price Estimation Using Linear Regression: A Machine Learning Perspective
Abstract: House price prediction plays a crucial role in the real estate industry, helping buyers, sellers, and investors make well-informed decisions. Accurate estimation of property values enables stakeholders to assess market trends, plan investments, and minimize financial risks. This study focuses on the application of linear regression, a fundamental and widely used machine learning algorithm, to predict house prices based on multiple influencing factors. These factors include location, property size, number …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 21–29 Read article
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An Innovative Approach to Find the Optimum Lubricant for Diverse Applications Based on Scikit-Learn Library Using Python
Abstract: This paper presents an innovative approach for finding the optimum lubricant using the Scikit-learn library in Python. The proposed approach uses a linear regression model to analyze a dataset of lubricant properties and performance, specifically the viscosity, wear, and friction. The model is trained on the dataset to predict the wear and friction for a given viscosity, which can be used to identify the optimum lubricant. By analyzing a dataset …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 25–35 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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Financial Forecast: Systematic Analysis Using Principal Component Analysis
Abstract: The most popular technique for data exploration and analysis across all scientific disciplines that can influence the classification model's accuracy is principal component analysis (PCA). In this study, the high dimensionality of the stock market is examined in order to forecast market movements using PCA in conjunction with linear regression. While reducing data redundancy, PCA can aid in enhancing the predictive performance of machine learning techniques. The New York Stock …
Published in E-Commerce for Future & Trends · Vol. 9, Issue 2, 2022 · pp. 18–24 Read article
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Stature Estimation for Human Identification by PA Cephalometric Mandibular Parameters
Abstract: Background: Biological profile assessment for establishing identity can be done by using cephalometric radiographs. As often the skull and mandible are the only remains available, they can be used to get estimate of stature which is one of the important parameters for personal identification. This study was aimed at deriving stature from Posterio-anterior (PA) cephalometric mandibular parameters in adult Chhattisgarh population. Method: About 50 males and 50 females in the …
Published in Research and Reviews: A Journal of Dentistry · Vol. 10, Issue 1, 2019 · pp. 31–35 Read article
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Evaluation Algorithm for Discrimination between Fault and Power Swing Using Independent Component Analysis
Abstract: The analysis of faults and disturbances in power systems is a basic requirement for a secure and reliable electrical power supply. Independent component analysis (ICA) is an efficient computational method used to find out hidden components in a set of sampled data. The basic target of ICA is to find a linear representation and relation between nongaussian data captured during disturbance, so that the components are statistically independent, or as …
Published in Journal of Power Electronics and Power Systems · Vol. 6, Issue 3, 2016 · pp. 53–59 Read article
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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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Performance of Some Modified Ordinary Ridge Regression Estimators
Abstract: In multiple linear regressions, if the data suffer from severe multicollinearity, then the ordinary least squares (OLS) method become more sensitive to it, and in such a case OLS could yield wrong sign for some of the regression coefficients. Therefore, when such a situation arises, we could use one of the biased regression methods viz., ridge regression, principal component regression, and so on, as an alternative method to OLS. This …
Published in Research & Reviews : Journal of Statistics · Vol. 11, Issue 4, 2022 Read article
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Analysis of Air Pollutants in Pre-pandemic and Pandemic Era
Abstract: The paper deals with the impact of the Coronavirus pandemic induced lockdown on the air quality levels of cities of India like Delhi, Mumbai, Kolkata and Bengaluru. PM2.5 and PM10 are the main pollutants on which this study is based. This project compares the actual data of PM2.5 and PM10 of each city with the hypothetical data if the pandemic caused lockdown had not occurred. The hypothetical data was obtained …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 11, Issue 2, 2021 · pp. 19–25 Read article
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Effect of Radiation Dose, Dose Rate and Annealing Temperature on Edible Potato Starch by Spectroscopic Methods
Abstract: Potato starch (PS) is a favorite food choice in different forms. During its storage and applications the PS is exposed to different radiations. In the present study the authors attempt to compare radiation effects (gamma and Electron beam of same radiation dose) in PS by Electron spin resonance (ESR) and Fourier transform infrared (FTIR) methods. ESR spectra of gamma irradiated PS appeared to have resolved shapes than the electron beam …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 198–209 Read article
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T-π Network Simulation and Thevenin- Norton Equivalent Circuit Values From Laplace Description Using Pspice Software
Abstract: From the conversion methods of T-π (star-delta) for impedances circuits, the behavioral modeling of Pspice simulation program is used to obtain equivalent circuits using LAPLACE option. The conversions are verified for two types of circuits by obtaining AC values of voltages and currents at various nodes and branches using Pspice computer simulations. There are many ways of expressing Thevenin/Norton equivalent circuit parameters such as (a) as real numbers for pure …
Published in Journal of Semiconductor Devices and Circuits · Vol. 9, Issue 2, 2022 · pp. 43–58 Read article
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Bank Loan Prediction by using Logistic Regression
Abstract: In the modern era of science and technology, the banking sector is also growing very fast and a lot of people are applying for bank loans. But the bank has limited assets and can be granted to limited number of people only, so the bank must ensure that the person whom the loan is granted is eligible enough to pay it back. So, in this study, we will try to …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 2, 2021 · pp. 17–21 Read article
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Morphological Characterization of Indigenous Chickens in Silti, Dalocha, and Wulbareg Woredas of Silte Zone, South Region, Ethiopia
Abstract: A survey together with visual observation and body measurement was conducted in twelve selected farmers' kebeles of Silti, Dalocha, and Wulbareg woredas, located in the Silte zone south region of Ethiopia; to characterize the morphological characteristics of domestic indigenous chicken. Data on visual appraisal and linear body measurements were obtained from 600 matured local chickens of both sexes drawn from 120 households. Five mature chickens (aged more than 6 months) …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 11, Issue 3, 2022 · pp. 10–22 Read article
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Modeling Dispersed Count Data: Evaluating the Conway–Maxwell–Poisson Regression with COVID-19 Mortality Data
Abstract: Count data are prevalent in diverse fields such as biology, healthcare, psychology, and marketing, characterized by non-negativity and inherent heteroskedasticity, often exhibiting overdispersion or underdispersion. Traditional Poisson regression, which assumes equal mean and variance, is inadequate for such dispersed data. To address this, various generalized linear models (GLMs) and their extensions, including negative binomial (NB) and Conway–Maxwell–Poisson (CMP) regressions, are utilized. This study evaluates the performance of CMP regression compared …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 18–26 Read article
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Experimental investigation on non-linearity in understanding large scale fires
Abstract: Fire doesn't spread in a uniform manner it has an unpredictable nature. The pervasive uncertainty associated with large-scale fires has resulted in the irreparable loss of invaluable human lives, natural resources, critical infrastructure, and systems. To combat this significant issue, substantial financial investments are made annually in research endeavours aimed at preventing and mitigating such devastating incidents. These dedicated research efforts strive to develop innovative strategies, cutting-edge technologies, and robust …
Published in Journal of Industrial Safety Engineering · Vol. 10, Issue 1, 2023 · pp. 27–40 Read article
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Design and Evaluation of Dynamic Testing in Object Oriented Programming Through Computational Techniques
Abstract: Software testing is one of the most labour-intensive and expensive phase of the software development life cycle. It is an important and valuable part of it. Software testing successfulness is always determined on the basis of generated test cases and their prioritization. So, it consumes more effort, time and cost. Today, a numerous search-based optimization techniques are available for better accuracy in testing. The aim of this paper is to …
Published in Journal of Advances in Shell Programming · Vol. 2, Issue 1, 2015 · pp. 1–6 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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Quantification and Forecasting of Plastic waste in Gorakhpur city, India
Abstract: Plastic pollution is one of the biggest environmental threats faced by human society, especially in cities like Gorakhpur, which have minimal resources for waste management but a very high amount of waste that keeps on increasing day by day. The purpose of this research is to determine the total amount of plastic waste (PW) generated in Gorakhpur city and forecast plastic waste generation. The snowball sampling method was used for …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 946–962 Read article