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352 articles for “log data”
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Improved Performance by Using k-means Clustering in Vehicular Ad Hoc Network
Abstract: AbstractVANETs are formed by applying the principles of MANETs, in which all node, i.e., vehicles can pursue traffic law with high speed. VANETs support two types of communication: vehicle - to- vehicle (V2V) and vehicle to-infrastructure (V2I). Vehicles communicate to RSU for the exchange of keys for the security purpose and RSU communicate to Authentication Server (AS) for the formation of secret keys. But in existing work they perform nonsymmetric …
Published in Journal of Communication Engineering & Systems · Vol. 7, Issue 1, 2017 · pp. 17–24 Read article
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Mothers Practice and Associated Factors on Kangaroo Mother Care, in Mekelle City Hospitals Tigray, North Ethiopia: A Cross-Sectional Survey
Abstract: Kangaroo mother care (KMC) is a special way of holding low birth weight, preterm and hypothermic babies with skin-to-skin contact between the mother and the newborn in a position like a kangaroo. Most neonatal units in the world do not has appropriate space and material to offer a comfort to mothers providing a continuous KMC. In Ethiopia, KMC has not expanded as broadly as we hoped. To assess the practice …
Published in Research and Reviews : A Journal of Immunology · Vol. 6, Issue 1, 2016 · pp. 21–31 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Prevalence of Sexual Violence and Its Associated Factors Among Female Night Time Students of Junior And Secondary Schools in Mekelle City, Northern Ethiopia, 2013
Abstract: Sexual violence refers to any sexual act directed against a person’s sexuality by any person regardless of their relationship to the victim. Sexual violence is prevalent and is a major public health and human rights problem worldwide. The problem is not different from this in Ethiopia. However, lack of data has hindered full understanding and development of appropriate interventions. The objective of the study was to assess the prevalence of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 4, Issue 2, 2015 · pp. 6–20 Read article
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Intelligent Medical Devices and Robotics in Modern Healthcare: Technological Advancements and Economic Considerations
Abstract: The integration of robots and intelligent medical devices in intensive care units (ICUs) represents a significant advancement in healthcare technology. These systems, including robotic assistants, automated monitoring tools, and AI-powered diagnostic devices, are designed to enhance patient care, streamline workflows, and reduce human error. Robots in the ICU can assist with routine tasks such as medication delivery, patient repositioning, and even basic surgeries, enabling healthcare professionals to focus on critical …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 18–27 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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Designing an Educational Mentoring Model in Line with the Professional Development of Female Primary School Teachers with a Fuzzy Logic Approach
Abstract: The teacher is one of the most important elements known to have a close relationship with students and develop their various talents. If a teacher steps into the education scene with a new, creative and well-equipped attitude, he will naturally deliver capable, creative and new-thinking students to face life wisely and solve the problems of the human world. Therefore, the main goal of this research is to design an educational …
Published in International Journal of Education Sciences · Vol. 1, Issue 1, 2024 · pp. 35–50 Read article
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Unveiling Patterns in Complexity: The Role of Simple Statistics and Fuzzy Mathematics in Data Analysis
Abstract: In this study, statistical methods must be integrated with fuzzy mathematics to solve complex data. Statistical methods offer clear, unbiased, and computationally feasible tools for analysing numerical data. whereas fuzzy mathematics excels in describing the vagueness and ambiguity of human feeling by way of linguistic variables, membership functions, and inference systems. Giving it an apparent advantage when modelling complex conditions. Hybrid frameworks offer fine-grained decision-making and resilient adaptability to real-world …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 1, 2025 · pp. 01–10 Read article
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Harnessing Hydrolgeological Parametrs: Prediction of Water Probability and Levels for Water Well Construction Using Ai-Enabled Models
Abstract: The AI-Based Decision Support System for Water Well Construction utilizes data from the National Aquifer Mapping and Management System (NAQUIM) and employs advanced AI techniques like regression analysis, decision trees, and neural networks. This system predicts crucial parameters for water well construction, including location suitability, water-bearing zone depths, and groundwater quality. By integrating large datasets such as lithology, geophysical logs, and aquifer maps provided by the Central Ground Water Board …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 16–28 Read article
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A Lightweight Cost-Sensitive Explainable Ensemble Framework for Early Heart Disease Risk Prediction
Abstract: Cardiovascular disease is still one of the leading causes of death, and hence, the early prediction of risk is a very important task in preventive medicine. Although recent studies have shown encouraging results in the application of machine learning algorithms to the prediction of heart disease, it has been noticed that most of the algorithms are more concerned with accuracy-driven optimization than the concerns of safety and false negatives. In …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Early Pregnancy Levels of Fasting Glucose, HbA1c, and Adiponectin as Predictors of Gestational Diabetes Mellitus Among Pregnant Women in Tamil Nadu, India
Abstract: Background: Gestational diabetes mellitus (GDM) is rapidly becoming a major public health issue across India, and Tamil Nadu continues to report some of the country’s highest incidence figures. Identifying women at elevated risk during the first trimester allows health workers to intervene early and improve outcomes for both mothers and babies. This research, therefore, examines whether fasting plasma glucose, glycated haemoglobin, and adiponectin measured at that initial visit can reliably …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 10–18 Read article
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Knowledge, Attitude and Practice Towards Utilization of Long-Acting Contraceptive Methods and Predictors of Utilization among Reproductive Age Group Women in Addis Ababa Public Health Centers, Ethiopia.
Abstract: Long-acting contraceptives (LACs) such as intrauterine devices and hormonal implants are among the most effective methods that prevent unintended pregnancies. The methods are more convenient to clients who want to space or limit their births. But, their utilization is still very low and there is no strong evidence about the factors contributed to the low utilization level. The present study was undertaken to assess the utilization of LAC methods and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 6, Issue 2, 2016 · pp. 6–11 Read article
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Emergency Contraceptive Use among Female Students of Aksum University, Aksum, Northern Ethiopia
Abstract: Unintended pregnancy is a public health problem among young women in developing countries like Ethiopia. Emergency contraceptives (ECs) can be used as a backup in case regular contraception is not used, misused or failed. However, little is documented about sexual experiences and EC use in highly religious areas like Aksum where sexual rights may not be exercised freely. Therefore, this study was aimed at assessing sexual experiences and EC use …
Published in Research and Reviews: A Journal of Medicine · Vol. 6, Issue 3, 2016 · pp. 9–20 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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IoT Based Smart Power Grid.
Abstract: An inefficient power grid can be affected by human mistakes, data loss, and manual circuit and logbook operation, which are all parts of how a power grid works. An IoT-based power grid is introduced to address the issue. Here, we may measure the circuit's current and voltage as well as its active (kW), apparent (kVA), and energy (kWh) powers. We can also use a computer or a mobile device to …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 13, Issue 1, 2023 · pp. 35–40 Read article
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Fault Detection in Solar PV Systems Integrated with the Power Grid: Evaluating Logistic Regression through Confusion Matrix Analysis
Abstract: This paper proposes a method for failure detection in grid-integrated solar photovoltaic (PV) systems using logistic regression and real-time sensor data. The approach effectively classifies and identifies seven distinct fault types. The developed model demonstrates a high fault identification accuracy, ranging from 93% to 96.5% across various fault types and operational conditions. By leveraging logistic regression, the system utilizes key independent variables that significantly influence the classification process. Additionally, the …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 2, 2025 · pp. 45–52 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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Array-Linked Data Structure: Introducing a Hybrid Model of Memory Management and Faster and Easier Insertion and Reallocation Procedures
Abstract: Here, I have introduced a new data structure titled “Array-Linked Data Structure”. It incorporates a hybrid model of memory allocation, introducing a new insertion procedure in an existing data structure which is faster than that for arrays. It also offers O(c) access time where c is a constant. The access time is worse than O(1) for an array but still better than that for a linked list since the index …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 1–11 Read article
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Calculation Improvement of the Clay Content in the Hydrocarbon Formation Rocks
Abstract: Natural radioactivity of reservoir rocks of oil and gas in East Baghdad field is due to not only their content of clay material, but also the existence of uranium located in the skeleton of rocks. In connection with this, for the shale content determination of reservoir rocks, it is necessary to exclude the uranium contribution from the overall intensity of the gamma radiation. The paper presents the results of a …
Published in Journal of Petroleum Engineering & Technology · Vol. 7, Issue 1, 2017 · pp. 1–3 Read article