No abstract is provided for this article.
In this paper, the problem of robust fault detection filter (RFDF) design for a class of linear systems with some nonlinear perturbations and mixed neutral and discrete time-varying delays is investigated. By using a descriptor technique, Lyapunov–Krasovskii functional and a suitable change of variables, new required sufficient conditions are established in terms of delay-dependent linear matrix inequalities (LMIs) to synthesize the residual generation scheme. Based on the Luenberger type observers, the explicit expression of the filters is derived for the fault such that both asymptotic stability and a prescribed level of disturbance attenuation are satisfied for all admissible nonlinear perturbations. A numerical example is provided to demonstrate the effectiveness and the applicability of the proposed method.
The humidity sensitive characteristics of the sensor fabricated from 10 mol% La 2 O 3 doped CeO 2 nanopowders with particle size 17.26 nm synthesized via hydrothermal method were investigated at different frequencies. It was found that the sensor shows high humidity sensitivity, rapid response-recovery characteristics, and narrow hysteresis loop at 100 Hz in the relative humidity range from 11% to 95%. The impedance of the sensor decreases by about five orders of magnitude as relative humidity increases. The maximum humidity hysteresis is about 6% RH, and the response and recovery time is 12 and 13 s, respectively. These results indicate that the nanosized La 2 O 3 doped CeO 2 powder has potential application as high-performance humidity sensor.
Social media, e.g. Twitter, has become a widely used medium for the exchange of information, but it has also become a valuable tool for hackers to spread misinformation through compromised accounts. Hence, detecting compromised accounts is a necessary step toward a safe and secure social media environment. Nevertheless, detecting compromised accounts faces several challenges. First, social media activities of users are temporally correlated which plays an important role in compromised account detection. Second, data associated with social media accounts is inherently sparse. Finally, social contagions where multiple accounts become compromised, take advantage of the user connectivity to propagate their attack. Thus how to represent each user's network features for compromised account detection is an additional challenge. To address these challenges, we propose an End-to-End Compromised Account Detection framework (E2ECAD). E2ECAD effectively captures temporal correlations via an LSTM (Long Short-Term Memory) network. Further, it addresses the sparsity problem by defining and employing a user context representation. Meanwhile, informative network-related features are modeled efficiently. To verify the working of the framework, we construct a real-world dataset of compromised accounts on Twitter and conduct extensive experiments. The results of experiments show that E2ECAD outperforms the state of the art compromised account detection algorithms.
Graph partitioning, a classical NP-hard combinatorial optimization problem, is widely applied to industrial or management problems. In this study, an approximated solution of the graph partitioning problem is obtained by using a deterministic annealing neural network algorithm. The algorithm is a continuation method that attempts to obtain a high-quality solution by following a path of minimum points of a barrier problem as the barrier parameter is reduced from a sufficiently large positive number to 0. With the barrier parameter assumed to be any positive number, one minimum solution of the barrier problem can be found by the algorithm in a feasible descent direction. With a globally convergent iterative procedure, the feasible descent direction could be obtained by renewing Lagrange multipliers red. A distinctive feature of it is that the upper and lower bounds on the variables will be automatically satisfied on the condition that the step length is a value from 0 to 1. Four well-known algorithms are compared with the proposed one on 100 test samples. Simulation results show effectiveness of the proposed algorithm.
This paper studies the fixed-order piecewise-affine (PWA) output-feedback control of PWA systems in an H∞ setup. In particular, the conventional output-feedback closed-loop system is first augmented with the introduction of the input vector, and a descriptor presentation of PWA system is acquired. Then, a bounded real lemma is derived for the resulting PWA system, which is realized by the construction of a smooth piecewise Lyapunov function and application of the S-procedure. Furthermore, by availing oneself of the descriptor formulation, the fixed-order PWA output-feedback controller synthesis is carried out in a unified framework. An illustrative example is provided to show the efficacy and impact of the proposed control design methodology in a Chua's circuit.
In this chapter, the relevance and potential of micro-sized wind turbines (μSWTs) have been discussed and the following facts have been stated In wide areas of developing countries with a poor grid power supply, μSWTs can be an important factor of social, economic and technological development. From an educational point of view, μSWTs can be a valuable source of motivation, helping to provide a practical presentation of basic and advanced mechatronical principles. Moreover, μSWTs can also be an excellent field for cooperative and project-based learning, allowing to define a wide variety of experimental projects with a direct real-life application. From a research perspective, μSWTs constitute a unique opportunity to perform full-scale physical experimentation on advanced research topics at a very low cost and with very limited resources. To provide a practical demonstration of the μSWTs potential in academic and research experimentation, a low-cost platform for active magnetic bearing vibration control has been presented.
There are various real-world applications such as video ads, airport screenings, courtroom trials, and job interviews where deception detection can play a crucial role. Hence, there are immense demands on deception detection in videos. Videos contain rich information including acoustic, visual, temporal, and/or linguistic information, which provides great opportunities for advanced deception detection. However, videos are inherently complex; moreover, they lack detective labels in many real-world applications, which poses tremendous challenges to traditional deception detection. In this manuscript, I present my Ph.D. research on the problem of deception detection in videos. In particular, I provide a principled way to capture rich information into a coherent model and propose an end-to-end framework DEV to detect DEceptive Videos automatically. Preliminary results on real-world videos demonstrate the effectiveness of the proposed framework.
Focusing on the amplifier performance evaluation demand, a novel evaluation strategy based on<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>δ</mml:mi></mml:mrow></mml:math>-support vector regression (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>δ</mml:mi></mml:mrow></mml:math>-SVR) is proposed in this paper. Lower computer calculation demand is considered firstly. And this is dealt with by the superiority of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mrow><mml:mi>δ</mml:mi></mml:mrow></mml:math>-SVR which can be significantly improved on the number of support vectors. Moreover, the function of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mrow><mml:mi>δ</mml:mi></mml:mrow></mml:math>-SVR employs the modified RBF kernel function which is constructed from an original kernel by removing the last coordinate and adding the linear term with the last coordinate. Experiment adopted the typical circuit Sallen-Key low pass filter to prove the proposed evaluation strategy via the eight performance indexes. Simulation results reveal that the need of the number of<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M5"><mml:mrow><mml:mi>δ</mml:mi></mml:mrow></mml:math>-SVR support vectors is the lowest among the other two methods LSSVR and ε -SVR under obtaining nearly the same evaluation result. And this is also suitable for promotion computational speed.
Accepted version of a paper published by IEEE. (c) 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works Published version:http://dx.doi.org/10.1109/CCA.2010.5611107
No abstract is provided for this article.
Vibrations is an extremely important issue to consider when designing various systems. It may lead to discomfort and malfunction or in some cases collapse of structures. To compensate for these vibrations different types of damping devices can be applied. The main focus which the following work addresses has been to look at standard methodology which enables determining the hysteresis from defined range of measurements which special focus on the MR damper.The mathematical equations that lie behind the Bingham, Dahl, Lugre and Bouc-Wen have been studied to describe the behavior of the MR damper. The hysteresis equations of Bouc-Wen, Lugre, and Dahl have been modeled and simulated in Matlab/Simulink. We have manipulated the different parameters in the models and analyzed their effects on the outcome. The hysteresis models of Bouc-Wen, Dahl and LuGre have been analyzed and compared analytically to really show the difference in the models. At last the Bouc-Wen model was implemented together with the SAS(Semi Active Suspension) system in the laboratory. The model parameters were tuned manually to try to fit the response of the system. This paper shows that the methodology flowchart can be implemented and generalized for any kind of dampers and used to find behavior of MR damper with different mathematical models. The Bouc-Wen model was found to be model to both illustrate the MR damper and recreate the behavior of the SAS system.
This paper reports on a study undertaken within the CEPT SE42 project team, with the objective of deriving regulatory radiation limits which mitigate the impact of adjacent-channel interference from fixed/mobile communication network base stations (BSs) in the Digital Dividend spectrum (790-862 MHz) to digital terrestrial television (DTT) services below 790 MHz. A novel stochastic approach for the calculation of BS block-edge mask (BEM) out-of-block (or baseline) limits is presented. Results indicate that, for a typical BS in-block EIRP of 59 dBm/(10 MHz) or greater, the fraction of locations in which a DTT receiver would suffer unacceptable levels of interference does not improve significantly with a reduction in the BS BEM baseline EIRP limit below 0 dBm/(8 MHz). This is due to the finite frequency selectivity of the DTT receivers. It is also shown that for in-block EIRPs below 59 dBm, the baseline EIRP limit should be reduced proportionately in order for the DTT location failure rate to be broadly independent of the communication network deployment geometry.
In this paper, we investigate the stability problem for some Markovian switching reaction–diffusion coupled systems on networks (MSRDCSNs). By using the Lyapunov function, we establish some novel stability principles for stochastic stability, asymptotically stochastic stability, globally asymptotically stochastic stability and almost surely exponential stability of the MSRDCSNs. These stability principles have a close relation to the topology property of the network. We also provide a systematic method for constructing global Lyapunov function for these MSRDCSNs by using graph theory. The new method can help analyze the dynamics of complex networks.
This paper deals with the problem of fault detection for linear uncertain time-delay systems. The proposed method for Luenberger observers is developed for unknown input observers (UIOs), and a novel procedure for the design of residual based on UIOs is presented. The design procedure is carried out based on the <svg style="vertical-align:-3.3907pt;width:28.9125px;" id="M1" height="16.512501" version="1.1" viewBox="0 0 28.9125 16.512501" width="28.9125" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg"> <g transform="matrix(.017,-0,0,-.017,.625,11.675)"><path id="x1D43B" d="M865 650q-1 -4 -4 -14t-4 -14q-62 -5 -77 -19.5t-29 -82.5l-74 -394q-12 -61 -0.5 -77t75.5 -21l-6 -28h-273l8 28q64 5 82 21t29 76l36 198h-380l-37 -197q-11 -64 0.5 -78.5t79.5 -19.5l-6 -28h-268l6 28q60 6 75.5 21.5t26.5 76.5l75 394q13 66 2 81.5t-77 20.5l8 28
h263l-6 -28q-58 -5 -75.5 -21t-30.5 -81l-26 -153h377l29 153q12 67 2 81t-74 21l5 28h268z" /></g> <g transform="matrix(.012,-0,0,-.012,15.525,15.75)"><path id="x221E" d="M983 225q0 -112 -67 -174.5t-150 -62.5q-91 0 -154.5 43.5t-113.5 129.5q-49 -85 -104 -129t-138 -44q-98 0 -158.5 66t-60.5 154q0 59 21 106.5t54.5 75.5t70.5 43t73 15q90 0 152.5 -43.5t112.5 -128.5q48 84 104.5 128t140.5 44q93 0 155 -65t62 -158zM478 196
q-27 49 -47 80t-50 67t-64 54t-73 18q-48 0 -81.5 -47t-33.5 -128q0 -96 37.5 -157.5t99.5 -61.5q68 0 117.5 47t94.5 128zM889 204q0 91 -35.5 151t-99.5 60q-68 0 -119 -47t-95 -127q27 -49 47 -80.5t50 -67.5t65 -54t74 -18q113 0 113 183z" /></g> </svg> model matching approach which minimizes the difference between generated residuals by the optimal observer and those by the designed observer in the presence of uncertainties. The optimal observer is designed for the ideal system and works so that the fault effect is maximized while the exogenous disturbances and noise effects are minimized. This observer can give disturbance decoupling in the presence of noise and uncertainties for linear uncertain time-delay systems. The developed method is applied to a numerical example, and the simulation results show that the proposed approach is able to detect faults reliably in the presence of modeling errors, disturbances, and noise.
No abstract is provided for this article.
Network alignment, in general, seeks to discover the hidden underlying correspondence between nodes across two (or more) networks when given their network structure. However, most existing network alignment methods have added assumptions of additional constraints to guide the alignment, such as having a set of seed node-node correspondences across the networks or the existence of side-information. Instead, we seek to develop a general network alignment algorithm that makes no additional assumptions. Recently, network embedding has proven effective in many network analysis tasks, but embeddings of different networks are not aligned. Thus, we present our Deep Adversarial Network Alignment (DANA) framework that first uses deep adversarial learning to discover complex mappings for aligning the embedding distributions of the two networks. Then, using our learned mapping functions, DANA performs an efficient nearest neighbor node alignment. We perform experiments on real world datasets to show the effectiveness of our framework for first aligning the graph embedding distributions and then discovering node alignments that outperform existing methods.
