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567 articles for “Training”
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Advances in Polymer-Modified Concrete using XAI
Abstract: Industry 4.0 technologies are being quickly adopted by the construction sector, opening new avenues for enduring operational and environmental issues. This sector looks at how explainable AI can forecast air and enhance the quality of building materials. XAI, AI, ML, and big data drive a new paradigm in polymeric material development. The effective XAI and ML-assisted design creates innovative, high-performance polymeric materials. It covers building a database and representing structures, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 133–144 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Fraud Detection in Government Procurement Using Machine Learning
Abstract: Fraud represents a significant challenge in the realm of procurement, with estimates indicating that between 12 and 30% of global procurement budgets are lost to fraudulent activities (OECD, 2023). The pervasive nature of procurement fraud, which may encompass a range of deceptive practices such as bid rigging, invoice fraud, and procurement kickbacks, not only undermines the integrity of financial operations but also results in substantial losses for organizations. These losses …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 19–34 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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The Impact of Geographical Indications on Sustainable Rural Development: Comprehensive Economic and Cultural Insights from Wayanad, Kerala
Abstract: Geographical Indications (GIs) play a vital role in fostering sustainable rural development by linking unique local products to their geographic origins. This study explores the impact of GIs on economic growth, cultural preservation, and environmental sustainability in Wayanad, Kerala. Drawing from extensive secondary data and detailed case studies including Wayanad Coffee, Jeerakasala Rice, and traditional handicrafts, the research highlights how GI certification enhances market value, improves income levels, and preserves …
Published in International Journal of Rural and Regional Development · Vol. 3, Issue 2, 2025 · pp. 18–29 Read article
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Review article on Quality Control in Clinical Trials
Abstract: Quality control (QC) is a critical component in the conduct of clinical trials, ensuring the accuracy, reliability, and credibility of data collected throughout the study. It encompasses a systematic set of procedures designed to monitor trial conduct and data integrity, thus safeguarding the rights, safety, and well-being of participants. This review explores the principles, implementation, and evolving practices of quality control in clinical trials, highlighting its importance across all phases …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 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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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 Read article
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Self Esteem and Sociotropy - Autonomy as predictors of Workplace Burnout among Private Sector Employees
Abstract: Workplace burnout is a growing concern in the private sector, where employees face intense performance pressures, leading to stress and reduced productivity. While job-related factors are well-documented contributors, the role of personality traits in burnout remains an area of interest. This study examines the impact of Self-Esteem, Sociotropy, and Autonomy on Workplace Burnout among private sector employees. A sample of 120 employees was analyzed using ANOVA, Pearson correlation, and multiple …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 · pp. 81–89 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Dual-Stream Deep Learning Framework for Brain CT Image Classification and Implications for Polymer Composite Neuro Implant Evaluation
Abstract: Early and accurate classification of brain CT images is critical for diagnosing conditions such as aneurysms, tumors, and related lesions. We present a dual-stream image-classification framework that fuses convolutional neural network (CNN) features with handcrafted Histogram of Oriented Gradients (HOG) descriptors to jointly capture global semantics and local textural cues. The pipeline begins with modality unification via pixel-wise averaging to form a fused input, which is then processed in parallel …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 172–179 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 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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The Evolution of Ransomware: In-Depth Analysis of Threat Development and Modern Defense Mechanisms
Abstract: Ransomware is the most severe of all cybersecurity threats the contemporary digital world is confronted with. It is a form of malware that encrypts a victim's information and requests ransom, usually in cryptocurrency, for its decryption. From its first appearance in the late 1980s, ransomware grew from simple malware into very advanced and targeted attacks that can be used to bring down entire organizations, businesses and critical infrastructure. This study …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 35–43 Read article
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Assessing Knowledge and Awareness of Artificial Intelligence in Academic Research Among Tertiary Students in Ghana
Abstract: Background: While Artificial Intelligence (AI) technologies are evolving rapidly in education, a major deficit in tertiary students' awareness and use of AI-based academic research is observed in Ghana. Prior research notes general awareness but limited use in practice and mentions issues with trust, ethics, and accessibility. Methodology: A cross-sectional survey was undertaken with a sample size of 450 undergraduates and postgraduates from diverse disciplines through stratified random sampling. The study …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article
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Routing Protocols in FANETs with Future Enhancements
Abstract: Flying Ad Hoc Networks (FANETs), which are swarms of Unmanned Aerial Vehicles (UAVs), are an emerging solution which revolutionized the area of mission-critical and infrastructure-less communication systems. These networks provide real-time data transfer for use cases such as disaster relief, battlefield observation, environmental monitoring, and 6G-based smart cities. However, the dynamic profile of FANETs, which is defined by high 3D mobility, limited energy resources, unstable wireless links, and constant topology …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 8–13 Read article
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Adaptive Routing Protocol to Optimize the Quality of Service of MANET Using Neural Network
Abstract: A MANET is a group of mobile nodes that create a temporary network without relying on centralized administration or standard supporting devices, often functioning as a conventional network. These dynamic environments present significant challenges for traditional routing and switching protocols, particularly in delivering Quality of Service (QoS) benchmarks such as bandwidth, latency, packet delivery ratio, and robustness. This study proposes an Adaptive Routing Protocol (ARP) leveraging Neural Network (NN) techniques …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
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Mobile Technology for Libraries: Trends, Challenges, and Future Prospects
Abstract: Mobile technology has a great impact on both individuals and organizations. Over the time, the computational capabilities of these sophisticated technologies have become more accessible and reasonably priced. These technologies have an impact on how people choose to communicate, how they use and access the internet, and how they produce and consume content or services. Furthermore, these technologies have permeated the educational field and changed the way universities and other …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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Microneedles: An Innovative Drug Delivery System
Abstract: Microneedles represent a groundbreaking innovation in drug delivery systems, offering a transformative alternative to conventional hypodermic needles and transdermal patches. This advanced technology combines the precision and efficacy of needle-based delivery with the convenience and pain-free nature of patches, creating a minimally invasive platform that addresses many limitations of traditional drug administration. Microneedles are designed to penetrate the stratum corneum – the skin’s outermost layer – without reaching pain-sensitive nerves …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 60–67 Read article