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21 articles for “LR”
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Radon Estimation in Some Lakes and Fraser River Water of British Columbia, Canada using LR-115 Type II Alpha Track Detector
Abstract: Radon activity levels were measured in the five Lakes and Fraser River water samples collected from different locations of British Columbia in Canada. The purpose of this study was to compare Radon activity levels in all six sources of water. Water was collected in air tight bottles and stored for two weeks before investigation. LR-115 Type II nuclear track detectors of 1.2 cm2 were used for recording radon alpha tracks. …
Published in Research and Reviews: A Journal of Toxicology 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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SmartTrack : Advanced Attendence System using LR RFID
Abstract: This project presents the design and implementation of a long-range RFID attendance system aimed at transforming how educational institutions track attendance by making the process faster, more accurate, and completely contactless. Tradi- tional methods, whether manual roll calls or short-range RFID scanners, often interrupt class routines and leave room for errors or proxy attendance. To address these issues, the proposed system integrates long-range RFID readers, beam sensors, and ESP32 microcontrollers …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 1, 2026 Read article
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Presence of a Bulk Viscous Universe within f(R, T) Gravity
Abstract: This paper offers a comprehensive analysis of a bulk viscous universe in the context of f(R, T) gravity, where (R) signifies the Ricci scalar and (T) represents the trace of the energy-momentum tensor. The primary objective of our work is to get explicit solutions to the modified field equations by using a power-law scale factor representation. With this method, we have obtained functions of cosmic time and redshift for the …
Published in International Journal of Universe · Vol. 1, Issue 1, 2025 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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Seismic Analysis of Base Isolation for Protection of Rural Building of Different Shapes
Abstract: India is a developing country, more than 50% of Indian population lives in unreinforced masonry structures. Masonry structures are vulnerable to seismic loading and load acting in it’s out of plane, hence performs poorly and sometimes leads to sudden collapse. Collapse of structure not only damages public property but also costs the lives of people. Base isolation techniques for these types of structure can be proven to be beneficial, in …
Published in Journal of Structural Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 32–43 Read article
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Machine Learning-Based Approach for Heart Disease Prediction
Abstract: Heart disease is a significant global health challenge, with early diagnosis and prediction being essential for reducing mortality rates. Machine Learning (ML), an efficiently developing field within Artificial Intelligence, provides innovative methods for analyzing complex clinical data to predict heart disease. This review examines the basic machine learning techniques, data, and metrics used in cardiovascular disease prediction. It explores the role of supervised learning, such as decision trees and logistic …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 64–73 Read article
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The Burden of Empirical Therapy: Analyzing the Predominance of Broad-Spectrum Antibiotic Usage in Lower Respiratory Tract Infections
Abstract: Lower respiratory tract infections (LRTIs) remain one of the leading causes of morbidity and hospitalization worldwide, particularly among older adults, immunocompromised individuals, and patients with chronic respiratory disorders. These infections include conditions such as community-acquired pneumonia, hospital-acquired pneumonia, bronchitis, and acute infective exacerbations of chronic lung disease, all of which often require rapid clinical intervention. Because microbiological confirmation of the causative pathogen frequently takes 48–72 hours, clinicians generally initiate empirical …
Published in International Journal of Antibiotics · Vol. 3, Issue 2, 2026 Read article
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Comparative Analysis of using Rubber isolator and Friction isolator in G+8 Building by SAP 2000
Abstract: Base isolation technique has become most popular that improves resistant quality during a seismic earthquake. These bases seclude moves under high pressure and they soak up an earth tremor smash by minimizing oscillating and trembling of ground. Adaptive base solitude system includes the separation system is Lead Rubber Bearing, Friction Isolators, channel Method, Laminated Rubber Bearing. Base separation is the broadly accepted seismic protected skeleton employed in any edifice in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 479–487 Read article
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Building a Modern Land Registration System: Leveraging Node.js and React.js for Efficiency, Security and Scalability
Abstract: Land registration systems are critical for safeguarding property ownership and enabling efficient real estate transactions. However, traditional systems often suffer from inefficiencies, including lengthy processing times, susceptibility to fraud, and limited accessibility. This study proposes a modernized Land Registration System (LRS) leveraging Node.js for backend development and React.js for frontend design to address these challenges. The system integrates real-time data processing, automated document verification, and role-based access control (RBAC) to …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 1–6 Read article
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Saccharomyces Cerevisiae and Pichia Pastoris Optimize NH4NO3 by 50 % in Solanum Lycopersicum Preventing N2O Release.
Abstract: In agriculture, the unregulated application of NH4NO3 for healthy growth of Solanum lycopersicum is associated in the soil with the denitrification of free NO3- (nitrate), with an increase in N2O, a greenhouse gas, that contributes to global warming, loss of soil fertility. An ecological option to avoid denitrification that releases N2O as other environmental problems is to inoculate S. lycopersicum seeds with endophytic yeasts that promote plant growth, such as …
Published in International Journal of Pollution: Prevention & Control · Vol. 2, Issue 1, 2024 · pp. 7–13 Read article
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Data Handling Algorithms for the Healthcare System for the Prediction of Diabetes in Health Data Science (HDS): A Review Report
Abstract: In recent years, diabetes has become the biggest disease in different countries around the world. This disease is caused by adulteration in food ingredients, unhealthy food habits, a lack of physical exercise, and changing the lifestyle every time without a routine chart. The main objective of this review paper is to provide a proper understanding of the machine learning algorithm used in the healthcare system to handle diabetic patients' data. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Evaluation of Machine Learning Classifiers for Sentiment Analysis
Abstract: Sentiment in social media refers to users’ emotions and opinions through their posts and interactions. Sentiment analysis (SA) refers to relating and classifying the sentiments expressed as engagement and interactions between users. When analyzed, tweets frequently produce a large source of clustered data. These data help determine people’s opinions about a variety of motifs. Thus, this study presents an Automated Machine Learning (ML) Sentiment Analysis Model to detect media sentiment. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 141–154 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Application of B-trees for Design of Optimal Page Replacement Technique in Modern Operating Systems
Abstract: Algorithms related to replacing the memory pages in operating systems are critical components of modern operating systems that manage virtual memory efficiently. Current algorithms such as LRU (Least Recently Used), Clock algorithms as well as FIFO (First-In-First-Out), often struggle with the increasing demands of contemporary applications and larger memory hierarchies. This research work proposes a novel approach utilizing B-tree data structures to design an optimal page replacement technique. The proposed …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 23–30 Read article
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AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article