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143 articles for “Data Cleaning”
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Survey of Data Cleaning and Image Recognition using Neural Networks
Abstract: AbstractThis paper reviews the existing developments of data cl eaning and image recognition using neural networks At present most of the work in image recognition is done by using more than one method. Neural networks t ake the advantage a nd show good improvement in recognition of images In t his work, the authors hav e discusse d their advantages over traditional methods.Keywords: Data cleaning, image recognition, data transformation, artificial …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 1, 2014 · pp. 30–36 Read article
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Streamlining Data Quality: A Conceptual Model and Excel-based Tool for Email Duplicate Removal
Abstract: In the realm of data management, ensuring data quality is paramount for meaningful analysis and decision making. This research paper presents a novel conceptual model and practical tool designed to address the challenge of removing duplicate entries from datasets containing email IDs. The proposed mathematical model for duplicate removal is meticulously developed and subsequently implemented in Microsoft Excel, leveraging Visual Basic for Applications. The Excel interface is enhanced with user-friendly …
Published in Journal of Advanced Database Management & Systems · Vol. 10, Issue 3, 2023 · pp. 41–59 Read article
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Attack Detection and Analysis in Virtual Wireless Networks using Mininet-WiFi, CIC Flowmeter, Wireshark, and Machine Learning
Abstract: Mininet-WiFi is a powerful tool for creating virtual wireless network environments to test various networking scenarios. However, attacks like Distributed Denial of Service (DDOS) attacks can still affect these simulated networks. A CIC flowmeter can be used to monitor network traffic and Wireshark can be used to record and analyse network data in real-time to detect and analyse such assaults. However, the data obtained from these tools may be noisy, …
Published in Journal of Operating Systems Development & Trends · Vol. 10, Issue 1, 2023 · pp. 34–45 Read article
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A study on Parametric and Non-Parametric Statistical Tools
Abstract: This research report provides a brief overview of the most recent research techniques. The field of the research process has seen a resurgence of attention due to recent advancements in academia. Professors, Ph.D. candidates, researchers, investigative officers, and university students comprise the demographic of this research article. The article will become an essential part of your research papers, projects, and reports for citations due to future obligations. This study is …
Published in Journal of Production Research & Management · Vol. 16, Issue 1, 2026 · pp. 10–31 Read article
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An Implementation of Extracting Data and Mining Extracted Data from Web Pages
Abstract: Web contains various information of particular object, which could be relevant as well as non-relevant are called as data records. It is necessary to extract relevant information from web pages. Web data extraction is the system which is used for extracting data from various web pages. Data present on web pages are in un-structured format. In the process of data extraction, we convert un-structured data into structured format. This paper …
Published in Journal of Advances in Shell Programming · Vol. 1, Issue 1, 2014 · pp. 9–12 Read article
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Analysis of Various Diabetes Prediction Techniques Based on Machine Learning
Abstract: AbstractData mining is a method of mine from the underdone data for maintains useful information. In organize to obtain fundamental knowledge it is important to remove bulky quantity of data. This method is consist of many important components like data cleaning, data selection, data integrity, pattern evaluation with data mining engine and database with graphical user interface. Diabetes is a chronic disease that is also known as Non‐Insulin Dependent Diabetes …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 8, Issue 1, 2021 · pp. 17–22 Read article
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House Price Prediction Using Linear Regression In Machine Learning
Abstract: In the modern world, real estate is among the most important investments, particularly in a city like Chennai, which is where many people aspire to work and settle down. Due to people's high purchasing power, this will cause property prices to rise daily. When purchasing a home, buyers will consider whether or not it will yield a healthy profit margin. Hence, before spending your hard-earned money on any property, it …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 92–100 Read article
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An Enhanced Application Oriented Predictive Analytic using Optimal Deep Learning Model
Abstract: In order to presents better Predictiveanalytic models of different data using various machine learning algorithms. The data prediction is developed on various applications. These applications are facing many challenges while collecting data and data selection etc. The proposed prediction model involves several phases like (a) Data acquisition, (b) Data cleaning, (c) Data normalization, (d) Optimal Feature selection, and (e) Prediction. The optimal feature selection will be accomplished by a new …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 7, Issue 2, 2020 · pp. 5–10 Read article
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Animal Species Prediction Using Deep Learning
Abstract: In the face of escalating biodiversity loss, effective monitoring of animal species is critical for conservation efforts. This study presents a deep learning approach for species detection and a multimodal feature identification technique for animals vulnerable to poaching. The suggested prediction system recognizes objects automatically by the application of deep learning techniques to detect objects and then recognize them by using computer vision techniques, and it is triggered when an …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 14–22 Read article
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Assessment of Knowledge, Attitude, Practice and Associated Factors of Emergency Contraceptive Pills among Female Youths in Mekelle City, Tigray Region, North Ethiopia
Abstract: For girls and young women aged 15–19, pregnancy and childbirth is the number one killer. It’s the cause of 50,000 deaths of teenage girls every year. Ensuring that adolescent girls are able to use suitable contraception to delay the age at which they first become pregnant is a key part of the family planning challenge. Around 16 million girls between the ages of 15 and 19 give birth each year. …
Published in Research and Reviews: A Journal of Health Professions · Vol. 5, Issue 1, 2015 · pp. 7–21 Read article
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Emerging Trends in Data Structures for Modern Machine Learning Applications
Abstract: In the realm of machine learning, data structures play a pivotal role in facilitating efficient data manipulation, storage, and retrieval, thereby significantly impacting the performance and scalability of machine learning algorithms. In recent years, the field of machine learning has witnessed the emergence of novel data structures tailored to address scalability and efficiency challenges inherent in handling large-scale and high-dimensional data. This study provides a look at the data preprocessing, …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
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Textual Clues to Stress: A Machine Learning Approach
Abstract: Nowadays, numerous individuals utilize social media platforms to share tweets about their daily lives, which often reflect their mental well-being. Recognizing and managing stress is essential before it becomes a serious issue. Each day, a significant volume of informal messages is posted on discussion forums, blogs, and social networking sites. This study introduces a method for detecting stress using information gathered from social media, with a focus on Twitter. The …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 72–76 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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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Lightweight Models for Per-PC Energy Consumption Forecasting: Comparative Study with ML and DL Approaches
Abstract: We have collected primary data from automated logging of parameters like CPU utilization, estimated power, active or idle state, user logging activity, and the type of day. Additionally, survey data showed user awareness, energy-saving behaviour, and PC usage patterns. The data is pre-processed and merged by applying processes such as data cleaning, normalization, and feature extraction, i.e., determining the peak active timings and downtime. Developed lightweight prediction models based on …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article
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Data Science: Domains, Process, Roles and Responsibilities
Abstract: The study of information retrieval and analysis, or data science, tries to identify information and correspondence hidden in raw, defined information. To extract useful information from data, data science therefore combines programming expertise with understanding of mathematics and statistics. In the field of data science, machine learning algorithms are employed to handle various types of input, including numerical, textual, visual, and auditory data. Therefore, algorithms perform certain tasks related to …
Published in Journal of Advanced Database Management & Systems · Vol. 10, Issue 2, 2023 · pp. 29–35 Read article
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Android Based Recognition of Nutrition Intake with Piezoelectric Sensor
Abstract: Ingestion rate, food intake level; these are the factors which are responsible for overweight. We design a system for the user which gives feedback about his eating habits. The sensor used here to detect swallows is MEAS piezoelectric sensor. This sensor is placed against throat. This system classifies food types in broad categories like liquid and solid food by using sensor data and also the application is developed which gives …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 4, Issue 2, 2016 · pp. 7–11 Read article
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Mid-Year Epidemiological Profile of COVID-19 Posi ve Cases in Rajasthan, India
Abstract: Background: COVID-19, caused by SARS-CoV-2, has posed persistent public health challenges globally since its emergence in late 2019. India, through enhanced surveillance and vaccina on, has seen a progressive decline in case burden. Despite improvements, localized surges and emerging variants necessitate con nuous monitoring. Rajasthan, with its urban-rural health dispari es, experienced a modest resurgence of cases in early 2025, raising concerns about exis ng immunity gaps and health system …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 3, 2025 Read article