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Showing 141 - 160 results of 382 for search '(((( elements cc3d algorithm ) OR ( complex based algorithm ))) OR ( level using algorithm ))', query time: 0.11s Refine Results
  1. 141

    A geometric-primitives-based compression scheme for testingsystems-on-a-chip by El-Maleh, A.

    Published 2001
    “…The increasing complexity of systems-on-a-chip with the accompanied increase in their test data size has made the need for test data reduction imperative. …”
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    article
  2. 142

    Semantics-based approach for detecting flaws, conflicts and redundancies in XACML policies by Jebbaoui, Hussein

    Published 2015
    “…First, our approach resolves the complexity of policies by elaborating an intermediate set-based representation to which the elements of XACML are automatically converted. …”
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    article
  3. 143

    A method for data path synthesis using neural networks by Harmanani, H.

    Published 2017
    “…The proposed algorithm has a running time complexity of O(1) for a neural network with n vertices and c cliques. …”
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    conferenceObject
  4. 144

    An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network by Tawfik Beghriche (19563184)

    Published 2021
    “…Such algorithms are state‐of‐the‐art in computer vision, language processing, and image analysis, and when applied in healthcare for prediction and diagnosis purposes, these algorithms can produce highly accurate results. …”
  5. 145

    A Survey of Data Clustering Techniques by Sobeh, Salma

    Published 2023
    “…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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    masterThesis
  6. 146

    Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

    Published 2023
    “…First, the comments were classified as (positive/negative/neutral), and then the negative comments were further classified into two categories based on their level of negativity (toxic, bullying). …”
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  7. 147

    Efficient Seismic Volume Compression using the Lifting Scheme by Khene, M. F.

    Published 2000
    “…A separable 3-D discrete wavelet transform (DWT) using long biorthogonal filters is used. The computation efficiency of the DWT is improved by factoring the wavelet filters using the lifting scheme. …”
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    article
  8. 148

    A heuristics for HTTP traffic identification in measuring user dissimilarity by Adeyemi R. Ikuesan (14157123)

    Published 2020
    “…This study reveals that, with the current complex nature of Internet and HTTP traffic, browser complexity, dynamic web programming structure, the surge in network delay, and unstable user behavior in network interaction, user-initiated requests can be accurately determined. …”
  9. 149
  10. 150

    A Geometric-Primitives-Based Compression Scheme for Testing Systems-on-a-Chip by El-Maleh, Aiman H.

    Published 2001
    “…The increasing complexity of systems-on-a-chip with the accompanied increase in their test data size has made the need for test data reduction imperative. …”
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    article
  11. 151

    Resources Allocation for Drones Tracking Utilizing Agent-Based Proximity Policy Optimization by De Rochechouart, Maxence

    Published 2023
    “…This paper presents a reinforcement learning agent-based model that works by incorporating the MESA environment with the Stone Soup radar systems simulator. …”
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  12. 152
  13. 153

    On-demand deployment of multiple aerial base stations for traffic offloading and network recovery by Sharafeddine, Sanaa

    Published 2019
    “…We present performance results for the proposed algorithm as a function of various system parameters and demonstrate its effectiveness compared to the close-to-optimal greedy approach and its superiority compared to recent related work from the literature.…”
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    article
  14. 154

    Modulation With Metaheuristic Approach for Cascaded-MPUC49 Asymmetrical Inverter With Boosted Output by Kaif Ahmed Lodi (16855518)

    Published 2020
    “…For the calculation of optimum angles, a meta-heuristic based Genetic Algorithm (GA) technique is employed. The generation of 49-level output requires 24 transitions in one quarter of a cycle. …”
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  17. 157

    FPGA-Based Network Traffic Classification Using Machine Learning by Elnawawy, Mohammed

    Published 2020
    “…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. In this paper, the suitability of packet-level and flow-level features is validated using stepwise regression and random forest feature selection. …”
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    article
  18. 158

    UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks by Ebrahimi, Dariush

    Published 2018
    “…We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. …”
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    article
  19. 159

    Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials by Ghouti, Lahouari

    Published 1997
    “…The proposed techniques are: i) a batch-type deconvolution method using the complex bicepstrum algorithm, and ii) automatic ultrasonic defect classification system using a modular learning strategy. …”
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    masterThesis
  20. 160

    An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

    Published 2022
    “…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …”