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Research ArticleOpen accessEvery word in the titleThe Definition of Extended High-level Timed Petri NetsCheng Guangming, Liao Minghong, Wu XianghuMany extensions of Petri nets have been proposed to model the behaviors and time relations of embedded system, yet these models are all based on some assumptions about the behaviors of embedded systems. Especially they all do not have the actual ability to model interrupt mechanism of embedded system. A new net which is called Extended High Level Timed Petri … …Journal of Computer Science, Vol. 2, Issue 2 · 28 Feb 2006 · 7,042 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleThe Use of Neural Network to Recognize the Parts of the Computer MotherboardAbbas M. Ali, S. D. Gore, Musaab AL-SarierahThis study suggests a new approach of learning which utilizes the techniques of computer vision to recognize the parts inside the motherboard. The main thrust is to identify different parts of the motherboard using a Hopfield Neural Network. The outcome of the net is compared with the objects stored in the database. The proposed scheme is implemented using bottom -up … …Journal of Computer Science, Vol. 1, Issue 4 · 31 Dec 2005 · 6,871 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEnergy and Carbon Flux Coupling: Multi-ecosystem Comparisons Using Artificial Neural NetworkAssefa M. Melesse, Rodney S. HanleyA multi-ecosystems carbon flux simulation from energy fluxes is presented. A new statistical learning technique based on Artificial Neural Network (ANN) back propagation algorithm and multi-layer perceptron architecture was used in the CO2 simulation. Four input layers (net radiation, soil heat flux, sensible and latent heat flux) were used for training (calibration) and testing (verification) of model outputs. The 15-days … …American Journal of Applied Sciences, Vol. 2, Issue 2 · 28 Feb 2005 · 7,349 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Integrated Framework to Predict the Strength of New SMILE Using Graph Attention NetworkSandhi Kranthi Reddy, S. V. G. ReddyMachine Learning (ML) and Deep Learning (DL) have significantly advanced various fields, including healthcare, finance, autonomous systems, and scientific research. In healthcare, these technologies have been widely applied to disease prediction, such as cancer and diabetes. However, the challenge of drug resistance persists, creating a need for more effective drugs. Developing new drugs is a complex, expensive, and time-intensive process, … …Journal of Computer Science, Vol. 21, Issue 10 · 25 Nov 2025 · 2,167 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleExploratory Data Analysis of Applications of Encryption for Netflix by ML ModelsAnanth Maria Pushpa, Subramanian ShanmugamThis study examines the performance of various machine learning algorithms in analyzing Netflix's dataset, with a focus on encryption methods used for data protection. We evaluated several models including Ada BoostM1, IBk, Random Forest, and Decision Stump using multiple performance metrics. This work analysis revealed that the Ada BoostM1 model achieved the highest accuracy at 97.14%, outperforming other algorithms. It … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 1,930 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAdaptive Cybersecurity: Dynamically Retrainable Firewalls for Real-Time Network ProtectionSina AhmadiThe growing complexity of cyberattacks has necessitated the evolution of firewall technologies from static models to adaptive, machine learning-driven systems. This research introduces “Dynamically Retrainable Firewalls”, which respond to emerging threats in real-time. Unlike traditional firewalls that rely on static rules to inspect traffic, these advanced systems leverage machine learning algorithms to analyze network traffic patterns dynamically and identify threats. … …Journal of Computer Science, Vol. 21, Issue 9 · 7 Nov 2025 · 2,562 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Feature Reduction Techniques for Enhanced Network Threat Detection in Wireless Sensor NetworksBikash Kalita, Satyajit SarmahThe security of Wireless Sensor Networks (WSNs) is currently seriously threatened by numerous threats. Consequently, a number of applications are offered to regulate data and information sharing along with the related security features that need to be maintained throughout data transfer. This study suggests an intelligent feature reduction methodology based on machine learning that uses Modified Principal Component Analysis (MPCA) … …Journal of Computer Science, Vol. 21, Issue 8 · 10 Oct 2025 · 2,295 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMFQ: Network Bandwidth Utilization among Data Centers on Software Defi ned Network Using Multilevel-Feedback QueueR Shanthy, K Sutha, J Emerson RajaThe growing complexity of network traffic patterns and congestion within data centers necessitate innovation in traditional network infrastructure. While advancements in storage, computing, and applications have progressed rapidly, networking has remained relatively stagnant, limiting the overall performance of data centers. Software-Defined Networking (SDN) emerges as a powerful solution by decoupling the control plane from the data plane, offering enhanced flexibility … …Journal of Computer Science, Vol. 21, Issue 7 · 29 Jul 2025 · 3,748 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRK4 Differential Equation to improve QoS in an eUTRAN LTE Network: A Deterministic vs. Stochastic ApproachBrou Pacôme, Pandry Ghislain, Bodjré Aka Hugues Félix, Oumtanaga SouleymaneImproving Quality of Service (QoS) in an eUTRAN LTE network is essential to guarantee optimal performance in the face of dynamic variations in user traffic and radio channel interference. In this context, this paper explores the use of 4th-order Runge-Kutta differential equations (RK4) to model and optimize radio resource management, by comparing a deterministic approach, which assumes stable and predictable … …Journal of Mathematics and Statistics, Vol. 21, Issue 1 · 3 Jul 2025 · 5,880 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleResearch on Deep Neural Network for Afaan-Oromo Language Text-to-Speech SynthesisDiriba Gichile Rundasa, Arulmurugan Ramu, Teshome Debushe Adugna et al.Text-to-speech synthesis is the automatic translation of unlimited natural language sentences from Text to spoken form that closely mimics the spoken form of the same Text by a native speaker of the language. The purpose of a Texttext-to-speech synthesizer is to generate comprehensible, natural signalling human voice from text transcriptions. Despite the wide range of potential applications for Text-to-speech systems, … …Journal of Computer Science, Vol. 21, Issue 5 · 14 Apr 2025 · 7,360 accessesView PDFCite