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Automatic search for photoacoustic marker using automated transrectal ultrasound

Biomedical Optics Express 2023年第11期14卷 6016-6030页

作者： Wu, Zijian Moradi, Hamid Yang, Shuojue Song, Hyunwoo Boctor, Emad M. Salcudean, Septimiu E. Johns Hopkins University Laboratory for Computational Sensing and Robotics BaltimoreMD United States University of British Columbia Dept. of Electrical and Computer Engineering VancouverBC Canada University of Texas at Austin Walker Department of Mechanical Engineering AustinTX United States Johns Hopkins University Dept. of Computer Science BaltimoreMD United States

Real-time transrectal ultrasound (TRUS) image guidance during robot-assisted laparoscopic radical prostatectomy has the potential to enhance surgery outcomes. Whether conventional or photoacoustic TRUS is used, the robotic system and the TRUS must be registered to each other. Accurate registration can be performed using photoacoustic (PA markers). However, this requires a manual search by an assistant [IEEE Robot. Autom. Lett 8, 1287 (2023).]. This paper introduces the first automatic search for PA markers using a transrectal ultrasound robot. This effectively reduces the challenges associated with the da Vinci-TRUS registration. This paper investigated the performance of three search algorithms in simulation and experiment: Weighted Average (WA), Golden Section Search (GSS), and Ternary Search (TS). For validation, a surgical prostate scenario was mimicked and various ex vivo tissues were tested. As a result, the WA algorithm can achieve 0.53°±0.30° average error after 9 data acquisitions, while the TS and GSS algorithm can achieve 0.29◦±0.31◦ and 0.48°±0.32° average errors after 28 data acquisitions. © 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Urology

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Exploring the Economic Feasibility of Advanced Air Mobility in the Early Stages

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 4826-4830页

作者： Jingqiu Guo Long Chen Lingxi Li Xiaoxiang Na Ljubo Vlacic Fei-Yue Wang Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University–Purdue University Indianapolis (IUPUI) Indianapolis IN USA Department of Engineering University of Cambridge Cambridge U.K. Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith University Nathan QLD Australia State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.

关键词： Active appearance model Costs Economics Transportation Helicopters Aircraft propulsion Public transportation

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Stealthy Attacks on Sampled-Data Control and Encryption-Based Countermeasures

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IEEE Transactions on Automatic Control 2025年

作者： Shang, Jun Li, Yuzhe Chen, Tongwen Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

This paper investigates stealthy attacks on sampled-data control systems, where a continuous process is sampled periodically, and the resultant discrete output and control signals are transmitted through dual channels in wireless communication networks. Acknowledging the vulnerability of these transmitted data to cyber threats, we analyze two types of stealthy attacks that compromise either one or both channels. We explicitly present the necessary and sufficient conditions for the existence of stealthy single-channel attacks. To mitigate these security risks, we implement encryption-based countermeasures, including linear time-invariant and periodic encryption methods. We detail sufficient conditions under which these encryption strategies effectively thwart single- and dual-channel stealthy attacks. The effectiveness of these approaches and the theoretical findings are demonstrated through numerical simulations. © 1963-2012 IEEE.

关键词： Cyber attacks

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Deep learning-based segmentation of breast masses using convolutional neural networks 12

Deep learning-based segmentation of breast masses using conv...

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12th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2023

作者： Anghelache Nastase, I.-N. Moldovanu, S. Moraru, L. The Modelling & Simulation Laboratory Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Emil Racovita Theoretical Highschool 12-14 Regiment 11 Siret Street Galati800332 Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Department of Chemistry Physics & Environment Faculty of Sciences and Environment Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania

Automatic breast tumor segmentation based on convolutional neural networks (CNNs) is significant for the diagnosis and monitoring of breast cancers. CNNs have become an important method for early diagnosis of breast cancer and, thus, can help decrease the mortality rate. In order to assist medical professionals in breast cancer investigation a computerized system based on two encoder-decoder architectures for breast tumor segmentation has been developed. Two pre-trained DeepLabV3+ and U-Net models are proposed. The encoder generates a high-dimensional feature vector while the decoder analyses the low-resolution feature vector provided by the encoder and generates a semantic segmentation mask. Semantic segmentation based on deep learning techniques can overcome the limitations of traditional algorithms. To assess the efficiency of breast ultrasound image segmentation, we compare the segmentation results provided by CNNs against the Local Graph Cut technique (a semi-automatic segmentation method) in the Image Segmenter application. The output segmentation results have been evaluated by using the Dice similarity coefficient that compares the ground truth images provided by the specialists against the predicted segmentation results provided by the CNNs and Local Graph Cut algorithm. The proposed approach is validated on 780 breast ultrasonographic images of the BUSI public database of which 437 are benign and 210 are malignant. The BUSI database provides classification (benign or malignant) labels for ground truth in binary mask images. The average Dice scores computed between the ground truth images against CNNs were as follows: 0.9360 (malignant) and 0.9325 (benign) for the DeepLabV3+ architecture and of 0.6251 (malignant) and 0.6252 (benign) for the U-Net, respectively. When the segmentation results provided by CNNs were compared with the Local Graph Cut segmented images, the Dice scores were 0.9377 (malignant) and 0.9204 (benign) for DeepLabV3+ architecture and 0.61

关键词： Graphic methods

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Dynamic quantized consensus under DoS attacks: Towards a tight zooming-out factor

arXiv

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arXiv 2023年

作者： Feng, Shuai Ran, Maopeng Ishii, Hideaki Xu, Shengyuan The School of Automation Nanjing University of Science and Technology Nanjing210094 China The School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Zhongguancun Laboratory Beijing100094 China The Department of Computer Science Tokyo Institute of Technology Yokohama226-8502 Japan

This paper deals with dynamic quantized consensus of dynamical agents in a general form under packet losses induced by Denial-of-Service (DoS) attacks. The communication channel has limited bandwidth and hence the transmitted signals over the network are subject to quantization. To deal with agent’s output, an observer is implemented at each node. The state of the observer is quantized by a finite-level quantizer and then transmitted over the network. To solve the problem of quantizer overflow under malicious packet losses, a zooming-in and out dynamic quantization mechanism is designed. By the new quantized controller proposed in the paper, the zooming-out factor is lower bounded by the spectral radius of the agent’s dynamic matrix. A sufficient condition of quantization range is provided under which the finite-level quantizer is free of overflow. A sufficient condition of tolerable DoS attacks for achieving consensus is also provided. At last, we study scalar dynamical agents as a special case and further tighten the zooming-out factor to a value smaller than the agent’s dynamic parameter. Under such a zooming-out factor, it is possible to recover the level of tolerable DoS attacks to that of unquantized consensus, and the quantizer is free of overflow. © 2023, CC BY-NC-ND.

关键词： Packet loss

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Design and Application of a One-Stop Mobile Application Sharing Platform for Steel Enterprises

Design and Application of a One-Stop Mobile Application Shar...

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Chinese Control Conference (CCC)

作者： Xinzhe Chen Luefeng Chen Jie Hu Qingfeng Yang Min Wu Witold Pedrycz School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance.

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Comments on “Distributed Synthesis of Local Controllers for Networked Systems With Arbitrary Interconnection Topologies”

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IEEE Transactions on Automatic Control 2022年第12期67卷 6987-6989页

作者： Etika Agarwal S. Sivaranjani Yang Song Vijay Gupta Panos Antsaklis Walmart Global Tech Bangalore India School of Industrial Engineering at Purdue University West Lafayette IN USA Department of Automation School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Key Laboratory of Power Station Automation Technology Shanghai China Elmore Family School of Electrical and Computer Engineering at Purdue University West Lafayette IN USA Department of Electrical Engineering University of Notre Dame Notre Dame IN USA

In the article entitled “Distributed synthesis of local controllers for networked systems with arbitrary interconnection topologies” published in the IEEE Transactions on Automatic Control, vol. 66, pp. 683–698, 2021, there were some missing terms in Lemma 1 and the definition of the messenger matrices. Here, we include these terms and suitably modify the corresponding proofs. Note that all the main claims of the original article, including distributed analysis, distributed synthesis, and compositionality hold with the modified results.

关键词： Topology Network topology Symmetric matrices automation Switched systems Mechatronics Knowledge engineering

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Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

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arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

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Rebalanced Region-Pixel Loss for Concrete Defects Segmentation 4

Rebalanced Region-Pixel Loss for Concrete Defects Segmentati...

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4th International Conference on Artificial Intelligence and Pattern Recognition, AIPR 2021

作者： Hong, Kunlong Wang, Hongguang Yang, Liang Yuan, Bingbing State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China The CCNY Robotics Lab Electrical Engineering Department City College of New York New York United States

ISBN: (纸本)9781450384087

The deep convolution neural network (DCNN) using cross-entropy loss has already achieved high accuracy on the single defect classification task. However, for multi-defect segmentation, the imbalance of categories makes the segmentation of small targets (cracks) not meticulous enough. It also has to adjust the weight of categories manually. This research proposes a region-pixel loss function, which uses a rebalanced training method to balance category weights automatically and classify small categories more accurately. First, we use a wall-climbing robot to obtain the color and depth (RGB-D) information of the surface. Then, we adopt the visual based simultaneous localization and mapping (V-SLAM) method to select key-frame as the input of DCNN. Finally, reconstructing the 3D model of the environment with the output segmentation results. At the same time, to address the weak links of human-computer interaction in the post-processing of defect monitoring, a fast searching method from global 3D model to local details is proposed so that the staff can calmly obtain the local defects' detailed image. Experiments show that our loss function improves the intersection over union (IoU) of small flaws on the verification set. The designed global-to-local interaction method has been applied in the actual dam surface detection and provided an automated solution for monitoring large concrete surfaces. © 2021 ACM.

关键词： Semantic Segmentation

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A novel strategy for sparse attack detection and localization in secure state estimation of power systems

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Electric Power Systems Research 2025年 248卷

作者： Marzieh Samimiat Ali-Akbar Ahmadi Abolfazl Nateghi Manoochehr Kelarestaghi Industrial Automation laboratory Electrical and Computer Engineering Department Kharazmi University Tehran Iran Electrical and Computer Engineering Department Faculty of Engineering Kharazmi University Tehran Iran

In this paper, problem of secure state estimation in power systems in the presence of sparse attack is investigated. Using secure measurements technique for the first time, the required secure measurements are determined for each sparse attack. In the proposed scheme, it is not necessary that all measurements be encoded or transmitted in a dedicated communication channels such as fiber optic links. Therefore, implementation of it is cost-effective. Using the secure measurements technique, modified measurement Jacobian matrices are obtained and then modified residual vectors are designed. The residual vectors are designed such that only one detector is reacted to the specific sparse attack, so attacks are localized. The design procedure is based on a simple search which can be done easily and in a fast manner even for the large power systems. Due to the fact that the exact location of the attack in the power system is identified (measurements under the sparse attack), an algorithm is proposed that obtains the correct state estimation. The simulation results on the IEEE-14 bus power system are presented to show the effectiveness of the proposed scheme.

关键词： Bad data detection algorithms Consistent set Detection and localization Minimum sparse attack Similar sparse attack set

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