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21st ieee international Symposium on Parallel and Distributed Processing with Applications, 13th ieee international conference on Big Data and Cloud Computing, 16th ieee international conference on Social Computing and Networking and 13th international conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zhang, Feng Wang, Hao Guo, Ruixin Xue, Erkang Qu, Guangzhi China University of Geosciences School of Computer Science Wuhan China Oakland University Department of Computer Science and Engineering Rochester United States

ISBN: (纸本)9798350329223

Tensor factorization plays a fundamental role in multiple areas of AI research. Nevertheless, it encounters significant challenges related to privacy breaches and operational efficiency. In this study, we propose a novel approach that addresses both of these issues simultaneously by integrating differential privacy with parallel and distributed computing. To accommodate diverse scenarios, we introduce two models: DPTF-SVRG and ADMM-DPTF, each leveraging specific techniques. DPTF-SVRG is designed for single-GPU environments and utilizes a unique strategy to reduce gradient variance, enabling faster convergence compared to SGD. Moreover, it achieves parallelism on the GPU through a lock-free asynchronous approach. On the other hand, ADMM-DPTF utilizes distributed ADMM to parallelize DPTF-SVRG, enabling multi-GPU parallelism. Experimental results demonstrate that our algorithms outperform existing benchmarks while maintaining differential privacy. © 2023 ieee.

关键词： Tensors

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Distance Metric-Based Classification Comparisons for a Brain-computer Interface Authentication

Distance Metric-Based Classification Comparisons for a Brain...

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2023 ieee international conference on Systems, Man, and Cybernetics, SMC 2023

作者： Lewis, Tyree Agarwal, Rupal Andujar, Marvin University of South Florida Department of Computer Science and Engineering University of South Florida United States Department of Computer Science and Engineering TampaFL33620 United States Faculty of Computer Science and Engineering TampaFL33620 United States

ISBN: (纸本)9798350337020

The rise of security concerns has spurred on-going research into Brain-computer Interfaces (BCI) based authentication. These applications utilize electroencephalogram (EEG) signals, due to their properties that can enhance security systems. In previous studies, EEG data has been incorporated into various authentication systems to compare the performance of new and existing classification methods. However, using EEG data to compare the performance of distance metrics in a P300-based BCI authentication system has not been explored yet. In this study, EEG data is used to determine the most effective distance metric for authenticating users in a closed-loop system. To accomplish this task, we conducted a longitudinal study to evaluate three distance metrics (Cosine, Correlation and Chebyshev) while participants interacted with our BCI authentication system. Our results indicated that the Cosine similarity outperformed all other distance metrics for each user. © 2023 ieee.

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Segmentation Method of Boxed Lunch Images by Weight Optimization Using Color Texture Dissimilarity 22

Segmentation Method of Boxed Lunch Images by Weight Optimiza...

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22nd ieee/ACIS international conference on Software engineering Research, Management and Applications, SERA 2024

作者： Qian, Yangyang Hayakawa, Koki Nishifuji, Seiji Mu, Shenglin Nakashima, Shota Yamaguchi University Department of Electrical and Electronic Engineering Yamaguchi Ube Japan Graduate School of Science and Engineering Ehime University Ehime Matsuyama Japan

ISBN: (纸本)9798350391343

People with severe upper limb disabilities need assistance from caregivers when eating, which becomes a burden for caregivers. Our laboratory has developed meal assistance robots that use image recognition and voice recognition to solve this problem. In a previous study, we proposed a region segmentation method using color and texture differences derived from input images as an image recognition method. However, this method was less effective because lighting and shadows affected the selection of appropriate features in the calculation of differences. In this study, we introduce a method for calculating the degree of difference between color segmented regions based on the HSV color space and texture obtained from color information. Furthermore, we propose a method that uses the HSV color space based on saturation and texture weight optimization to calculate differences to perform environment-independent region segmentation. A validation experiment was conducted to properly divide the food area of boxed lunch to confirm the effectiveness of the proposed method. The results showed that the accuracy exceeded 90% for all boxed lunch. Therefore, the proposed method can accurately identify food areas, regardless of the environment. © 2024 ieee.

关键词： Unsupervised learning

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Orbeez-SLAM: A Real-time Monocular Visual SLAM with ORB Features and NeRF-realized Mapping

Orbeez-SLAM: A Real-time Monocular Visual SLAM with ORB Feat...

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ieee international conference on Robotics and automation (ICRA)

作者： Chung, Chi-Ming Tseng, Yang-Che Hsu, Ya-Ching Shi, Xiang-Qian Hua, Yun-Hung Yeh, Jia-Fong Chen, Wen-Chin Chen, Yi-Ting Hsu, Winston H. Natl Taiwan Univ Taipei Taiwan Natl Yang Ming Chiao Tung Univ Taipei Taiwan Mobile Drive Technol Plano TX USA

ISBN: (纸本)9798350323658

A spatial AI that can perform complex tasks through visual signals and cooperate with humans is highly anticipated. To achieve this, we need a visual SLAM that easily adapts to new scenes without pre-training and generates dense maps for downstream tasks in real-time. None of the previous learning-based and non-learning-based visual SLAMs satisfy all needs due to the intrinsic limitations of their components. In this work, we develop a visual SLAM named Orbeez-SLAM, which successfully collaborates with implicit neural representation and visual odometry to achieve our goals. Moreover, Orbeez-SLAM can work with the monocular camera since it only needs RGB inputs, making it widely applicable to the real world. Results show that our SLAM is up to 800x faster than the strong baseline with superior rendering outcomes. Code link: https://***/MarvinChung/Orbeez- SLAM.

关键词： computer vision

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Knowledge Graph for China's Genealogy1

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ieee Transactions on Knowledge and Data engineering 2023年第1期35卷 634-646页

作者： Wu, Xindong Jiang, Tingting Zhu, Yi Bu, Chenyang Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Anhui Hefei230009 China Hefei University of Technology Research Institute of Big Knowledge Anhui Hefei230009 China Mininglamp Technology Mininglamp Academy of Sciences Beijing100102 China Hefei University of Technology School of Computer Science and Information Engineering Anhui Hefei230009 China Hefei University of Technology Ministry of Education Key Laboratory of Knowledge Engineering with Big Data Anhui Hefei230009 China

Genealogical knowledge graphs depict the relationships of family networks and the development of family histories. They can help researchers to analyze and understand genealogical data, search for genealogical descendant paths, and explore the origins of a family. However, the heterogenous, autonomous, complex, and evolving natures of genealogical data bring challenges to the development of contemporary genealogical knowledge graph models. Applying existing methods to genealogical data may be improper because general knowledge graph models lack in-depth domain knowledge. In this paper, we propose a genealogical knowledge graph model named Huapu-KG that combines HAO intelligence (human intelligence + artificial intelligence + organizational intelligence) to implement the construction and applications of genealogical knowledge graphs. Furthermore, challenges in constructing genealogical knowledge graphs are demonstrated, and experiments conducted on real-world genealogical datasets verify the feasibility and effectiveness of our proposed model. © 1989-2012 ieee.

关键词： History

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Multi-view stereo based on adaptive expansion propagation 7

Multi-view stereo based on adaptive expansion propagation

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7th international conference on computer Information science and Application Technology, CISAT 2024

作者： Nie, Zixuan Fu, Haohai Jilin Institute of Chemical Technology School of Information and Control Engineering Jilin132022 China Changchun Institute of Technology School of Computer Technology and Engineering Changchun130012 China

ISBN: (纸本)9798350375107

Through computer vision and image processing techniques, a set of images from a scene can be reconstructed in 3D to recover a 3D model of the scene, in which dense reconstruction is a crucial part, and most existing algorithms cannot effectively recover weak texture regions in dense reconstruction. In response to this issue, this article proposes a hypothesis propagation strategy based on adaptive extension. In the hypothesis propagation stage of PatchMatch MVS, an adaptive mechanism for region propagation is introduced, and an update counter is set to regulate the expansion of the sampling area. This ensures that there are enough excellent hypotheses for sampling in this algorithm iteration, and the quality of sampling hypotheses is not limited by fixed sampling pixel positions, thereby improving the probability of excellent hypotheses being sampled in the sampling space. It is demonstrated in the ETH3D dataset that our method reconstructs models with higher integrity, and fewer voids and smoother surfaces in the reconstruction of weakly textured regions. © 2024 ieee.

关键词： 3D reconstruction

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ResNet Optimization Model for High-resolution Range Profile Target Recognition 4

ResNet Optimization Model for High-resolution Range Profile ...

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4th international conference on Electronic Information engineering and computer science, EIECS 2024

作者： Zhang, Zhansheng Zhang, Yongjie Li, Hongli Liu, Zhengkun Institute of Beijing Remote Sensing Device Beijing China China Academy of Aerospace Science and Innovation Beijing China

ISBN: (纸本)9798331531409

This paper proposes a radar high-resolution range profile (HRRP) recognition algorithm based on ResNet, combined with the SE (Squeeze-and-Excitation) channel attention mechanism. In most current HRRP target recognition methods, feature extraction largely relies on manual extraction, followed by recognition through machine learning techniques. With the emergence of intelligent System-on-Chip (SoC) devices, which offer high-performance computing capabilities and low power consumption, it has become feasible to deploy deep learning algorithms on smaller radar platforms. By introducing the channel attention mechanism, the sensitivity and discriminative ability of the model to key features are enhanced, enabling ResNet to achieve high-precision recognition of different vehicle targets and corner reflector arrays. Validation using real-world data demonstrates that the proposed recognition algorithm yields superior results. © 2024 ieee.

关键词： Intelligent systems

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Sample-and-Hold Based Security Control for CPSs with DoS Attakcs and Disturbances 22

Sample-and-Hold Based Security Control for CPSs with DoS Att...

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22nd ieee international conference on Industrial Informatics, INDIN 2024

作者： Zhang, Cheng Wang, Enci Zhang, Enze Yi, Yang Department of Information Engineering Yangzhou University Yangzhou China

ISBN: (纸本)9798331527471

This article investigates the security control problem of cyber-physical systems (CPSs) with unknown disturbance and denial-of-service (DoS) attacks. To address the impact of DoS attacks on state loss and unknown disturbances on the system, we propose a new full-order disturbance observer. By introducing the"sample and hold" method, the system has achieved a certain degree of attack tolerance, and even in the case of unreliable output information caused by network attacks and disturbance, the observer can simultaneously monitor the system state and unknown disturbance. Finally, through the integration of Lyapunov stability theory and convex optimization analysis, the system gains are determined. © 2024 ieee.

关键词： Convex optimization

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Security of Networked Systems with Random Sampling Intervals and Deception Attacks Via Non-Fragile Sampled-Data Control 13

Security of Networked Systems with Random Sampling Intervals...

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13th ieee international conference on CYBER Technology in automation, Control, and Intelligent Systems, CYBER 2023

作者： Hu, Zhipei Wang, Chen Zhang, Jin Li, Xutao Zou, An-Min School of Electrical and Information Engineering Shantou University Shantou515063 China School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China

ISBN: (纸本)9798350315196

This study is concerned with the security of networked systems with random sampling intervals and deception attacks using non-fragile sampled-data control. We first establish a discrete-time stochastic model framework for the networked system with random sampling intervals and deception attacks. Subsequently, by the vectorization and Kronecker product operation, a non-fragile controller is designed such that the exponential mean-square stability of resulting discrete-time stochastic system is guaranteed. Finally, a numerical example is presented to show the effectiveness of the designed algorithm. © 2023 ieee.

关键词： Stochastic models

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Understanding URDF: A Survey Based on User Experience 19

Understanding URDF: A Survey Based on User Experience

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19th ieee international conference on automation science and engineering, CASE 2023

作者： Tola, Daniella Corke, Peter Aarhus University Department of Electrical and Computer Engineering Aarhus Denmark Centre for Robotics Qut Brisbane Australia

ISBN: (纸本)9798350320695

With the increasing complexity of robot systems, it is necessary to simulate them before deployment. To do this, a model of the robot's kinematics or dynamics is required. One of the most commonly used formats for modeling robots is the Unified Robot Description Format (URDF). The goal of this article is to understand how URDF is currently used, what challenges people face when working with it, and how the community sees the future of URDF. The outcome can potentially be used to guide future research. This article presents the results from a survey based on 510 anonymous responses from robotic developers of different backgrounds and levels of experience. We find that 96.8% of the participants have simulated robots before, and of them 95.5% have used URDF. We identify a number of challenges that complicate the use of URDF, such as the inability to model parallel linkages and closed-chain systems, no real standard, lack of documentation, and a limited number of dynamic parameters to model the robot. Future perspectives for URDF are also determined, where 53.5% believe URDF will be more commonly used in the future, 12.2% believe other standards or tools will make URDF obsolete, and 34.4% are not sure what the future of URDF will be. Most participants agree there is a need for better tools to ensure URDF's future use. © 2023 ieee.

关键词： Robots

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