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347 articles for “Model Evaluation”
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Research ArticleOpen accessIn the abstractOptimized XGBoost for Ethereum Fraud Detection: A Cost-Sensitive ApproachSupriya P., Rubah Sheriff, Shreya Padaki et al.In today’s technologically advancing world, many fields from finance to healthcare and education are shifting toward a digital and decentralized format. A significant transformation is underway with the currency of the masses. Blockchain-based cryptocurrencies like Bitcoin and Ethereum allow users to generate fungible tokens anonymously through smart contracts. However, these features also facilitate illicit transactions and cybercrimes like fraud, phishing, … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,774 accessesView PDFCite
Research ArticleOpen accessIn the abstractStock Closing Price Forecasting Using LSTM, Sentiment Analysis, Kalman FilterAssel Abdildayeva, Galymzhan Nurtugan, Guldana Taganova, Ardak AkhmetovaThe article explores the problem of predicting the closing prices of stocks using an innovative approach that combines methods of machine learning, sentiment analysis and noise filtering. The focus is on the development and testing of a comprehensive model that integrates recurrent neural networks (LSTM) for time series analysis, the GPT-3 language model for processing and analyzing textual data from … …Journal of Computer Science, Vol. 20, Issue 11 · 4 Sep 2024 · 6,266 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Analysis of Garbage Classification Using Balanced and Unbalanced Dataset with EfficientNetV2B1 ArchitectureRetinderdeep Singh, Chander Prabha, Ayman Noor et al.This research concentrates on EfficientNetV2B1 deep learning model to classify garbage collection tasks, with both balanced and unbalanced dataset configurations. The dataset includes 7,260 images for the balanced dataset and 15,515 for the unbalanced one, both of the datasets are used to train and evaluate the model. Training and evaluation of the deep learning model with the standard performance variables: … …Journal of Computer Science, Vol. 20, Issue 10 · 27 Aug 2024 · 5,096 accessesView PDFCite
Review ArticleOpen accessIn the abstractThe Impact of Di-2-Ethylhexyl Phthalate (DEHP) in Focus on the Reproductive System and Toxicity in Rat or Mammalian ModelVenkataramanaiah Poli, Srinivasulu Reddy MotireddyAbsalan, F., Saremy, S., Mansouri, E., Moghadam, M. T., Moghadam, A. R. E., & Razie, G. (2016). Effects of Mono-(2-Ethylhexyl) Phthalate and Di-(2-Ethylhexyl) Phthalate Administrations on Oocyte Meiotic Maturation, Apoptosis and Gene Quantification in Mouse Model. Cell Journal, 18(4), 503–513. https://doi.org/10.22074/cellj.2016.4717 Acevedo‐Rodriguez, A., Kauffman, A. S., Cherrington, B. D., Borges, C. S., Roepke, T. A., & Laconi, M. (2018). Emerging … …American Journal of Pharmacology and Toxicology, Vol. 19, Issue 1 · 6 Jun 2024 · 13,008 accessesView PDFCite
Research ArticleOpen accessIn the abstractProtective Role of Ganoderma lucidum Polysaccharides Against Stress Induced by Heavy Metals in Caenorhabditis elegansHuixiu Ma, Dehui Dai, Guicai Chen, Weilian HuAli, H., Khan, E., & Ilahi, I. (2019). Environmental Chemistry and Ecotoxicology of Hazardous Heavy Metals: Environmental Persistence, Toxicity, and Bioaccumulation. Journal of Chemistry, 2019, 6730305. https://doi.org/10.1155/2019/6730305 Aljerf, L., & Aljerf, N. (2023). Food products quality and nutrition in relation to public. Balancing health and disease. Progress in Nutrition, 25(1), e2023024. https://doi.org/10.23751/pn.v25i1.13928 Aljerf, L., Williams, M., Ajong, A. B., Onydinma, … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 2 · 18 May 2024 · 6,949 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 743 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmpirical Study on Modified Pre-Trained CNN Architectures for Fitzpatrick17k Skin Diseases Prediction ModellingSteven Matthew, Nur Afny Catur Andryani, Rojali et al.Preventing missed diagnosis of skin diseases is critical for enhancing patient outcomes. Technology support empowered by AI based algorithms have been recently developed to minimize the burden. Convolutional Neural Networks (CNNs) are increasingly utilized for image classification tasks including skin's diseases prediction modelling. Its advancement architectures such as pre-trained models, VGG16 andResNet50 provide a strong foundation to up-skill the prediction … …Journal of Computer Science, Vol. 21, Issue 7 · 8 Jul 2025 · 3,938 accessesView PDFCite
Research ArticleOpen accessIn the abstractCybersecurity Mechanism for Automatic Detection of IoT Intrusions Using Machine LearningCheikhane Seyed, MBaye Kebe, Mohamed El Moustapha El Arby et al.This article proposes an ML-based cyber security mechanism to optimize intrusion detection that attacks internet objects (IoT). Our approach consists of bringing together several learning methods namely supervised learning, unsupervised learning and reinforcement learning within the same Canvas. The objective is to choose among them the most optimal for classifying and predicting attacks while minimizing the impact linked to the … …Journal of Computer Science, Vol. 20, Issue 1 · 11 Dec 2023 · 6,186 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Robust Ensemble Convolutional Neural Networks for Diagnosing Chest DiseasesMansour Ali Alhlalat, Ahmad Abdel-Aziz Sharieh, Mohammed Belal Al-ZoubiRadiologists employ X-ray images to differentiate various chest diseases. Given the intricate and meticulous nature of this diagnostic procedure, the assistance of automated models becomes imperative in detecting and diagnosing diseases from X-ray images. This research paper proposed a novel approach called Ensemble Convolutional Neural Network for Diagnosing Chest Diseases (ECDCNet), aimed at accurately and efficiently diagnosing fifteen different chest … …Journal of Computer Science, Vol. 19, Issue 12 · 27 Oct 2023 · 5,108 accessesView PDFCite
Research ArticleOpen accessIn the abstractStrengths and Weaknesses of Digital Maturity ModelsAbdoulaye Sadio Barry, Saliha Assoul, Nissrine SouissiAssessing digital maturity is a prerequisite for any digital transformation initiative. This assessment allows the business to know its current level of digital maturity and assess its ability to manage change. The evaluation also enables society to identify the main thrusts and objectives of its digital strategy. This article analyses the strengths and weaknesses of 8 digital maturity models to … …Journal of Computer Science, Vol. 19, Issue 6 · 31 May 2023 · 6,966 accessesView PDFCite