检索结果-内蒙古大学图书馆

12th International Conference on Optimization and Applications, OPTIMA 2021

作者： Malyshev, Dmitry Rybak, Larisa Mohan, Santhakumar Diveev, Askhat Cherkasov, Vladislav Pisarenko, Anton Belgorod State Technological University named after V.G. Shukhov Belgorod Russia Indian Institute of Technology Palakkad Palakkad India Federal Research Center "Computer Science and Control" of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783030927103

The paper presents the method of optimal geometric parameters synthesis for a robotic rehabilitation system of the lower limbs as based on a passive orthosis in the form of a serial RRRR mechanism and an active parallel 3-PRRR mechanism. A mathematical model of the kinematics of the RRRR mechanism is formulated. A numerical method is worked out for determining the workspace of the RRRR mechanism. The workspace description is based on the approximation of many solutions of systems of nonlinear inequalities to provide the required rotation angle of rotation in the joints. Effective numerical methods and algorithms are developed and tested. The paves the way for determining the minimum geometric parameters of an active parallel mechanism that ensure movements of a passive orthosis within the workspace under clinical data constrains when simulating walking. In order to implement the developed methods, an effective algorithm, software package and visualization system are synthesized for exported three-dimensional workspaces in STL. © 2021, Springer Nature Switzerland AG.

关键词： Mechanisms

来源：评论

学校读者我要写书评

暂无评论

Augmenting GRIPS with Heuristic Sampling for Planning Feasible Trajectories of a Car-Like Robot

Augmenting GRIPS with Heuristic Sampling for Planning Feasib...

引用

European Conference on Mobile Robots (ECMR)

作者： Brian Angulo Ivan Radionov Konstantin Yakovlev Moscow Institute of Physics and Technology LLC "Integrant" Federal Research Center "Computer Science and Control" RAS

Kinodynamic motion planning for non-holomonic mobile robots is a challenging problem that is lacking a universal solution. One of the computationally efficient ways to solve it is to build a geometric path first and then transform this path into a kinematically feasible one. Gradient-informed Path Smoothing (GRIPS) [1] is a recently introduced method for such transformation. GRIPS iteratively deforms the path and adds/deletes the waypoints while trying to connect each consecutive pair of them via the provided steering function that respects the kinematic constraints. The algorithm is relatively fast but, unfortunately, does not provide any guarantees that it will succeed. In practice, it often fails to produce feasible trajectories for car-like robots with large turning radius. In this work, we introduce a range of modifications that are aimed at increasing the success rate of GRIPS for car-like robots. The main enhancement is adding an additional step that heuristically samples the waypoints along the bottleneck parts of the geometric paths (such as sharp turns). The results of the experimental evaluation provide a clear evidence that the success rate of the suggested algorithm is up to 40% higher compared to the original GRIPS and hits the bar of 90%, while its runtime is lower.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Convergence Analysis of the Best Response Algorithm for Time-Varying Games

arXiv

引用

arXiv 2023年

作者： Wang, Zifan Shen, Yi Zavlanos, Michael M. Johansson, Karl H. Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology also with Digital Futures StockholmSE-10044 Sweden the Department of Mechanical Engineering and Materials Science Duke University DurhamNC United States

— This paper studies a class of strongly monotone games involving non-cooperative agents that optimize their own time-varying cost functions. We assume that the agents can observe other agents’ historical actions and choose actions that best respond to other agents’ previous actions;we call this a best response scheme. We start by analyzing the convergence rate of this best response scheme for standard time-invariant games. Specifically, we provide a sufficient condition on the strong monotonicity parameter of the time-invariant games under which the proposed best response algorithm achieves exponential convergence to the static Nash equilibrium. We further illustrate that this best response algorithm may oscillate when the proposed sufficient condition fails to hold, which indicates that this condition is tight. Next, we analyze this best response algorithm for time-varying games where the cost functions of each agent change over time. Under similar conditions as for time-invariant games, we show that the proposed best response algorithm stays asymptotically close to the evolving equilibrium. We do so by analyzing both the equilibrium tracking error and the dynamic regret. Numerical experiments on economic market problems are presented to validate our analysis. Copyright © 2023, The Authors. All rights reserved.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

A Practical Cross-Device Federated Learning Framework over 5G Networks

arXiv

引用

arXiv 2022年

作者： Yang, Wenti Wang, Naiyu Guan, Zhitao Wu, Longfei Du, Xiaojiang Guizani, Mohsen School of Control and Computer Engineering North China Electric Power University China Department of Mathematics & Computer Science Fayetteville State University United States Department of Electrical and Computer Engineering Stevens Institute of Technology HobokenNJ United States Department of Computer Science and Engineering Qatar University Qatar

The concept of federated learning (FL) was first proposed by Google in 2016. Thereafter, FL has been widely studied for the feasibility of application in various fields due to its potential to make full use of data without compromising the privacy. However, limited by the capacity of wireless data transmission, the employment of federated learning on mobile devices has been making slow progress in practical. The development and commercialization of the 5th generation (5G) mobile networks has shed some light on this. In this paper, we analyze the challenges of existing federated learning schemes for mobile devices and propose a novel cross-device federated learning framework, which utilizes the anonymous communication technology and ring signature to protect the privacy of participants while reducing the computation overhead of mobile devices participating in FL. In addition, our scheme implements a contribution-based incentive mechanism to encourage mobile users to participate in FL. We also give a case study of autonomous driving. Finally, we present the performance evaluation of the proposed scheme and discuss some open issues in federated learning. Copyright © 2022, The Authors. All rights reserved.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

Enhancing Visual Representation for Text-Based Person Searching

SSRN

引用

SSRN 2024年

作者： Shen, Wei Fang, Ming Wang, Yuxia Xiao, Jiafeng Chen, Huangqun Xu, Ling Zhang, Weifeng Metrological Verification and Testing Institute of Jiaxing China School of Artificial Intelligence Zhejiang Sci-Tech University Zhejiang China College of Computer Science and Technology Zhejiang University Zhejiang China College of Information Science and Engineering Jiaxing University Zhejiang China Shandong Center for Disease Control and Prevention China

Text-based person search aims to retrieve the matched pedestrians from a large scale image database according to the text description. The core difficulty of this task is how to extract effective details from pedestrian images and texts, and achieve cross-modal alignment in common latent space. Prior works adopt image and text encoders pre-trained on unimodal data to extract global and local features from image and text respectively, and then global-local alignment is achieved explicitly. However, these approaches still lack the ability of understanding visual details, and the retrieval accuracy is still limited by identity confusion. In order to alleviate the above problems, we rethink the importance of visual features for text-based person search, and propose VFE-TPS, a Visual Feature Enhanced Text-based Person Search model. It introduces a pre-trained multimodal backbone and constructs Text Guided Masked Image Modeling task to enhance the model’s ability of learning local visual details without explicit annotation. In addition, we design Identity Supervised Global Visual Feature Calibration task to guide the model learn identity-aware global visual features. Experimental results on three benchmarks demonstrate that our proposed model exceeds the existing approaches, and the Rank-1 accuracy is significantly improved with a notable margin of about 1% ∼ 9%. Our code has been released at https://***/zhangweifeng1218/VFE_TPS. © 2024, The Authors. All rights reserved.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Knowledge Graph Completion with Low-Dimensional Gated Hierarchical Hyperbolic Embedding

SSRN

引用

SSRN 2024年

作者： Fang, Yan Liu, Xiaodong Lu, Wei Pedrycz, Witold Lang, Qi Yang, Jianhua School of Control Science and Engineering Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian116024 China Department of Electrical and Computer Engineering University of Alberta EdmontonT6R 2V4 AB Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia School of Computer Science and Information Technology Northeast Normal University Changchun130117 China

Knowledge Graph Embedding aims to advance the learning performance of knowledge graphs by deliberating the complexity of hierarchical data structures in a finite-dimensional space. Most traditional Euclidean models struggle to accurately describe and navigate the intricate hierarchical relationships between nodes. The hyperbolic embedding methods, particularly in conjunction with graph neural networks, offer promise in effectively modeling complex hierarchies in a limited-dimensional space. These methods can accommodate more information about nodes under the same conditions but are also more susceptible to interference from complex neighborhood features. This paper introduces HyperGatE, which novelty combines a hyperbolic graph hierarchical neighbor structure based on a gated filter and a hyperbolic isometric rotation model for knowledge graph completion. By analyzing the hierarchical structure of the knowledge base and using a gated mechanism to form multi-layer embedding networks of entity-relational paths, the gated filter selects diverse uneven multi-hop relations within the entity neighborhood and measures them through graph attention networks. Furthermore, the simplified hyperbolic isometric model allows for uncovering hierarchical structures in the data. HyperGatE experimentally surpasses the state-of-the-art Euclidean and hyperbolic space models in high and low dimensions across four well-known data, namely WN18RR, FB15k-237, NELL-995, and Kinship. © 2024, The Authors. All rights reserved.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Leveraging Explainable AI Methods Towards Identifying Classification Issues on IDS Datasets

Leveraging Explainable AI Methods Towards Identifying Classi...

引用

Conference on Local computer Networks (LCN)

作者： Eric Lanfer Sophia Sylvester Nils Aschenbruck Martin Atzmueller Osnabrück University Institute of Computer Science Osnabrück Germany Department of Mental Health Norwegian University of Science and Technology (NTNU) Trondheim Norway German Research Center for AI (DFKI) Plan-Based Robot Control Osnabrück Germany

Nowadays, anomaly-based network intrusion detection system (NIDS) still have limited real-world applications; this is particularly due to false alarms, a lack of datasets, and a lack of confidence. In this paper, we propose to use explainable artificial intelligence (XAI) methods for tackling these issues. In our experimentation, we train a random forest (RF) model on the NSL-KDD dataset, and use SHAP to generate global explanations. We find that these explanations deviate substantially from domain expertise. To shed light on the potential causes, we analyze the structural composition of the attack classes. There, we observe severe imbalances in the number of records per attack type subsumed in the attack classes of the NSL-KDD dataset, which could lead to generalization and overfitting regarding classification. Hence, we train a new RF classifier and SHAP explainer directly on the attack types. Classification performance is considerably improved, and the new explanations are matching the expectations based on domain knowledge better. Thus, we conclude that the imbalances in the dataset bias classification and consequently also the results of XAI methods like SHAP. However, the XAI methods can also be employed to find and debug issues and biases in the data and the applied model. Furthermore, the debugging results in higher trustworthiness of anomaly-based NIDS.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Efficient Multi-Query Oriented Continuous Subgraph Matching

Efficient Multi-Query Oriented Continuous Subgraph Matching

引用

International Conference on Data Engineering

作者： Ziyi Ma Jianye Yang Xu Zhou Guoqing Xiao Jianhua Wang Liang Yang Kenli Li Xuemin Lin School of Artificial Intelligence Hebei University of Technology China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University China Cyberspace Institute of Advanced Technology Guangzhou University China Department of New Networks PengCheng Laboratory China College of Computer Science and Electronic Engineering Hunan University China Shenzhen Research Institute Hunan University China Antai College of Economics and Management Shanghai Jiao Tong University China

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Continuous subgraph matching (CSM) is a critical task for analyzing dynamic graphs and has a wide range of applications, such as merchant fraud detection, cyber-attack hunting, and rumor detection. Although many efficient CSM algorithms have been recently proposed, they are mainly designed to process a single query. However, in some application scenarios, multi-query oriented continuous subgraph matching (MQCSM) may be of more interest. To our knowledge, the two existing solutions to MQCSM are outdated due to unsatisfactory performance. In this paper, we propose MQ-Match, an efficient approach to MQCSM. First, we design a compact yet effective index structure CCG, which maintains the local matching result of vertices in the data graph using a directed graph. The directed edges in CCG can be utilized as an effective pruning rule for the subsequent incremental matching algorithm when expanding a partial match. Then, we develop a computation sharing incremental matching algorithm. In specific, a set of matching trees is constructed based on the depth-first search trees of the query graphs. By utilizing CCG, we conduct subgraph matching for the matching tree to collect the incremental matches for the query graphs, where the common structures of query graphs are matched only once. Extensive experiments show that MQ-Match can achieve 3.1x-7071.4x speedup over the competitors, and consumes much less memory under the majority of the experiment settings.

关键词： Heuristic algorithms Memory management Directed graphs Data engineering Fraud Computational efficiency Indexes

来源：评论

学校读者我要写书评

暂无评论

Autoregressive Queries for Adaptive Tracking with Spatio-Temporal Transformers

Autoregressive Queries for Adaptive Tracking with Spatio-Tem...

引用

Conference on computer Vision and Pattern Recognition (CVPR)

作者： Jinxia Xie Bineng Zhong Zhiyi Mo Shengping Zhang Liangtao Shi Shuxiang Song Rongrong Ji Key Laboratory of Education Blockchain and Intelligent Technology Ministry of Education Guangxi Normal University Guilin China Guangxi Key Lab of Multi-Source Information Mining & Security Guangxi Normal University Guilin China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University School of Computer Science and Technology Harbin Institute of Technology Media Analytics and Computing Lab School of Informatics Xiamen University

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

The rich spatio-temporal information is crucial to capture the complicated target appearance variations in visual tracking. However, most top-performing tracking algorithms rely on many hand-crafted components for spatio-temporal information aggregation. Consequently, the spatio-temporal information is far away from being fully explored. To alleviate this issue, we propose an adaptive tracker with spatio-temporal transformers (named AQA-Track), which adopts simple autoregressive queries to effectively learn spatio-temporal information without many hand-designed components. Firstly, we introduce a set of learnable and autoregressive queries to capture the instantaneous target appearance changes in a sliding window fashion. Then, we design a novel attention mechanism for the interaction of existing queries to generate a new query in current frame. Finally, based on the initial target template and learnt autoregressive queries, a spatio-temporal information fusion module (STM) is designed for spatiotemporal formation aggregation to locate a target object. Benefiting from the STM, we can effectively combine the static appearance and instantaneous changes to guide robust tracking. Extensive experiments show that our method significantly improves the tracker's performance on six popular tracking benchmarks: LaSOT, LaSOT ext , TrackingNet, GOT-10k, TNL2K, and UAV123. Code and models will be https://***/orgs/GXNU-ZhongLab.

关键词： Adaptation models Visualization computer vision Target tracking Computational modeling Transformers Market research

来源：评论

学校读者我要写书评

暂无评论

Online SVR Neural Network Based Ultra High Voltage Transmission Early Warning of Construction Progress 8

Online SVR Neural Network Based Ultra High Voltage Transmiss...

引用

8th IEEE Conference on Energy Internet and Energy System Integration, EI2 2024

作者： Zhou, Liang Zhu, Yinjie Qian, Yi Zhang, Yiquan Chen, Mingyang Xu, Yuhan Wu, Xingtang Fang, Fang State Grid Shanghai Economic Research Institute Design Management Center Shanghai China Shanghai Power Transmission & Transformation Engineering Co. LTD. Engineering Technology Management Department Shanghai China North China Electric Power University School of Control and Computer Engineering Beijing China

ISBN: (纸本)9798331523527

Ultra high-voltage (UHV) transmission construction involves live work, requires crossing long distances, and must overcome terrain and climate challenges. Therefore, to enhance the accuracy of UHV transmission construction progress prediction and address the issue of online early warning, an early warning method for UHV transmission construction progress based on the online support vector regression (Online SVR) algorithm is proposed. Utilizing the digital twin model of UHV transmission construction, principal component analysis is employed to extract and analyze key factors influencing construction progress, the Online SVR algorithm dynamically learns and predicts construction progress. The prediction results are compared with the planned construction warning line to provide early warnings of potential construction progress risks. Finally, the method is applied to an actual UHV transmission construction site to verify its effectiveness. © 2024 IEEE.

关键词： UHV power transmission

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：