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101 articles for “Hybrid Application”
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Research ArticleOpen accessEvery word in the titleMalware Detection Based on Hybrid Signature Behaviour Application Programming Interface Call GraphAmmar Ahmed E. Elhadi, Mohd Aizaini Maarof, Ahmed Hamza OsmanProblem statement: A malware is a program that has malicious intent. Nowadays, malware authors apply several sophisticated techniques such as packing and obfuscation to avoid malware detection. That makes zero-day attacks and false positives the most challenging problems in the malware detection field. Approach: In this study, the static and dynamic analysis techniques that are used in malware detection are … …American Journal of Applied Sciences, Vol. 9, Issue 3 · 9 Jan 2012 · 9,150 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Fog Resource Provisioning and Resource Allocation using MKFCM and FPANagarjun E, Dharamendra Chouhan, Dilip Kumar SMThe expansion of Internet of Things (IoT) deployments has motivated the Fog Computing (FC) paradigm, which brings mobile-edge and cloud resources together under a single model. Allocating and provisioning application tasks across such environments poses challenges due to constrained resource capabilities, heterogeneity, mobility, network hierarchy, and unpredictability. This paper addresses the need for additional computing devices that prioritize delay-sensitive applications … …Journal of Computer Science, Vol. 22, Issue 10 · 6 Oct 2026 · 472 accessesView PDFCite
Research ArticleOpen accessIn the abstractActive Reset and Scheduling in Fault-Tolerant Quantum-Classical Cloud ComputingMohamed El-DosukyQuantum-classical cloud computing refers to a hybrid computing model that integrates quantum computing with classical computing resources, typically hosted on the cloud. The objective of this paper is threefold: First, to scrutinize the computing paradigm of quantum-classical cloud computing; second, to study the three pillars of the underpinning techniques: Active reset, scheduling, and fault tolerance; third, to demonstrate the realization … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Sep 2026 · 775 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,042 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Based Evaluation of Museum Display Design through Hybrid IndoBERT and Rule-Based LexiconErneza Dewi Krishnasari, Yaddarabullah, Bayyinah Nurrul Haq et al.Traditional museums remain vital cultural institutions but face persistent challenges in engaging contemporary audiences. The Wayang Museum in Indonesia, despite partial digital renovation, continues to rely heavily on static, text-based displays that often hinder visual comfort and informational comprehension. Conventional sentiment analysis techniques have demonstrated limitations in accurately capturing the subtle feedback from visitors, particularly within the culturally nuanced contexts … …Journal of Computer Science, Vol. 22, Issue 5 · 30 May 2026 · 1,340 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,754 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmploying Hybrid Serial Cascaded Adaptive Network for Anomaly Detection and Prevention in IoT Time Series Data With Optimal Interdomain RoutingKante Satyanarayana, K. VenkateshNowadays, emerging Internet of Things (IoT) in data processing becomes interested research topic and is used for various applications. This varies from big data processing and analytics for accumulating entire sensor data to detect and generate long-term trends. Nevertheless, this results in the requirement for resources like the execution of power, memory, and bandwidth, in which resource-constrained IoT tools suffers … …Journal of Computer Science, Vol. 22, Issue 1 · 21 Feb 2026 · 1,476 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Computational Efficiency Analysis of LSB and Hybrid Steganographic MethodsDivya Sharma, Chander PrabhaElectronic Medical Images (EMI) are of various types such as X-rays, CT scans, MRIs, etc. EMIs are generally large, but they vary in dimensions and sizes based on the body part to which they belong. Not much research has been done to secure EMIs due to their varied and large sizes, while ensuring their accessibility for real-time transmission. Where access … …Journal of Computer Science, Vol. 21, Issue 10 · 28 Nov 2025 · 2,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-Source Cyber Intrusion Detection Using Ensemble Machine LearningTaskeen Ali Khan, Sara Abbas, Biswaranjan Senapati et al.The increased usage of digital technologies across businesses has led to an increase in cybercrime. It is difficult for existing intrusion detection systems to detect highly skilled hacking attempts; however, machine learning has been suggested as a way around these drawbacks. The purpose of this study is to evaluate how well various machine learning algorithms identify and stop cyberattacks in … …Journal of Computer Science, Vol. 21, Issue 1 · 14 Dec 2024 · 5,705 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Hybrid Model to Predict the Performance of Trainee Teachers Based on Clustering and ClassificationYissam Lakhdar, Khawla EL-Bendadi, Brahim BakkasThis article explores how artificial intelligence, particularly machine learning, can be used to assess and predict the performance of trainee teachers in Morocco. Considering the country's focus on integrating technology into education and the challenges posed by the COVID-19 pandemic, the authors propose a novel hybrid model that combines clustering and classification algorithms. This model aims to understand the Information … …Journal of Computer Science, Vol. 20, Issue 9 · 26 Jun 2024 · 5,106 accessesView PDFCite