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125 results for “Performance Monitoring”
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Research ArticleOpen accessIn the abstractFine-Tuned and Optimized Transformer-Based Model for EEG Seizure DetectionPuspanjali Mallik, Ajit Kumar Nayak, Kumar Janardan Patra et al.Epilepsy, a widely recognized neurological disorder, results from irregularities in the transmission of electrical impulses among neurons in the brain. Over the last two decades, significant efforts have been made by researchers and clinicians to develop effective methods for its early detection and management. The electroencephalogram (EEG), a non-invasive tool used to monitor brainwave activity, has become a central device … …Journal of Computer Science, Vol. 21, Issue 11 · 11 Feb 2026 · 1,412 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvanced Assessing Techniques of the Reproductive Performance of BullsGulzat Turysbayeva, Isatay Jakupov, Aisulu Kuzerbayeva, Zhanargul ZharkimbayevaThe sperm quality supplied by producers is an urgent problem in the field of livestock breeding. Therefore, monitoring the health of male producers and sperm quality is of great priority. The study aimed to assess the reproductive performance of bulls using laboratory, clinical, morphological, ultrasound and reflexological techniques. A total of 17 heads of Kazakh-white-headed, Holstein-Frieze and Simmental breeds were … …American Journal of Animal and Veterinary Sciences, Vol. 18, Issue 1 · 23 Jan 2023 · 5,666 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Learning Platform for Computer Numerical Control (CNC) LaboratoryCharinee Chaichana, Seetala Wongkalasin, Apichat SanrutsadakornInformation Technology has played a major role in education. Rajamangala University of Technology, Isan Sakonakhon Campus, is committed to promoting a 21st Century education. For example, the university provides an environment that supports this development by integrating the use of Computer Numerical Control (CNC) in teaching practices. The model of CNC machines used in teaching and learning is outdated though, … …Journal of Computer Science, Vol. 18, Issue 8 · 4 Aug 2022 · 6,951 accessesView PDFCite
Research ArticleOpen accessIn the abstractGermination Study and Monitoring in the Nursery of Young Seedlings of Garcinia mangostana L.Haba Jean Florent, Dembele Ardjouma, Koffi Kouao Jean et al.Mangosteen tree (Garcinia mangostana L.) is a plant of the Clusiaceae family cultivated for its particular taste and for its excellent medicinal properties. However, the vegetative propagation of the plant by cuttings or grafting being difficult to achieve, seed germination remains the main means of production used. This study was therefore initiated with the aim of determining the influence of … …American Journal of Agricultural and Biological Sciences, Vol. 16, Issue 1 · 23 Sep 2021 · 7,440 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Geographical Land Structure Using Convolution Neural Network and Transfer LearningMustafa Majeed Abd Zaid, Ahmed Abed Mohammed, Putra SumariSatellite imagery has dramatically revolutionized the field of geography by giving academics, scientists, and policymakers unprecedented global access to spatial data. Manual methods typically require significant time and effort to detect the generic land structure in satellite images. This study can produce a set of applications such as urban planning and development, environmental monitoring, disaster management, etc. Therefore, the research … …Journal of Computer Science, Vol. 20, Issue 12 · 24 Oct 2024 · 5,079 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 593 accessesView PDFCite
Research ArticleOpen accessIn the abstractClimate-Driven Productivity Responses and Implications for Genetic Adaptation and Breeding of Boreal Trees in KazakhstanZhadyra Baigazakova, Kuralay Mazarzhanova, Asset Satayev et al.Kazakhstan’s boreal and forest-steppe forests form the southern ecotonal edge of the West Siberian taiga, where relatively small changes in heat and moisture can trigger disproportionate impacts on tree growth, mortality, and regeneration. Although forests cover only ~4% of Kazakhstan, they provide critical ecosystem services: stabilizing hydrological regimes, buffering microclimates, protecting agricultural lands from wind and water erosion, and supporting … …OnLine Journal of Biological Sciences, Vol. 26, Issue 3 · 10 Aug 2026 · 709 accessesView PDFCite
Research ArticleOpen accessIn the abstractGait Analysis Combining Sports Biomechanics and ImagingChao ZhuAiming at the problems of marker positioning error, soft tissue interference, and insufficient personalized modeling ability in traditional gait analysis, this study proposes a gait assessment method that integrates sports biomechanics and multimodal imaging analysis. Firstly, based on the public OU-ISIR gait database, a Convolutional Neural Network (CNN) is used to extract the key gait features in the human silhouette … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 20 Jul 2026 · 850 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection from EEG Signal Using Progressive Channel Selection and Deep LearningSuraiya Akter Mumu, Shupta Das, M. A. H. Akhand et al.Epileptic Seizures (ES), marked by abrupt abnormal electrical discharges in the brain, represent the primary symptom of epilepsy, making timely and accurate detection critical because of their unpredictable recurrence and potentially severe consequences. The Electroencephalogram (EEG), a widely used, non-invasive, and economical method for monitoring brain activity, plays a key role in automated ES detection through Machine Learning (ML) and … …Journal of Computer Science, Vol. 22, Issue 6 · 8 Jul 2026 · 1,393 accessesView PDFCite