79 results for “long-term performance”

Set a search alert

Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 accessesView PDF Cite

Literature ReviewOpen accessIn the abstractRemineralization Potential of Bioactive Composite Resins: A Systematic ReviewLuiza Maria Schneider, Maria Ritha Veiga Colognese, Poliana Maria de Faveri Cardoso et al.To evaluate the clinical performance and potential of giomer-based materials in promoting the remineralization of dental structures through a systematic review of the literature. A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science databases up to March 2024. “giomer,” “S-PRG,” “bioactive restorative materials,” “remineralization,” and “dental caries.” Inclusion criteria comprised clinical studies involving human subjects, with … …Current Research in Dentistry, Vol. 17, Issue 1 · 29 Jan 2026 · 3,135 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDeep 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 PDF Cite

Research ArticleOpen accessIn the abstractDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA GUI-Enabled, Automated LSTM-Based Inverse Kinematics Pipeline for 6-DOF Robotic Arms Using MATLAB and CoppeliaSimWaleed Abdulrahman Saleh Al-Akwa, Mohammed Abdulwahab Ahmed DabaExisting deep learning-based inverse kinematics (IK) solutions often target specific robotic arms and require significant modifications when applied to different configurations. To support early-phase design and testing of 6-degree-of-freedom (6-DOF) robotic arms, this study presents a fast and adaptable IK solution through a user-friendly interface. Unlike traditional numerical methods that are computationally intensive, sensitive to initial conditions, and may not … …Journal of Mechatronics and Robotics, Vol. 9, Issue 1 · 26 May 2025 · 8,252 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEnhancing Indian Language Speech Recognition Systems with Language-Independent Phonetic Script: An Experimental ExplorationJose Stephan, Muthayyan Kamalam JayakumarIndia has a distinct linguistic profile that makes it extremely challenging to train Automatic Speech Recognition (ASR) systems correctly because most Indian languages have limited training material and are generally low-resource in nature. However, due to their similarity in phonemes, these languages offer an opportunity to create a single speech recognition technology. This study proposes an optimized phonetic script which … …Journal of Computer Science, Vol. 21, Issue 5 · 9 May 2025 · 6,536 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEstrous Synchronization Protocols in South African Merino EwesNhlakanipho Sam Zulu, Fhulufhelo Vincent Ramukhithi, Khoboso Christine LehloenyaThe South African Merino breed is the most important sheep breed in South Africa due to its superior wool quality. With an increasing wool demand from China and Europe, the need for wool production in South Africa has risen significantly. To meet this high demand, it is crucial to enhance the reproduction rate of the Merino sheep using assisted reproduction … …American Journal of Animal and Veterinary Sciences, Vol. 20, Issue 1 · 29 Jan 2025 · 7,007 accessesView PDF Cite

Research ArticleOpen accessIn the abstractStudent Course Recommendation System Using Semantic Aware Temporal Gating With Time TransformerJoshi Vinay Kumar, Dahlia Sam, N. KanyaCourse recommendation system works by analyzing users’ interests and recognizes their historical behavior such as course enrollment and previously watched videos to recommend relevant courses. However, the existing course recommendation systems in Massive Open Online Courses (MOOCs) face challenges in capturing complex semantic information, which impacts student requirements with an unsatisfied recommendation. By combining historical behaviors without temporal awareness, the … …Journal of Computer Science, Vol. 22, Issue 11 · 9 Oct 2026 · 580 accessesView PDF Cite

Research ArticleOpen accessIn the abstractBrain Tumor Segmentation and Classification Using HardNet Transformer With Gated Recurrent Unit ModelSaida D, Srinivas Adepu, Thade Lakshmi Devi et al.The uncontrolled growth of brain tumor cells presents a severe health risk, making early diagnosis and accurate classification essential for improving treatment outcomes. However, the existing approaches used for segmentation fail to delineate the tumor regions accurately due to a lack of global contextual information of brain tumors, resulting in poor classification performance. To overcome this limitation, this research proposes … …Journal of Computer Science, Vol. 22, Issue 9 · 26 Sep 2026 · 630 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 922 accessesView PDF Cite