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1,449 articles for “3-3-1 Models”
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Review ArticleOpen accessEvery word in the titleStructural Barriers to the Deployment of AI Foundation ModelsHristo Hristov, Elena Somova, Emil FuchedzhievArtificial Intelligence (AI) foundation models excel at benchmarks but are not always cost-effective or successfully deployed in enterprise systems. This paper analyzes the failures in their deployment through interconnected structural components characterized by: Economic constraints (computational costs, memory, and latency that scale with increasing use of AI model services), cognitive constraints (related to training objectives that optimize plausibility rather than … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 808 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Novel Characterization of the Incidence Term in Epidemic Models: Interpretation of the Resulting Basic Reproduction Number in Terms of Healthcare AccessibilityFrancis BenyahWe propose a novel characterization of the incidence term in mathematical epidemic models. This new characterization takes into consideration the fact that at any given time, only a proportion $\kappa \ (0 \, \le \, \kappa \, \le \, 1)$, of infectives have access to healthcare. Infectives without access remain untreated and therefore, become reservoirs for new transmissions.The proposed incidence … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 1 Oct 2026 · 582 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEvaluation of Language Models (LLMs) in the Interpretation of Tuberculosis Concepts: Design of a Virtual Assistant for Clinical Support and Patient EducationMauricio Acevedo-Carrillo, Shirley Fiorella Simbron EspejoTuberculosis (TB) remains a global public health challenge, where access to accurate and up-to-date information is crucial for professionals and patients. This research comparatively evaluated the performance of five language models (LLMs) Med-PaLM 2, GPT-4, MEDITRON-70B, Me-LLaMA, and Clinical Camel in the TB domain and implemented a mobile virtual assistant as a proof-of-concept based on the best-performing model. Clinical accuracy … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 491 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,355 accessesView PDFCite
Literature ReviewOpen accessEvery word in the titleExtraction Performance of Essential Oils by Hydrodistillation Using Mathematical Models: A Systematic ReviewLenin Quiñones Huatangari, Frank Fernandez Rosillo, Eliana Milagros Cabrejos Barrios et al.Essential oils are complex mixtures of volatile organic compounds valued for their antimicrobial and antioxidant properties, with widespread applications in the food, pharmaceutical, and cosmetic industries. Among the various extraction techniques employed, hydrodistillation remains one of the most widely used methods. The extraction yield of essential oils by hydrodistillation is influenced by multiple factors, and quantifying these through mathematical modelling … …OnLine Journal of Biological Sciences, Vol. 26, Issue 1 · 25 Mar 2026 · 2,508 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePleural Effusion Detection Using Optimized Pretrained ModelsRehab Fathi Ibrahim, Nashwa Mohamed Elsayed et al.Pleural effusion is an abnormal accumulation of fluid in the pleural cavity, posing a significant thoracic issue with various causes. Even with a variety of diagnostic techniques, accurate diagnosis remains challenging. Delays in diagnosis and treatment heighten the risks of the disease. In this paper, we introduce a novel approach by leveraging the Grey Wolf Optimizer (GWO) to systematically optimize … …Journal of Computer Science, Vol. 21, Issue 8 · 17 Oct 2025 · 2,308 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSuicide Ideation and Risk Detection from Social Media Using GPT ModelsSara Lasri, El Habib Nfaoui, Karima MrizikAs a reason for the sensitiveness of suicide ideation and its considerable impact on people's lives, the demand to treat and prevent the suicide ideation issue has become an obligation. Suicide ideation is a result of a combination of psychological pain and hopelessness. According to the World Health Organization, the task of reducing the global suicide mortality rate is a … …Journal of Computer Science, Vol. 20, Issue 10 · 26 Aug 2024 · 5,704 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePrompt-Based Data Augmentation with Large Language Models for Indonesian Gender-Based Hate Speech DetectionMuhammad Amien Ibrahim, Faisal, Zefanya Delvin Sulistiya, Tora Sangputra Yopie WinartoThe increasing amount of content on social media content makes the use of automatic moderation crucial for preserving a healthy online community and reducing the spread of offensive and abusive content, such as hate speech based on gender. Developing automated social media moderation using machine learning demands a large and balanced dataset. However, difficulties such as data scarcity and class … …Journal of Computer Science, Vol. 20, Issue 8 · 27 May 2024 · 5,881 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEmpowering Small Language Models With Chain of Thought and Parameter Efficient Fine Tuning for Efficient Deep ReasoningAryan Raina, Shiwani Gupta, Jagruti Jadhav et al.Small Language Models (SLMs) run faster and fit on modest hardware, yet solving multi-step logic problems has traditionally been difficult for them. This work investigates a systematic, multi-model framework that combines Chain-of-Thought (CoT) prompting with Low-Rank Adaptation (LoRA) parameter-efficient fine-tuning, and measures the contribution of each component independently. We evaluate three SLMs (TinyLlama-1.1B, Phi-3-mini-4k-instruct, and Qwen2.5-1.5B) using 1,164 training samples … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 862 accessesView PDFCite