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Optimal energy efficient path planning of UAV using hybrid MACO-MEA* algorithm: theoretical and experimental approach

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 13847-13867页

作者： Balasubramanian, E. Elangovan, E. Tamilarasan, P. Kanagachidambaresan, G.R. Chutia, Dibyajyoti Department of Mechanical Engineering Head-Centre for Autonomous System Research Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Avadi Tamilnadu Chennai600062 India Department of Electronics and Communication Engineering Centre for Autonomous System Research Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Avadi Tamilnadu Chennai600062 India Department of Aeronautical Engineering Centre for Autonomous System Research Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Avadi Tamilnadu Chennai600062 India Department of Computer Science and Engineering and Associate Editor Wireless Networks Springer Vel Tech Rangarajan Dr Sagunthala R & D Institute of Science and Technology Avadi Tamilnadu Chennai600062 India Department of Space North Eastern Space Applications Centre ISRO Meghalaya Umiam793103 India

Autonomous mission capabilities with optimal path are stringent requirements for Unmanned Aerial Vehicle (UAV) navigation in diverse applications. The proposed research framework is to identify an energy-efficient optimal path to achieve the designated missions for the navigation of UAVs in various constrained and denser obstacle prone regions. Hence, the present work is aimed to develop an optimal energy-efficient path planning algorithm through combining well known modified ant colony optimization algorithm (MACO) and a variant of A*, namely the memory-efficient A* algorithm (MEA*) for avoiding the obstacles in three dimensional (3D) environment and arrive at an optimal path with minimal energy consumption. The novelty of the proposed method relies on integrating the above two efficient algorithms to optimize the UAV path planning task. The basic design of this study is, that by utilizing an improved version of the pheromone strategy in MACO, the local trap and premature convergence are minimized, and also an optimal path is found by means of reward and penalty mechanism. The sole notion of integrating the MEA* algorithm arises from the fact that it is essential to overcome the stringent memory requirement of conventional A* algorithm and to resolve the issue of tracking only the edges of the grids. Combining the competencies of MACO and MEA*, a hybrid algorithm is proposed to avoid obstacles and find an efficient path. Simulation studies are performed by varying the number of obstacles in a 3D domain. The real-time flight trials are conducted experimentally using a UAV by implementing the attained optimal path. A comparison of the total energy consumption of UAV with theoretical analysis is accomplished. The significant finding of this study is that, the MACO-MEA* algorithm achieved 21% less energy consumption and 55% shorter execution time than the MACO-A*. moreover, the path traversed in both simulation and experimental methods is 99% coherent with each other.

关键词： Energy utilization

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Poster: Chameleon: Automatic and Adaptive Tuning for DCQCN Parameters in RDMA Networks 23

Poster: Chameleon: Automatic and Adaptive Tuning for DCQCN P...

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ACM SIGCOMM 2023 Conference

作者： Chen, Ziteng Zhang, Menghao Li, Guanyu Xu, Mingwei School of Cyber Science and Engineering Southeast University Nanjing China Kuaishou Technology Beijing China Department of Computer Science and Technology Tsinghua University Beijing China Institute for Network Sciences and Cyberspace Tsinghua University Beijing China Quan Cheng Laboratory Jinan China Department of Computer Science and Technology Institute for Network Sciences and Cyberspace Tsinghua University Beijing China

ISBN: (纸本)9798400702365

Datacenter Quantized Congestion Notification (DCQCN) [12] is the default congestion control algorithm for Mellanox RDMA (Remote Direct Memory Access) NICs [2] in RoCEv2 (RDMA over Converged Ethernet v2) networks, one of the most widely used NICs in leading industry companies [4, 5, 7, 9]. In DCQCN, firstly switches mark packets with ECN (Explicit Congestion Notification) when the queue length exceeds ECN thresholds, then receivers respond to ECN-marked packets with CNPs (Congestion Notification Packets), and finally senders reduce transmission rate when receiving CNPs. DCQCN has 10+ parameters at both NICs and switches, including Alpha Update, Rate Increase & Decrease, Notification Point and ECN thresholds [3], and these parameters have a non-negligible impact on the network performance. Our experiments also verify the network performance of common AI (Artificial Intelligence) training workloads in RoCEv2 networks (e.g., all-to-all collective communication) is greatly influenced by different DCQCN parameter settings (§3). Therefore, when deploying applications in practice, the DCQCN parameters need to be carefully tested and tuned to improve the network performance. © 2023 Owner/Author(s).

关键词： Network performance

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Pseudo-label Assisted Optimization of Multi-branch Network for Cross-domain Person Re-identification 20

Pseudo-label Assisted Optimization of Multi-branch Network f...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Zhengyang Guo, Shuxiang Shang, Xue Ye, Xiufen Harbin Engineering University College of Intelligent Systems Science and Engineering Harbin China National University of Singapore Department of Electrical and Computer Engineering Singapore Beijing Institute of Technology School of Life Science Beijing China

ISBN: (纸本)9798350320831

Person re-identification plays an important role in the field of robot intelligence perception and public safety. Its main task is to identify person targets under cross-camera. However, the domain diversity between different datasets poses a clear challenge for adapting a model trained on one dataset to another. Currently, person re-identification methods based on domain adaptive learning and pseudo-label have made good progress on this problem. Unfortunately, inferior pseudo-labels and source domain noise affect the performance. In order to improve the quality of generated pseudo-labels and enhance the feature representation capability of the model, we propose a pseudo-label assisted optimization of a multi-branch person re-identification method. The multi-branch network is able to extract and represent more effective global and local features, and the generated pseudo-labels are optimized by using cosine similarity and DBSCAN clustering on the feature vectors, thus improving the consistency of the supervised information to enhance the cross-domain recognition performance. We also use a loss function combining cross-entropy loss and triplet loss to make the best feature learning. Experiments show that our method performs well in the Market-to-Duke and Duke-to-Market cross-domain recognition tasks. © 2023 IEEE.

关键词： Intelligent robots

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Spatial data intelligence and city metaverse: A review

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Fundamental Research 2025年第3期5卷 1169-1193页

作者： Meng, Xiaofeng Li, Yong Liu, Ke Liu, Yu Yang, Bin Song, Xuan Liao, Guoqiong Wang, Senzhang Yu, Ziqiang Chen, Longbiao Pan, Xiao Lin, Yuming School of Information Renmin University of China Beijing 100872 China Department of Electronic Engineering Tsinghua University Beijing 100084 China Department of Information Sciences National Natural Science Foundation of China Beijing 100085 China Institute of Remote Sensing and Geographic Information Systems School of Earth and Space Sciences Peking University Beijing 100871 China School of Data Science and Engineering East China Normal University Shanghai 200062 China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen 518055 China School of Information Management Jiangxi University of Finance and Economics Nanchang 330013 China School of Computer Science and Engineering Central South University Changsha 410017 China School of Computer and Control Engineering Yantai University Yantai 264005 China Department of Computer Science Xiamen University Xiamen 361000 China College of Information Science and Technology Shijiazhuang Tiedao University Shijiazhuang 050043 China

Spatial Data Intelligence (SDI) encompasses acquiring, storing, analyzing, mining, and visualizing spatial data to gain insights into the physical world and uncover valuable knowledge. These understandings and knowledge play a crucial role in connecting physical and virtual realms, such as in developing a City Metaverse (CM) aimed at enhancing and optimizing modern urban environments. The advancement of CM holds immense potential to benefit urban dwellers, making research on SDI an increasingly prominent area of focus. This paper contributes significantly by organizing the relevant research and technologies within a coherent framework. Firstly, we identify SDI technologies capable of collecting real-world information to construct a virtual CM. Subsequently, we delve into the technologies that can be compositely integrated with SDI to facilitate interaction with and management of actual cities from the virtual perspective. Additionally, we emphasize the effectiveness and potential of these methods in practical applications. Lastly, we conclude our survey by discussing emerging challenges associated with technological progress, the industrial chain, legal and regulatory aspects, and ethical and moral considerations. © 2024

关键词： Application prospect City metaverse Smart city Spatial data intelligence Virtual-real interaction

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An Improved Doppler Radar Imaging Model for Retrieving Ocean Current Velocity from SAR Image under DCA Framework

An Improved Doppler Radar Imaging Model for Retrieving Ocean...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： Du, Yanlei Yin, Junjun Yang, Jian Chinese Academy of Sciences National Key Laboratory of Microwave Imaging Technology Aerospace Information Research Institute Beijing100101 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Tsinghua University Department of Electronic Engineering Beijing100084 China

ISBN: (纸本)9798350375909

In this paper, an improved Doppler radar imaging model (IDopRIM) is proposed by considering all three radar imaging modulation transfer functions and implementing a modified hydrodynamic model. The proposed model is validated by comparing to the measurements and the widely-used empirical model. It is indicated that the IDopRIM effectively addresses the overestimation issue of the original DopRIM model and presents a significant accuracy improvement. For most conditions, the root mean square (RMS) errors of the proposed model are within 0.3 m/s. © 2024 IEEE.

关键词： Radar imaging

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Robust Spectral Efficiency Maximization in 5G Networks Using Non-Linear Stochastic Precoding 2

Robust Spectral Efficiency Maximization in 5G Networks Using...

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2nd International Conference on Disruptive Technologies, ICDT 2024

作者： Ponnaian, Geetha Jayanthi, N. Sarasu, R. Sajitha, L.P. Ramalakshmi, R. Manimegalai, L. Department of Computer Science and Engineering Thandalam Chennai India Pallavaram Tamil Nadu Chennai600117 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences India R. M. K Engineering College Department of Computer Science and Business System Tamilnadu Kavaraipettai India Ramco Institute of Technology Department of Electronics and Communication Engineering Rajapalayam India R.M.K. College of Engineering and Technology Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350371055

This research focuses on enhancing the spectral efficiency of 5G networks through the utilization of nonlinear stochastic precoding techniques. The proposed approach aims to mitigate the detrimental effects of channel impairments and noise by employing advanced precoding schemes that exploit the statistical properties of the wireless channel. By incorporating nonlinear precoding algorithms and stochastic optimization methods, the system can dynamically adapt to varying channel conditions, resulting in improved data transmission rates and overall spectral efficiency. Through extensive simulations and analysis, the effectiveness of the proposed method is demonstrated, showcasing its potential to significantly enhance the performance of 5G networks in real-world scenarios. © 2024 IEEE.

关键词： 5G networks channel impairments nonlinear stochastic precoding spectral efficiency stochastic optimization

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A Portable Surgeon's Habits-based Master Manipulator for Vascular Interventional Surgery Robots 20

A Portable Surgeon's Habits-based Master Manipulator for Vas...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Zhao, Duohao Guo, Shuxiang Lyu, Chuqiao Yan, Yonggan Lin, Zhijun Beijing Institute of Technology The Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

The emergence of vascular interventional surgery robot (VISR) has brought good news to patients. However, the current research on the master manipulator is still in its infancy. Nowadays, the shortcomings of the developed master manipulator include poor portability, lack of tactile feedback devices, not in line with surgeon's operating habits and so on. In order to solve the above problems, a novel master manipulator is proposed in this paper. In order to realize the linear displacement measurement of the operating handle, a linear displacement measurement (LDM) unit based on rollers was proposed. By using the brushed DC motor and the bevel gears, the angular displacement measurement (ADM) unit and the circumferential force feedback (CFF) unit were designed. The decoupling of the operating rod and the rotating rod facilitated the portability of the proposed manipulator. Evaluation experimental results showed that the maximum linear error of the master manipulator was 0.296mm and the maximum angular displacement error was 7.66 degrees, which is acceptable. Moreover, the mathematical relationship between the circumferential force generated by the CFF and the input current was also obtained. To sum up, compared with other master manipulators, the proposed master manipulator is shown to be better and more promising. © 2023 IEEE.

关键词： Manipulators

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Parallel Acceleration of Real-time Feature Extraction Based on SURF Algorithm 15

Parallel Acceleration of Real-time Feature Extraction Based ...

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15th International Conference on computer Research and Development, ICCRD 2023

作者： Yu, Jiyang Huang, Dan Li, Jinyang Li, Wenjie Wang, Xianjie Shi, Xiaolong China Academy of Space Technology Beijing Institute of Spacecraft System Engineering Beijing China China Research and Development Academy of Machinery Equipment Chongqing University of Technology Chongqing Beijing China Chongqing Feima Innovation Research Institute Intelligent Equipment Research Department Chongqing China College of Computer Science and Engineering Chongqing University of Technology Chongqing China

ISBN: (纸本)9781665487504

Visual feature extraction is the key to target registration calculation. Compared with SIFT, SURF feature extraction algorithm has less computational complexity and better applicability when image signal-to-noise ratio is low. In this paper, an FPGA-based SURF algorithm for real-time feature extraction and parallel acceleration is designed for large-field scene registration applications of space targets. Firstly, the application scenario of space target is analyzed, and the grayscale features of the data containing the target used for registration are counted. Then, the five main parts of SURF algorithm were analyzed, and the algorithm was simplified based on the gray feature of the image. Finally, according to the simplified results, the parallel pipeline architecture of each module is designed based on FPGA. SURF computing modules are also given in this paper the design of the architecture and data flow of information, in XC7K325 completed the whole design of experiment, the results show that the design for 1024 × 1024 pixel image, single frame image processing time need only 51 us, resource usage is not more than 18.6%, power consumption is not more than 7.5 W, The computational efficiency is 87% higher than the previous design. Low signal-to-noise ratio (SNR) was used to simulate space target scene data for simulation test calculation, and the SURF descriptor error was less than 3%, ensuring the system's calculation error while effectively utilizing resources. © 2023 IEEE.

关键词： Field programmable gate arrays (FPGA)

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A Classification Method for ECG Signals Based on Convolutional Neural Network 20

A Classification Method for ECG Signals Based on Convolution...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Yang, Yuan Guo, Jin Lyu, Fengze Guo, Shuxiang Beijing Institute of Technology The Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

Cardiovascular disease is a chronic disease with high incidence, high disability and high mortality, which poses a great threat to the life and health of people all over the world. At present, the incidence and mortality of cardiovascular disease are increasing year by year worldwide, so the prevention and treatment of cardiovascular disease has become a top priority. In recent years, with the development of computer technology in the field of auxiliary diagnosis and treatment, the research on automatic classification of Electrocardiogram (ECG) signals has ushered in new opportunities. In this study, ECG signals are taken as the research object, to analyze the auxiliary diagnosis needs of users such as patients and pathologists. This study mainly uses ECG data from MIT-BIH database, combined with relevant preprocessing knowledge and deep learning classification model, to achieve ECG reading, denoising, segmentation, classification and so on. It can effectively improve the efficiency of diagnosis. It has certain reference value for assisting users to diagnose arrhythmia. © 2023 IEEE.

关键词： Convolutional neural networks

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Preliminary Bilateral Upper Limb Rehabilitation system Based on sEMG and Muscle Tone 20

Preliminary Bilateral Upper Limb Rehabilitation System Based...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Wang, Hanze Guo, Shuxiang Li, He Bu, Dongdong Key Laboratory of Convergence Biomedical Engineering System and Healthcare Technology The Ministry of Industry and Information Technology Beijing Institute of Technology Beijing100081 China Southern University of Science and Technology The Department of Electronic and Electrical Engineering Guangdong Shenzhen518055 China

ISBN: (纸本)9798350320831

In recent years, with the increasing number of stroke patients, master-slave telerehabilitation has become one of the research hotspots in the field of rehabilitation. However, when estimating the angle of the main end, the angle estimation model is difficult to be widely applicable due to the different muscle tension of the physiotherapist itself. During remote rehabilitation training, it is difficult for physical therapists to obtain the damage of the affected limb, so it is difficult to arrange appropriate training intensity and training volume, which affects the effect of remote rehabilitation to a certain extent. To address these issues, this paper proposes a novel master-slave rehabilitation system. The therapist obtains his own muscle tension level a priori through FSR402, and jointly estimates the movement angle through the (Surface Electromyography) sEMG signal collected by MYO, so as to control the slave end. While following the rehabilitation training, the patient at the slave end reflects real-time muscle force of the affected limb and the true feeling of the movement to the master end through the muscle tension measurement arm cuff and the relevant buttons on the PC end. The overall system realizes data transmission through (User Datagram Protocol) UDP, so as to realize more secure and personalized master-slave control. The experiment proves that the new master-slave rehabilitation system is real and feasible. © 2023 IEEE.

关键词： Muscle

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