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decrease » increase (توسيع البحث)
reduction » education (توسيع البحث)
networks » network (توسيع البحث)
decrease » increase (توسيع البحث)
reduction » education (توسيع البحث)
networks » network (توسيع البحث)
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Efficient experimental design for uncertainty reduction in gene regulatory networks
منشور في 2015"…The proposed approximate method also outperforms the random selection policy significantly.</p><p dir="ltr">Erratum - Erratum to: Efficient experimental design for uncertainty reduction in gene regulatory networks: <a href="https://dx.doi.org/10.1186/s12859-015-0839-y" target="_blank">https://dx.doi.org/10.1186/s12859-015-0839-y</a>, published online 14 December 2015.…"
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Degree-Based Network Anonymization
منشور في 2020"…Our thorough experimental studies provide empirical evidence of the effectiveness of the new approach; by specifically showing that the introduced anonymization algorithm has a negligible effect on the way nodes are clustered, thereby preserving valuable network information while significantly improving the data privacy.…"
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masterThesis -
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VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems
منشور في 2019"…In this paper, we introduce VHDRA, a Vertical and Horizontal Data Reduction Approach, to improve the classification accuracy and speed of the NNGE algorithm and reduce the computational resource consumption. …"
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Morphological changes in amblyopic eyes in choriocapillaris and Sattler’s layer in comparison to healthy eyes, and in retinal nerve fiber layer in comparison to fellow eyes through...
منشور في 2021"…Results The method of measuring reflectivity is good to excellent reliability for all regions of interest except the fourth. The mean reflectivity of the choriocapillaris and Sattler’s layer in amblyopic eyes were significantly lower than in healthy eyes (p = 0.003 and p = 0.008 respectively). …"
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Modelling the Impact of Bottlenecks on Arterial Travel Time Using Neural Networks
منشور في 2012احصل على النص الكامل
doctoralThesis -
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ECP: Error-Aware, Cost-Effective and Proactive Network Slicing Framework
منشور في 2024"…<p dir="ltr">Recent advancements in Software Defined Networks (SDN), Open Radio Access Network (O-RAN), and 5G technology have significantly expanded the capabilities of wireless networks, extending beyond mere data transmission. …"
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Exploring Effects of Mental Stress with Data Augmentation and Classification Using fNIRS
منشور في 2025"…Linear discriminant analysis (LDA) showed a maximum accuracy of 60%, whereas non-augmented data classified by a convolutional neural network (CNN) provided the highest classification accuracy of 73%. …"
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EEG-Based Multi-Level Mental State Classification Using Partial Directed Coherence and Graph Convolutional Networks: Impact of Binaural Beats on Stress Mitigation
منشور في 2025"…Utilizing EEG signals, graph convolutional neural networks (GCNs), and binaural beats stimulation (BBs), the research investigates stress detection and reduction in two population sample groups with distinct baselines (group 1: low daily baseline, and group 2: stressed daily baseline). …"
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A full privacy-preserving distributed batch-based certificate-less aggregate signature authentication scheme for healthcare wearable wireless medical sensor networks (HWMSNs)
منشور في 2023"…The communication cost is 400 bits which is a significant reduction when compared with its counterparts. …"
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Estimating the Transformer Health Index Using Artificial Intelligence Techniques
منشور في 2016احصل على النص الكامل
doctoralThesis -
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Learning-Based Automatic Modulation Classification
منشور في 2015احصل على النص الكامل
doctoralThesis -
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Scalable Nonparametric Supervised Learning for Streaming and Massive Data: Applications in Healthcare Monitoring and Credit Risk
منشور في 2025"…Receiver Operating Characteristic (ROC) analysis shows superior Area Under the Curve (AUC) for the offline classifier but at a significant computational cost. A second study on larger database of credit scoring confirms these findings, showing that the online classifier achieves an F1-score of 96.40% and an accuracy of 93.08%, closely matching the performance of neural networks (96.46%, 93.22%) and boosting (96.51%, 93.31%). …"