Showing 301 - 320 results of 334 for search '(( elements could algorithm ) OR ((( data encoding algorithm ) OR ( data learning algorithm ))))', query time: 0.13s Refine Results
  1. 301

    Generic metadata representation framework for social-based event detection, description, and linkage by Abebe, Minale A.

    Published 2020
    “…SEDDaL consists of four main modules for: i) describing social media objects in a generic Metadata Representation Space Model (MRSM) consisting of three composite dimensions: temporal, spatial, and semantic, ii) evaluating the similarity between social media objects’ descriptions following MRSM, iii) detecting events from similar social media objects using an adapted unsupervised learning algorithm, where events are represented as clusters of objects in MRSM, and iv) identifying directional, metric, and topological relationships between events following MRSM’s dimensions. …”
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  2. 302

    Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test by Hasan T. Abbas (8115014)

    Published 2019
    “…Furthermore, personal information such as age, ethnicity and body-mass index was also a part of the data-set. Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. …”
  3. 303
  4. 304

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

    Published 2001
    “…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data.…”
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  5. 305

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

    Published 2001
    “…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data…”
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  6. 306

    Exploratory risk prediction of type II diabetes with isolation forests and novel biomarkers by Yousef, Hibba

    Published 2024
    “…In particular, Isolation Forest (iForest) was applied as an anomaly detection algorithm to address class imbalance. iForest was trained on the control group data to detect cases of high risk for T2DM development as outliers. …”
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  7. 307
  8. 308

    Digital-Twin-Based Diagnosis and Tolerant Control of T-Type Three-Level Rectifiers by Ali Sharida (17947847)

    Published 2023
    “…To develop the DT, a dense deep neural network (DNN) machine learning approach is used. The DT is trained offline using a set of experimental data and updated online to get the maximum possible accuracy. …”
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  10. 310

    Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

    Published 2024
    “…The first method uses an offline technique based on a global optimizer called the CMA-ES algorithm and the second one uses LSTM in its different forms to learn the online adjustment of the fusion weights between the two tracks. …”
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  11. 311
  12. 312

    Clustering Tweets to Discover Trending Topics about دبي (Dubai) by ALYALYALI, SALAMA KHAMIS SALEM KHAMIS

    Published 2018
    “…One of these social networks is Twitter - a microblogging hub and rich environment of data. Scanning tweets online is a hard task and searching effortlessly to find intended topic from huge amount of data is also time consuming. …”
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  13. 313

    Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic by Saeed Al-Maroof, Rana

    Published 2020
    “…The study has made use of Google Meet© as an educational social platform in private higher education institutes. The data obtained from the study were analyzed by using the partial least squares structural equation modeling (PLS-SEM) and machine learning algorithms. …”
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  14. 314
  15. 315

    Real-Time Social Robot’s Responses to Undesired Interactions Between Children and their Surroundings by Ahmad Yaser Alhaddad (7017434)

    Published 2022
    “…Additionally, we evaluate the performance of the best developed model with children. Machine learning algorithms experiments showed that XGBoost achieved the best performance across all metrics (e.g., accuracy of 90%) and provided fast predictions (i.e., 0.004 s) for the test samples. …”
  16. 316

    CEAP by Abdel Wahab, Omar

    Published 2016
    “…We propose as well a propagation algorithm that disseminates only the final decisions (instead of the whole dataset) among clusters with the aim of reducing the overhead of either exchanging results between each set of vehicles or repeating the detection steps for the already detected malicious vehicles. …”
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  17. 317

    Query acceleration in distributed database systems by Haraty, Ramzi A.

    Published 2001
    “…Query optimization strategies aim to minimize the cost of transferring data across networks. Many techniques and algorithms have been proposed to optimize queries. …”
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  18. 318

    Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... by BACHIR, HIBAH AHMAD

    Published 2025
    “…Findings referred these barriers to limited teacher training, technological accessibility, and data privacy concerns, as well as ethical biases in AI algorithms. …”
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  19. 319

    PROVOKE: Toxicity trigger detection in conversations from the top 100 subreddits by Hind Almerekhi (7434776)

    Published 2022
    “…Implications are that toxicity trigger detection algorithms can leverage generic approaches but must also tailor detections to specific communities.…”
  20. 320

    Deepfakes Signatures Detection in the Handcrafted Features Space by Hamadene, Assia

    Published 2023
    “…In the Handwritten Signature Verification (HSV) literature, several synthetic databases have been developed for data-augmentation purposes, where new specimens and new identities were generated using bio-inspired algorithms, neuromotor synthesizers, Generative Adversarial Networks (GANs) as well as several deep learning methods. …”
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