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Computer Modeling in engineering & Sciences 2023年第2期134卷 873-892页

作者： Wentao Liu Junxia Ma Weili Xiong Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) School of Internet of Things EngineeringJiangnan UniversityWuxi214122China

This paper studies the parameter estimation problems of the nonlinear systems described by the bilinear state space models in the presence of disturbances.A bilinear state observer is designed for deriving identification algorithms to estimate the state variables using the input-output *** on the bilinear state observer,a novel gradient iterative algorithm is derived for estimating the parameters of the bilinear systems by means of the continuous mixed p-norm cost *** gain at each iterative step adapts to the data quality so that the algorithm has good robustness to the noise ***,to improve the performance of the proposed algorithm,a dynamicmoving window is designed which can update the dynamical data by removing the oldest data and adding the newestmeasurement data.A numerical example of identification of bilinear systems is presented to validate the theoretical analysis.

关键词： Bilinear state space model parameter estimation moving window continuous mixed p-norm

Design and investigation of novel ultra-high-voltage junction field-effect transistor embedded with NPN

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Chinese Physics B 2021年第7期30卷 619-623页

作者： Xi-Kun Feng Xiao-Feng Gu Qin-Ling Ma Yan-Ni Yang Hai-Lian Liang engineering Research Center of internet of things Technology Applications(Ministry of Education) Department of Electronic EngineeringJiangnan UniversityWuxi 214122China

Ultra-high-voltage(UHV)junction field-effect transistors(JFETs)embedded separately with the lateral NPN(JFETLNPN),and the lateral and vertical NPN(JFET-LVNPN),are demonstrated experimentally for improving the electrostatic discharge(ESD)*** ESD characteristics show that both JFET-LNPN and JFET-LVNPN can pass the 5.5-k V human body model(HBM)*** JFETs embedded with different NPNs have 3.75 times stronger in ESD robustness than the conventional *** failure analysis of the devices is performed with scanning electron microscopy,and the obtained delayer images illustrate that the JFETs embedded with NPN transistors have good voltage endurance ***,the internal physical mechanism of the JFETs embedded with different NPNs is investigated with emission microscopy and Sentaurus simulation,and the results confirm that the JFET-LVNPN has stronger ESD robustness than the JFET-LNPN,because the vertical NPN has a better electron collecting *** JFET-LVNPN is helpful in providing a strong ESD protection and functions for a power device.

关键词： junction field-effect transistors NPN electrostatic discharge(ESD)robustness ESD protection

Abnormal Traffic Detection for internet of things Based on an Improved Residual Network

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Computers, Materials & Continua 2024年第6期79卷 4433-4448页

作者： Tingting Su Jia Wang Wei Hu Gaoqiang Dong Jeon Gwanggil school of Computer Science and Technology Xinjiang UniversityUrumqi830046China school of Cyber Science and engineering Jinling Institute of Technology CityNanjing210000China College of Information Technology Incheon National UniversityIncheon22012Korea

Along with the progression of internet of things(IoT)technology,network terminals are becoming continuously more *** has been widely applied in various scenarios,including urban infrastructure,transportation,industry,personal life,and other socio-economic *** introduction of deep learning has brought new security challenges,like an increment in abnormal traffic,which threatens network *** feature extraction leads to less accurate classification *** abnormal traffic detection,the data of network traffic is high-dimensional and *** data not only increases the computational burden of model training but also makes information extraction more *** address these issues,this paper proposes an MD-MRD-ResNeXt model for abnormal network traffic *** fully utilize the multi-scale information in network traffic,a Multi-scale Dilated feature extraction(MD)block is *** module can effectively understand and process information at various scales and uses dilated convolution technology to significantly broaden the model’s receptive *** proposed Max-feature-map Residual with Dual-channel pooling(MRD)block integrates the maximum feature map with the residual *** module ensures the model focuses on key information,thereby optimizing computational efficiency and reducing unnecessary information *** results show that compared to the latest methods,the proposed abnormal traffic detection model improves accuracy by about 2%.

关键词： Abnormal network traffic deep learning residual network multi-scale feature extraction max-feature-map

OFF-grid full-dimension channel estimation for mm Wave/THz systems with angular block prior

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Science China(Information Sciences) 2021年第11期64卷 245-246页

作者： Hongyun CHU Wei FENG Maoqi LI Zhichao ZHU Guilu WU school of Communications and Information engineering Xi'an University of Posts and Telecommunications National Mobile Communications Research Laboratory Southeast University school of internet of things engineering Jiangnan University

Dear editor,The acquirement of the channel state information(CSI) is indispensable for designing efficient beamformers [1]. Unfortunately, estimating CSI is extremely challenging in the mm Wave/THz systems where the number of antennas is super-large and the receive signal-to-noise ratio(SNR) is relatively low. Most of the existing estimators are based on the direct applications of inherent channel sparsity and generic compressive sensing(CS) techniques, which cannot lead to fine enough performances in channel estimation because it puts strict requirements on the channel sparsity or the data measurements [2–7].

关键词： mmWave/THz communication full-dimension channel estimation super-large antenna array weighted atomic norm sparsity angular block

Coverage-optimization based guidance of mobile agents for improved control of distributed parameter systems

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Journal of Systems engineering and Electronics 2019年第3期30卷 601-612页

作者： ZHUANG Bo CUI Baotong WU Wei JIANG Zhengxian school of internet of things engineering Jiangnan University Wuxi 214122 China Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Wuxi 214122 China

The control problem of a class of parabolic distributed parameter systems (DPSs) is investigated by using mobile agents with capabilities of sensing and actuating. The guidance strategies of mobile agents based on coverage optimization methods are proposed to improve the control performance of the system and make the state norm of the system converge to zero faster. The coverage optimization problems are constructed based on the measurement of each agent. By solving the coverage optimization problems, the local optimal moving direction of each agent can be obtained. Then the gradient-based agent motion control laws are established. With the indicator function and the surface delta function, this method is generalized to n-dimensional space, and suitable for any sensing region with piecewise smooth boundaries. The stability and control performance of the system are analyzed. Numerical simulations show the effectiveness of the proposed methods.

关键词： distributed parameter systems (DPSs) mobile agents coverage optimization indicator function

Probability hypothesis density filter with adaptive parameter estimation for tracking multiple maneuvering targets

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Chinese Journal of Aeronautics 2016年第6期29卷 1740-1748页

作者： Yang Jinlong Yang Le Yuan Yunhao Ge Hongwei school of internet of things engineering Jiangnan UniversityWuxi 214122China Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Wuxi 214122China

The probability hypothesis density(PHD) filter has been recognized as a promising technique for tracking an unknown number of targets. The performance of the PHD filter, however, is sensitive to the available knowledge on model parameters such as the measurement noise variance and those associated with the changes in the maneuvering target trajectories. If these parameters are unknown in advance, the tracking performance may degrade greatly. To address this aspect, this paper proposes to incorporate the adaptive parameter estimation(APE) method in the PHD filter so that the model parameters, which may be static and/or time-varying, can be estimated jointly with target states. The resulting APE-PHD algorithm is implemented using the particle filter(PF), which leads to the PF-APE-PHD filter. Simulations show that the newly proposed algorithm can correctly identify the unknown measurement noise variances, and it is capable of tracking multiple maneuvering targets with abrupt changing parameters in a more robust manner, compared to the multi-model approaches.

关键词： Adaptive parameter estimation Multiple target tracking Multivariate Gaussian distribution Particle filter Probability hypothesis density

Bioinspired Multifunctional Self-Sensing Actuated Gradient Hydrogel for Soft-Hard Robot Remote Interaction

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Nano-Micro Letters 2024年第4期16卷 139-152页

作者： He Liu Haoxiang Chu Hailiang Yuan Deliang Li Weisi Deng Zhiwei Fu Ruonan Liu Yiying Liu Yixuan Han Yanpeng Wang Yue Zhao Xiaoyu Cui Ye Tian College of Medicine and Biological Information engineering Northeastern UniversityShenyang 110169People’s Republic of China Foshan Graduate school of Innovation Northeastern UniversityFoshan 528300People’s Republic of China

The development of bioinspired gradient hydrogels with self-sensing actuated capabilities for remote interaction with soft-hard robots remains a challenging endeavor. Here, we propose a novel multifunctional self-sensing actuated gradient hydrogel that combines ultrafast actuation and high sensitivity for remote interaction with robotic hand. The gradient network structure, achieved through a wettability difference method involving the rapid precipitation of MoO_(2) nanosheets, introduces hydrophilic disparities between two sides within hydrogel. This distinctive approach bestows the hydrogel with ultrafast thermo-responsive actuation(21° s^(-1)) and enhanced photothermal efficiency(increase by 3.7 ℃ s^(-1) under 808 nm near-infrared). Moreover, the local cross-linking of sodium alginate with Ca^(2+) endows the hydrogel with programmable deformability and information display capabilities. Additionally, the hydrogel exhibits high sensitivity(gauge factor 3.94 within a wide strain range of 600%), fast response times(140 ms) and good cycling stability. Leveraging these exceptional properties, we incorporate the hydrogel into various soft actuators, including soft gripper, artificial iris, and bioinspired jellyfish, as well as wearable electronics capable of precise human motion and physiological signal detection. Furthermore, through the synergistic combination of remarkable actuation and sensitivity, we realize a self-sensing touch bioinspired tongue. Notably, by employing quantitative analysis of actuation-sensing, we realize remote interaction between soft-hard robot via the internet of things. The multifunctional self-sensing actuated gradient hydrogel presented in this study provides a new insight for advanced somatosensory materials, self-feedback intelligent soft robots and human–machine interactions.

关键词： Self-sensing Gradient structure Bioinspired actuator Hydrogel sensor Remote interaction

Coherent beam combination of broad-area laser diode array using off-axis external cavity with double feedback

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Chinese Optics Letters 2012年第10期10卷 38-40页

作者：苏宙平纪志成阙立志朱焯炜 school of Science Jiangnan University school of internet of things engineering Jiangnan University

In this letter, we demonstrate coherent beam combination of laser diode array using the external Talbot cavity with double feedback. The double feedback elements consist of grating and high-reflection plane mirror. Compared with single high-reflection plane mirror feedback, the external Talbot cavity with double feedback reduce the number of interference strips in the far-field pattern and narrow spectral line-width of the laser diode array. The results indicate that the application of the external Talbot cavity with double feedback produces a clear far-field interference pattern. In addition, line-width is reduced to 0.15 nm full-width at half-maximum （FWHM）.

关键词： Interference suppression Mirrors

Ultra-low Power CMOS Front-End Readout ASIC for Portable Digital Radiation Detector

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Tsinghua Science and Technology 2011年第2期16卷 157-163页

作者：周云波杨煜单悦尔曹华锋杨兵于宗光 school of internet of things engineering Jiangnan University 58th Research Institute China Electronic Technology Group Corporation

An ultra-low power complementary metal-oxide-semiconductor （CMOS） front-end readout ASIC was developed for a portable digital radiation detector. The ASIC having a charge sensitive amplifier and a semi-Gaussian pulse-shaper was produced using the CSMC 0.5 μm DPDM process. The ENC noise of 363 e at 0 pF with a noise slope of 23 e/pF complies with the stringent low noise requirements. The peaking time was 250 ns at a 100 mV/fC conversion gain （detector capacitance is 20 pF）. By operating this frontend readout ASIC in the weak inversion region, the ultra-low power dissipation is only 0.1 mW/channel （3.0 V） Simulations and test results suggest that this design gives lower power consumption than the front-end readout ASICs working in the strong inversion and is appropriate for the portable digital radiation detectors.

关键词： charge sensitive shaper readout circuit weak inversion region nested feedback loop

Security and Privacy Challenges in SDN-Enabled IoT Systems: Causes, Proposed Solutions,and Future Directions

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Computers, Materials & Continua 2024年第8期80卷 2511-2533页

作者： Ahmad Rahdari Ahmad Jalili Mehdi Esnaashari Mehdi Gheisari Alisa A.Vorobeva Zhaoxi Fang Panjun Sun Viktoriia M.Korzhuk Ilya Popov Zongda Wu Hamid Tahaei Institute of Artificial Intelligence Shaoxing UniversityShaoxing312000China Department of Computer engineering Gonbad Kavous UniversityGonbad-e Kavus49717-99151Iran Faculty of Computer engineering K.N.Toosi University of TechnologyTehran196976-4499Iran Department of Computer Science and engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Secure Information Technologies Department National Research University ITMOSt.Petersburg197101Russia school of Electrical and Computer engineering Shiraz UniversityShiraz71946–84334Iran Department of Computer Science and engineering Islamic Azad UniversityDamavand***Iran Department of R&D Shenzhen BKD Co.Ltd.Shenzhen518000China

Software-Defined Networking(SDN)represents a significant paradigm shift in network architecture,separating network logic from the underlying forwarding devices to enhance flexibility and centralize ***-rently,the internet of things(IoT)connects numerous devices to the internet,enabling autonomous interactions with minimal human ***,implementing and managing an SDN-IoT system is inherently complex,particularly for those with limited resources,as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN *** findings of this study underscore the primary security and privacy challenges across application,control,and data planes.A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy *** investigations have explored cutting-edge methods,such as leveraging blockchain for transaction recording to enhance security and privacy,along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service(DoS)and Distributed DoS(DDoS)***,the analysis indicates that encryption and hashing techniques are prevalent in the data plane,whereas access control and certificate authorization are prominently considered in the control plane,and authentication is commonly employed within the application ***,this paper outlines future directions,offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem.

关键词： Security privacy-preserving software-defined network internet of things