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776 articles for “data evaluation”
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Sentiment Analysis of E-Commerce Reviews using Machine Learning
Abstract: In e-commerce, sentiment pertains to the emotional responses, opinions, or perceptions that customers have about their online shopping experiences, including factors like product quality, service, and various processes such as ordering, shipping, and customer support. Sentiment analysis, which involves machine learning techniques, plays a crucial role in deciphering these sentiments. By using sentiment analysis, companies can obtain valuable insights from customer feedback from diverse online sources, including social media, surveys, …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 25–37 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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AI-Based Intelligent Traffic Signal Management System: A Review
Abstract: Traffic congestion is a growing problem in urban areas worldwide, leading to economic losses, increased pollution, and commuter frustration. Traditional traffic management systems rely on fixed timing cycles and lack adaptability to real-time traffic conditions. Intelligent traffic light control systems based on artificial intelligence (AI) have become a viable substitute for traditional techniques. These systems are able to evaluate large volumes of traffic data in real time, identify patterns, and …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 1–5 Read article
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Review on Automatic Irrigation System
Abstract: The Automatic Irrigation System is a contemporary technological innovation aimed at improving water efficiency in farming and landscaping uses. This system guarantees that water reaches plants according to real-time data including soil moisture, weather conditions, and set irrigation schedules by combining sensors, microcontrollers, and automated valves or pumps. The main objective of an automated irrigation system is to increase water efficiency, decrease waste, and boost crop production while limiting human …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Blockchain-Enabled Secure Data Sharing in Mobile IoT Networks
Abstract: The rapid proliferation of mobile Internet of Things (IoT) devices has resulted in an exponential increase in data generation, storage, and sharing, which poses significant challenges related to security, privacy, integrity, and trustworthiness. Traditional centralized architectures for IoT data exchange are inherently vulnerable to single points of failure, unauthorized access, data tampering, and limitations in scalability. Blockchain technology, with its decentralized ledger structure, cryptographic integrity, and consensus mechanisms, provides a …
Published in International Journal of Mobile Computing Technology · Vol. 4, Issue 1, 2026 · pp. 38–44 Read article
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An Analytical Study on Cybersecurity Threats and AI-Driven Mitigation Strategies in Next-Generation Smart Grids
Abstract: The increasing adoption of next-generation smart grids has introduced significant cybersecurity challenges due to their reliance on interconnected digital infrastructures and IoT-based control mechanisms. This study aims to analyze cybersecurity threats in smart grids and explore AI-driven mitigation strategies to enhance grid security and resilience. The research examines common cyber threats such as malware attacks, denial-of-service (DoS), data breaches, and insider threats while evaluating the effectiveness of AI-based solutions, including …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 16–25 Read article
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Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration
Abstract: The “Intelligent Traffic Monitoring: YOLO v8 and CSV Data Integration” project is a cutting-edge solution for intelligent traffic monitoring, with YOLO v8 (You Only Look Once) serving as the fundamental technology for real-time vehicle detection and traffic counting on roads. In addition to these features, the system interfaces effortlessly with data pipelines and machine learning projects by storing gathered traffic data in CSV (Comma-Separated Values) format. The major goal of …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 20–24 Read article
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Effectiveness of Structured Teaching on Immunization Knowledge and Attitude Among Mothers of Children Under-5 years of Age at Bal Mahila Chikitsalaya, Lucknow
Abstract: This section offers a thorough overview of the study's background, explaining the significance of vaccination, the variables affecting vaccination coverage, the role mothers play in the decision-making process regarding vaccinations, and the necessity of focused interventions to improve immunization uptake among children under five. As a fundamental component of preventive healthcare, immunization shields both individuals and communities from a variety of infectious diseases. In order to comprehensively assess changes in …
Published in International Journal of Children · Vol. 1, Issue 1, 2024 · pp. 5–22 Read article
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Structural Health Monitoring of Polypropylene Fiber- Reinforced Composite Using Accelerometer Sensors
Abstract: This study explores the application of accelerometer sensors for structural health monitoring (SHM) in evaluating the performance of polypropylene fiber-reinforced composites (PFRC). Incorporating polypropylene fibers into concrete enhances its structural integrity and durability. However, accurately assessing PFRC behavior under various conditions is crucial for its practical application in construction. This research employs advanced accelerometer sensor technology for real-time monitoring and assessment of PFRC performance. Experimental investigations captured and analyzed the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 621–634 Read article
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Smart Soil Health Monitoring: Leveraging Sensors and Big Data to Optimize Crop Growth
Abstract: The increasing demand for sustainable farming practices has necessitated the development of innovative technologies that improve crop productivity while reducing environmental harm. This study investigates the combination of internet of things (IoT) sensors and big data analytics for real-time soil health monitoring, with the aim of maximizing crop yield and efficient resource management. This allows for informed decision-making in key agricultural practices, such as fertilization, irrigation, and crop rotation, based …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 36–43 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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A Study to Assess the Effectiveness of Self-Instructional Module Regarding Common Psychological Problems of Postpartum Psychosis and Its Management Among Trained Staff Nurses of Netaji Subhash Chandra Bose Medical College, Jabalpur
Abstract: A quasi-experimental study employing a one-group pretest and posttest design was undertaken to evaluate the impact of a self-instructional module on staff nurses’ knowledge of postpartum psychosis and its management. The research was conducted at Netaji Subhash Chandra Bose Medical College Hospital and included 60 trained staff nurses selected through a non-probability convenience sampling technique. Data were collected through a structured questionnaire designed to assess knowledge levels. The reliability of …
Published in International Journal of Women's Health Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 24–28 Read article
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To Assess the Knowledge and Practices Regarding Postnatal Assessment of Women Among Nurses Working in Gynaecology Units of Selected Hospitals of District Ludhiana, Punjab: A Descriptive Study
Abstract: This study was done to evaluate nurses' postnatal assessment of women's knowledge and practices. Postnatal assessment is a vital part of postnatal care in the fourth stage of labor for the women as it confirms the mother’s recovery from the effects of pregnancy, labor, and delivery. It provides an opportunity for the nurses to prevent many life-threatening complications and promote health status during this period. A descriptive research design was …
Published in International Journal of Midwifery Nursing And Practices · Vol. 1, Issue 1, 2023 · pp. 17–24 Read article
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Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm
Abstract: Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner's consent and with no intention of paying for the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 21–30 Read article
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Enhancing the Direct Assessment Method for ABET Accreditation: A Proposal for a Lightweight, Comprehensive, Precise, and Informative Approach
Abstract: This study introduces a new method aimed at improving the direct assessment technique used for assessing students in the context of ABET accreditation. The traditional direct assessment method has long been utilized for ABET accreditation, involving steps such as goal identification, assessment planning, selection of assessment instruments, data collection and analysis, interpretation and evaluation, and feedback and improvement. While this approach has served as a valuable tool for evaluating student …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 12–27 Read article