A high-performance formaldehyde sensor based on nickel (Ni)-doped indium trioxide (In2O3)/tungsten disulfide (WS2) nanocomposite was demonstrated. An epoxy substrate served as matrix of the ...Ni–In2O3/WS2 nanocomposite sensor. The material properties of self-assembled Ni–In2O3/WS2 nanoheterostructure were fully characterized and confirmed. The formaldehyde-sensing properties of the Ni–In2O3/WS2 composite were tested at 25 °C. Compared to the In2O3, WS2, and their composite, the Ni–In2O3/WS2 sensor demonstrated significant improvement on the formaldehyde-sensing performance, including a low detection limit of 15 ppb, good selectivity, repeatability, fast detection rate, and a fair logarithmic function toward formaldehyde concentration. The dramatically enhanced sensing performance of Ni–In2O3/WS2 film sensor can be attributed to the Ni ion doping and synergistic interfacial incorporation of In2O3/WS2 heterojunction. The sensitive mechanism of the Ni–In2O3/WS2 film sensor toward formaldehyde is explored through density functional theory (DFT) simulation. This work verified that the synthesis of Ni-doped In2O3/WS2 nanofilm provides a new avenue to develop promising hybrids for formaldehyde sensing.
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We propose an open-loop and a closed-loop stochastic event-triggered sensor schedule for remote state estimation. Both schedules overcome the essential difficulties of existing schedules in recent ...literature works where, through introducing a deterministic event-triggering mechanism, the Gaussian property of the innovation process is destroyed which produces a challenging nonlinear filtering problem that cannot be solved unless approximation techniques are adopted. The proposed stochastic event-triggered sensor schedules eliminate such approximations. Under these two schedules, the minimum mean squared error (MMSE) estimator and its estimation error covariance matrix at the remote estimator are given in a closed-form. The stability in terms of the expected error covariance and the sample path of the error covariance for both schedules is studied. We also formulate and solve an optimization problem to obtain the minimum communication rate under some estimation quality constraint using the open-loop sensor schedule. A numerical comparison between the closed-loop MMSE estimator and a typical approximate MMSE estimator with deterministic event-triggered sensor schedule, in a problem setting of target tracking, shows the superiority of the proposed sensor schedule.
In power system operation, the economic dispatch problem (EDP) aims to minimize the total generation cost while meeting the demand and satisfying generator capacity limits. This paper proposes an ...algorithm based on the gradient push-sum method to solve the EDP in a distributed manner over communication networks potentially with time-varying topologies and communication delays. This paper shows that the proposed algorithm is guaranteed to solve the EDP if the time-varying directed communication network is uniformly jointly strongly connected. Moreover, the proposed algorithm is also able to handle arbitrarily large but bounded time-varying delays on communication links. Numerical simulations are used to illustrate and validate the proposed algorithm.
We consider sensor data scheduling for remote state estimation. Due to constrained communication energy and bandwidth, a sensor needs to decide whether it should send the measurement to a remote ...estimator for further processing. We propose an event-based sensor data scheduler for linear systems and derive the corresponding minimum squared error estimator. By selecting an appropriate event-triggering threshold, we illustrate how to achieve a desired balance between the sensor-to-estimator communication rate and the estimation quality. Simulation examples are provided to demonstrate the theory.
Due to cost reduction and device miniaturization, amateur drones are now widely used in numerous civilian and commercial applications. However, the abuse of amateur drones has resulted in emerging ...threats to personal privacy and public security. To alleviate these threats, we design an acoustic-based surveillance system, which can achieve the capacity of amateur drones detection and localization with 24/7 (24 hours per day and 7 days per week under normal circumstances) availability. In the designed system, a detection fusion algorithm and a TDOA estimation algorithm based on the Bayesian filter are applied to improve the performance of drone detection and localization. Field experiments are carried out, and the results demonstrate that the designed system can detect and locate an amateur drone in real time with high accuracy and 24/7 availability.
Automatic detection of subsequence anomalies (i.e., an abnormal waveform denoted by a sequence of data points) in time series is critical in a wide variety of domains. However, most existing methods ...for subsequence anomaly detection often require knowing the length and the total number of anomalies in time series. Some methods fail to capture recurrent subsequence anomalies due to using only local or neighborhood information for anomaly detection. To address these limitations, in this paper, we propose a novel graph-represented time series (GraphTS) method for discovering subsequence anomalies. In GraphTS, we provide a new concept of time series graph representation model, which represents both recurrent and rare patterns in a time series. Particularly, in GraphTS, we develop a new 2D time series visualization (2Dviz) method, which compacts all 1D time series patterns into a 2D spatial temporal space. The 2Dviz method transfers time series patterns into a higher-resolution plot for easier sequence anomaly recognition (or detecting subsequence anomalies). Then, a Graph is constructed based on the 2D spatial temporal space of time series to capture recurrent and rare subsequence patterns effectively. The represented Graph also can be used to discover single and recurrent subsequence anomalies with arbitrary lengths. Experimental results demonstrate that the proposed method outperforms the state-of-the-art methods in terms of accuracy and efficiency.
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Although research on servant leadership has been expanding over the past several years, a concise, valid scale for assessing global servant leadership has been lacking. In the current investigation a ...7-item measure of global servant leadership (SL-7), based on Liden, Wayne, Zhao, and Henderson's (2008) 28-item servant leadership measure (SL-28), is introduced. Psychometric properties of the SL-7 were assessed at the individual level with data collected from 729 undergraduate students, 218 graduate students, and 552 leader–follower dyads from 11 organizations, and at the team level with a study consisting of a total of 71 ongoing intact work teams. Results across three independent studies with six samples showed correlations between the SL-7 and SL-28 scales ranging from .78 to .97, internal consistency reliabilities over .80 in all samples, and significant criterion-related validities for the SL-7 that parallel those found with the SL-28.
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This paper considers a remote state estimation problem, where a sensor measures the state of a linear discrete-time process and has computational capability to implement a local Kalman filter based ...on its own measurements. The sensor sends its local estimates to a remote estimator over a communication channel that is exposed to a Denial-of-Service (DoS) attacker. The DoS attacker, subject to limited energy budget, intentionally jams the communication channel by emitting interference noises with the purpose of deteriorating estimation performance. In order to maximize attack effect, following the existing answer to "when to attack the communication channel", in this paper we manage to solve the problem of "how much power the attacker should use to jam the channel in each time". For the static attack energy allocation problem, when the system matrix is normal, we derive a sufficient condition for when the maximum number of jamming operations should be used. The associated jamming power is explicitly provided. For a general system case, we propose an attack power allocation algorithm and show the computational complexity of the proposed algorithm is not worse than O(T ), where T is the length of the time horizon considered. When the attack can receive the real-time ACK information, we formulate a dynamic attack energy allocation problem, and transform it to a Markov Decision Process to find the optimal solution.
Driven by smart grid technologies, a great effort has been made in developing distributed energy resources (DERs) in recent years for improving reliability and efficiency of distribution systems. ...Emerging DERs require effective and efficient control and coordination in order to harvest their potential benefits. In this paper, we consider optimal DER coordination problem, where the goal is to minimize the total generation cost while meeting total demand and satisfying individual generator output limit. This paper develops a distributed algorithm for solving the optimal DER coordination problem over lossy communication networks with packet-dropping communication links. Under the assumption that the underlying communication network is strongly connected with a positive probability and the packet drops are independent and identically distributed, we show that the proposed algorithm is able to solve the optimal DER coordination problem even in the presence of packet drops. Numerical simulation results are used to validate and illustrate the proposed algorithm.
The advancement of the electric vehicle industry has inevitably resulted in the increased production and numerous scraps of lithium-ion batteries (LIBs), among which the nickel cobalt manganese ...ternary material has become the fastest growing and largest proportion material in the lithium battery cathode material market. Therefore, a practical and effective method to recycle spent LIBs must be established. In this study, an efficient recycling method was proposed to leach value metals from cathode materials via the excellent solubility of deep eutectic solvents to metals, and regenerated LiNi1/3Co1/3Mn1/3O2 was prepared via coextraction and coprecipitation. 91.63% of Li, 92.52% of Co, 94.92% of Ni, and 95.47% of Mn are leached from the recycled cathode electrode. The kinetic experiments indicated that the leaching process fitted well to the shrinking core model controlled by chemical reactions. The value metals could be extracted with high efficiencies by adjusting the operating parameters in the step of coextraction. Moreover, the electrochemical tests of the regenerated ternary material revealed that the material had an excellent electrochemical performance. The proposed method, which can realize the sustainable development of spent LIBs, has great potential in the deep recycling of spent LIBs.
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