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776 articles for “data evaluation”
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Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
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A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
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Optimizing Customer Care Centre Performance: A Data Analytics Approach
Abstract: Customer care centres are essential in today's competitive corporate environment for ensuring client loyalty and satisfaction. By utilizing data analytics approaches, one may gain important insights regarding performance overall, operational effectiveness, and customer interactions. Data analytics encompasses the analysing, interpretation, and extraction of valuable insights from data to aid decision-making and address intricate issues. Call centre analytics is the process of gathering and evaluating call data to assist companies in …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 34–49 Read article
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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Intelligent Planning of Transmission Networks: Addressing Uncertainties Through Artificial Intelligence
Abstract: Power grid planning is a critical aspect of power grid topology, traditionally relying on manual methods that are prone to various uncertainties. These uncertainties, both subjective (stemming from human judgment) and objective (resulting from data limitations), can significantly affect the reliability and efficiency of the planning process. This paper presents an artificial intelligence (AI) method aimed at improving the smart planning of transmission networks. By utilizing AI, the proposed method …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 40–46 Read article
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Encoder-Decoder Based Fine-Tuned Model for Code Doubt Solver
Abstract: As we are growing in technology, more technologically skilled persons are needed in industry. They all often rely on programming in their daily work, and when some doubts arise, they seek help from teachers to LLMs like GPT to Deepseek. However, when errors arise, then comes hectic part to troubleshoot and resolve the error. Usually, people seek help from some LLMs like GPT, or Deepseek for the solution; they give …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 35–42 Read article
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A study to assess the effect of nutritional supplementation on the hemoglobin level and the associated signs and symptoms of the students identified with anaemia in selected colleges of SNDT Womens’ University Mumbai
Abstract: The purpose of this study was to assess the effects of nutritional supplements on haemoglobin levels and related symptoms among students at SNDT Women's University in Mumbai who had been diagnosed with anaemia in a few particular institutions. Non-occurrence A sample of thirty anaemic students was selected via easy sampling. With a one-group pre-test-post-test methodology, the study used a descriptive evaluative design. Data collecting instruments included measurement devices, opinion questionnaires, …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 2, 2024 · pp. 16–25 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Assessment of Water Quality along River Ethiope, Delta State
Abstract: The environment, economic growth, and human health all depend on the quantity and quality of water supplies. Given this, the significance of water quality monitoring cannot be overstated.This study was aimed at assessing the water quality of River Ethiope. To achieve this, surface water samples were collected from Ethiope River along its banks at the following towns; Umuaja (SWI), Ebedie (SW2), Abraka (SW3), Sapele (SW4) and Ughara (SW5) axis during …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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Advancing Sustainability: A Comprehensive Review of Environmental, Social, and Governance (ESG) Practices
Abstract: Environmental, Social, and Governance (ESG) frameworks have emerged as critical pillars guiding sustainable business practices and responsible investment decisions. This review explores the multifaceted role of ESG principles in promoting environmental stewardship, advancing social equity, and ensuring ethical governance. Environmentally, ESG focuses on combating climate change, conserving biodiversity, and managing resources through renewable energy adoption, waste reduction, and carbon emission control. Socially, it emphasizes employee well-being, diversity, community engagement, and …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 1–9 Read article
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Bio Materials and Nanotechnology: Green Tea (Waste)– Aluminium Nanoparticles (Gt-Al Nps) For Methylene Blue Adsorption
Abstract: This study examines the adsorption of Methylene Blue (MB) dye from aqueous solutions using Aluminium Nanoparticles synthesized with green tea powder as a biological reducing agent. Methylene Blue, an aromatic phenothiazine dye, is widely applied in medical diagnostics and various industrial processes, but its uncontrolled release into water bodies leads to environmental pollution due to its intense colour, stability, and potential toxicity. Therefore, identifying an efficient and eco-friendly adsorbent for …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 96–107 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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Comparison of Models of Machine Learning and Hyperparameter optimization methods on various datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameters tuning step. The traditional exhaustive methods of search (Grid Search and others) ensure that the search space is covered, but are computationally very inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian Optimization, Tree-structured Parzen Estimator (TPE), Genetic Algorithms) are thought to …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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Automated Intelligence, Machine Learning, and Big Data in Education: A Practical Framework, Synthetic Demonstration, and Deployment Guidance
Abstract: Artificial intelligence (AI), machine learning (ML), and big-data methods are increasingly used to improve educational decision making through personalization, early-warning systems, scalable feedback, and operational analytics. This manuscript proposes a practical end-to-end framework for educational AI/ML projects, covering problem definition, data engineering, modeling, evaluation, intervention design, and responsible governance. To provide a complete and reproducible template without exposing sensitive student data, we present a synthetic demonstration study that mirrors typical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Convolutional Neural Network Based Ripeness Detection of Fruits
Abstract: The accurate and efficient assessment of fruit ripeness plays a crucial role in ensuring the quality of fruits and optimizing supply chain management. This paper presents a novel approach for the automated detection of apple and banana ripeness using Convolutional Neural Networks (CNNs). The suggested method supports the capability of CNNs to learn hierarchical features from images, variations in color and shape associated with different ripeness stages. The online dataset …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 13, Issue 2, 2024 · pp. 30–36 Read article
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Synthesis and Characterization of VO 2+ doped SrMg 2 (PO 4 ) 2 Nanopowder by Solid State Reaction technique suitable for White LED material
Abstract: VO2+ doped SrMg2(PO4)2 nanopowder was synthesized by using solid state reaction (SSR) technique. Various experimental techniques have been performed on prepared sample. XRD analysis has revealed that prepared nanopowder is in monoclinic phase. The average crystallite size, micro strain and dislocation density evaluated and make an analogy with W-H plot method. SEM micrographs shows that agglomerated stone like structure and EDS spectrum shows elemental compositions of synthesized sample. FTIR spectrum …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 95–110 Read article
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Enhancement in Biomedical Polymer Nanocomposites: Biocompatibility and Mechanical Property Predictions using Machine Learning
Abstract: A machine learning (ML)-based framework is developed and validated through experimental analysis and comparative modeling to enhance system dependability and improve prediction performance. The proposed framework includes key stages such as data preprocessing, feature evaluation, model training, and performance benchmarking to determine the most effective prediction technique. Several machine learning models were evaluated, including Ensemble models, Artificial Neural Networks (ANN), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 275–296 Read article