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21

Non-technical loss detection in power distribution networks using machine learning.
Abro SA ; Laghari JA ; Memon SA ; et al.
Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE

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22

Mechanization and Maize Productivity in Tanzania’s Ruvuma Region: A Python-Based Analysis on Adoption and Yield Impact
James Jackson Majebele ; Minli Yang ; Muhammad Mateen ; et al.
Agriculture, Vol 15, Iss 13, p 1412 (2025)

agricultural mechanizati... maize productivity smallholder farmers yield gaps adoption constraints innovation diffusion the... …
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23

Machine Learning in the National Economy
Azamjon A. Usmonov
Открытое образование (Москва), Vol 29, Iss 3, Pp 4-10 (2025)

machine learning economics forecasting risks data analysis regression …
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24

Regression modeling with convolutional neural network for predicting extent of resection from preoperative MRI in giant pituitary adenomas: a pilot study.
Patel BK ; Tariciotti L ; DiRocco L ; et al.
Publisher: American Association of Neurological Surgeons Country of Publication: United States NLM ID: 0253357 Publication Model: Electronic-Print Cited Medium: Internet ISSN: 1933-0693 (Electronic) Linking ISSN: 00223085 NLM ISO Abbreviation: J Neurosurg Subsets: MEDLINE

Aged Female Humans Male Middle Aged Convolutional Neural Net... …
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25

Detection of compromised devices or user credentials
Silva, João Manuel Castanheira da

User entity behaviour an... Anomaly detection Machine learning Cybersecurity
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26

A model for the simulated design of Turkish RC frame buildings in seismic vulnerability analysis.
Hasanoğlu, Serkan ; Ozsarac, Volkan ; O'Reilly, Gerard J.
Bulletin of Earthquake Engineering. Dec2025, Vol. 23 Issue 15, p6829-6856. 28p.

TURKEY NONLINEAR analysis RISK assessment EARTHQUAKE hazard analys... CONSTRUCTION management VIRTUAL design …
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27

Model-Based Deep Learning.
Shlezinger, Nir ; Eldar, Yonina C.
Foundations & Trends in Signal Processing; 2023, Vol. 17 Issue 4, p291-416, 126p

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28

The pandemic semesters: Examining public opinion regarding online learning amidst COVID‐19.
Asare, Andy Ohemeng ; Yap, Robin ; Truong, Ngoc ; et al.
Journal of Computer Assisted Learning; Dec2021, Vol. 37 Issue 6, p1591-1605, 15p

TWITTER (Web resource) ONLINE education TEACHING methods RE-entry students LEARNING strategies VOCABULARY …
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29

Using Data Analysis Tools in Non-Profit Organizations: Practical Applications and Selection Guidelines
Anna Neya Kazanskaia
NEYA Global Journal of Non-Profit Studies.

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30

Previsão da potência média produzida por turbinas eólicas utilizando redes neurais
Campos, Letícia Góes ; Teixeira, João Teixeira ; Poubel , Raphael Paulo Braga ; et al.
urn:tid:204045266

Artificial neural networ... Wind power Multi-layer perceptron Python Forecasting Time series prediction …
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31

A Data-driven Approach for FPSO Electric Power System Modelling
Junior, Daniel Araujo ; Ferreira, Vitor Hugo ; Pessoa, Arthur Alves ; et al.

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32

Deep learning in public health, and contributions to statistical learning
Apprentissage profond en santé publique, et contributions en apprentissage statistique
Yu, Yiyang ; Laboratoire de Probabilités, Statistique et Modélisation (LPSM (UMR_8001)) ; Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité) ; et al.
Statistics [math.ST]. Université Paris Cité, 2022. English. ⟨NNT : 2022UNIP7209⟩

Online logistic regressi... Random forests Contrastive learning Medical claims data Deep learning Machine learning …
Dissertation
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33

BUG PREDICTOR: A BIO-INSPIRED ENSEMBLE FRAMEWORK FOR ACCURATE SOFTWARE BUG PREDICTION
International Journal for Research In Science amp Advanced Technologies ; T. SUBBALAKSHAMAMMA, P.VISWANATHA REDDY

Predictive Analysis Predictive Models Software Bugs Priority Severity SVM …
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34

Synthetic data for developing surrogate models–A case study of multistep forecasting in mineral processing
Zeb, Akhtar ; Verma, Nikhil ; Linnosmaa, Joonas
Zeb, A, Verma, N & Linnosmaa, J 2025, Synthetic data for developing surrogate models–A case study of multistep forecasting in mineral processing. in 2025 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA). IEEE Institute of Electrical and Electronic Engineers, International Conference on Artificial Intelligence, Computer, Data Sciences and Applications, ACDSA 2025, Antalya, Turkey, 7/08/25. https://doi.org/10.1109/ACDSA65407.2025.11166053

gold flotation mineral processing multistep time series pr... surrogate model synthetic data generatio...
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36

Synthetic Data Generation and Sampling for Online Training of DNN in Manufacturing Supervised Learning Problems
Thiyagarajan, Prithivrajan ; Industrial and Systems Engineering ; Jin, Ran ; et al.

Data Generation Data Sampling Deep Neural Networks Industrial Internet
Dissertation
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38

25th Annual Computational Neuroscience Meeting: CNS-2016.
BMC Neuroscience, vol 17 Suppl 1, iss Suppl 1

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39

8.G. Skills building seminar: AI for public health dummies – overview and a benchmark algorithm: Random Forests.
European Journal of Public Health; 2021 Supplement, Vol. 31, piii216-iii216, 1p

MEDICINE information ser... PUBLIC health ARTIFICIAL intelligence CONFERENCES & convention... HEALTH information servi... BENCHMARKING (Management... …
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