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341 articles for “and regression analysis”
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Defining Regression Polynomials with Process Similarity Criteria
Abstract: Highly accurate monitoring and prediction is essential in detecting abnormality events and forecasting demands in supply chains. This investigation provides a computational procedure for defining polynomials that satisfy similarity criteria in the monitoring process for a polynomial of any degree. It provides an example of using algorithms to predict transient thermal processes in electronic devices. The second-degree polynomial defined with this algorithm is compared with a polynomial defined using a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 10, Issue 2, 2023 · pp. 13–20 Read article
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The Importance of Self-Care for Healthcare Professionals in North India: A Regional Analysis of Burnout, Resilience and Institutional Support
Abstract: Background: Burnout in healthcare professionals is described using the framework of Occupational Health and Resilience Theory, where self-care is an individual-level coping mechanism and institutional support is an organizational-level moderator. However, there is a lack of regional data from North India on the structural and contextual factors influencing burnout. Healthcare workers (HCWs) in North India face mounting pressures due to high patient loads, limited mental health resources, and overlapping professional …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 24–29 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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Machine Learning-Based Disease Prediction: A Comparative Analysis for Diabetes, Brain Tumor, and Parkinson's Disease
Abstract: This paper presents a web-based disease prediction system that integrates machine learning and deep learning techniques to assist in the early detection of Parkinson’s Disease, Diabetes, and Brain Tumors. By utilizing clinical data and MRI images, the platform provides rapid and interpretable predictions to support proactive health management. Logistic Regression models are applied to classify structured datasets for predicting Parkinson’s disease and Diabetes, making use of their effectiveness in binary …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 44–54 Read article
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Effect of Diarrhea at Admission on Time to Recovery in Treatment of Severe Acute Malnourished Children in Inpatient Therapeutic Feeding Program in Tigray Region, Ethiopia
Abstract: The mortality rate in inpatient settings remained unacceptably higher, 20–30% for marasmus and 50–60% for Kwashiorkor. This is due to inappropriate case management and co-morbidities mainly diarrhea. Despite, there was no study conducted to show the effect of diarrhea at admission on the length of time to recovery in the treatment of severe acute malnutrition among children aged 6–59 months and then there is little understanding about this issue. The …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 5, Issue 2, 2016 · pp. 25–40 Read article
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Machine Learning Regression Based Approach for Prediction of the Ultimate Tensile Strength of Tungsten Inert Gas Welded Joints
Abstract: Many leaders in technology education have shown that the main difference between the technical design process and the process of engineering construction analysis and efficiency [1–3]. The engineering analysis phase of the construction process is where the mathematical and scientific models principles are used to help the designer predict the design results. The engineering feasibility phase process is a systematic process that uses structural elements and conditions to allow the …
Published in Trends in Machine design · Vol. 8, Issue 2, 2021 · pp. 1–10 Read article
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Voting Classification Method for Network Traffic Prediction
Abstract: Prediction analysis (PA) is a data mining-based technique. The futuristic outcomes based on present data can be predicted using this technique. As the dataset is large and complex, network traffic classification is a big concern in prediction analysis. Three phases are included in network traffic strategies. The data collection is obtained in the first step of pre-processing, and it is analysed to delete incomplete and obsolete values. The relationship between …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 23–30 Read article
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Study on Single-Slope Solar Still for Experimental and Data-Driven Analysis for Improving Productivity with Different Basin Materials.
Abstract: This study investigates the single-slope solar still under the diurnal variation of water temperature and distillate yield under identical operating conditions. Experimental analysis was conducted to evaluate the performance enhancement through the incorporation of natural basin materials, namely hemp and sand. The water distillation process is focused on improving potable water productivity and thermal behaviour. The inclusion of hemp and sand in the basin leads to noticeable differences in productivity …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 31–46 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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Stock Market Prediction Based on News Sentiments
Abstract: AbstractIn today’s era, the count of investor is increasing day by day. For identifying the market risk and for the growth of profit, the market stock prediction is an important factor. People are using traditional theorems for predicting market behavior. Different methods are used for predicting the market share price such as support vector machine, regression, sentiments from different social websites like Twitter and Facebook, etc. which have some limitations. …
Published in Journal of Advances in Shell Programming · Vol. 4, Issue 2, 2017 · pp. 26–33 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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An Analysis on Feature Selection Method using Real Coded Genetic Algorithm (RCGA)
Abstract: The work presented in this thesis mainly focuses on the solving protein structure prediction (PSP) problem from machine learning models. The prediction of distance-to-native of protein structure is carried out using regression machine learning models with six physicochemical properties. The objective is to predict the distance to the native like structure in the absence of its true native state and report how far a structure is from its true native. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 5, Issue 1, 2018 · pp. 23–30 Read article
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ML-Driven Optimization Framework for the Analysis, Design, and Development of Efficient Wireless Power Transfer Systems for EV Charging
Abstract: The fast uptake of electric vehicles (EVs) has heightened the necessity of effective, dependable and convenient charging systems. The Wireless Power Transfer (WPT) systems can be taken as a potential solution as they allow charging cells without contact, without any risks, and without any overcrowding; the efficiency of the system is strongly influenced by the alignment of coils, the fluctuations of air-gaps, the conditions of the loads, and geometrical arrangements …
Published in International Journal of Manufacturing and Production Engineering · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Machine Learning Techniques for Early Detection of Heart Disease
Abstract: Cases of heart disease are increasing rapidly, thus it's important and concerning to be aware of any potential ailment beforehand. This diagnosis is a difficult task that must be completed fast and precisely. The primary goal of this study is to determine which patient, based on different medical features, has a higher chance of having heart disease. We created a heart disease prediction algorithm based on the patient's medical history …
Published in Journal of Microelectronics and Solid State Devices · Vol. 10, Issue 3, 2023 · pp. 16–21 Read article
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Magnitude of Premarital Sex and Associated Factors among Preparatory School Students in Alamata Town, North Ethiopia, 2014
Abstract: Worldwide adolescents, both boys and girls, are physically mature earlier and the age at which people marry is rising. These leave a widening of gap time during which adolescents can potentially engage in unprotected and unsafe premarital sex. The purpose of this study was to assess the magnitude of premarital sex and associated factors among Alamata preparatory school students, Northern Ethiopia. A school-based, cross-sectional study was conducted in Alamata town …
Published in Research and Reviews: A Journal of Health Professions · Vol. 6, Issue 2, 2016 · pp. 12–20 Read article
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Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
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Experimental Assessment and Statistical Argument of Al-Si/CSA/MoS2 Hybrid Composites for Mechanical and Tribological Characteristics
Abstract: To augment the mechanical and tribological properties of Al-Si matrix composites complement with molybdenum disulphide (MoS₂) and coconut shell ash (CSA), a mixed experimental and Face-Centered Composite (FCC)strategy was employed. A liquid metallurgical method called stir casting was used to create hybrid composites with 5–15 wt.% CSA and 1–3 wt.% MoS₂. A FCC experimental design with thirty runs was used to thoroughly evaluate the materials. This design allowed for the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 792–802 Read article
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Quantitative Structure Activity Relationship Studies of Some New 4-Thiazolidinone Derivatives as Antimicrobial Agents
Abstract: In the present study, quantitative structure activity relationship (QSAR) studies have beenperformed on series of 24 compounds of 4-thiazolidinone derivatives with antimicrobialactivity using Chemoffice version 8.0 software. The QSAR models have been developed byusing multiple linear regressions in order to identify descriptors, which are actually focusingtowards the biological activity. Leave one out (LOO) method was employed in crossvalidation analysis to validate the developed model. The best predictive QSAR model derived,had …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 8, Issue 2, 2017 · pp. 1–3 Read article
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3D QSAR Studies of 2,3-Disubstituted Quinazolin Phenyl Acetic Acid Derivatives as Antimicrobial Agents
Abstract: Quantitative structure activity relationship (QSAR) studies have been performed on series of31 compounds of 2,3-disubstituted quinazolin phenyl acetic acid derivatives withantimicrobial activity using Chemoffice version 8.0 software. The QSAR models have beendeveloped by using multiple linear regressions in order to identify descriptors, which areactually focusing towards the biological activity. Leave one out (LOO) method was employedin cross validation analysis to validate the developed model. The best predictive QSAR modelderived, had …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 8, Issue 2, 2017 · pp. 4–7 Read article