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Electronic power grid is a distributed network used for transferring electricity and power from power plants to consumers. Based on sensor readings and control system signals, power grid states are measured and estimated. As a result, most conventional attacks, such as denial-of-service attacks and random attacks, could be found by using the Kalman filter. However, false data injection attacks are...
This paper proposes a novel online condition monitoring algorithm estimating battery states and model parameters. The proposed method includes: 1) an electrical circuit battery model incorporating the hysteresis effect, 2) an extended Kalman Filter-based online parameter identification algorithm for the electrical battery model, and 3) a smooth variable structure filter (SVSF)-based state estimation...
While not included at some institutions and relegated to 3 (minimum) hours of core coverage by the ACM / IEEE Computer Society model curriculum, project management is becoming an integral component of computer science education. The prevalence of failed software projects dictates a focus on this discipline which provides the tools and processes relevant to effective performance of software creation,...
This paper proposes a novel estimator for active and reactive power control of single-phase power electronic applications. The proposed estimator includes: 1) an instantaneous grid power regression model; 2) a fast upper-triangular and diagonal recursive least square (FUDRLS) algorithm for parameter identification of the regression model; and 3) a new self-tuning variable forgetting factor included...
In this paper, a new distributed least-squares algorithm is proposed to solve the sensor fusion problem in using wireless sensor networks (WSN) to monitor the behaviors of large-scale multiagent systems. Under the assumption that each sensor can take the measurements of a limited number of agents but the complete multiagent systems are covered under the union of all sensors in the network, the proposed...
The microbial diversity and taxonomic profiles of human microbiome carries indicative signals associated with several complex human diseases. Methods quantifying and differentiating profiles belonging to healthy/disease microbiomes have a potential to be used as non-invasive diagnostic tools. 16S rRNA sequencing is a currently popular and feasible technology to generate the required data for such...
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