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Research ArticleOpen accessIn the abstractIntelligent Traffic Light System Using Convolutional Neural Network to Optimize Vehicle Flow in IndonesiaBhustomy Hakim, Fergie Joanda Kaunang, Yemima Monica Geasela, Regina HillaryTraffic congestion remains a persistent challenge in major Indonesian cities due to rapidly increasing vehicle density and the continued reliance on fixed-time traffic signal scheduling. This study aims to develop an intelligent traffic light system that dynamically adjusts sequencing based on real-time road conditions. A dataset of 902 CCTV images was collected from intersections in six large cities across Indonesia, … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 2,155 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Multi Task Analysis Model Based on EEG Features in the Study of the Correlation between Depression and Sleep Disorders in College StudentsFeng MaWith the improvement of multi-modal technology, research on depression recognition combining multiple biological signal features has been increasing. Electroencephalogram signals reflect brain activity, and by analyzing their characteristics, the accuracy and stability of depression recognition can be effectively improved. Therefore, this study proposes a correlation analysis between depression and sleep disorders in college students based on electroencephalogram feature analysis, innovatively … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 2 Feb 2026 · 1,994 accessesView PDFCite
Research ArticleOpen accessIn the abstractFault-Tolerant Control of a Nonlinear Uncertain System: A Neural Network-Based Passive Approaches and Comparative Study with State-of-the-Art Control ApproachesSejal K. Raval, Himanshukumar Rajendrabhai Patel, Vipul A. ShahThis article suggests passive methods for designing Fault-Tolerant Control (FTC) for nonlinear uncertain systems with actuator and leak faults. To anticipate the Fault-Tolerant Control (FTC) action to overcome the actuator and leak faults, two-layer Feed-Forward Back-Propagation Neural Network (FFBPNN) and two-layer Cascade Forward Neural Network (CFNN) have been used, it will also tolerate external process additive disturbances. We employ the … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 6,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Exploitation of Errors in Redundant Residue Number System ArchitectureYaw AfriyieResidue Number System (RNS) is an unweighted number system that symbolizes big integers with smaller numbers. It can perform operations in particular addition and multiplication in parallel. Because of this property, RNS is extensively used in communication, Finite Impulse Response (FIR), cryptography and signal processing devices. The transfer of data in digital channels is very important for some critical applications … …American Journal of Applied Sciences, Vol. 18, Issue 1 · 30 Jun 2021 · 7,616 accessesView PDFCite
Research ArticleOpen accessIn the abstractFDIR Strategy for Sensor Faults During Re-entry FlightGianfranco Morani, Mariangela Di LorenzoIn this study, a Fault Detection, Isolation and Reconfiguration (FDIR) strategy is proposed for dealing with the problem of single sensor faults during a re-entry flight. The proposed algorithms rely on a model based Fault Detection and Isolation. After the generation of a residual through a Kalman filter observer, detection is obtained via the estimation of residual signal statistics while … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 2 · 7 Apr 2018 · 8,690 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,134 accessesView PDFCite
Research ArticleOpen accessIn the abstractSpatial Interaction Image of Electroencephalography Signal during Epileptic Seizure on Flat ElectroencephalographyGoh Chien Yong, Tahir Ahmad, Normah MaanElectroencephalogram (EEG) is widely used for recording the brain electrical activity. It plays an important role in the detection and classification of epilepsy seizures. In addition, it is believed to possess the ability to detect the location of epileptic focus to some degree. In this study, an EEG data during seizure obtained is analysed and transformed into an image form, … …Journal of Mathematics and Statistics, Vol. 13, Issue 1 · 13 Mar 2017 · 6,899 accessesView PDFCite
InvestigationOpen accessIn the abstractDesign and Realization of Pre-Amplifier and Filters for on-Board Radar SystemN. Dinesh Kumar, R. Divya Ravali, Panchavati R. SrirekhaToday's warfare situation incorporates a considerable measure of innovative weaponry and every nation is attempting to outmaneuver the other utilizing high engineering, henceforth it is of most extreme criticalness to be at the front line of the bleeding edge innovation and having the best weapons conceivable to secure the country. One of the innovations which give the one having it … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 4 · 9 Nov 2015 · 7,803 accessesView PDFCite
Technical ReportOpen accessIn the abstractAnalysis of Low Probability of Intercept Radar Signals Using the Reassignment MethodDaniel L. Stevens, Stephanie A. SchuckersDigital intercept receivers are currently moving towards classical time-frequency analysis techniques for analyzing low probability of intercept radar signals. Although these techniques are an improvement over existing Fourier-based techniques, they still suffer from a lack of readability, due to poor time-frequency localization and cross-term interference, which may lead to inaccurate detection and parameter extraction. In this study, the reassignment method, … …American Journal of Engineering and Applied Sciences, Vol. 8, Issue 1 · 25 Mar 2015 · 7,210 accessesView PDFCite
Research ArticleOpen accessIn the abstractMULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTIONG. Palanivel, K. DuraiswamyWe propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which … …American Journal of Applied Sciences, Vol. 11, Issue 8 · 27 Jun 2014 · 6,776 accessesView PDFCite