Results 1 to 10 of about 3,853,271 (192)

Adaptive Compressive Sensing and Data Recovery for Periodical Monitoring Wireless Sensor Networks [PDF]

Sensors, 2018
The development of compressive sensing (CS) technology has inspired data gathering in wireless sensor networks to move from traditional raw data gathering towards compression based gathering using data correlations. While extensive efforts have been made
Jian Chen, Jie Jia, Yansha Deng, Xingwei Wang, Abdol-Hamid Aghvami   +4 more
doaj   +2 more sources

Pipeline monitoring data recovery using novel deep learning models: an engineering case study [PDF]

Frontiers in Artificial Intelligence
Pipeline monitoring frequently encounters missing data, leading to incomplete evaluation and hindering a comprehensive assessment of the pipeline’s structural health. To address this issue, this study proposes a novel PDO-BiGRU-GAN model for missing data
Yong Zhao, Xinpeng Zhang, Yanli Liu, Xuecheng Mao, Xi Chen, Yasheng Maimaitituerxun, Weidong He   +6 more
doaj   +2 more sources

CDSTAEP: Cross-Domain Spatial-Temporal Association Learning for Abnormal Events Prediction

Applied Sciences, 2023
Predicting network abnormal events and behavior can enhance security situation awareness and the ability to infer attack intentions. Most of the existing abnormal event prediction methods usually rely on the temporal relationship features between events ...
Mingcheng Gao, Ruiheng Wang, Hongliang Zhu, Yang Xin   +3 more
doaj   +1 more source

Pathological study on uncertain numbers and proposed solutions for discrete fuzzy fractional order calculus

Open Physics, 2023
A pathological study in the definition of uncertain numbers is carried out, and some solutions are proposed. Fundamental theorems for uncertain discrete fractional and integer order calculus are established.
Shiri Babak, Baleanu Dumitru, Ma Chang-You   +2 more
doaj   +1 more source

Harmonic Data Recovery Method Based on Multivariate Norm Matrix

Journal of Modern Power Systems and Clean Energy, 2023
During state perception of a power system, fragments of harmonic data are inevitably lost owing to the loss of synchronization signals, transmission delays, instrument failures, or other factors.
Ying Wang, Rui Xu, Shiqi Song, Xiaoyang Ma, Huaying Zhang, Xian Wu   +5 more
doaj   +1 more source

Recovery Algorithm of Power Metering Data Based on Collaborative Fitting

Energies, 2022
Electric energy metering plays a crucial role in ensuring fair and equitable transactions between grid companies and power users. With the implementation of the State Grid Corporation’s energy Internet strategy, higher requirements have been put forward ...
Yukun Xu, Xiangyong Kong, Zheng Zhu, Chao Jiang, Shuang Xiao   +4 more
doaj   +1 more source

Linguistic Interval-Valued Intuitionistic Fuzzy Copula Heronian Mean Operators for Multiattribute Group Decision-Making

Journal of Mathematics, 2020
As a generalization of the intuitionistic fuzzy number (IFN), the linguistic interval-valued intuitionistic fuzzy number (LIVIFN) is a flexible and superior tool to describe complex fuzzy uncertainty information.
Lei Xu, Yi Liu, Haobin Liu
doaj   +1 more source

Time Series Recovery Using Adjacent Channel Data Based on LSTM: A Case Study of Subway Vibrations

Applied Sciences, 2022
Multi-sensor technology has been widely applied in the condition monitoring of rail transit. In practice, the data of some channels in the high channel counts are often abnormal or lost due to the abnormality and damage of the sensors, thus resulting in ...
Tao Xin, Yi Yang, Xiaoli Zheng, Jing Lin, Sen Wang, Pengsong Wang   +5 more
doaj   +1 more source

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke [PDF]

, 2020
The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches.
Assogna, Francesca, Baugh, Lee A., Bhattacharya, Anup K., Bigjahan, Bavrina, Borich, Michael R., Boyd, Lara A., Brodtmann, Amy, Buetefisch, Cathrin M., Byblow, Winston D., Cassidy, Jessica M., Conforto, Adriana B., Craddock, R. Cameron, Cramer, Steven C., Dimyan, Michael A., Dula, Adrienne N., Ermer, Elsa, Etherton, Mark R., Fercho, Kelene A., Gregory, Chris M., Hadidchi, Shahram, Hayward, Kathryn S., Holguin, Jess A., Hwang, Darryl H., Jahanshad, Neda, Juliano, Julia M., Jung, Simon, Kautz, Steven A., Khlif, Mohamed Salah, Khoshab, Nima, Kim, Bokkyu, Kim, Hosung, Kuceyeski, Amy, Lang, Catherine E., Liew, Sook‐Lei, Lohse, Keith R., Lotze, Martin, MacIntosh, Bradley J., Margetis, John L., Mohamed, Feroze B., Piras, Fabrizio, Ramos‐Murguialday, Ander, Richard, Geneviève, Roberts, Pamela, Robertson, Andrew D., Rondina, Jane M., Rost, Natalia S., Sanossian, Nerses, Schweighofer, Nicolas, Seo, Na Jin, Shiroishi, Mark S., Soekadar, Surjo R., Spalletta, Gianfranco, Stinear, Cathy M., Suri, Anisha, Tang, Wai Kwong W., Thielman, Gregory T., Thompson, Paul M., Vecchio, Daniela, Villringer, Arno, Ward, Nick S., Werden, Emilio, Westlye, Lars T., Winstein, Carolee, Wittenberg, George F., Wong, Kristin A., Yu, Chunshui, Zavaliangos‐Petropulu, Artemis   +66 more
core   +4 more sources

Data Secure De-Duplication and Recovery Based on Public Key Encryption With Keyword Search

IEEE Access, 2023
In the current era of information explosion, users’ demand for data storage is increasing, and data on the cloud has become the first choice of users and enterprises.
Le Li, Dong Zheng, Haoyu Zhang, Baodong Qin   +3 more
doaj   +1 more source