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| 1 | Decentralized Event-Triggered Average Consensus for Multi-Agent Systems in CPSs with Communication Constraints显示文摘The paper investigates decentralized event-triggered average consensus problem for multi-agent systems in cyberphysical systems(CPSs) with communication constraints.To reduce communication burden and improve the communication efficiency of multi-agent systems in CPSs,event-trigger is distributed at subsystem/agent level.A multi-agent system is then modeled as a reduced dimension hybrid system by taking into account decentralized event-triggered mechanism,communication delays and data dropouts within one framework.Some sufflcient conditions for average consensus of each agent and an upper bound of communication delay and maximal allowable number of successive data dropouts(MANSD) are obtained,which can conveniently provide the relationship between the triggering parameters,communication constraints and the system stability.Specially,the quantitative relationship between the triggering parameters,MANSD and the system stability is derived.Finally,simulation results are given to illustrate the effectiveness of the proposed method. | Zhaoxia Wang Minrui Fei Dajun Du Min Zheng | 2015 | IEEE/CAA Journal of Automatica Sinica2015，2，3： | 6 |
| 2 | IL-17 sustains the plasma cell response via p38-mediated Bcl-xL RNA stability in lupus pathogenesis显示文摘Recent studies have demonstrated a central role for plasma cells in the development of autoimmune diseases,such as systemic lupus erythematosus(SLE).Currently,both the phenotypic features and functional regulation of autoreactive plasma cells during SLE pathogenesis remain largely unclear.In this study,we first found that a major subset of IL-17 receptor-expressing plasma cells potently produced anti-dsDNA IgG upon IL-17A(IL-17)stimulation in SLE patients and lupus mice.Using a humanized lupus mouse model,we showed that the transfer of Th17 cell-depleted PBMCs from lupus patients resulted in a significantly reduced plasma cell response and attenuated renal damage in recipient mice compared to the transfer of total SLE PBMCs.Moreover,long-term BrdU incorporation in lupus mice detected highly enriched long-lived BrdU+subsets among IL-17 receptor-expressing plasma cells.Lupus mice deficient in IL-17 or IL-17 receptor C(IL-17RC)exhibited a diminished plasma cell response and reduced autoantibody production with attenuated renal damage,while the adoptive transfer of Th17 cells triggered the plasma cell response and renal damage in IL-17-deficient lupus mice.In reconstituted chimeric mice,IL-17RC deficiency resulted in severely impaired plasma cell generation but showed no obvious effect on germinal center B cells.Further mechanistic studies revealed that IL-17 significantly promoted plasma cell survival via p38-mediated Bcl-xL transcript stabilization.Together,our findings identified a novel function of IL-17 in enhancing plasma cell survival for autoantibody production in lupus pathogenesis,which may provide new therapeutic strategies for the treatment of SLE. | Kongyang Ma Wenhan Du Fan Xiao Man Han Enyu Huang Na Peng Yuan Tang Chong Deng Lixiong Liu Yulan Chen Jingjing Li Shiwen Yuan Qin Huang Xiaoping Hong Dajun Hu Xiaoyan Cai Quan Jiang Dongzhou Liu Liwei Lu | 2021 | Cellular & Molecular Immunology2021，18，7： | 6 |
| 3 | Two-layer networked learning control using self-learning fuzzy control algorithms显示文摘Since the existing single-layer networked control systems have some inherent limitations and cannot effectively handle the problems associated with unreliable networks, a novel two-layer networked learning control system (NLCS) is proposed in this paper. Its lower layer has a number of local controllers that are operated independently, and its upper layer has a learning agent that communicates with the independent local controllers in the lower layer. To implement such a system, a packet-discard strategy is firstly developed to deal with network-induced delay and data packet loss. A cubic spline interpolator is then employed to compensate the lost data. Finally, the output of the learning agent based on a novel radial basis function neural network (RBFNN) is used to update the parameters of fuzzy controllers. A nonlinear heating, ventilation and air-conditioning (HVAC) system is used to demonstrate the feasibility and effectiveness of the proposed system. | Du Dajun Fei Minrui Hu Huosheng Li Lixiong | 2007 | 仪器仪表学报2007，28，12： | 3 |
| 4 | Compact extreme learning machine for biological systems显示文摘 | Li Kang Deng Jing He Haibo Du Dajun | 2010 | International Journal of Computational Biology and Drug Design2010，3，2： | 1 |
| 5 | Entropy Error Model of Planar Geometry Features in GIS显示文摘Positional error of line segments is usually described by using 'g-band', however, its band width is in relation to the confidence level choice. In fact, given different confidence levels, a series of concentric bands can be obtained. To overcome the effect of confidence level on the error indicator, by introducing the union entropy theory, we propose an entropy error ellipse index of point, then extend it to line segment and polygon, and establish an entropy error band of line segment and an entropy error donut of polygon. The research shows that the entropy error index can be determined uniquely and is not influenced by confidence level, and that they are suitable for positional uncertainty of planar geometry features. | LI Dajun GUAN Yunlan GONG Jianya DU Daosheng LI Dajun,Ph.D candidate, National Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University,129 Luoyu Road, Wuhan 430079,China. | 2003 | Geo-Spatial Information Science2003，6，2： | 1 |
| 6 | Compact extreme learning machine for biological systems 显示文摘 | Li Kang Deng Jing He Haibo Du Dajun | 2010 | International Journal of Computational Biology and Drug Design2010，3，2： | 1 |
| 7 | A Review on Cybersecurity Analysis,Attack Detection,and Attack Defense Methods in Cyber-physical Power Systems显示文摘Potential malicious cyber-attacks to power systems which are connected to a wide range of stakeholders from the top to tail will impose significant societal risks and challenges.The timely detection and defense are of crucial importance for safe and reliable operation of cyber-physical power systems(CPPSs).This paper presents a comprehensive review of some of the latest attack detection and defense strategies.Firstly,the vulnerabilities brought by some new information and communication technologies(ICTs)are analyzed,and their impacts on the security of CPPSs are discussed.Various malicious cyber-attacks on cyber and physical layers are then analyzed within CPPSs framework,and their features and negative impacts are discussed.Secondly,two current mainstream attack detection methods including state estimation based and machine learning based methods are analyzed,and their benefits and drawbacks are discussed.Moreover,two current mainstream attack defense methods including active defense and passive defense methods are comprehensively discussed.Finally,the trends and challenges in attack detection and defense strategies in CPPSs are provided. | Dajun Du Minggao Zhu Xue Li Minrui Fei Siqi Bu Lei Wu Kang Li | 2023 | Journal of Modern Power Systems and Clean Energy2023，11，3： | 1 |
| 8 | Two-point estimate method for probabilistic optimal power flow computation including wind farms with correlated parameters显示文摘 | Li Xue Cao Jia Du Dajun | 2013 | Communications in Computer and Information Science2013，355，： | 1 |
| 9 | Epigenetic alterations as cancer diagnostic,prognostic,and predictive biomarkers显示文摘 | Deng Dajun Liu Zhaojun Du Yantao | 2010 | Adv Genet2010，71，： | 1 |
| 10 | A Novel Dynamic Watermarking-Based EKF Detection Method for FDIAs in Smart Grid显示文摘Dear editor,The existing bad data detection(BDD)cannot effectively detect false data injection attacks(FDIAs)in smart grid.The objectiveness of this letter is to investigate a novel dynamic watermarking(DW)-based extended Kalman filter(EKF)detection method to detect FDIAs.Firstly,security weakness of traditional χ^(2) detector is analyzed,and a novel DW-based EKF detection method is proposed for FDIAs.Secondly,the detection effectiveness and security property of the proposed method are analyzed theoretically,where not only the positive correlation between the detection performance and DW signal intensity but also zero impact of FDIAs not being detected on smart grid(SG)are revealed.Finally,the effectiveness of the proposed method is confirmed by experimental results. | Xue Li Ziyi Wang Changda Zhang Dajun Du Minrui Fei | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，7： | 1 |
| 11 | Designing Discrete Predictor-Based Controllers for Networked Control Systems with Time-varying Delays:Application to A Visual Servo Inverted Pendulum System显示文摘A discrete predictor-based control method is developed for a class of linear time-invariant networked control systems with a sensor-to-controller time-varying delay and a controller-to-actuator uncertain constant delay,which can be potentially applied to vision-based control systems.The control scheme is composed of a state prediction and a discrete predictor-based controller.The state prediction is used to compensate for the effect of the sensor-to-controller delay,and the system can be stabilized by the discrete predictor-based controller.Moreover,it is shown that the control scheme is also robust with respect to slight message rejections.Finally,the main theoretical results are illustrated by simulation results and experimental results based on a networked visual servo inverted pendulum system. | Yang Deng Vincent Léchappé Changda Zhang Emmanuel Moulay Dajun Du Franck Plestan Qing-Long Han | 2022 | IEEE/CAA Journal of Automatica Sinica2022，9，10： | 0 |
| 12 | A Multi-Objective and Multi-Constraint Optimization Model for Cyber-Physical Power Systems Considering Renewable Energy and Electric Vehicles显示文摘Dear Editor,To tackle the global challenges of climate change and energy secu-r ity, building low carbon energy systems has become a research hotspot. Cyber-physical power systems(CPPSs) is an important infrastructure to link both energy and transport systems, two major sectors that are difficult to decarbonize, and it is necessary to establish CPPSs model to consider the integration of both renewable energy and electric vehicle(EV). | Yu Zhang Minrui Fei Qing Sun Dajun Du Aleksandar Rakic Kang Li | 2023 | IEEE/CAA Journal of Automatica Sinica2023，10，6： | 0 |
| 13 | PROG1 acts upstream of LAZY1 to regulate rice tiller angle as a repressor显示文摘Rice tiller angle,as a component of plant architecture,affects rice grain yield via plant density.However,the molecular mechanism underlying rice tiller angle remains elusive.We report that the key domestication gene PROSTRATE GROWTH 1(PROG1)controls rice tiller angle by regulating shoot gravitropism and LAZY1(LA1)-mediated asymmetric distribution of auxin.Acting as a transcriptional repressor,PROG1 negatively regulates the expression of LA1 in light-grown rice seedlings.Overexpression of LA1 partially rescued the larger tiller angle of the PROG1 complementation transgenic plant(prog1-D).Double-mutant analysis showed that PROG1 acts upstream of LA1 to regulate shoot gravitropism and tiller angle.Mutation of Suppressors of lazy1(SOL1),encoding DWARF3(D3)acting in the strigolactone signal pathway,suppressed the large tiller angle of prog1-D by rescuing the transcription of LA1.The discovery of a light-sensitive PROG1-LA1 transcription regulatory module controlling rice shoot gravitropism and tiller angle sheds light on the genetic control of rice tiller angle. | Han Zhang Xiang Li Dajun Sang Linzhou Huang Yuqi Song Mengchen Du Jiajia Cao Wenguang Wang | 2023 | The Crop Journal2023，11，2： | 0 |
| 14 | An online anomaly detection method for stream data using isolation principle and statistic histogram显示文摘Online anomaly detection for stream data has been explored recently,where the detector is supposed to be able to perform an accurate and timely judgment for the upcoming observation.However,due to the inherent complex characteristics of stream data,such as quick generation,tremendous volume and dynamic evolution distribution,how to develop an effective online anomaly detection method is a challenge.The main objective of this paper is to propose an adaptive online anomaly detection method for stream data.This is achieved by combining isolation principle with online ensemble learning,which is then optimized by statistic histogram.Three main algorithms are developed,i.e.,online detector building algorithm,anomaly detecting algorithm and adaptive detector updating algorithm.To evaluate our proposed method,four massive datasets from the UCI machine learning repository recorded from real events were adopted.Extensive simulations based on these datasets show that our method is effective and robust against different scenarios. | Zhiguo Ding Minrui Fei Dajun Du | 2015 | International Journal of Modeling, Simulation, and Scientific Computing2015，6，2： | 0 |
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