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IEEE International Conference on Soft Robotics (RoboSoft)

作者： Seoyeon Ham Brian Byunghyun Kang Kevin Abishek Hyunglae Lee Wansoo Kim Department of Interdisciplinary Robot Engineering Systems Hanyang University Gyeonggi-do Republic of Korea Neuromuscular Control and Human Robotics Lab. Arizona States University AZ USA Department of Intelligent Mechatronics Engineering Sejong University Seoul Republic of Korea Robotics Department Ansan-si Gyeonggi-do Republic of Korea

This paper presents a tunable stiffness actuator with a soft-rigid combined layer jamming mechanism. The tunable stiffness actuator is aimed to be integrated into an exosuit to prevent ankle sprain and avoid or mitigate the development of chronic ankle instability. The main purpose of the soft-rigid layer jamming mechanism is to produce large stiffness with a small volume and achieve a linear stiffness characteristic. To this end, the actuator is designed to include rigid retainer pieces within the soft silicone layers, and each soft-rigid layer is jammed to induce stiffness changes. To validate the stiffness characteristics of the proposed soft-rigid actuator, a series of experiments were performed and stiffness changes were investigated for varying jamming states from unjammed to fully jammed states. Increasing the number of jamming layer effectively increased the actuator stiffness, which was consistent with expected results from the analytical model. Soft-rigid actuator's stiffness at the fully jammed state was 212.1% and 123.1% higher than the unjammed state for one-side and both sides anchored conditions, respectively. Compared to the soft actuator without the rigid retainer, the soft-rigid actuator exhibited a more linear characteristic (Pearson correlation coefficient = 0.990 and 0.997 for one-side and both sides anchored conditions, respectively). Moreover, the soft-rigid actuator achieved significantly higher stiffness than the soft actuator in all jamming states (at least 41.3% increase in each jamming state). The results suggest a potential use of the tunable stiffness actuator to develop a soft ankle exosuit with highly variable but linear stiffness characteristics.

关键词： Correlation coefficient Actuators Analytical models Composite materials Mechanical cables Soft robotics Jamming

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UAV-Aided Secure Communication With Deployment Optimization and Cooperative Jamming 11

UAV-Aided Secure Communication With Deployment Optimization ...

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11th International Conference on intelligent control and Information Processing, ICICIP 2021

作者： Li, Hongbing Wu, Juan Luo, Lei Xiong, Jiang Chongqing Three Gorges University Key Lab. of Intelligent Information Processing and Control of Chongqing Municipal Institutions Chongqing Engineering Research Center of Internet of Things and Intelligent Control Technology Wanzhou China Chongqing Three Gorges University Chongqing Key Laboratory of Geological Environment Monitoring and Disaster Early-Warning Wanzhou China Beijing University of Posts and Telecommunications School of Artificial Intelligence Beijing China

ISBN: (纸本)9781665425155

This paper investigates the jointly transmit power and unmanned aerial vehicle (UAV)/jammer deployment optimization problem for UAV enabled jammer-assisted secure communication systems, where a jammer is exploited to assist transmitting data from a source node to a legitimate destination node in the presence of multiple eavesdroppers. To increase the secrecy energy efficiency, which is defined as the achievable secrecy rate per energy consumption unit, we formulate a secrecy energy efficiency maximization problem by jointly optimizing the transmit power and UAV/jammer deployment. The resulting optimization problem is shown to be a non-convex and fractional optimization problem, which is challenging to solve. As such, we decompose the original problem into two sub-problems, and then, an efficient iterative algorithm is proposed by leveraging the extensive search method and Dinkelbach method in combination with successive convex approximation (SCA) techniques. Numerical simulation results show that the proposed scheme significantly improves the secrecy energy efficiency of the system. © 2021 IEEE.

关键词： Energy efficiency

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Research Status of 6LoWPAN in the Field of Internet of Things 5

Research Status of 6LoWPAN in the Field of Internet of Thing...

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5th International Conference on Automation, control and Robotics engineering, CACRE 2020

作者： Zhao, Liang Wang, Guangwen School of Control Science and Engineering Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China Dalian University of Technology School of Control Science and Engineering Dalian China

ISBN: (纸本)9781728198880

The increasing number of wireless sensor nodes brings more application markets and challenges to the Internet of things (IoT). The traditional IPv4 address resources cannot meet the needs of the development of the IoT, so we need a communication mechanism with better compatibility and scalab.lity. With the proposal of the 6LoWPAN protocol, the application of 6LoWPAN to the communication network of the IoT has become the focus of research. This paper studies the research status of 6LoWPAN in the field of Internet of things in the past four years, and analyzes the system architecture, system composition and monitoring parameters of 6LoWPAN through different application scenarios. Experiments in related literatures show that 6LoWPAN has stable network transmission performance and can be used for precise monitoring and management in combination with web applications. In addition, RPL routing protocol security algorithm can be one of the future research directions. © 2020 IEEE.

关键词： Internet of things

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Rethinking Disentanglement in Unsupervised Domain Adaptation for Medical Image Segmentation

Rethinking Disentanglement in Unsupervised Domain Adaptation...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Yan Wang Yixin Chen Yingying Zhang Haogang Zhu School of Instrumentation and Optoelectronic Engineering Beihang University Beijing China State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Biomedical Engineering Beihang University Beijing China BioMind Technology Zhongguancun Medical Engineering Center Beijing China School of Biological Science and Medical Engineering Beihang University Beijing China Blockchain Lab. Xiong’An Intelligent City Innovation Federation China

Domain adaptation has become an important topic because the trained neural networks from the source domain generally perform poorly in the target domain due to domain shifts, especially for medical image analysis. Previous DA methods mainly focus on disentangling domain features. However, it is based on feature independence, which often can not be guaranteed in reality. In this work, we present a new DA approach called Dimension-based Disentangled Dilated Domain Adaptation (D 4 A) to disentangle the storage locations between the features to tackle the problem of domain shift for medical image segmentation tasks without the annotations of the target domain. We use Adaptive Instance Normalization (AdaIN) to encourage the content information to be stored in the spatial dimension, and the style information to be stored in the channel dimension. In addition, we apply dilated convolution to preserve anatomical information avoiding the loss of information due to downsampling. We validate the proposed method for cross-modality medical image segmentation tasks on two public datasets, and the comparison experiments and ablation studies demonstrate the effectiveness of our method, which outperforms the state-of-the-art methods.

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Reconstructing Three-Degree-of-Freedom Pose through Temporal Phase-Shifted Low-Coherence Spatial Interferograms

Reconstructing Three-Degree-of-Freedom Pose through Temporal...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Liheng Shi Jinxu Zhang Yingying GU Fangqin Gai Jing Liu Guanhao Wu Department of Precision Instrument State Key Laboratory of Precision Measurement Technology and Instruments Tsinghua University Beijing China Research Center of Opto-electronic Sensing Yangtze Delta Region Institute of Tsinghua University Zhejiang Zhejiang China Space Optoelectronic Measurement and Perception Lab. Beijing Institute of Control Engineering Beijing China National Key Laboratory of Space Intelligent Control China Academy of Space Technology Beijing China

We introduce a method for measuring three degrees of freedom using low-coherence light and temporal phase-shifting to discern position and orientation from the coherence envelope shape, enabling direct measurement wit... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Phase measurement Shape Shape measurement Measurement by laser beam Coherence Position measurement Lasers and electrooptics

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Dual-View Pyramid Pooling in Deep Neural Networks for Improved Medical Image Classification and Confidence Calibration

arXiv

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arXiv 2024年

作者： Zhang, Xiaoqing Nie, Qiushi Xiao, Zunjie Zhao, Jilu Wu, Xiao Guo, Pengxin Li, Runzhi Liu, Jin Wei, Yanjie Pan, Yi Center for High Performance Computing Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Statistics and Actuarial Science The University of Hong Kong 999077 Hong Kong Cooperative Innovation Center of Internet Healthcare Zhengzhou University Zhengzhou450001 China Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha410083 China Xinjiang Engineering Research Center of Big Data and Intelligent Software School of software Xinjiang University Wulumuqi830046 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen China

Spatial pooling (SP) and cross-channel pooling (CCP) operators have been applied to aggregate spatial features and pixel-wise features from feature maps in deep neural networks (DNNs), respectively. Their main goal is to reduce computation and memory overhead without visibly weakening the performance of DNNs. However, SP often faces the problem of losing the subtle feature representations, while CCP has a high possibility of ignoring salient feature representations, which may lead to both miscalibration of confidence issues and suboptimal medical classification results. To address these problems, we propose a novel dual-view framework, the first to systematically investigate the relative roles of SP and CCP by analyzing the difference between spatial features and pixel-wise features. Based on this framework, we propose a new pooling method, termed dual-view pyramid pooling (DVPP), to aggregate multi-scale dual-view features. DVPP aims to boost both medical image classification and confidence calibration performance by fully leveraging the merits of SP and CCP operators from a dual-axis perspective. Additionally, we discuss how to fulfill DVPP with five parameter-free implementations. Extensive experiments on six 2D/3D medical image classification tasks show that our DVPP surpasses state-of-the-art pooling methods in terms of medical image classification results and confidence calibration across different DNNs. © 2024, CC BY.

关键词： Deep neural networks

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AIDE: Attack Inference Based on Heterogeneous Dependency Graphs with MITRE ATT&CK

AIDE: Attack Inference Based on Heterogeneous Dependency Gra...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Weidong Zhou Chunhe Xia Nan Feng Xinyi Pan Tianbo Wang Xiaojian Li Beijing Key Lab. of Network Technology Beihang University Beijing China Guangxi Collaborative Innovation Center of Multi-Source Information Integration and Intelligent Processing Guangxi Normal University Guilin China School of Software & Microelectronics Peking University Beijing China School of Cyber Science and Technology Beihang University Beijing China School of Computer Science and Engineering Guangxi Normal University Guilin China

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

The MITRE ATT&CK Framework provides a rich and actionable repository of adversarial tactics, techniques, and procedures (TTPs). By leveraging the associations among these techniques, we can infer unobserved techniques based on those have been observed. Current machine learning inference methods based on small-scale data face the following problems: "logical dependencies missing" and "complex associations missing." The former means that current association methods rely solely on the statistical dependencies between attack techniques while ignoring the logical dependencies involved in executing those techniques. The latter indicates that current inference methods simplify the complex associations between technologies based on statistical assumptions, failing to adequately capture the long-range and intricate real-world relationships between techniques. To address these problems, we propose an Attack Inference model based on heterogeneous DEpendency graphs (AIDE). First, we extract three types of logical dependencies: CVE, Pattern, and Conditional, which allows us to construct a heterogeneous dependency graph among the techniques, thus addressing the "logical dependencies missing" problem. Second, we employ Relation Graph Convolution Neural Networks (RGCN) to aggregate heterogeneous dependencies into representation vectors of the techniques. Finally, we utilize the sequence inference model Decoder, which excels at capturing implicit contextual associations, to infer unknown attacks, thus addressing the "complex associations missing" problem. Experiments conducted on real datasets demonstrate that our model significantly outperforms state-of-the-art baseline models in both hits@k and map@k metrics.

关键词： Adaptation models Aggregates Refining Machine learning Vectors Threat assessment Real-time systems Decoding Security Context modeling

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Research on Denoising Method Based on Iterative SVD Decomposition

Research on Denoising Method Based on Iterative SVD Decompos...

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Chinese Automation Congress (CAC)

作者： Dongting Chu Bingyou Liu Guoyang Wan Jingjing Qi Luanfei Wan College of Electrical Engineering Anhui Polytechnic University Wuhu China The Key Lab. of Advanced Perception and Intelligent Control of High-end Equipment Ministry of Education Anhui Polytechnic University Wuhu China Wuhu HIT Robot Industrial Technology Research Institute Co. Ltd Wuhu China College of Electrical Engineering Wuhu Institute of Technology Wuhu China

In response to the poor denoising ability of Singular Value Decomposition (SVD), and the extracted motion waveform containing some residual noise signals, this paper proposes an iterative SVD decomposition denoising method. Firstly, the original signal is constructed into a binary recursive matrix form, and then SVD decomposition is used to obtain singular values with different contributions to the original matrix. Then, singular values with small contributions are discarded, while those with large contributions are retained. By modifying the signal reconstruction method, the denoised signal can be obtained once, and the required signal can be obtained by repeating the above process continuously. In simulation experiments and tuning fork vibration experiments, this article uses the iterative SVD decomposition denoising method and two existing denoising methods to denoise signals containing noise and uses signal-to-noise ratio (SNR) and root mean square error method (RMSE) as denoising performance indicators for data comparison, confirming the effectiveness and superiority of iterative SVD decomposition denoising method and its excellent denoising ability. In the tuning fork vibration experiment, the error between the measured results and the actual results is 0.3125%, proving that this denoising method has practical application value.

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Respiratory Rate Measurement Method Based on Singular Value Decomposition

Respiratory Rate Measurement Method Based on Singular Value ...

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Chinese Automation Congress (CAC)

In order to enhance the measurement accuracy of respiratory rate, a respiratory rate measurement method based on high-speed vision is presented in this paper. Initially, a high-speed camera is utilized to capture the experimenter's chest breathing movement video sequence, and singular value decomposition (SVD) is applied to extract the displacement resulting from respiratory movement. However, the extracted motion waveform contains some noise signals due to the poor denoising capabilities of SVD. To address this issue, an improved wavelet denoising approach is proposed in this paper to enhance the accuracy of respiratory measurement frequency. Finally, the respiratory frequency measurement method based on high-speed vision is simulated and experimented, and the respiratory rate is calculated through spectral analysis. The experiments indicate that the proposed method can accurately extract the respiratory displacement signal and effectively denoise it, making it convenient for practical use.

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A Many-Objective Evolutionary Algorithm Assisted by Ideal Hyperplane

SSRN

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SSRN 2022年

作者： Zhang, Zhixia Wen, Jie Wang, Hui Cai, Xingjuan Cui, Zhihua Zhang, Wensheng School of Computer Science and Technology Taiyuan University of Science and Technology China School of Information Engineering Nanchang Institute of Technology Nanchang330099 China State Key Laboratory of Intelligent Control and Management of Complex System Institute of Automation Chinese Academy of Sciences China State Key Lab. for Novel Software Technology Nanjing University China

In many-objective optimization problems (MaOPs), it is a difficult task for evolutionary algorithms to balance convergence and diversity while rapidly converging to the Pareto front. As the number of objectives increases, the difficulty of evolutionary algorithms increases with individual selection pressure. To address above problems, we propose a many-objective evolution algorithm assisted by an ideal hyperplane (MaOEA-IH). Firstly, the ideal hyperplane as a reference surface to guide the individual to search the Pareto front, which is established from the extremum of each dimension of the objective space. Secondly, a parallel p -norm mating selection strategy is proposed to improve convergence. In addition, two factors are considered in this strategy: 1) different p -norm are used to measure different spatial scales;2) individual selection uncertainty is defined by incorporating a probabilistic perturbation mechanism. Thirdly, the improved shift-based density estimation strategy is used as the evaluation criterion for environmental selection to improve the convergence and diversity of solution sets and enhance selection pressure. To verify the effectiveness of the proposed algorithm, MAOEA-IH is compared with seven excellent algorithms in three benchmark sets (DTLZ, WFG and MaF). The results show that the proposed MAOEA-IH is highly competitive in solving MaOPs. © 2022, The Authors. All rights reserved.

关键词： Geometry

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