Results 61 to 70 of about 7,383 (190)
A Field Study of Nonintrusive Load Monitoring Devices and Implications for Load Disaggregation
Sensors, 2023 Evaluations of nonintrusive load monitoring (NILM) algorithms and technologies have mostly occurred in constrained, artificial environments. However, few field evaluations of NILM products have taken place in actual buildings under normal operating ...
Ebony Mayhorn +2 more
doaj +1 more source
Human papillomavirus genotyping among the women with cervical abnormalities in Ulaanbaatar, Mongolia [PDF]
, 2019 学位記番号 ...
TSEDENBAL, BATCHIMEG +2 more
core
Diagnostic Cytopathology, Volume 54, Issue 2, Page 146-159, February 2026.ABSTRACT Over four decades, Korea has advanced from a limited cytology service to a global model of digital and AI‐integrated cytopathology. Since the founding of the Korean Society for Cytopathology (KSC) in 1986, a nationwide framework has been established—encompassing standardized practices, systematic education for specialists and cytotechnologists,
Yosep Chong +6 more
wiley +1 more source
Apply Graph Signal Processing on NILM: An Unsupervised Approach Featuring Power Sequences
Sensors, 2023 As a low-cost demand-side management application, non-intrusive load monitoring (NILM) offers feedback on appliance-level electricity usage without extra sensors.
Bochao Zhao +3 more
doaj +1 more source
NILM Applications for the Energy-Efficient Home [PDF]
, 2012 We present a forecast for systems-focused applications of non-intrusive load monitoring (NILM), which meet the needs of homeowners, the technology sector, the service sector, and/or utilities. We discuss both near- and long-term applications.
Christensen, D., Earle, L., Sparn, B.
openaire +2 more sources
Abnormal Power Usage Detection: A Metrics‐Based Scheme for Low Sampling Data
Electronics Letters, Volume 62, Issue 1, January/December 2026.This letter proposes a new scheme for non‐intrusive load monitoring (NILM) of household equipment at low resolution to identify potential abnormal consumption and electrical risks by computing targeted metrics instead of running continuous disaggregation.
Yu Liu +5 more
wiley +1 more source
A Non-invasive Load Recognition Approach Incorporating SENet Attention Mechanism and GA-CNN
Zhongguo dianliWith the popularization of smart meters and the gradual improvement of grid informatization and digitization, non-intrusive load monitoring (NILM) on the demand side of residential customers' energy usage is becoming one of the key technologies for power
Xin SHEN +5 more
doaj +1 more source
Non-Intrusive Load Monitoring via Deep Learning Based User Model and Appliance Group Model
Energies, 2020 Non-Intrusive Load Monitoring (NILM) increases awareness on user energy usage patterns. In this paper, an efficient and highly accurate NILM method is proposed featuring condensed representation, super-state and fusion of two deep learning based models ...
Ce Peng +4 more
doaj +1 more source
IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.This paper proposes the federated watermark closed‐loop learning (FWM‐CL) method for non‐intrusive load monitoring (NILM) to tackle Byzantine attacks and inefficient power disaggregation. FWM‐CL improves system robustness and disaggregation accuracy through watermark‐based attack detection and a feedback optimisation mechanism.
Yuefeng Lu +3 more
wiley +1 more source
Comprehensive feature selection for appliance classification in NILM [PDF]
Energy and Buildings, 2017 Abstract Since the inception of non-intrusive appliance load monitoring (NILM), extensive research has focused on identifying an effective set of features that allows to form a unique appliance signature to discriminate various loads. Although an abundance of features are reported in literature, most works use only a limited subset of them.
Sadeghianpourhamami, Nasrin +4 more
openaire +1 more source