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Showing 221 - 240 results of 328 for search '(((( data negative algorithm ) OR ( data processing algorithm ))) OR ( elements data algorithm ))', query time: 0.10s Refine Results
  1. 221

    A novel few shot learning derived architecture for long-term HbA1c prediction by Marwa Qaraqe (10135172)

    Published 2024
    “…Short-term CGM time-series data are processed using both novel image transformation approaches, as well as using conventional signal processing methods. …”
  2. 222

    Automated skills assessment in open surgery: A scoping review by Hawa Hamza (17707224)

    Published 2025
    “…We highlight the progress in automated skills assessment during open surgery with advancements in sensor technology, and AI algorithms with high prediction accuracies. Further developments in data acquisition and processing methods are essential to facilitate clinical implementation of such technologies.…”
  3. 223

    Full-fledged semantic indexing and querying model designed for seamless integration in legacy RDBMS by Tekli, Joe

    Published 2018
    “…To do so, we design and construct a semantic-aware inverted index structure called SemIndex, extending the standard inverted index by constructing a tightly coupled inverted index graph that combines two main resources: a semantic network and a standard inverted index on a collection of textual data. We then provide a general keyword query model with specially tailored query processing algorithms built on top of SemIndex, in order to produce semantic-aware results, allowing the user to choose the results' semantic coverage and expressiveness based on her needs. …”
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  4. 224

    Dataset built for Arabic Sentiment Analysis by AL MUKHAITI, AYESHA JUMAA SALEM

    Published 2016
    “…Key stages of the framework takes three dimensions. We followed an Algorithm which involves Data Acquisition stage, Filtering Stage and Annotation Stage. …”
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    Optimizing ADWIN for Steady Streams by Moharram, Hassan

    Published 2022
    “…However, online machine learning comes with many challenges for the different aspects of the learning process, starting from the algorithm design to the evaluation method. …”
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  8. 228

    Integrative toxicogenomics: Advancing precision medicine and toxicology through artificial intelligence and OMICs technology by Ajay Vikram Singh (204056)

    Published 2023
    “…As personalized medicine and toxicogenomics involve huge data processing, AI can expedite this process by providing powerful data processing, analysis, and interpretation algorithms. …”
  9. 229

    Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning by ALFALASI, FARIS Jr

    Published 2023
    “…Pre-processing is a vital part of the data preparation process for cyberbullying detection. …”
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  10. 230

    Spectral energy balancing system with massive MIMO based hybrid beam forming for wireless 6G communication using dual deep learning model by Ramesh Sundar (19326046)

    Published 2024
    “…The proposed approach of DDN is trained with proper data sequences used for communication and the training phase is conducted with the norms of numerous channel variants. …”
  11. 231

    Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

    Published 2023
    “…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER<sup>+</sup>), HER2<sup>+</sup>, ER<sup>+</sup>HER2<sup>+</sup>, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …”
  12. 232

    Evacuation of a highly congested urban city by El Khoury, John

    Published 2017
    “…As the evacuation route planning is computationally challenging, an evacuation scheduling algorithm was adopted to expedite the solution process. …”
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  13. 233

    Shuffled Linear Regression with Erroneous Observations by Saab, Samer S.

    Published 2019
    “…Existing methods are either applicable only to data with limited observation errors, work only for partially shuffled data, sensitive to initialization, and/or work only with small dimensions. …”
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  14. 234

    High-order parametrization of the hypergeometric-Meijer approximants by Abouzeid M. Shalaby (16329062)

    Published 2023
    “…<p>In this work, we introduce an extension to the hypergeometric algorithm we developed before for the resummation of divergent series.The extension overcome the time-consuming problem we face in the parametrization process of the hypergeometric approximants. …”
  15. 235

    Student advising decision to predict student's future GPA based on Genetic Fuzzimetric Technique (GFT) by Kouatli, Issam

    Published 2015
    “…Decision making and/or Decision Support Systems (DSS) using intelligent techniques like Genetic Algorithm and fuzzy logic is becoming popular in many new applications. …”
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  16. 236

    Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

    Published 2022
    “…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
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  17. 237

    A Novel Encryption Method for Dorsal Hand Vein Images on a Microcomputer by M. Z. Yildiz (16855476)

    Published 2019
    “…Second, the pre- and post-processed images were encrypted with a new encryption algorithm in the microcomputer environment. …”
  18. 238

    The Role of Artificial Intelligence in Decoding Speech from EEG Signals: A Scoping Review by Uzair Shah (15740699)

    Published 2022
    “…The study selection process was carried out in three phases: study identification, study selection, and data extraction. …”
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    Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort by Sergio Márquez-Sánchez (19437985)

    Published 2023
    “…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”