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Showing 1 - 20 results of 251 for search 'blank (plan OR learn) data processing', query time: 0.10s Refine Results
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    Sulfur oxidative coupling of methane process development and its modeling via machine learning by Giovanni Scabbia (13751501)

    Published 2022
    “…The outcomes of the simulated process were used to design a data-driven modeling approach, based on machine learning methods, and to evaluate its interpolation accuracy. …”
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    Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

    Published 2021
    “…One thousand distribution transformers' real data from Spain for three years are used to demonstrate the performance of the proposed methodology with a trade-off between accuracy and processing time.…”
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    LocationSpark: In-memory Distributed Spatial Query Processing and Optimization by Mingjie Tang (227920)

    Published 2020
    “…<p>Due to the ubiquity of spatial data applications and the large amounts of spatial data that these applications generate and process, there is a pressing need for scalable spatial query processing. …”
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    An Empirical Analysis of NMT-Derived Interlingual Embeddings and Their Use in Parallel Sentence Identification by Cristina Espana-Bonet (19720063)

    Published 2017
    “…</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Journal of Selected Topics in Signal Processing<br>License:<a href="https://creativecommons.org/licenses/by/4.0/" rel="noreferrer" target="_blank"> https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/jstsp.2017.2764273" target="_blank">https://dx.doi.org/10.1109/jstsp.2017.2764273</a></p>…”
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    Nonlinear analysis of shell structures using image processing and machine learning by M.S. Nashed (16392961)

    Published 2023
    “…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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    Assessing the risk of vibration-induced fatigue in process pipework using convolutional neural networks by Ahmed Mohamed (628889)

    Published 2025
    “…In contrast, vibration data can be efficiently collected using accelerometers and single-channel data loggers, providing a more feasible solution for initial screening. …”
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    An efficient approach for textual data classification using deep learning by Abdullah Alqahtani (7128143)

    Published 2022
    “…This paper employs machine and deep learning techniques to classify textual data. Textual data contains much useless information that must be pre-processed. …”
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    RDFFrames: knowledge graph access for machine learning tools by Aisha Mohamed (5152970)

    Published 2021
    “…Machine learning tools work on data in tabular format and process it using an imperative programming style, while SPARQL is declarative and has as its basic operation matching graph patterns to RDF triples. …”
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    What do Neural Machine Translation Models Learn about Morphology? by Yonatan Belinkov (18973897)

    Published 2017
    “…However, little is known about what these models learn about source and target languages during the training process. …”
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    Faux-Data Injection Optimization for Accelerating Data-Driven Discovery of Materials by Abdul Wahab Ziaullah (16027076)

    Published 2023
    “…Among the mechanics of a BO is the use of a machine learning (ML) model that learns about the scope of the problem through data being acquired on the fly. …”