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99 results for “Computational-Based Research”
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Research ArticleOpen accessIn the keywordsComputational Techniques for Stability Analysis of a Class of Dynamic Economic ModelsGeorge E. Halkos, Kyriaki D. TsilikaModern microeconomics and macroeconomics study dynamic phenomena. Dynamics could predict future states of an economy based on its structural characteristics. Dynamic models in discrete time discrete state economic systems may take the form of one single linear difference equation or a system of linear difference equations. In this study we use Xcas and Mathematica as software tools in order to … …American Journal of Applied Sciences, Vol. 9, Issue 12 · 12 Dec 2012 · 7,379 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancing Digital Forgery Detection: A Comparative Analysis of U-Net, Buster Net, Efficient B0+ U-Net, and VGG 16+ U-Net ModelsPreeti Dhiman, Usha ChauhanForgery Detection in the area of digital images is indispensable for insuring authenticity, particularly in detecting Copy-Move, Splicing. In this research, a meticulous analysis of latest learning architectures i.e. U-Net, Buster Net, Efficient B0+U-Net and VGG16+U-Net are compared for the detecting these types of forgeries. U-Net is popular due to its potent segmentation capabilities to provide pixel-level forgery localization while … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 383 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 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 · 2,458 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptivity in Role-Based Access Control During Stochastic Situations: A Comprehensive Study between Graph and Relational DatabasesKriti Srivastava, Dhruv Jain, Aarya Kamdar et al.Role-based control is straightforward to implement in static systems where there are specific policies for role and resource mapping. The main challenge is faced in dynamic and unpredictable systems with erratic workflows. Conventional methods prove to be inadequate in dynamic environments. Over the Years methods suggested include probabilistic, machine learning, ontology, and decision tree models to improve the adaptability. However, … …Journal of Computer Science, Vol. 20, Issue 12 · 18 Nov 2024 · 5,372 accessesView PDFCite
Research ArticleOpen accessIn the abstractSemSimp: A Parametric Method for Evaluating the Semantic Similarity of Digital ResourcesAntonio De Nicola, Anna Formica, Ida Mele, Francesco TaglinoAbioui, H., Idarrou, A., Bouzit, A., & Mammass, D. (2018). Towards a Novel and Generic Approach for OWL Ontology Weighting. Procedia Computer Science, 127, 426–435. https://doi.org/10.1016/j.procs.2018.01.140 Adhikari, A., Dutta, B., Dutta, A., Mondal, D., & Singh, S. (2018). An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology. Journal of the Association for … …Journal of Computer Science, Vol. 20, Issue 8 · 27 May 2024 · 5,773 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Comprehensive Review of Post-Quantum Cryptography AlgorithmsSamandeep Kaur, Jaswinder SinghThe development of quantum computing has been rapid, and an existential threat to computational hardness assumptions that underlie today's public-key cryptography has been encountered. This manuscript is a complete and thoroughly organized review of Post-Quantum Cryptography (PQC), discussing the mathematical concepts, complexity, and mechanisms of the algorithms that underpin quantum-safe security infrastructures. Rather than the principles of quantum mechanics, the … …Journal of Computer Science, Vol. 22, Issue 9 · 25 Sep 2026 · 723 accessesView PDFCite
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 abstractDiscrete to Continuous Algorithm for Optimal Channel Selection to Detect Alcoholism through EEG RecordingsHayat Sedrati, Wajih Rhalem et al.Alcoholism is a serious public health issue, and early diagnosis of this brain disease can be performed by analyzing Electroencephalogram (EEG) signals. However, the high dimensionality of EEG datasets requires significant computational time and resources for the automatic processing of EEG signals. This study proposes a novel method to reduce EEG dataset dimensionality using a Discrete to Continuous algorithm (DtC) … …Journal of Computer Science, Vol. 19, Issue 1 · 17 Jan 2023 · 5,904 accessesView PDFCite