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30 results for “Transformers”
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Research ArticleOpen accessEvery word in the titleSQL Generation from Natural Language: A Sequence-to-Sequence Model Powered by the Transformers Architecture and Association RulesYoussef Mellah, Abdelkader Rhouati, El Hassane Ettifouri et al.Using Natural Language (NL) to interacting with relational databases allows users from any background to easily query and analyze large amounts of data. This requires a system that understands user questions and automatically converts them into structured query language such as SQL. The best performing Text-to-SQL systems use supervised learning (usually formulated as a classification problem) by approaching this task … …Journal of Computer Science, Vol. 17, Issue 5 · 23 May 2021 · 10,027 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNeurofeedback Therapy Meets Transformers: Rewiring Sleep Disorders Through AI-Driven EEG ModulationAmala Ann KA, Vaidhehi VSleep disorders such as insomnia, sleep Apnea, and hypersomnia significantly impair neurophysiological functioning, yet conventional treatments like Cognitive Behavioral Therapy for Insomnia (CBT-I) remain resource-intensive and difficult to personalize. This study introduces a novel AI-powered neurofeedback simulation framework designed to detect dysregulated EEG frequency band activity across sleep stages and simulate targeted interventions. A Transformer-based model serves as the core … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,674 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleTransforming Retinal Diagnostics: Advanced Detection of Diabetic Retinopathy Using Vision Transformers and Capsule NetworksVishal Sharma, Rishu, Vinay Kukreja et al.Diabetic Retinopathy (DR), nowadays is one of the leading causes of blindness worldwide, it is a severe complication of diabetes mellitus that affects the retina blood vessels. Accurate diagnosis depends on early detection of DR. The study aims to develop a hybrid model that is the combination of a Vision Transformer and Capsule Network (ViT-CapsNet) to classify the DR at … …Journal of Computer Science, Vol. 21, Issue 2 · 14 Jan 2025 · 6,755 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,113 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePredicting the Remaining Lifetime of Distribution Transformers using Machine LearningNtiminity Abontakoyah Enoch, Puguo Gbene George, Justice AningDistribution Transformer is a crucial element in deciding the power flow in large power systems. Their better performance implies high power system efficiency and enhanced power transfer capability. However, various Distribution Transformer failures in the recent past lead to power supply disturbance and have acquired much attention from the electrical intellectuals. It is of considerable significance to accurately get the … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 4 · 1 Jan 2021 · 6,644 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassifcation of Social Media Posts X For Mental Health Symptoms Identification Using NLP Techniques and Transformers ModelAndika Dwi Asmoro Wicaksono, RojaliThe increasing use of social media has enabled large-scale analysis of user-generated content to monitor mental health trends. This study focuses on sentiment prediction of mental health-related posts on platform X using transformer-based models, specifically IndoBERT, DistilBERT, and IndoRoBERTa. The goal is to evaluate the effectiveness of these models in classifying social media posts into positive, negative, and neutral sentiment … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,851 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePsychological Behavior Prediction through Sentiment Analysis Technics: Transformers and ML ApproachMaryame Naji, Najima Daoudi, Rachida AjhounIn the era of the COVID-19 epidemic, governmentshave imposed nationwide lockdowns, which make a huge change to people's dailyroutines. This last impacts indirectly the well-being of people's mentalhealth. And due to social media, many conversations about these phenomena occuronline, especially those related to people's emotions. Which brought challengesand opportunities for sentiment analysis researchers. In this article, we areinterested in extracting … …Journal of Computer Science, Vol. 18, Issue 9 · 14 Sep 2022 · 5,753 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComparison of Losses and Flux Distribution in 3 Phase 100 kVA Distribution Transformers Assembled from Various Type of T-Joint GeometryI. Daut, Dina M.M. Ahmad, S. Zakaria et al.This paper describes results of an investigation of the variation of power loss, building factor, flux leakage and flux distribution in 3-phase model transformer cores assembled from various type of T-joint geometry. The loss of the core with T-joint 60o was 10%, 12% and 15% better than the core with T-joint 45o, T-joint 23o and T-joint 90o respectively and 1.7 … …American Journal of Applied Sciences, Vol. 3, Issue 9 · 31 Dec 2009 · 6,893 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Sentiment Analysis Approach for Affective State Recognition With SWISH-Activated DenseNet-169 in Human Event ForecastingKarthik Elangovan, Prabhakaran Paulraj, Dinesh Babu G L et al.Detecting human feelings from images is perhaps one of the most useful and challenging social communication problems in research. Emotion detection-based deep computing outperforms classic image processing techniques. Facial recognition technology has permeated every aspect of our daily lives, from unlocking our phones to getting private file access on our systems. Machine Learning and Deep Learning make it easy to … …Journal of Computer Science, Vol. 22, Issue 8 · 29 Jul 2026 · 1,211 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,849 accessesView PDFCite