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143 articles for “Data Cleaning”
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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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A Supervised Learning Approach for Toxic Comment Detection on Social Media Platforms
Abstract: Nowadays everyone uses social media platforms like X (formerly Twitter), Instagram, Facebook, etc. for various purposes. With the help of this, we share our opinions, ideas, and feelings. Generally, the datasets obtained from the internet are constructive; however, there is a significant proportion of toxic ones. The datasets are filtered to remove noise, and noise is removed in post-processing. The study initiates with the upload and preprocessing of a toxic …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 2, 2024 · pp. 7–14 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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HBsAg Prevalence and Determinant Risk Factors among Voluntary Counseling and Testing Clients Visiting Gondar Health Center, Northwest Ethiopia
Abstract: Globally, an astounding number of people are infected with HBV, HCV and HIV. Due to shared routes of transmission, HBV and human immunodeficiency virus co-infection is common and is an emerging concern in the clinical management of patients because of increased mortality, accelerated hepatic disease progression, and the frequent hepatotoxicity caused by hepatitis B virus. The aim of this study was to assess the prevalence and risk factors of HBsAg …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 5, Issue 2, 2015 · pp. 15–20 Read article
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Analysis of World Population Growth Using Python
Abstract: In this research work, we studied data analysis using the Python programming language. The fundamental steps in data analysis, such as cleansing, converting, and modelling of data is briefly explained in this study. In order to come up with good results, data analysis is required. Python has been used by us for data analysis. This language is interactive, interpreted, and follows an object-oriented programming paradigm. It is open source and …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 15–20 Read article
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Determinants of Short Inter-Birth Interval among Child Bearing Age Women in Mekelle City, Northern Ethiopia: Community Based Case Control Study
Abstract: Background: In Ethiopia, where there is high maternal mortality and fertility rate, enhancing optimal inter-birth interval is one of the key strategies to promote the health status of mothers and their children. The purpose of this study is therefore, to understand the determinants for having short inter-birth interval among women in child bearing age. Methods: This unmatched case-control study involved 330 (110 cases and 220 controls) women in child bearing …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 7, Issue 2, 2018 · pp. 6–20 Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation Read article
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IoT and Autonomous RC Boats for Water Quality Assessment: Trends, Challenges, and Future Prospects
Abstract: Nowadays the application of Internet of things (IoT) increasing in many applications like drone, remote control vehicles, electrical vehicle, etc. In this paper we proposed a way to check quality of water present in vast water bodies by Remote Controlled (RC) Boat. This RC environmental monitor boat collects water quality data and sends it online via the Internet of Things. So that we maintain the water by clean from received …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 1, 2025 · pp. 13–21 Read article
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Machine Learning Driven Mobile Price Prediction Using Feature Selection and Parameter Optimization
Abstract: Machine learning calculations are utilized in many fields like money, training, industry, medication, and online business. Machine learning calculations show execution contrasts relying upon the dataset and handling steps. Picking the right calculation, preprocessing and post-handling techniques have incredible significance in accomplishing great outcomes. The Random Forest classifier, K-nearest neighbor classifier, and support vector machine methods are evaluated to forecast mobile phone price categories. The “prediction” dataset which is taken …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 18–25 Read article
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Carbon-Aware Autonomous AI Systems: Reinforcement Learning for Sustainable Cloud and Edge Computing
Abstract: The field of communication and information technology is expanding quickly. Because of this, a significant amount of carbon emissions are produced by cloud data centres and edge computing nodes. In fact they are now responsible for 3 to 4 percent of the worlds total greenhouse gas emissions. Most of the time people who manage these resources focus on how they are working and how quickly they can get things done.. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 2, 2026 Read article
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Multiple Disease Prediction Using Machine Learning Algorithms
Abstract: The incorporation of machine learning algorithms into healthcare has transformed disease prediction and diagnosis. This research introduces a method for predicting various diseases using machine learning techniques. A comprehensive dataset, consisting of patient records, medical histories, and key disease-related features, was utilized to build predictive models. Data preprocessing methods, including feature selection and normalization, were implemented to clean and prepare the dataset. Several machine learning algorithms, such as Decision Trees, …
Published in Research and Reviews : A Journal of Immunology · Vol. 14, Issue 3, 2024 · pp. 34–38 Read article
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A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
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Predictive Modeling and Optimization of Tensile and Flexural Strength in FDM 3D Printing Using Decision Trees and Bayesian Optimization.
Abstract: This research investigates predictive modelling and optimization technique for the tensile and flexural strength of PlA (Poly Lactic Acid) in Fused Deposition Modelling (FDM) 3D printing. Employing Decision Trees and Bayesian Optimization enhances comprehension and control of 3D printing process. Precise model predicts PLA material properties based on input parameters. Methodology involves rigorous data preprocessing, encompassing, cleaning, transformation, and normalization. Hyperparameter optimization via grid search systematically explores configurations, optimizing model …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 203–214 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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Determinants of Caesarean Delivery in Ayder Referral Hospital, Mekelle, Tigray, Ethiopia 2015: A Case Control Study
Abstract: Caesarean delivery rates have been increasing around the world from time to time, with current rates in developing countries comparable to other industrialized nations. International concern over such increases has prompted the World Health Organization to suggest that caesarean section rates should not exceed 15%. A study conducted in Ayder Referral Hospital indicated that the rate of caesarean section was 21.90%. The aim of the study was to assess the …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 5, Issue 1, 2016 · pp. 52–59 Read article
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Assessment of Modern Contraceptive Utilization and Factors Associated Among Married Women of Reproductive Age Group at Mekelle City, North Ethiopia in August 2013
Abstract: Ethiopia is the second most populous nation in Africa. Its population has increased nearly seven times from 11.8 million at the beginning of the 20th century to about 80 million today. Where, only 27% in reproductive age groups are currently using modern contraceptive and number of factors could affect for effective use of modern contraception. But, still evidence showed that, as there is high maternal mortality and unwanted pregnancy. However, …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 5, Issue 2, 2015 · pp. 1–23 Read article
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Patterns and Risk Factors of Gestational Diabetes Mellitus among Mothers Who Visited Antenatal Clinics in Public Health Centers of Mekelle City, Tigray, Ethiopia, 2015
Abstract: Gestational diabetes mellitus is associated with significant morbidity in the short and long-term, for both mother and offspring. It is now well established that women with a history of GDM are at a significant increased risk of developing type-2 diabetes, later in life. There were limited studies conducted on pattern and risk factors of gestational diabetes mellitus in Tigray region. The aim of this study is to assess patterns and …
Published in Research and Reviews : Journal of Surgery · Vol. 5, Issue 2, 2016 · pp. 12–20 Read article
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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 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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Monitoring of Unauthorized Identity and Access Behaviour for Outsourced Data in Cloud Environment
Abstract: The outsourcing of data is a significant challenge in the modern cloud computing ecosystem when it comes to tracking unauthorized identification and access behaviour. In order to overcome this issue, this research suggests a thorough method for reliable anomaly detection in cloud systems. Improving data security and offering a trustworthy monitoring system are the two main goals. The suggested approach proceeds methodically, gathering information from several sources such as user …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 9–19 Read article