Sign inSubmit
Tips: “quotes” for a phrase · author:Lee · a DOI goes straight to its article

5,204 results for “DAT”
Set a search alert
Research ArticleOpen accessEvery word in the titleComparative Evaluation of Aqueous and Freeze Dried Antigen for Sero-diagnosis of VL and PKDL Cases by DATSanjiva Bimal, Shubhankar K. Singh, P. K. Sinha et al.The efficacy of aqueous and freeze dried (FD) antigen was evaluated by direct agglutination test (DAT) for sero-diagnosis of visceral leishmaniasis. A total of 16 samples collected from 5 confirmed Kala-azar (KA) cases, 6 cases 2 each of filariasis, malaria, leprosy and 5 non-endemic healthy subjects were used in determination of cut off titre of both the antigens in DAT. … …American Journal of Immunology, Vol. 1, Issue 2 · 30 Jun 2005 · 6,834 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleExplainability Aware Heterogeneous Temporal Graph Transformer for Automated Genetic Disorder Detection from Genomic DataPuvaneswari Subramaniapillai, Indirani Govindasamy, Revathy GurumurthyGenetic disorders affect millions worldwide, posing major challenges for accurate diagnosis and effective treatments. New developments in genomic technologies, especially Next-Generation Sequencing (NGS), have enhanced the classification of genetic modification and improved diagnostic abilities. Moreover, the Machine Learning (ML) and Deep Learning (DL) methods emerged as efficient tools for evaluating the intricate genomic data and determining the patterns, which can … …Journal of Computer Science, Vol. 22, Issue 11 · 14 Oct 2026 · 566 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleReal-Time Monitoring and Injury Risk Warning Algorithm Based on Data Fusion of Motor Muscle ContractionGuomin Wang, Jingying HuangThe existing sports injury warning algorithms are difficult to achieve dynamic injury risk modeling based on individual muscle characteristics while ensuring real-time fusion efficiency of multimodal signals. This article proposes a real-time muscle contraction state perception and injury risk warning algorithm based on adaptive weighted feature fusion and lightweight temporal modeling. The system synchronously collected surface electromyography (sEMG), Inertial Measurement … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 3 · 10 Aug 2026 · 1,089 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Data Security Approach Based on GAN Teganographyand AES-RSA Encryption in a Distributed SystemDerrick Méthode Bagaza, Abraham Walake, Mamoudou Kourouma, Blaise Omer YenkeData security in distributed environments has become a major challenge due to the dispersion of resources, the expansion of the attack surface, and the increasing sophistication of cyber threats. Although traditional mechanisms such as data encryption, multi-factor authentication, and access control systems help to strengthen information protection, these approaches still have certain limitations when faced with advanced attacks and human … …Journal of Computer Science, Vol. 22, Issue 8 · 28 Jul 2026 · 1,062 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleVolatility-Aware Hybrid Memory Architecture for Real-Time and Persistent Big Data SystemsMohammed Elhabib Maicha, Mohammed Redha BouzidiAs data volumes and real-time analytics demands grow, DRAM only memory systems struggle to scale cost-efficiently and sustainably. We present VA-HMA, a volatility-aware hybrid memory architecture that combines DRAM and Non-Volatile Memory (NVM) with a lightweight, machine-learned placement layer and endurance-aware fault tolerance. VA-HMA continuously monitors access patterns and applies a Random Forest–based predictor to guide batched page migrations and … …Journal of Computer Science, Vol. 22, Issue 6 · 27 Jun 2026 · 1,214 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEvaluation of Machine Learning Models to Predict Student Academic Performance Using Structured Educational DataHardik Ishwarbhai Patel, Dharmendra PatelThis study analyses the use of machine learning for predicting the academic performance of students using their academic information from the institution, combined with socio-economic information that comes from outside sources. The collection of information is done using structured questionnaires as well as through data extraction from the Student Information System (SIS). To increase the reliability of models built, a … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,419 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 · 1,804 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Comparative Study of Resampling, Cost-Sensitive, and Ensemble Techniques for Handling Class Imbalance in Indonesian Financial DataGunawan Kurnia, Ditdit Nugeraha UtamaHandling class imbalance is a critical challenge in machine learning applications, particularly in financial domains where minority instances often represent significant anomalies such as fraud or audit risks. Various oversampling and undersampling methods were tested, alongside cost-sensitive adjustments and ensemble models including Random Forest, AdaBoost, Gradient Boosting, and XGBoost. The evaluation, based on 10-fold stratified cross-validation and performance metrics such … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,874 accessesView PDFCite