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299 results for “neural system”
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Research ArticleOpen accessIn the keywordsA Novel Approach to Head positioning using Fixed Center Interpolation Net with Weight Elimination AlgorithmMahmoud Zaki IskandaraniA reliable algorithm for head movements inside a vehicle is designed. The proposed algorithm allowed the adjustment of basic functions such as indicators, mirrors and reverse lights based on the driver final head position. The algorithm system mapped a predefined coordinates for driver’s head that resulted in a computable geometry via a sensory system which is fed to the vehicle … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,309 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe Artificial Neural Network Based Approach for Mortality Structure AnalysisSokolova M. Kursk, Rashad J. Rasras, D. SkopinThe theoretical outcomes and experimental results of applying of Artificial Neural Networks towards mortality structure examination in Russian Federation are presented in the paper. The most influencing classes of diseases are selected by sensitivity analysis. It is proved that Neural Network Models appear to be an adequate tool for mortality structure examination. Some interesting results for males and females total … …American Journal of Applied Sciences, Vol. 3, Issue 2 · 28 Sep 2006 · 7,061 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 422 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA REVIEW OF INTELLIGENT CONTROL SYSTEMS APPLIED TO THE INVERTED-PENDULUM PROBLEMPedro Ponce, Arturo Molina, Eugenio AlvarezThis study shows the latest advances in the application of intelligent control to the inverted-pendulum problem. A complete review regarding intelligent control design is presented in this study in order to show the most important artificial intelligence methods used for controlling an Inverted-Pendulum. Also this study proposed the use of a neural-fuzzy-with-genetic-algorithms controller for the inverted pendulum problem which gives … …American Journal of Engineering and Applied Sciences, Vol. 7, Issue 2 · 7 Apr 2014 · 8,387 accessesView PDFCite
Review ArticleOpen accessIn the keywordsRCMV ALL-03 Model and Study of CMV Pathogenesis in Congenital InfectionAshwaq Ahmed Abdullah, Krishnan Nair Balakrishnan, Yusuf Abba et al.Cytomegalovirus (CMV) is one of the most commonly studied members of the Herpesviridae family. So far several strains have been identified but human CMV (HCMV) remains the most important due to its ability to infect humans and also cross the placenta causing neonatal infection and mortality. However, there are several limitations in the study of this strain which includes availability … …American Journal of Animal and Veterinary Sciences, Vol. 10, Issue 3 · 18 Jul 2015 · 8,065 accessesView PDFCite
Research ArticleOpen accessIn the keywordsEmotion Regulation in Childhood with Cancer (Acute Lymphocytic Leukemia)Siti Yuyun Rahayu Fitri, Ediasri T. Atmodiwirjo, Winarini WilmanProblem statement: Emotion regulation in children with Leukemia actively undergoing a chemotherapy program has distinctive forms of regulation in the research on different cultures. Furthermore, the capability of children to regulate their emotions during a dynamic process involving frequent hospitalization and painful treatment is of increasing interest to researchers. This must also take into account how the role of culture … …Current Research in Medicine, Vol. 2, Issue 2 · 4 Oct 2011 · 7,587 accessesView PDFCite
Research ArticleOpen accessIn the keywordsIdentification of Electrooculography Signals Frequency Energy Distribution Using Wavelet AlgorithmW.M. Bukhari, W. Daud, Rubita Sudirman, Camallil OmarProblem statement: The time frequency analysis of non-stationary signals has been the considerable research effort in recent years. Wavelet transform is one of the favored tool for the analyzing the biomedical signals. Approach: We describe the identification of Electro-Oculograph (EOG) signals of eye movement potentials by using wavelet algorithm which gives a lot of information than FFT. The capability of … …Journal of Computer Science, Vol. 7, Issue 11 · 18 Aug 2011 · 8,556 accessesView PDFCite
Research ArticleOpen accessIn the keywordsBehaviour Based Worm Detection and Signature AutomationMohammed Anbar, Selvakumar Manickam, Al-Samarraie Hosam et al.Problem statement: A worm is a malicious piece of code that self-propagates, often via network connections, to exploit security flaws in computers connected through the network. In general, worms do not need any human intervention to propagate and are considered a real threat to network assets and the properties of organizations. An Intrusion Detection Systems (IDSs) are employed to detect … …Journal of Computer Science, Vol. 7, Issue 11 · 6 Sep 2011 · 6,899 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 711 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 · 1,409 accessesView PDFCite