检索结果-内蒙古大学图书馆

5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2023

作者： Hure, Nikola Vasak, Mario University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Renewable Energy Systems Zagreb Croatia

ISBN: (纸本)9798350337525

This paper focuses on the identification of thermodynamic models for temperature prediction in households. The proposed temperature dynamics model falls under the class of Linear Time-Invariant (LTI) models, making it suitable for model predictive control synthesis. However, the presence of significant and variable thermal disturbances in households adds complexity to the identification process. The performance of various prediction error methods, such as ARX, ARARMAX, and BJ models, along with simplified models incorporating persistent disturbance excitation, is analyzed. The findings highlight the substantial impact of unknown disturbances on temperature predictions, emphasizing the crucial need for accurate prediction of these disturbances for effective household heating and cooling planning. The identification and evaluation of model performance measures are conducted using two months of experimental data collected from five households. This study contributes to understanding of the significance of addressing unknown disturbances and variability in thermodynamic model identification for temperature prediction. © 2023 IEEE.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Model Identification of Building Thermal Dynamics 31

Data-Driven Model Identification of Building Thermal Dynamic...

引用

31st Telecommunications Forum, TELFOR 2023

作者： Jakšić, Mihael Lešić, Vinko Laboratory for Renewable Energy Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

ISBN: (纸本)9798350303131

This paper investigates a potential of using data-driven models for identification of the thermal model of buildings. Firstly, it gives a brief overview of approaches to develop suitable methods for control and explains the need for these suitable methods. Furthermore, it explains the experimental environment that has been set up on the 9th floor of the skyscraper at the University of Zagreb, Faculty of electrical engineering and computing and the process of data collection. Then, it explains the process of data preparation and proposes the experiment. Finally, it provides model parameters as the results for six data-driven modelling methods of machine learning and deep neural networks and discussion of the results. For the selected case study and corresponding dataset, LightGBM resulted in the lowest MSE, MAE and MAPE, offering thus a strong point for a fast building thermal model acquisition and alternative to costly physical modeling process. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Incorporating a High-speed Camera in the Lightning Current Measurement System for Wind Turbines 4

Incorporating a High-speed Camera in the Lightning Current M...

引用

4th International Conference on Smart Grid Metrology, SMAGRIMET 2023

作者： Vukovic, Franjo Milardic, Viktor Filipovic-Grcic, Bozidar Stipetic, Nina Franc, Bojan Milos, Dominik University of Zagreb Faculty of Electrical Engineering and Computing Department of Energy and Power Systems Zagreb Croatia

ISBN: (纸本)9798350323597

A lightning current measurement system for wind turbines was developed and tested in the High Voltage Laboratory at the Faculty of electrical engineering and computing, University of Zagreb, to determine actual distributions of lightning current parameters in a particular wind turbine area. The output of the measurement system is a waveform of lightning current. The measurement system consists of two current sensors with different frequency and amplitude ranges and a real-Time controller with two digitizers and a GPS module. The current sensors are Rogowski coils connected to integrators with coaxial cables. The prototype was installed on a wind turbine in a high winter lightning activity area. The current stage of development involves integrating the high-speed camera into the prototype measurement system to obtain the visual confirmation of the waveform measurements and help categorize lightning strikes into downward or upward strikes. The camera control application was developed in LabVIEW. The camera was set to trigger by the real-Time controller. Also, a redundant trigger occurs when there is a change in motion in the camera frame in case the prototype measurement system fails to register a lightning strike and therefore fails to send a trigger signal to the camera. The camera control application was tested in the High Voltage Laboratory by recording a flashover in a spark gap and a flashover on the insulator. © 2023 IEEE.

关键词： High speed cameras

来源：评论

学校读者我要写书评

暂无评论

A Deep Reinforcement Learning Approach for Cost Optimized Workflow Scheduling in Cloud computing Environments 24

A Deep Reinforcement Learning Approach for Cost Optimized Wo...

引用

2024 Asia Pacific Conference on computing Technologies, Communications and Networking, CTCNet 2024

作者： Jayanetti, Amanda Halgamuge, Saman Buyya, Rajkumar Lab School of Computing and Information Systems The University of Melbourne Australia School of Electrical Mechanical and Infrastructure Engineering The University of Melbourne Australia

ISBN: (纸本)9798400709609

Cost optimization is a common goal of workflow schedulers operating in cloud computing environments. The use of spot instances is a potential means of achieving this goal, as they are offered by cloud providers at discounted prices compared to their on-demand counterparts in exchange for reduced reliability. This is due to the fact that spot instances are subjected to interruptions when spare computing capacity used for provisioning them is needed back owing to demand variations. Also, the prices of spot instances are not fixed as pricing is dependent on long term supply and demand. The possibility of interruptions and pricing variations associated with spot instances adds a layer of uncertainty to the general problem of workflow scheduling across cloud computing environments. These challenges need to be efficiently addressed for enjoying the cost savings achievable with the use of spot instances without compromising the underlying business requirements. To this end, in this paper we use Deep Reinforcement Learning for developing an autonomous agent capable of scheduling workflows in a cost efficient manner by using an intelligent mix of spot and on-demand instances. The proposed solution is implemented in the open source container native Argo workflow engine that is widely used for executing industrial workflows. The results of the experiments demonstrate that the proposed scheduling method is capable of outperforming the current benchmarks. © 2024 Copyright held by the owner/author(s).

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

LPL-VIO: monocular visual-inertial odometry with deep learning-based point and line features

引用

Neural computing and Applications 2024年第36期36卷 23061-23075页

作者： Liu, Changxiang Yang, Qinhan Yu, Hongshan Fu, Qiang Akhtar, Naveed College of Electrical and Information Engineering School of Robotics Quanzhou Institute of Industrial Design and Machine Intelligence Innovation Hunan University Changsha China School of Computing and Information Systems The University of Melbourne VIC Australia

Visual-inertial SLAM (VINS) has garnered substantial interest in the field of mobile robotics due to its robustness and cost-effectiveness. The incorporation of both point and line features in visual SLAM has shown significant performance improvements compared to relying solely on point features. Furthermore, learning-based features consistently outperform traditional hand-crafted features across a diverse range of tasks. Leveraging all these observations, we propose a novel deep learning technique, termed learning-based point and line visual-inertial odometry (LPL-VIO), which is aimed to enhance robustness and performance of traditional systems. LPL-VIO takes a 2-stage approach, including a deep learning front-end and a traditional nonlinear optimization back-end. In the first stage (front-end), we employ proposed networks for points and lines to extract and track deep learning-based point and line features in visual images, while implementing IMU preintegration. In the second stage (back-end), we adopt a sliding window strategy to tightly couple point and line re-projection errors with IMU preintegration residuals. These residuals are optimized using bundle adjustment for precise global pose estimation. Extensive experiments are conducted on both public EuRoC datasets and our own real-world dataset collected in challenging outdoor environments. Qualitative and quantitative results show that our method exhibits strong competitiveness compared with the existing point–line techniques, and outperforms the popular VINS-Mono. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： SLAM robotics

来源：评论

学校读者我要写书评

暂无评论

Analysis of LiDAR-Camera Fusion for Marine Situational Awareness with Emphasis on Cluster Selection in Camera Frustum 15

Analysis of LiDAR-Camera Fusion for Marine Situational Aware...

引用

15th IFAC Conference on Control Applications in Marine systems, Robotics and Vehicles, CAMS 2024

作者： Obradović, Juraj Fabijanić, Matej Batoš, Matko Mišković, Nikola Faculty of Electrical Engineering and Computing University of Zagreb Department LABUST Laboratory for Underwater Systems and Technologies Unska 3 Zagreb Croatia

Providing accurate information about all objects in the environment surrounding an autonomous vehicle is essential for the development of a maritime navigation system used on board autonomous and unmanned vessels. In this paper, we introduce a method that integrates LiDAR and camera data for precise 3D object detection and tracking. The approach utilizes LiDAR for acquiring object position information and ensures accurate object classification through data from the camera. The proposed architecture is presented with a detailed explanation of all algorithms used. Several scenarios have been created in a simulated environment to compare three approaches for the selection of target object in the camera frustum (the Nearest Center, Gaussian Likelihood, and Intersection-Over-Union). Finally, the full algorithm setup is tested in a simulator environment with multiple vessels and a background coast. © 2024 Elsevier B.V.. All rights reserved.

关键词： Marine navigation

来源：评论

学校读者我要写书评

暂无评论

Novel Darknet traffic data synthesis using Generative Adversarial Networks enhanced with oscillatory Growing Cosine Unit activated convolution layers

引用

International Journal of Cognitive computing in engineering 2024年第1期5卷 58-65页

作者： Pradeep C, Antony Amali D, Geraldine Bessie Noel, Mathew Mithra Ghalib, Muhammad Rukunuddin Subramaniam, Prabhakar Rontala Venugopal, Chitra School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Electrical Engineering Vellore Institute of Technology Vellore India School of Computing De Montfort University Dubai United Arab Emirates Information Systems and Technology Westville South Africa Electrical Engineering & Renewable Energy Oregon Institute of Technology United States

The Darknet is an anonymous, encrypted collection of websites, with a passive listening nature - accepting incoming packets, while not supporting outgoing packets. Thus, it can potentially host criminal or malicious activity and software, becoming a cyber security threat. Network Detection systems are effective in identifying dark net traffic and mitigating its ill effects. However, capturing and extracting data from raw network traffic for training these systems can be time-intensive and costly. Using the CIC-Darknet 2020 dataset, this paper proposes using a Novel Generative Adversarial Networks (GAN) Architecture generating the required training and testing data for these systems. This uses a combination of Growing Cosine Unit (GCU) activated convolution layers and Dense layers for the Generator. Feature selection with statistical correlation methods is used to select the most relevant features. An independently trained Evaluator network is used to evaluate the generated data. The proposed system is compared to other established Tabular data GANs like Conditional Tabular GAN (CTGAN) and Copula GAN with similar parameters and on the same data. The Proposed GAN architecture outperforms CTGAN and CopulaGAN by 20 % and 10 % in ters of accuracy while also taking 90 % and 30 % less time to train respectively. Results from measuring similarity of data using the Inverted Kolmogorov - Smirnov D statistic also show significantly better results for the Proposed GAN Architecture. This shows significant promise in using Generative models to reduce the time and effort costs associated with collecting and formatting data to use in research and for training detection systems. © 2024

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Robust and Computationally Efficient Estimation of State of Power and Maximum Energy for Lithium-Ion Batteries in Electric Vehicles

Robust and Computationally Efficient Estimation of State of ...

引用

2023 IEEE Conference on Control Technology and Applications, CCTA 2023

作者： Leko, Dorijan Vasak, Mario University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Renewable Energy Systems Zagreb10000 Croatia

ISBN: (纸本)9798350335446

Battery management system (BMS) affects the safety and performance of electric vehicles by providing adequate power ranges (e.g., state of power or power profile of maximum energy) to the vehicle dynamics control. The main task of the BMS is to ensure battery longevity while maximizing the power ranges the battery can give or receive. This paper proposes a procedure for estimating the state of power (SoP) and maximum energy (ME) for a lithium-ion battery cell based on sequential linear programming and using the nonlinear dual polarization equivalent circuit model (ECM) with average power input. The estimation procedure is based on the optimization problem with linear optimization criterion and nonlinear constraints on a fixed prediction horizon. The ECM with power input enables timewise efficient on-line SoP and ME estimation for battery charging and discharging. The SoP and ME estimation is verified through a case study by using the derived ECM with power input. © 2023 IEEE.

关键词： Lithium-ion batteries

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Multivariate Autoregression Based EEG Data Compressor Circuit 3rd

Performance Analysis of Multivariate Autoregression Based EE...

引用

The 3rd International Conference on Frontiers in computing and systems (COMSYS 2022)

作者： Chowdhury, Md. Mushfiqur Rahman Chowdhury, Shubhajit Roy Biomedical Systems Laboratory School of Computing and Electrical Engineering Indian Institute of Technology HP Mandi India

ISBN: (纸本)9789819926794

This paper presents a Field Programmable Gate Array (FPGA)-based effective real-time data compressor circuit for lossless compression of single and multichannel EEG data. The main goal of this design is to develop real-time architecture that gives us live EEG data which can be sent to a doctor wirelessly and further which may monitor signal abnormalities in EEG when a seizure occurs. The circuit implements an efficient algorithm resulting in high compression ratio. The bio-signal compressing algorithm is based on the combination of modified multivariate autoregression method and data entropy prediction algorithm. The prediction algorithm also includes the application of low-pass FIR Filter. The algorithm has been implemented in hardware using Verilog HDL and the system has been implemented on a Xilinx Zynq Ultrascale MPSoC ZCU 104 FPGA board. The resulting compression ratio (CR) of the proposed method is 76.2% on average, in some cases, it goes up to 99% for a few channels, which is more than any other state-of-the-art algorithms. The performance of the algorithm and circuit both have been evaluated and compared with the modern peer designs. The signal parameters have been evaluated, where the signal accuracy is 92.7% on average for several datasets. The circuit has a power consumption of 0.511 micro-Watts. This FPGA-based solution uses the hardware resources effectively while achieving high-speed signal recovery. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Dynamic Event-Triggered Leader-Following Consensus of Multiagent systems under DoS Attacks 43

Dynamic Event-Triggered Leader-Following Consensus of Multia...

引用

43rd Chinese Control Conference, CCC 2024

作者： Ma, Ji Chen, Xiangyong Wu, Yue Sun, Ji Liu, Jianhua Linyi University The Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong School of Automation and Electrical Engineering Linyi276005 China

ISBN: (纸本)9789887581581

In this paper, the leader-following consensus of multi-agent systems (MASs) under denial-of-service (DoS) attacks over undirected networks is studies. First, introduce an estimator under DoS attacks to design a dynamic event-triggered communication protocol, which avoids continuous communication between agents. Then, with the presence of the estimator between the triggering instants can reduce the state shift. In contrast to the conventional method, the existence of dynamic threshold need fewer triggering times. Under this control strategy, the systems only need the states in triggering instants according to estimated states. Finally, verify the effectiveness of the proposed approach by a simulation example. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Denial-of-service attack

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：