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225 articles for “linearity of data”
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Effect of Various Process Parameters on MRR in Manual Air Plasma Arc Cutting of AISI 1017 Mild Steel using ANN
Abstract: As per recent industrial surveys it is investigated that manufacturing companies define the quality of thermal cutting process by the dimension of work material and cutting surface appearance. Therefore, the surface roughness and material removal rate (MRR) are primarily considered. In this work the effect of three input parameters air pressure (P), cutting current (I) and cutting velocity (v) on material removal rate (MRR) is obtained experimentally. An artificial neural …
Published in Journal of Mechatronics and Automation · Vol. 2, Issue 2, 2015 · pp. 8–14 Read article
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Utilization of Statistical Learning Algorithms for Prediction of Elastic Modulus of Jointed Rock Mass
Abstract: This study uses two statistical learning algorithms for the prediction of elastic modulus (Ej) of jointed rockmass. The first algorithm uses support vector machine (SVM) that is firmly based on the theory of statisticallearning and uses regression technique by introducing -insensitive loss functionhas been adopted. Thesecond algorithm uses relevance vector machine (RVM). It is based on a Bayesian formulation of a linearmodel with an appropriate prior that results in a …
Published in Recent Trends in Civil Engineering & Technology · Vol. 1, Issue 1-3, 2011 · pp. 81–94 Read article
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Assessing Urban Land Utilization Using Geographical Information System
Abstract: In all urban centers of the Tigray region, Ethiopia in general, there is inefficient urban land utilization. Inefficient buildable urban land development and management is manifested in the form of vacant, partially utilized and underutilized lands. Most of these lands are exposed to urban sprawl, squatting and land speculation. Moreover, there is inadequate infrastructure provision, under regulation, and shortage of buildable lands; speculation and tenure insecurity are the problems of …
Published in Journal of Remote Sensing & GIS · Vol. 10, Issue 1, 2019 · pp. 9–23 Read article
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Procedure for Conventional Facial Emotion Detection Algorithms Based on Machine Learning
Abstract: Researchers in psychology, computer science, linguistics, neurology, and allied fields have become more interested in a human-computer interface system for autonomous face recognition or facial expression recognition. This study has recommended an Automatic Facial Expression Recognition System (AFERS). The proposed methodology consists of face detection, feature extraction, and facial expression identification processes. The initial phases of the face detection procedure include skin color identification using the YCbCr color model, illumination …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 07–13 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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A New Evaluation Index for Application of Machine Learning Algorithms to Determine Trust in Skewed Social Media Data
Abstract: In this paper we study the problem of accuracy paradox which arises on the application of machine learning algorithms for inference of trust in skewed social media data. Skewness is defined as the under representation of one class over another in a binary classification problem. We achieved our purpose of identifying the accuracy paradox problem in various algorithms by identifying a new evaluation index called predictive index. The dataset used …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 49–57 Read article
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Comparative Study of Linear Regression Techniques for Analyzing THPP of Solar Parabolic Trough Receiver with Twisted Tape Inserts using Machine Learning.
Abstract: This study presents a comparative analysis of four different linear regression techniques for predicting the THPP of a solar parabolic trough receiver with twisted tape inserts. The four techniques analyzed are: ordinary linear regression, interaction linear regression, robust linear regression, and stepwise linear regression. The study is aimed at determining the most suitable technique for predicting the heat transfer characteristics of the solar parabolic trough receiver with twisted tape inserts. …
Published in Journal of Experimental & Applied Mechanics · Vol. 13, Issue 3, 2022 · pp. 39–47 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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Variation in Ozone at Night in Barrow, Alaska, during Different seasons, and its Relationship to Methane at Different Pressures
Abstract: The study is focus on the investigation of the night-time seasonal variability of ozone (O₃) at Barrow, Alaska, and also it examines its association with methane (CH₄) concentrations at different pressure levels along with solar flux variations on the basis of eighteen years (2003–2020) of observational data, including ground-based ozone measurements, satellite-derived methane data at 100, 200, 300, 400, and 500 hPa, and solar flux (F10.7) values. For finding the …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 44–53 Read article
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Network Traffic Analysis Using Machine Learning
Abstract: Network traffic analysis and prediction has applications in a variety of fields and has recently attracted a considerable number of studies. To find numerous issues with current computer network applications, various sorts of studies are carried out and reported. A proactive strategy to guarantee safe, dependable, and high-quality network communications is network traffic analysis and prediction. For network traffic analysis, several methods, including data mining and neural network-based methods, are …
Published in Current Trends in Signal Processing · Vol. 12, Issue 3, 2022 · pp. 17–23 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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Enhance the Thermal Performance and Fluid Flow Behavior in Micro-Tube Heat Exchangers with Variable Fluid Properties for Cooling Applications
Abstract: This paper focus on the substantial effects of fluid property changes and phase change events, this study provides a comprehensive transient assessment of the heat exchanger's thermal performance and fluid flow behaviour for cooling and dehumidification applications. In response to a step-change perturbation, a dynamic model was created and co-simulated to describe the moist air (shell-side) and the two-phase refrigerant (tube-side), as well as their non-linear interactions. The significant correlation …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 2, 2026 Read article
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MEASUREMENT OF FARM EFFICIENCY IN AGRICULTURAL SECTOR OF INDIA:A STUDY
Abstract: While the non-parametric production function is based on linear programming, the parametric production function is estimated using stochastic frontier analysis (SFA). The efficiency is assessed using a non-parametric technique known as Data Envelopment Analysis (DEA) (Charnes, Cooper, & Rhodes, 1978).. The primary benefit of the DEA technique is that it circumvents certain drawbacks of the parametric approach by requiring simply a little portion of a priori assumptions about the functional …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 13, Issue 1, 2024 Read article
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QSAR Modeling Techniques A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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Parallel Greedy Approach for Phylogenetic Tree Construction in the Context of Marine Species
Abstract: The rebuilding of phylogenetic trees for marine species shows major computing problems because of the massive genomic data and the huge biodiversity inherent in ocean ecosystems. Traditional phylogenetic methods are accurate but become more expensive when they are processing with thousands of marine taxa parallelly. This article shows a critical analysis of parallel greedy algorithms as an adaptable solution for large-scale marine phylogenetics. It examines the main principles of greedy …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 33–45 Read article
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On the Relationship between Equivalent Potential Temperature (theta-e) and Convective Rain over Nigeria and Togo
Abstract: Convective precipitation is a key feature of West Africa's climate, driven by the West African monsoon system. Accurate forecasting of convective storms is challenging but essential for disaster mitigation in the region. This study investigates the ability of using equivalent potential temperature (theta-e) for predicting convective rainfall events in West Africa. Theta-e combines the thermodynamic effects of moisture and temperature to represent total energy available for convection. Daily rainfall and …
Published in International Journal of Atmosphere · Vol. 3, Issue 1, 2026 · pp. 26–43 Read article
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Mathematical modelling of Thrust profile and Kinematic parameters of Launch abort system
Abstract: The paper discusses a mathematical approach for analysis of thrust and related kinematic parameters produced by abort/escape motors of Launch abort system (LAS) during the initial seconds of abort sequence. The profile is generated applying simple numerical technique to the equations of thrust and motion during this non-linear process. Thrust value peaks during this phase, making it crucial for safety of LAS and the crew in particular. Computations involving data …
Published in Journal of Aerospace Engineering & Technology · Vol. 11, Issue 1, 2021 · pp. 33–47 Read article
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Robust Regression Models for Identifying Outliers in Medical Data
Abstract: Before applying any multivariate statistical analysis, it is important to determine whether outliers are present in the dataset. In regression analysis, the presence of outliers in the dataset can strongly mislead the classical least squares estimator and lead to unreliable results. In this paper, we prove the minimum covariance determinant estimator, which is commonly applied in a robust statistic to estimate location parameters and multivariate scales. These ideas can be …
Published in Research & Reviews : Journal of Statistics · Vol. 7, Issue 1, 2018 · pp. 69s–76s 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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Polarimetric Scattering Parameter Products of ALOS PALSAR for Forest Biomass Assessment
Abstract: One of the prime factors in the global carbon budget is forest biomass. Synthetic aperture radar polarimetry finds a useful application in remote sensing of forests as it can help with the assessment of forest structure and above-ground forest biomass. Pauli and H/A/alpha decomposition techniques are applied on the dual polarimetric L-Band ALOS PALSAR data. Relationship between ground biomass and corresponding polarimetric scattering parameter (PSP) products is investigated and a …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 5, Issue 1, 2016 · pp. 1–9 Read article