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776 articles for “data evaluation”
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A Data-driven Approach to Sales Analysis
Abstract: Decisions made using data from digital sources are said to be data-driven when they are analysed and interpreted. Across many sectors, a data-driven approach is an effective technique for gaining insights, making wise choices, and guiding corporate strategy. This study covers the concept of data analytics in sales analysis of bakery and mess. It involves evaluating diverse types of information, including sales data, customer preferences, production costs, and supplier details. …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 1, 2024 · pp. 29–41 Read article
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Multi-Scale Analysis of Polymer Based Energy Storage Systems for High Performance Battery Applications
Abstract: The energy storage systems based on polymers are becoming promising materials for the next generation of high performance batteries because of their excellent mechanical flexibility, improved safety, and favorable electrochemical properties. Even with computational tools in Python, polymer-based energy storage systems remain plagued by poor ionic conductivity, complicated electrochemical reactions and potential thermal runaway. Therefore, a multi-scale model is proposed to improve battery performance, thermal stability, reliability, and large-scale deployment …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1035–1048 Read article
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IoT Based Electricity Theft Detection System
Abstract: The proliferation of smart grids and advanced metering infrastructure has paved the way for innovative solutions to tackle the longstanding issue of electricity theft. This study presents an IoT-based electricity theft detection system that leverages real-time data analytics and machine learning algorithms to identify potential theft cases. The proposed system utilizes smart meters to collect electricity consumption data, which is then transmitted to a central server for analysis. The system …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 18–22 Read article
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Evaluation of Mammographic Breast Density in Benign and Malignant Breast Disease Patients
Abstract: The purpose of the study was to compare the breast density in benign breast disease and carcinoma of the breast and to evaluate the association between breast density and the Breast Imaging Reporting and Data Systems (BIRADS) score to investigate the potential of breast density as a prognostic indicator. In this study, histologically proven cases of 30 benign breast disease patients and 30 breast carcinoma patients were included. Breast density …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 Read article
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A Study to Assess the Prevalence of Tokophobia and the Effect of Nurse-led Intervention on Birth Experience Among Parturients Availing Services in a Tertiary Care Hospital, Kolkata
Abstract: Introduction: Tokophobia, the fear of childbirth, can significantly impact a woman's birth experience and overall well-being. This study aims to determine the prevalence of tokophobia among parturients and evaluate the effectiveness of a nurse-led intervention in improving birth experiences in a tertiary care hospital in Kolkata. Methods: A cross-sectional study design was employed to assess the prevalence of tokophobia among parturients receiving services at the selected tertiary care hospital in …
Published in International Journal of Midwifery Nursing And Practices · Vol. 2, Issue 1, 2024 · pp. 1–8 Read article
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Data Compression for Backbone Network
Abstract: This article involves the application of data compression techniques to improve the efficiency and performance of the core infrastructure of modern digital networks. This approach focuses on reducing the size of transmitted data without compromising its quality, aiming to enhance network throughput, reduce latency, and minimize energy consumption. The study also considers practical implementation challenges and trade-offs to optimize resource utilization in backbone networks. We delve into various compression methods, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 30–40 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 Read article
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Comparative Study of AI-Driven Fashion Trend Prediction System Using AI and ML: A Review
Abstract: To overcome the challenges in fashion trend forecasting, researchers have introduced several advanced and data-driven approaches. One such method uses a long short-term memory (LSTM) model combined with an encoder-decoder architecture to extract meaningful fashion content and recognize styles from product images. This model achieves higher accuracy in predicting upcoming fashion trends by incorporating varying price intervals and has shown impressive results when evaluated on the Amazon fashion dataset. Another …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 35–41 Read article
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Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method
Abstract: This study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. In order to achieve this, we analyzed detailed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various performance indicators. The datasets included comprehensive statistics from multiple matches and tournaments, allowing for an in-depth evaluation of players’ skills and contributions. PCA ranked players according to their participation …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 20–30 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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Advances in Data Security in Cryptography
Abstract: In the ultra-modern period, evaluation of networking and wireless networks within information and communication technology has brought many changes to deal with this technology using internet, growing strongly over the past several decades, data security has come a main concern for anyone connected to the web. Data security ensures that our data can only be accessed by authorized recipients and prevents any unauthorized access or alteration of the data. We …
Published in Journal Of Network security · Vol. 12, Issue 1, 2024 · pp. 1–7 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Advances in Total Knee Replacement: A Systematic Review of Clinical Outcomes and Complications
Abstract: Total Knee Replacement (TKR) is a widely used surgical intervention for patients with knee osteoarthritis and other degenerative knee disorders, offering significant improvements in pain relief, functional restoration, and quality of life. This systematic review synthesizes data from multiple clinical studies to evaluate the outcomes and complications associated with TKR. To find applicable research published in the last ten years, a thorough search of electronic databases was performed. Randomised controlled …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 1, 2024 · pp. 41–56 Read article
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Targeting Homogentisate Dioxygenase Dysfunction in Alkaptonuria: Investigating Curcuma longa’s Therapeutic Potential
Abstract: Objectives: Alkaptonuria is known to have a faulty gene HGO in the metabolic process. In the present research work, the focus is towards investigating the therapeutic capabilities of the Curcuma longa upon the faulty Homogentisate dioxygenase gene using ligand-protein binding, which would assist in the corrective tyrosine metabolism. Methods: This study is based on the computational approach using different phytochemicals for evaluation of the potency against the abnormal Homogentisate dioxygenase …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 2, Issue 2, 2024 · pp. 1–11 Read article
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A Study to Evaluate the Effectiveness of a Structured Teaching Programme on Knowledge and Attitude Regarding Selected Comfort Measures Among Post-Caesarean Mothers
Abstract: Introduction: The study was conducted to assess the levels of knowledge and attitudes related to selected comfort measures among mothers who had undergone caesarean delivery, both before and after an intervention. It also aimed to identify any associations between these outcomes and certain demographic variables. Methods: A pre-experimental design using a single group with pretest and posttest measures was employed. The sample consisted of 100 post-caesarean mothers, chosen through a …
Published in International Journal of Midwifery Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article
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Customer Churn Prediction Using ML Algorithms
Abstract: Comprehending customer churn is essential for businesses aiming to enhance and sustain customer relationships. This study introduces a machine learning approach aimed at forecasting customer churn by leveraging demographic and behavioral data. Our research involved developing predictive models using support vector machines (SVM), random forests, and decision trees, evaluating their efficacy using real-world data from the telecom industry. Our findings underscore that random forests consistently outperform SVM and decision trees …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 70–75 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article