These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

121 related articles for article (PubMed ID: 32242026)

  • 1. A synthetic energy dataset for non-intrusive load monitoring in households.
    Klemenjak C; Kovatsch C; Herold M; Elmenreich W
    Sci Data; 2020 Apr; 7(1):108. PubMed ID: 32242026
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Semi-Supervised Approach for Improving Generalization in Non-Intrusive Load Monitoring.
    Pujić D; Tomašević N; Batić M
    Sensors (Basel); 2023 Jan; 23(3):. PubMed ID: 36772483
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Multi-State Energy Classifier to Evaluate the Performance of the NILM Algorithm.
    Desai S; Alhadad R; Mahmood A; Chilamkurti N; Rho S
    Sensors (Basel); 2019 Nov; 19(23):. PubMed ID: 31795235
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Smart Distribution Boards (Smart DB), Non-Intrusive Load Monitoring (NILM) for Load Device Appliance Signature Identification and Smart Sockets for Grid Demand Management.
    Kerk SG; Hassan NU; Yuen C
    Sensors (Basel); 2020 May; 20(10):. PubMed ID: 32443817
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Towards Feasible Solutions for Load Monitoring in Quebec Residences.
    Hosseini SS; Delcroix B; Henao N; Agbossou K; Kelouwani S
    Sensors (Basel); 2023 Aug; 23(16):. PubMed ID: 37631824
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Exploiting Smart Meter Power Consumption Measurements for Human Activity Recognition (HAR) with a Motif-Detection-Based Non-Intrusive Load Monitoring (NILM) Approach.
    Wilhelm S; Kasbauer J
    Sensors (Basel); 2021 Dec; 21(23):. PubMed ID: 34884039
    [TBL] [Abstract][Full Text] [Related]  

  • 7. On enabling collaborative non-intrusive load monitoring for sustainable smart cities.
    Shi Y; Li W; Chang X; Yang T; Sun Y; Zomaya AY
    Sci Rep; 2023 Apr; 13(1):6569. PubMed ID: 37085586
    [TBL] [Abstract][Full Text] [Related]  

  • 8. IMPEC: An Integrated System for Monitoring and Processing Electricity Consumption in Buildings.
    Ahajjam MA; Bonilla Licea D; Ghogho M; Kobbane A
    Sensors (Basel); 2020 Feb; 20(4):. PubMed ID: 32075187
    [TBL] [Abstract][Full Text] [Related]  

  • 9. An adaptive-neuro fuzzy inference system based-hybrid technique for performing load disaggregation for residential customers.
    Abbas MZ; Sajjad IA; Hussain B; Liaqat R; Rasool A; Padmanaban S; Khan B
    Sci Rep; 2022 Feb; 12(1):2384. PubMed ID: 35149746
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A residential labeled dataset for smart meter data analytics.
    Pereira L; Costa D; Ribeiro M
    Sci Data; 2022 Mar; 9(1):134. PubMed ID: 35361780
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Towards Trustworthy Energy Disaggregation: A Review of Challenges, Methods, and Perspectives for Non-Intrusive Load Monitoring.
    Kaselimi M; Protopapadakis E; Voulodimos A; Doulamis N; Doulamis A
    Sensors (Basel); 2022 Aug; 22(15):. PubMed ID: 35957428
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Privacy-preserving household load forecasting based on non-intrusive load monitoring: A federated deep learning approach.
    Zhou X; Feng J; Wang J; Pan J
    PeerJ Comput Sci; 2022; 8():e1049. PubMed ID: 36092014
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Non-Intrusive Load Monitoring of Buildings Using Spectral Clustering.
    Ghaffar M; Sheikh SR; Naseer N; Din ZMU; Rehman HZU; Naved M
    Sensors (Basel); 2022 May; 22(11):. PubMed ID: 35684657
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Ageing Safely in the Digital Era: A New Unobtrusive Activity Monitoring Framework Leveraging on Daily Interactions with Hand-Operated Appliances.
    Bousbiat H; Leitner G; Elmenreich W
    Sensors (Basel); 2022 Feb; 22(4):. PubMed ID: 35214224
    [TBL] [Abstract][Full Text] [Related]  

  • 15. DiffNILM: A Novel Framework for Non-Intrusive Load Monitoring Based on the Conditional Diffusion Model.
    Sun R; Dong K; Zhao J
    Sensors (Basel); 2023 Mar; 23(7):. PubMed ID: 37050600
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Mitigating consumer privacy breach in smart grid using obfuscation-based generative adversarial network.
    Desai S; Sabar NR; Alhadad R; Mahmood A; Chilamkurti N
    Math Biosci Eng; 2022 Jan; 19(4):3350-3368. PubMed ID: 35341255
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Parallel Evolutionary Computing-Embodied Artificial Neural Network Applied to Non-Intrusive Load Monitoring for Demand-Side Management in a Smart Home: Towards Deep Learning.
    Lin YH
    Sensors (Basel); 2020 Mar; 20(6):. PubMed ID: 32188065
    [TBL] [Abstract][Full Text] [Related]  

  • 18. ELECTRIcity: An Efficient Transformer for Non-Intrusive Load Monitoring.
    Sykiotis S; Kaselimi M; Doulamis A; Doulamis N
    Sensors (Basel); 2022 Apr; 22(8):. PubMed ID: 35458907
    [TBL] [Abstract][Full Text] [Related]  

  • 19. DEDDIAG, a domestic electricity demand dataset of individual appliances in Germany.
    Wenninger M; Maier A; Schmidt J
    Sci Data; 2021 Jul; 8(1):176. PubMed ID: 34267230
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Real-time recommendations for energy-efficient appliance usage in households.
    Eirinaki M; Varlamis I; Dahihande J; Jaiswal A; Pagar AA; Thakare A
    Front Big Data; 2022; 5():972206. PubMed ID: 36204447
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.