检索结果-内蒙古大学图书馆

IEEE Conference on Decision and Control

作者： Shuhua Zhang Lifeng Ma Themistoklis Charalambous School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical and Computer Engineering School of Electrical Engineering University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland FinEst Centre for Smart Cities Tallinn Estonia

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper proposes a data-driven control (DDC) strategy for nonlinear automated vehicles, employing a multidescription coding (MDC) mechanism based on scalar quantization to address the challenges of data dropouts and limited bandwidth in networked communication environments. The developed MDC-based communication protocol enhances system robustness by reducing the probability of data dropout. It achieves this by transmitting multiple descriptions of source data through diverse channels, incorporating quantization and index reassignment to efficiently alleviate bandwidth constraints. Based on the reconstructed real-time data, a novel data-driven controller and a parameter estimation algorithm are designed, offering adaptability to varying driving conditions and rapid response in dynamic environments. A numerical simulation showcases the potential of the proposed approach as a reliable and efficient solution for the speed problem in nonlinear automated vehicles with challenging communication environments.

关键词： Quantization (signal) Protocols Parameter estimation Heuristic algorithms Velocity control Bandwidth Numerical simulation Encoding Robustness Vehicle dynamics

来源：评论

学校读者我要写书评

暂无评论

Novel development tool for IEC 61499 based on domain-specific languages

引用

IFAC-PapersOnLine 2022年第2期55卷 439-444页

作者： Radimir Sorokin Sandeep Patil Valeriy Vyatkin Department of Computer Technologies ITMO University Russia Department of Computer Science Computer and Space Engineering Lulea Tekniska Universitet Sweden Department of Electrical Engineering and Automation Aalto University Espoo Finland & Department of Computer Science Computer and Space Engineering Lulea Tekniska Universitet Sweden

This paper presents an example of a systematic approach based on domain-specific languages to implement Function Blocks Modelling Environment (FBME): an integrated development environment (IDE) for the international standard IEC 61499. The new open development environment for the standard of growing importance in the Industry 4.0 realm would contribute to the broader adoption of open standard-based development practices and facilitate efficient automation software development.

关键词： IEC 61499 distributed control application integrated development environment domain-specific language modular architecture

来源：评论

学校读者我要写书评

暂无评论

Analysis of 240CPWM with Three-Level Neutral-Point-Clamped Inverter

Analysis of 240CPWM with Three-Level Neutral-Point-Clamped I...

引用

IEEE Workshop on computers in Power Electronics

作者： Xiaosa Sui Hafsa Qamar Haleema Qamar Deliang Wu School of Mechatronic Engineering and Automation Shanghai University Shanghai China Department of Electrical Engineering Lahore University of Management Sciences Lahore Pakistan Department of Electrical and Computer Engineering Habib University Karachi Pakistan

ISBN: (数字)9798350307238

ISBN: (纸本)9798350307245

This paper analyzed the basic characteristics of neutral-point-clamped three-level inverters (NPC-3LI) with 240-degree clamped pulse-width modulation (240CPWM) method. Based on the stator flux ripple method, the output current total harmonic distortion (THD) is calculated for NPC-3LI with different PWM methods including the conventional SVPWM, discontinuous PWM (DPWM1) and 240CPWM. The losses of the switching devices and the output common mode voltage (CMV) of the inverter are also evaluated and compared. The analysis results show that adopting 240CPWM with NPC-3LI can reduce the switching losses by 89% at unit power factor, and has nearly equal THD compared to conventional SVPWM.

关键词： Space vector pulse width modulation Insulated gate bipolar transistors Reactive power Total harmonic distortion Switching loss Switches Stators

来源：评论

学校读者我要写书评

暂无评论

W2V-SELD: A SOUND EVENT LOCALIZATION AND DETECTION FRAMEWORK FOR SELF-SUPERVISED SPATIAL AUDIO PRE-TRAINING

arXiv

引用

arXiv 2023年

作者： dos Santos, Orlem Lima Rosero, Karen de Alencar Lotufo, Roberto Department of Computer Engineering and Industrial Automation University of Campinas Campinas Sao Paulo Brazil Department of Electrical and Computer Engineering The University of Texas at Dallas RichardsonTX United States

Sound Event Detection and Localization (SELD) constitutes a complex task that depends on extensive multichannel audio recordings with annotated sound events and their respective locations. In this paper, we introduce a self-supervised approach for SELD adapted from the pre-training methodology of wav2vec 2.0, which learns representations directly from raw audio data, eliminating the need for supervision. By applying this approach to SELD, we can leverage a substantial amount of unlabeled 3D audio data to learn robust representations of sound events and their locations. Our method comprises two primary stages: pre-training and fine-tuning. In the pre-training phase, unlabeled 3D audio datasets are utilized to train our w2v-SELD model, capturing intricate high-level features and contextual information inherent in audio signals. Subsequently, in the fine-tuning stage, a smaller dataset with labeled SELD data fine-tunes the pre-trained model. Experimental results on benchmark datasets demonstrate the effectiveness of the proposed self-supervised approach for SELD. The model surpasses baseline systems provided with the datasets and achieves competitive performance comparable to state-of-the-art supervised methods. The code and pre-trained parameters of our w2v-SELD model are available in this repository. © 2023, CC BY.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

Malware Detection Using Genetic Cascaded Support Vector Machine Classifier in Internet of Things 2

Malware Detection Using Genetic Cascaded Support Vector Mach...

引用

2nd International Conference on computer Science, engineering and Applications, ICCSEA 2022

作者： Gupta, Shashi Kant Pattnaik, Birajashis Agrawal, Vineet Boddu, Raja Sarath Kumar Srivastava, Archana Hazela, Bramah Integral University Computer Science and Engineering UP Lucknow India Amity University Mechanical & Automation Engineering Amity School of Engineering & Technology Kolkata India Babu Banarasi das Institute of Technology and Management Department of Computer Science and Engineering UP Lucknow India Lenora College of Engineering Department of Cse Andhra Pradesh Rampachodavaram India Bbd University School of Computer Applications UP Lucknow India Amity University Computer Science and Engineering Amity School of Engineering and Technology Lucknow Lucknow Campus India

ISBN: (数字)9781665458344

ISBN: (纸本)9781665458344

The Internet of Things (IoT) is a network of computing devices that can transmit and obtain data across a network without human intervention. In the last couple of decades, software and communication technology have advanced tremendously, resulting in a considerable increase in IoT devices. The rapid expansion has raised security and privacy issues. Threats and malware attacks on IoT devices have increased dramatically recently. Hence, in this paper, we proposed a novel malware detection framework based on machine learning in IoT using a Genetic Cascaded Support Vector Machine (GC-SVM) classifier. We introduce the Chaotic Binary Coded Cuckoo Search Optimization Algorithm (CBC-CSOA) for optimizing the detection process. The performance of the proposed method is evaluated and compared with various conventional methodologies. The proposed method produced accurate outputs this approach may be used to forecast and identify malware in IoT-based systems, according to the study. © 2022 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of IoT Enabled Smart Assistive Systems for Healthcare Applications 2

Design and Implementation of IoT Enabled Smart Assistive Sys...

引用

2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Dankan Gowda, V. Srinivas, D. Srinivas, Rachakonda Ingole, Balaji Shesharao Jadhav, Priya Dongare Prasad, K.D.V. Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Sr University School of Business Telangana Warangal506371 India Aditya Institute of Technology and Management Department of Computer Science & Engineering Tekkali Andhra Pradesh Srikakulam India GA United States Department of Robotics and Automation Maharashtra Pune412115 India Symbiosis Institute of Business Management Hyderabad India Pune India

ISBN: (纸本)9798350388916

The use of IoT technology in healthcare systems has been adopted in patient monitoring because IoT technology has been adopted rapidly in the systems. This paper discusses on design and implementation of an IoT integrated smart assistive health care system to enhance the precision and speed of patient health assessment. In the proposed system, wearable sensors are used to capture respiratory rate, pulse rate, blood pressure, oxygen saturation, and body temperature with data to be sent to the cloud server as and when it is received. Some of the features are, however, small data transmission delays, high accuracy in the physiological signals and long durations of monitoring due to the low power consumption. The simulations showed that the response time falls below 500ms, and physicians retain up to a 2 % variance to clinical grade devices, which actualized robust and effective patient care. The incorporation of predicting capacities, thus providing ways of early identification of health complications, makes the system applicable in chronic disease treatments and telemedicine. © 2024 IEEE.

关键词： Blood pressure

来源：评论

学校读者我要写书评

暂无评论

Exploiting 2.5D/3D Heterogeneous Integration for AI Computing

Exploiting 2.5D/3D Heterogeneous Integration for AI Computin...

引用

Asia and South Pacific Design automation Conference

作者： Zhenyu Wang Jingbo Sun Alper Goksoy Sumit K. Mandal Yaotian Liu Jae-Sun Seo Chaitali Chakrabarti Umit Y. Ogras Vidya Chhabria Jeff Zhang Yu Cao School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ USA Department of Electrical and Computer Engineering University of Wisconsin–Madison Madison WI USA Department of Computer Science and Automation Indian Institute of Science Bangalore India Department of Electrical and Computing Engineering Cornell Tech NY USA Department of Electrical and Computer Engineering University of Minnesota Twin Cities MN USA

The evolution of AI algorithms has not only revolutionized many application domains, but also posed tremendous challenges on the hardware platform. Advanced packaging technology today, such as 2.5D and 3D interconnection, provides a promising solution to meet the ever-increasing demands of bandwidth, data movement, and system scale in AI computing. This work presents HISIM, a modeling and benchmarking tool for chiplet-based heterogeneous integration. HISIM emphasizes the hierarchical interconnection that connects various chiplets through network-on-package. It further integrates technology roadmap, power/latency prediction, and thermal analysis together to support electro-thermal co-design. Leveraging HISIM with in-memory computing chiplets, we explore the advantages and limitations of 2.5D and 3D heterogenous integration on representative AI algorithms, such as DNNs, transformers, and graph neural networks.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Price Prediction of Digital Currencies using Machine Learning 10

Price Prediction of Digital Currencies using Machine Learnin...

引用

10th IEEE International Conference on Data Science and Advanced Analytics, DSAA 2023

作者： Dwivedi, Ashutosh Dhar Dutta, Subhayu Adhikary, Subhrangshu Pedersen, Jens Myrup Aalborg University Cyber Security Group Department of Electronic Systems Copenhagen Denmark Dr. B.C. Roy Engineering College Department of Computer Science & Engineering West Bengal Durgapur713206 India Spiraldevs Automation Industries Pvt. Ltd. Department of Research & Development West Bengal Raiganj733123 India

ISBN: (纸本)9798350345032

Cryptocurrencies have gained immense significance and popularity in recent times. With thousands of digital currencies available, selecting the right one can be challenging for users. In the financial sector, accurately predicting future prices is crucial for profitable investments in digital currencies. However, price prediction in this realm poses unique challenges, as it lacks physical goods or services as the basis, unlike stock prices. Machine learning emerges as a pivotal tool for addressing this challenge and plays a vital role in price prediction. This research analyzes five prominent currencies - Monero, Bitcoin, Ethereum, IOTA, and Zcash - employing five models: SVR, LRG, Huber, RANSAC, MLP, and AdaBoost. The experimental results demonstrate promising outcomes, showcasing the ability to predict digital currency prices with an impressive R2 score of 1.0 for specific machine learning algorithms. This advancement opens new avenues for informed decision-making and profitable ventures in the dynamic world of digital currencies. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Recursive Broadcasting Approach

Recursive Broadcasting Approach

引用

Euromicro Conference on Parallel, Distributed and Network-Based Processing

作者： Hovhannes A. Harutyunyan Narek Hovhannisyan Department of Computer Science and Software Engineering Concordia University Montreal QC Canada NAS RA Institute for Informatics and Automation Problems Yerevan Armenia

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

Broadcasting is one of the fundamental information dissemination primitives in interconnection networks, where a message is passed from one node (called originator) to all other nodes in the network. Following the increasing interest in interconnection networks, extensive research was dedicated to broadcasting. Two main research goals of this area are finding inexpensive network structures that maintain efficient broadcasting and finding the broadcast time for well-known and widely used network topologies. In the scope of this study, we will mainly focus on determining the broadcast time and nearoptimal broadcasting schemes in networks. Determination of the broadcast time of any node in an arbitrary network is known to be NP-hard. Polynomial time solutions are known only for a few network topologies. There also exist various heuristic and approximation algorithms for different network topologies. In this study, we consider the broadcast time problem on graphs that comprise some recursive structures. We initiate a novel direction to designing broadcasting algorithms on recursively defined graphs. We provide a theoretical foundation for future broadcasting studies, as well as discuss several practical applications of the approach we introduce.

关键词： Multicast algorithms Network topology Multiprocessor interconnection Heuristic algorithms Broadcasting Approximation algorithms Polynomials Topology

来源：评论

学校读者我要写书评

暂无评论

Fault Tolerance Technique Based on State Real-time Synchronization

Fault Tolerance Technique Based on State Real-time Synchroni...

引用

2021 IEEE International Conference on Data Science and computer Application, ICDSCA 2021

作者： Xu, Zhenpeng Liu, Hongwei Liu, Yu Jiangsu Automation Research Institute Department of Computer Lianyungang China Weifang University School of Computer Engineering Weifang China

ISBN: (纸本)9781665440530

Key service hosts in information systems have higher and higher requirements on high reliability and survivability. Combined with the development trend of fault-tolerant technology, the mechanisms of data synchronization, memory synchronization, IO synchronization, fault detection, and transparent switching between active and standby are introduced, and a dual-machine redundancy high availability model based on state real-time synchronization is constructed. In order to reduce the overhead of memory state synchronization, an event-driven memory synchronization trigger mechanism is designed, that is, the key IO event-driven event trigger mechanism is adopted for the synchronization timing of memory checkpoints, so as to minimize unnecessary memory data update operations between the main and standby computers and reduce the overhead of computer state synchronization. At the same time, combined with BMC monitoring interface based on physical host, a fine-grained fault detection method is proposed. Related work can greatly reduce the overhead caused by high availability mechanism, and reduce the impact of fault-tolerant mechanism on system computing performance to a certain extent. At the same time, it has the ability to switch between active and standby quickly, which is helpful to better guarantee the uninterrupted and continuous running ability of task applications in key systems. © 2021 IEEE.

关键词： Fault detection

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：