检索结果-内蒙古大学图书馆

IAENG International Journal of computer Science 2024年第3期51卷 222-231页

作者： Hu, Yaping Lin, Yiqian Nie, Yongquan Peng, Chaoyi He, Yubin Liu, Yuxuan Ma, Guang Seng, Dewen senior engineer of Power dispatch and control Center China Southern Power Grid Guangzhou510623 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China senior engineer of Power dispatch and control Center China Southern Power Grid Guangzhou510623 China senior engineer of Power dispatch and control Center China Southern Power Grid Guangzhou510623 China Power dispatch and control Center China Southern Power Grid Guangzhou510623 China Power dispatch and control Center China Southern Power Grid Guangzhou510623 China Guang Ma is an engineer of Power dispatch and control Center China Southern Power Grid Guangzhou510623 China School of Computer Science and Technology Hangzhou Dianzi University Hangzhou310018 China

As China's electricity market continues to evolve, the increasing number and diversity of market participants have led to a rapid increase in data volume. An immediate challenge is designing a robust blockchain system that ensures not only the transparency, credibility, tamper-resistance, traceability, privacy, and security of substantial market data in a complex environment, but also provides trusted data support for intelligent dispatching within the power market. This paper proposes a solution to this pressing issue through Blockchain as a Service (BaaS). BaaS leverages the capabilities of cloud computing platforms to enhance the ease and efficiency of deploying and operating blockchain systems. Specifically, the paper introduces a BaaS system built upon an integrated intelligent scheduling and operation cloud-edge platform (CEP). It incorporates technological solutions such as data on-chain, trusted comparison, edge cluster data transmission, optimized transaction authentication, and lightweight storage nodes. Rigorous testing has conclusively demonstrated that the proposed BaaS system meets the requirements of the digital transformation of the China Southern Power Grid, and provides robust technical support for its future practical applications. © (2024), (International Association of engineers). All Rights Reserved.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

IOT based wearable sensor system architecture for classifying human activity

引用

Measurement: Sensors 2025年 39卷

作者： Mahalakshmi, V. Kumar, Pramod Bhende, Manisha Keshta, Ismail Rathod, Swatiben Yashvantbhai Ramesh, Janjhyam Venkata Naga Department of Computer Science College of Engineering and computer science Jazan University Jazan45142 Saudi Arabia Computer science and Technology Ganga Institute of Technology and Management Kablana Haryana Jhajjar124104 India Dr. D. Y. Patil Vidyapeeth Pune India Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Instrumentation And Control Department Vishwakrma Government Engineer College Chandkheda Ahmedabad382424 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur Dist. Andhra Pradesh 522302 India

Human Activity Recognition (HAR) has applications in diverse fields, including sports management and behavior classification. Existing HAR methods can be categorized into three main approaches: camera-based, wearable sensor-based, and Wi-Fi sensing-based. Camera-based methods suffer from privacy concerns, while wearable sensor-based methods face limitations in battery longevity and continuous monitoring. Wi-Fi sensing methods mitigate privacy and battery issues but rely on costly Intel 5300 network cards or software-defined radio (SDR) platforms, limiting scalability. This paper presents a cost-effective IoT-based human activity recognition system using ESP32, leveraging its Wi-Fi sensing capabilities. The proposed system follows a structured workflow: (i) channel state information (CSI) is extracted from ESP32 modules, (ii) data preprocessing is performed using Hampel and Gaussian filters for noise and outlier removal, (iii) dimensionality reduction is achieved through Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT), and (iv) activity classification is conducted using Dynamic Time Warping (DTW) and the K-Nearest Neighbors (KNN) algorithm. Experimental evaluations demonstrate that the proposed system achieves an average recognition accuracy of 98.6 % across six human activities, comparable to high-end Intel 5300-based HAR systems, while significantly reducing hardware costs and improving ease of deployment. © 2025

关键词： Discrete wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

A Point-to-distribution Degeneracy Detection Factor for LiDAR SLAM using Local Geometric Models

A Point-to-distribution Degeneracy Detection Factor for LiDA...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Sehua Ji Weinan Chen Zerong Su Yisheng Guan Jiehao Li Hong Zhang Haifei Zhu Biomimetic and Intelligent Robotics Lab (BIRL) School of Electromechanical Engineer Guangdong University of Technology Guangzhou China JT-Innovation (Guangdong) Intelligent Technology Co. Ltd. Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent Manufacturing Guangdong Academy of Sciences Guangzhou China College of Engineering South China Agricultural University China Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Limited by the working principles, LiDAR-SLAM systems suffer from the degeneration phenomenon in environments such as long corridors and tunnels, due to the lack of sufficient geometric features for frame-to-frame matching. The accuracy and sensitivity of existing degeneracy detection methods need to be further improved. In this paper, we propose a novel method for degeneracy detection using local geometric models based on point-to-distribution matching. To obtain an accurate description of local geometric models, an adaptive adjustment of voxel segmentation according to the point cloud distribution and density is designed. The codes of the proposed method is open-source and available at https://***/jisehua/***. Experiments with public datasets and self-build robots were conducted to evaluate the methods. The results exhibit that our proposed method achieves higher accuracy than the other existing approaches. Applying our proposed method is beneficial for improving the robustness of the LiDAR-SLAM systems.

关键词： Point cloud compression Accuracy Simultaneous localization and mapping Sensitivity Laser radar Geometric modeling Noise

来源：评论

学校读者我要写书评

暂无评论

Learning Latent Semantic Attributes for Zero-Shot Object Detection

Learning Latent Semantic Attributes for Zero-Shot Object Det...

引用

International Conference on Tools for Artificial Intelligence (ICTAI)

作者： Kang Wang Lu Zhang Yifan Tan Jiajia Zhao Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China

ISBN: (数字)9781728192284

ISBN: (纸本)9781728185361

Zero-shot Object Detection (ZSD) aims to locate and classify instances of unseen categories. Existing methods focus on learning the mapping from visual space to semantic space, while the learning of discriminative representations for ZSD has not gained enough attention. In this paper, we demonstrate the necessity to learn discriminative semantic representations for ZSD, and propose a new end-to-end framework for this task. Our framework is able to learn discriminative semantic representations in an augmented space introduced for both user-defined and latent attributes, and refine the user-defined attributes with the help of unseen and external classes. The proposed method is extensively evaluated on two challenging ZSD datasets, and the experimental results show that our method significantly outperforms several existing methods.

关键词： Visualization Conferences Semantics Object detection Tools Boosting Task analysis

来源：评论

学校读者我要写书评

暂无评论

Network Parameter Generation for One-Shot Object Detection

Network Parameter Generation for One-Shot Object Detection

引用

2019 IEEE International Conference on Unmanned Systems, ICUS 2019

作者： Wang, Kang Zhao, Jiajia Wang, Yang Zhou, Shuigeng Fudan University Shanghai Key Lab of Intelligent Information Processing School of Computer Science Shanghai200433 China Beijing Electro-Mechanical Engineer Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Nanchang University School of Information Engineering 330031 China

ISBN: (纸本)9781728137926

Recent object detection models have achieved satisfactory performance by deep learning with large-scale annotated datasets. However, these models often perform poorly when the training examples are not sufficient enough, especially for one-shot object detection where there is only one training example of each target class. In this paper, we propose a network parameter generation framework for effective one-shot object detection. By leveraging the semantic relationship between the source-domain and the target-domain (new classes), our framework can generate network parameters for the new classes directly. Furthermore, we develop two implementation schemes for this framework: weighting-based parameter generation and regression-based parameter generation. These two schemes use different information to construct the relationship and transfer knowledge from the source-domain to the target-domain. Experiments on the PASCAL-OSCD benchmark show that our methods can significantly boost the performance of one-shot object detection. © 2019 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Network Parameter Generation for One-Shot Object Detection

Network Parameter Generation for One-Shot Object Detection

引用

IEEE International Conference on Unmanned Systems (ICUS)

作者： Kang Wang Jiajia Zhao Yang Wang Shuigeng Zhou Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineer Institute Beijing China School of Information Engineering Nanchang University China

ISBN: (纸本)9781728137933

关键词： Object detection Detectors Head Training Feature extraction Task analysis Training data

来源：评论

学校读者我要写书评

暂无评论

Sliding mode control for mixed conventional/braking actuation mobile robots

arXiv

引用

arXiv 2019年

作者： Nikshi, Walelign Hoover, Randy C. Bedillion, Mark D. Shahmiri, Saeed Simmons, Jeremy Control Systems Engineer at Icon build AustinTX78745 United States Department of Electrical and Computer Engineering South Dakota School of Mines and Technology Rapid CitySD57701 United States Department of Mechanical Engineering Carnegie Mellon University PittsburghPA15213 United States Department of Electrical Engineering South Dakota School of Mines and Technology Rapid CitySD57701 United States Department of Mechanical Engineering University of Minnesota MinneapolisMN55455 United States

The Mixed convention/braking Actuation Mobile Robot (MAMR) was designed to tackle some of the drawbacks of conventional mobile robots such as losing controllability due to primary actuator failures, mechanical complexity, weight, and cost. It replaces conventional steering wheels with braking actuators and conventional drive wheels with a single omni-directional wheel. This makes it fall under the category of under-actuated mobile robots. The brakes have only two states, ON and OFF, resulting in discontinuous dynamics. This inspires the use of a discontinuous control law to control the system. This work presents a Sliding Mode controller (SMC) design to park the MAMR system from a given initial configuration to a desired final configuration. Experimental results are presented to validate the parking control of the MAMR. Copyright © 2019, The Authors. All rights reserved.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Fuzzy logic control for mixed conventional/braking actuation mobile robots

arXiv

引用

arXiv 2019年

The use of conventional actuators in robotic systems (electric motors in particular), while often offering advantages in terms of flexibility and controllability, suffer from primary actuator failure, due to unexpected complexities in their environment, which can lead to loss of controllability. Conventional actuators can impose disadvantages on mechanical complexity, weight, and cost. Here, the Mixed conventional/braking Actuation Mobile Robot (MAMR), a new mobile robot platform, is proposed to tackle such drawbacks in actuation and explore the use and control of braking actuation. This platform substitutes the drive motors used in Ackermann steering with brakes that have only two states, ON and OFF. Additionally, the conventional drive wheels are replaced by a single, omni-directional wheel that only supports a driving force in the robots longitudinal direction. The ability of braking actuators in providing controllability under actuator failure is one of the primary motivations of this work. To validate the reliability and accuracy of MAMR approach, this paper studies the design of such robotic systems, the design and synthesis of fuzzy logic controllers along with the experimental assessments of these controllers in real-time. The experimental tests point out the controller performance enhancement using fuzzy logic controllers and MAMR. Copyright © 2019, The Authors. All rights reserved.

关键词： controllers

来源：评论

学校读者我要写书评

暂无评论

Essential matrix decomposition without dependence of singular value decomposition

引用

Journal of Information and Computational Science 2015年第8期12卷 3299-3309页

作者： Wu, Chunfu Tang, Qingshun Zhou, Fengyu Wang, David School of Mechanical and Electrical Engineering Longyan University Longyan China School of Control Science and Engineering Shandong University Jinan China Department of Systems and Computer Engineer Carleton University Canada

This paper presents a novel essential matrix decomposition method. Firstly, two constructed infinite homographies are affected on the original two views respectively, so that the principal points of the transformed views are point correspondence, and the transformed views' essential matrix is determined. Secondly, the camera translation is determined, after which an assisted rotation matrix is constructed to decompose camera rotation using NANSON formula. Finally, the unique solution is determined easily and conveniently with the 3D-point visibility constraint. The experimental results show that, it has a better real-time performance not only because of the avoidance of time consuming SVD operation, but also for the avoidance of the scene structure computation in the determination of the unique solution. Copyright © 2015 Binary Information Press.

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Fine-grained acronym expansion identification using latent-state neural structured prediction model

Fine-grained acronym expansion identification using latent-s...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jie Liu Caihua Liu Qemghua Hu Yalou Huang College of Computer and Control Engineer Nankai University Tianjin China School of Computer Science and Technology Tianjin University Tianjin China College of Software Nankai University Tianjin China

ISBN: (纸本)9781467372220

Identifying expansion forms for acronyms is beneficial to many natural language processing and information retrieval tasks. As a step to this goal, we study the problem of finding expansions in texts for given acronym queries by modeling the problem as a sequence labeling task. However, it is challenging for traditional sequence labeling models like the Conditional Random Fields (CRF) because of the complexity of the input sentences and the substructure of the categories. In this paper, we propose the neural conditional random fields model with latent variables (LNCRF) to deal with the aforementioned challenge. On one hand, we extend the CRF by coupling it with nonlinear hidden layers to learn better representations of the input data under the framework of the CR-F. On the other hand, we introduce latent variables to capture the fine-grained information from the intrinsic substructures within each label implicitly. Experimental results on real data show that our model achieves the best performance against the state-of-the-art baselines including the Support Vector Machines and the standard Conditional Random Fields.

关键词： Acronyms incoming data Support Vector Network Corticotropin-Releasing Hormone Conditional Substructures information retrieval optimum performance Prediction models

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：