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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 · 821 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 · 589 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 · 504 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Enhanced Neighbourhood and Latent Factor Model for Cold-Start RecommendationsAmritha P, Rajkumar KKAmong different recommendation strategies, collaborative filtering remains a commonly utilized method for generating personalized suggestions. The traditional collaborative algorithms face performance declines due to the sparse rating of data and the item cold-start problem. To overcome these challenges, this paper introduces a novel hybrid model called HCE-KNNCF (Hybrid Cognition-Enabled K-Nearest Neighbor Collaborative Filtering). The proposed model generates predicted rating by … …Journal of Computer Science, Vol. 22, Issue 9 · 21 Sep 2026 · 630 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 · 869 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleParameter-Expanded Data Augmentation for Analyzing Nominal Data With Missing Values Using Multinomial Probit ModelsSuwash Silwal, Xiao ZhangNominal data occur in many scientific fields, such as health-related studies, transportation, and econometrics. Due to the ubiquitousness of missing data, it is inevitable to analyze nominal data with missing values. As is well known, statistical methods for analyzing nominal variables are quite limited. The Multinomial Probit (MNP) model has been an essential tool for analyzing nominal categorical data, but … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 23 May 2026 · 1,814 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,488 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnhanced RoBERTa Model for OCR-Based EHR Parsing and Information ExtractionBalaji Ganesh Rajagopal, Amarnath C, Chidambaram Sawri Rajan, Deebalakshmi RamalingamHealthy source data for medical research and health analytics in general can be obtained from Electronic Health Records (EHRs). Nevertheless, due to the complexities of the design and especially the unstructured nature of them, it is not easy to extract important information from digital documents. This paper proposes a fundamentally new approach to the problem of interpreting EHRs obtained by … …Journal of Computer Science, Vol. 22, Issue 4 · 5 May 2026 · 1,590 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleExtension Model Based on Farmers’ Resources and Need to Improve Feed Technology AdoptionAgustina Abdullah, Indrawirawan IndrawirawanFeed technology is essential for improving beef cattle productivity, yet its adoption by farmers often remains partial and misaligned with their actual needs. This study aimed to develop a context-responsive agricultural extension model to enhance the adoption of feed-related innovations among beef cattle farmers. The research was conducted in Herlang and Bulukumpa Districts, Bulukumba Regency, South Sulawesi, Indonesia. Using a … …American Journal of Animal and Veterinary Sciences, Vol. 21, Issue 1 · 5 May 2026 · 1,476 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 · 1,363 accessesView PDFCite