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2023 International Russian automation Conference, RusAutoCon 2023

作者： Kamenskiy, Vladislav Sokolov, Sergey Kurinenko, Marianna Rostov State Transport University «automation and Remote Control in Railway Transport» Department Rostov-on-Don Russia Moscow Technical University of Communications and Informatics Department of Informatics and Computer Engineering Rostov-on-Don Russia

ISBN: (纸本)9798350345551

The article analyzes modern computing devices that perform multiplication operations. The main classes of multipliers built on the basis of both electronic and optical elements are considered. The main disadvantage of these devices, which negatively affects their performance, is the inability to carry out parallel calculations with them. In turn, this disadvantage is due to the fact that multiplication of the multi-bit binary number in general is carried out by calculating the partial products of the bits of the multipliers and their addition with the inevitable implementation of a corresponding, usually very large, number of transfers. The presence of a large number of transfers fundamentally does not allow solving the problem of increasing the speed of calculations. The developed optical binary digital-to-analog multiplier is devoid of this drawback. This optical digital-to-analog multiplier is implemented on the basis of optical splitters, optical couplers and optical banners with a well-developed technology for their manufacture today, which provides a minimum delay time of the optical signal (in the picosecond range). The functional diagram of the proposed optical digital-to-analog multiplier is shown and the principle of its operation is described. The possibility of increasing the speed of this optical digital-to-analog multiplier to the potential for optical information processing circuits is shown. © 2023 IEEE.

关键词： Optical data processing

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Signal Strength Based Ranging for Livestock Localization for Smart Farms 11

Signal Strength Based Ranging for Livestock Localization for...

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2023 IEEE 11th International Conference on Information, Communication and Networks, ICICN 2023

作者： Tu, Chunling Du, Shengzhi Tong, Jigang Wang, Lushuo Plessis, Deon Du Tshwane University of Technology Department of Computer Systems Engineering Pretoria South Africa Tshwane University of Technology Department of Electrical Engineering Pretoria South Africa Tianjin University of Technology Electrical Engineering and Automation Tianjin China Tshwane University of Technology Department of Information Technology Pretoria South Africa

ISBN: (纸本)9798350314014

An intelligent livestock monitoring system has become increasingly popular for monitoring and managing animals in smart farms. Various technologies have been developed to localize the animals with wearable sensors. This paper addresses ranging from Received Signal Strength Indicator (RSSI). ESP32C3-Mini chips are used to construct the localization system, where both ear tags and base stations are built on these chips. Based on the distances captured by multiple base stations, triangulation is employed to estimate the position of the concerned tags. To improve the positioning accuracy, a weighted triangulation method is used. The advantage and distances of the proposed RSSI-based ranging method are discussed using real data. © 2023 IEEE.

关键词： Triangulation

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Seeing the Fruit for the Leaves: Towards Automated Apple Fruitlet Thinning

Seeing the Fruit for the Leaves: Towards Automated Apple Fru...

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2022 Australasian Conference on Robotics and automation, ACRA 2022

作者： Qureshi, Ans Loh, Neville Kwon, Young Min Smith, David Gee, Trevor Bachelor, Oliver McCulloch, Josh Nejati, Mahla Lim, JongYoon Green, Richard Ahn, Ho Seok MacDonald, Bruce Williams, Henry Centre for Automation and Robotic Engineering Science University of Auckland New Zealand Department of Computer Science and Software Engineering University of Canterbury New Zealand

ISBN: (纸本)9781713866480

Following a global trend, the lack of reliable access to skilled labour is causing critical issues for the effective management of apple orchards. One of the primary challenges is maintaining skilled human operators capable of making precise fruitlet thinning decisions. Thinning requires accurately measuring the true crop load for individual apple trees to provide optimal thinning decisions on an individual basis. A challenging task due to the dense foliage obscuring the fruitlets within the tree structure. This paper presents the initial design, implementation, and evaluation details of the vision system for an automatic apple fruitlet thinning robot to meet this need. The platform consists of a UR5 robotic arm and stereo cameras which enable it to look around the leaves to map the precise number and size of the fruitlets on the apple branches. We show that this platform can measure the fruitlet load on the apple tree to with 84% accuracy in a real-world commercial apple orchard while being 87% precise. © 2022 Australasian Robotics and automation Association. All rights reserved.

关键词： Fruits

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Target tracking method of Siamese networks based on the broad learning system

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1043-1057页

作者： Dan Zhang C.L.Philip Chen Tieshan Li Yi Zuo Nguyen Quang Duy Navigation College Dalian Maritime UniversityDalianChina Innovation and Entrepreneurship Education College Dalian Minzu UniversityDalianChina Computer Science and Engineering College South China University of TechnologyGuangzhouChina Department of Computer and Information Science Faculty of Science and TechnologyUniversity of MacaoMacaoChina School of Automation Engineering University of Electronic Science and Technology of ChinaChengduChina Faculty of Navigation Vietnam Maritime UniversityHaiphongVietnam

Target tracking has a wide range of applications in intelligent transportation,real‐time monitoring,human‐computer interaction and other ***,in the tracking process,the target is prone to deformation,occlusion,loss,scale variation,background clutter,illumination variation,etc.,which bring great challenges to realize accurate and real‐time *** based on Siamese networks promotes the application of deep learning in the field of target tracking,ensuring both accuracy and real‐time ***,due to its offline training,it is difficult to deal with the fast motion,serious occlusion,loss and deformation of the target during ***,it is very helpful to improve the performance of the Siamese networks by learning new features of the target quickly and updating the target position in time *** broad learning system(BLS)has a simple network structure,high learning efficiency,and strong feature learning *** at the problems of Siamese networks and the characteristics of BLS,a target tracking method based on BLS is *** method combines offline training with fast online learning of new features,which not only adopts the powerful feature representation ability of deep learning,but also skillfully uses the BLS for re‐learning and re‐*** broad re‐learning information is used for re‐detection when the target tracking appears serious occlusion and so on,so as to change the selection of the Siamese networks search area,solve the problem that the search range cannot meet the fast motion of the target,and improve the *** results show that the proposed method achieves good results on three challenging datasets and improves the performance of the basic algorithm in difficult scenarios.

关键词： broad learning system siamese network target tracking

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Evaluation of the Energy Efficiency of Software Calculations in the Design of Microcontroller Devices 17

Evaluation of the Energy Efficiency of Software Calculations...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Topalov, Andrii Styslo, Taras Tkach, Vitalii Peschanenko, Volodymyr Styslo, Oksana Skrypyuk, Rostyslav Admiral Makarov National University of Shipbuilding Department of computerized control systems Mykolaiv Ukraine King Danylo University Department of IT Ivano-Frankivsk Ukraine Kherson State University Department of computer science and software engineering Ivano-Frankivsk Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of automation and computer-integrated technologies Ivano-Frankivsk Ukraine

ISBN: (纸本)9798331520564

The paper presents a study of the effectiveness of software from the point of view of minimizing the energy consumption of microprocessor devices. In this case, the programming of the microcontroller in various programming languages for arithmetic operations, as well as data output through the port, is considered. In the course of the tests, the peculiarities of the application of this or that program and their operation, taking into account the energy saving of the microcontroller, are noted. © 2024 IEEE.

关键词： Microcontrollers

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Automatic mouth sampling based on computer vision and robot control

Automatic mouth sampling based on computer vision and robot ...

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2023 China automation Congress, CAC 2023

作者： Huang, Wensi Li, Tianhua Liao, Qinsong Zhang, Yizhou Shi, Liangren Li, Yuanlong Shanghai Jiao Tong University Department of Automation Shanghai200240 China School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China

ISBN: (纸本)9798350303759

With the increasing application of robots, the automated and unmanned operation is becoming a new trend. In the scenario of nucleic acid sampling, the medical staff are under great exposure to high-risk substances. Compared to humans, unmanned sampling has higher accuracy and round-the-clock service capabilities, most importantly, it protects the medical staff from getting infected. To accomplish the benefit reached by the robot, an automatic nucleic acid sampling method based on computer vision and robot control is proposed in this paper. The pipeline first obtains 2D image coordinates of the target sampling points by YOLO detection algorithm, then translates the 2D image coordinates to 3D robot base coordinates, and finally controls the robot to achieve automatic mouth sampling. Experiment results demonstrate the feasibility and accuracy of the pipeline. © 2023 IEEE.

关键词： Robots

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MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models

MamMIL: Multiple Instance Learning for Whole Slide Images wi...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Fang, Zijie Wang, Yifeng Zhang, Ye Wang, Zhi Zhang, Jian Ji, Xiangyang Zhang, Yongbing Tsinghua University Tsinghua Shenzhen International Graduate School Shenzhen China Shenzhen China School of Computer Science and Technology Shenzhen China Peking University School of Electronic and Computer Engineering Shenzhen Graduate School Shenzhen China Tsinghua University Department of Automation Beijing China

ISBN: (纸本)9798350386226

Recently, pathological diagnosis has achieved superior performance by combining deep learning models with the multiple instance learning (MIL) framework using whole slide images (WSIs). However, the giga-pixeled nature of WSIs poses a great challenge for efficient MIL. Existing studies either do not consider global dependencies among instances, or use approximations such as linear attentions to model the pair-to-pair instance interactions, which inevitably brings performance bottlenecks. To tackle this challenge, we propose a framework named MamMIL for WSI analysis by cooperating the selective structured state space model (i.e., Mamba) with MIL, enabling the modeling of global instance dependencies while maintaining linear complexity. Specifically, considering the irregularity of the tissue regions in WSIs, we represent each WSI as an undirected graph. To address the problem that Mamba can only process 1D sequences, we further propose a topology-aware scanning mechanism to serialize the WSI graphs while preserving the topological relationships among the instances. Finally, in order to further perceive the topological structures among the instances and incorporate short-range feature interactions, we propose an instance aggregation block based on graph neural networks. Experiments show that MamMIL can achieve advanced performance than the state-of-the-art frameworks. The code can be accessed at https://***/Vison307/MamMIL. © 2024 IEEE.

关键词： Undirected graphs

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Resilient Consensus of Multi-Agent Systems on Time-Varying Directed Graphs Under Byzantine Attacks and Actuation Attacks

Resilient Consensus of Multi-Agent Systems on Time-Varying D...

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2023 China automation Congress, CAC 2023

作者： Gong, Xin Shu, Zhan Feng, Zhiguang Lin, Hong School of Cyber Science and Engineering Southeast University Nanjing China University of Alberta Department of Electrical and Computer Engineering AB Canada College of Automation Harbin Engineering University Harbin China Institute of Intelligence Science and Engineering Shenzhen Polytechnic University Shenzhen China

ISBN: (纸本)9798350303759

This work deals with the distributed attack-resilient consensus problem for continuous-time multi-agent systems on time-varying directed graphs. An unknown fraction of agents are Byzantine agents, which send false information to deceive their neighbors. Moreover, each normal agent suffers from actuation attacks. In order to ensure the resilience of all normal agents against the above hybrid attacks, a new kind of edge-based protocols is formulated, which achieves resilient consensus via signed feedback. Then, the finite-time zero-error control performance of the above protocol is proven for (2f+1) - robust time-varying directed topologies, based on strictly Lyapunov stability analysis. © 2023 IEEE.

关键词： Directed graphs

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Strategic Gradient Transmission With Targeted Privacy-Awareness in Model Training: A Stackelberg Game Analysis

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4635-4648页

作者： Sun, Hezhe Wang, Yufei Yang, Huiwen Huo, Kaixuan Li, Yuzhe Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China Liaoning ATS Intelligent Transportation Technology Company Ltd. Research Institute Shenyang110004 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong999077 Hong Kong

Privacy-aware machine learning paradigms have sparked widespread concern due to their ability to safeguard the local privacy of data owners, preventing the leakage of private information to untrustworthy platforms or malicious third parties. This article focuses on characterizing the interactions between the learner and the data owner within this privacy-aware training process. Here, the data owner hesitates to transmit the original gradient to the learner due to potential cybersecurity issues, such as gradient leakage and membership inference. To address this concern, we propose a Stackelberg game framework that models the training process. In this framework, the data owner's objective is not to maximize the discrepancy between the learner's obtained gradient and the true gradient but rather to ensure that the learner obtains a gradient closely resembling one deliberately designed by the data owner, while the learner's objective is to recover the true gradient as accurately as possible. We derive the optimal encoder and decoder using mismatched cost functions and characterize the equilibrium for specific cases, balancing model accuracy and local privacy. Numerical examples illustrate the main results, and we conclude with expanding discussions to suggest future investigations into reliable countermeasure designs. © 2020 IEEE.

关键词： Game theory

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Short-Term Wind Power Interval Prediction Based on GD-LSTM and Bootstrap Techniques 5

Short-Term Wind Power Interval Prediction Based on GD-LSTM a...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Zhang, Wei Quan, Hao Zhang, Wenjie Li, Zixiong Nanjing University of Science and Technology School of Automation Department of Electrical Engineering Nanjing210094 China National University of Singapore Department of Electrical and Computer Engineering 117576 Singapore

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

Wind power forecasting plays a significant role in the stability, security and reliability of power system. Compared with point forecast, interval forecast is able to quantify the uncertainty effectively. In this paper, a novel interval forecast method based on modified Gaussian-Dropout long short-term memory (GD-LSTM) network and block bootstrap is proposed to predict short-term wind power. In this model, prediction uncertainty is concerned to come from model parameters and data noise. Bootstrap is used to generate multiple subsets firstly, and then LSTM models are trained by these subsets. The test dataset prediction intervals (PIs) are generated with confidence levels ranging from 85% to 95%. The results demonstrate that the PIs generated by proposed method can always reach the targets, the coverage probability generated by block bootstrap may lower than other methods in sometimes, while the comprehensive scores are always the best. © 2022 IEEE.

关键词： Wind power

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