检索结果-内蒙古大学图书馆

16th International Conference on computer Supported Education, CSEDU 2024

作者： Nizamudeen, Faisal Gatti, Lorenzo Bouali, Nacir Ahmed, Faizan Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands

ISBN: (纸本)9789897586972

In our rapidly evolving technological landscape, AI tools have gained substantial power and integration across various domains. Through interviews and surveys conducted at a University in the Netherlands, we investigated students’ perceptions of AI tools. Our results show that students generally have a positive attitude towards the adoption of AI technologies and feel that it enhances their learning experience. Furthermore, this research project examines the capabilities of AI-powered tools, namely GitHub Copilot and ChatGPT, in solving a variety of university-level assignments. By empirically evaluating the capabilities of these AI tools and offering insights to educators, this research project aims to assist them in designing programming exercises that encompass essential learning processes while accounting for students’ utilization of AI tools. The findings indicate that a majority of the exercises currently utilized by the examined university could be solved partially or entirely with the aid of these tools. This project highlights the importance of educators understanding the capabilities of AI tools, as well as students’ attitudes towards them, to effectively adapt their teaching methods and promote essential learning goals. Copyright © 2024 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Deep Reinforcement Learning-Based AoI Minimization in UAV-Assisted Multi-Platoon Vehicular Networks 17

Deep Reinforcement Learning-Based AoI Minimization in UAV-As...

引用

IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart Data, SmartData 2024

作者： Du, Bochun Qu, Long Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China

ISBN: (纸本)9798350351637

In the current landscape of intelligent transportation, vehicle platooning has become a key strategy for improving traffic efficiency and safety. However, as multiple platoons move at high speeds, the platoon encounters an unpredictable communication environment, which poses a major challenge for coordinated control of multi-platoon vehicles. Meanwhile, the freshness of information plays a pivotal role in ensuring road traffic safety, quantified by the Age of Information (AoI). This study focuses on a UAV-assisted platooning system in Manhattan scenarios, aiming to minimize vehicle AoI while improving the communication success rate between vehicles and UAV nodes. To tackle this challenge, we model this problem as a Partially Observable Markov Decision Process (POMDP). We propose a trajectory and scheduling strategy based on the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) approach. Additionally, to better adapt to the dynamic nature of multi-platoon vehicular networks, we integrate the Prioritized Experience Replay (PER) technique to prioritize learning and processing of critical experience samples. Through simulation experiments and comparisons with baseline methods, the superiority of the proposed algorithm is verified. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Assesment of Cloud Security Posture Management Scenarios 23

Assesment of Cloud Security Posture Management Scenarios

引用

23rd RoEduNet Conference: Networking in Education and Research, RoEduNet 2024

作者： Leaua, Melina Silvia Chis, Alexandru Balan, Titus-Constantin Ilca, Lucian Florin Transylvania University Faculty Electrical Engineering and Computer Science Braşov Romania

ISBN: (纸本)9798331540388

The dynamic growth of the digital ecosystem presents evolving cybersecurity considerations, highlighting the constant change and emergence of new security concerns. While cloud providers offer robust security for the infrastructure, the user configurations of the cloud services can lead to misconfigurations, vulnerabilities, and compliance issues due to human error. The aim of the paper is to explore Cloud Security Posture Management solutions that can help mitigate these security risks. In this scope, two solutions are analyzed: A managed posture management solution using cloud native services and an open-source alternative solution. This comparison provides essential insights to understand their respective advantages and disadvantages helping to determine which solution is more suitable for specific cloud environments, taking into consideration various factors such as ease of use, complexity, costs, and dependency. © 2024 IEEE.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

A novel low-rank blind spot reconstruction network based on multi-scale mask convolution for hyperspectral anomaly detection

A novel low-rank blind spot reconstruction network based on ...

引用

2024 International Conference on Remote Sensing, Mapping, and Geographic Information Systems, RSMG 2024

作者： Yang, Zhiwei Zhao, Rui Meng, Xiangchao Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China

ISBN: (纸本)9781510685826

With the emergence of blind spot reconstruction networks in hyperspectral anomaly detection, a series of new challenges have arisen. The most significant issues include local anomaly identity mapping and inaccurate detection of large anomaly targets in deep learning networks. Therefore, we propose a busy point reconstruction network for hyperspectral anomaly detection based on multi-scale mask convolution. We creatively design a multi-scale mask convolution module that uses an inner window mask to isolate the center block and edge background for reconstruction. To further enhance space-spectral information interactivity, we introduce a joint space-spectral module. Additionally, to increase the network's focus on global low-rank backgrounds, we incorporate a block low-rank penalty to guide global low-rank attention. Finally, by considering the scale difference in detection performance between different mask convolutions, we develop a dynamic learnable fusion module that performs adaptive fusion of two mask convolution results for optimal detection performance on two real data sets. © 2024 SPIE.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Harmful Brain Activity Classification Using Ensemble Deep Learning 66

Harmful Brain Activity Classification Using Ensemble Deep Le...

引用

66th International Symposium ELMAR, ELMAR 2024

作者： Habijan, Marija Sojo, Robert Tolic, Ivana Hartmann Galic, Irena Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (纸本)9798350375411

Electroencephalography (EEG) is a crucial tool for monitoring electrical brain activity and diagnosing neurological conditions. Manual analysis of EEG signals is time-consuming and prone to variability, necessitating automated methods for accurate and efficient interpretation. This paper presents an ensemble learning approach for the automated classification of harmful brain activity from EEG data. The model combines the strengths of ResNet1d GRU, EfficientNetB0, and EfficientNetB1 to predict brain activity from spectrograms and raw EEG signals. By leveraging the unique capabilities of each model and employing a weighted averaging scheme, the ensemble achieves a competitive Kullback-Liebler divergence score of 0.3 on the testing dataset. This approach demonstrates the potential of ensemble learning to improve the accuracy and robustness of automated EEG signal classification, offering a valuable tool for early detection and diagnosis of neurological conditions. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Centripetal Intensive Deep Hashing for Remote Sensing Image Retrieval

引用

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 12439-12453页

作者： Wang, Weigang Guo, Zhongwen Cui, Ziyuan Zhao, Hailei Xian, Lintao The Faculty of Electrical Engineering and Computer Science Ocean University of China Qingdao266499 China The Department of Intelligent Medical Engineering Shandong Second Medical University Weifang261053 China

With the breakthrough of convolutional neural networks, deep hashing methods have demonstrated remarkable performance in large-scale image retrieval tasks. However, existing deep supervised hashing methods, which rely on pairwise or triplet labels, typically learn the hash function via random or hardest sample mining within training batches. This strategy primarily captures local sample similarities, causing a distribution shift and limiting retrieval performance. Furthermore, most methods emphasize global features while overlooking structural information, which is essential for understanding spatial relationships in images. To solve these limitations, we propose a Centripetal Intensive Deep Hashing (CIDH) method for remote sensing image retrieval. Initially, we design a Hybrid-Attention Guided Multiscale Refinement Network (HGMRN) that integrates channel and spatial attention to capture multiscale visual features and highlight salient regions at different scales. Subsequently, we introduce a central similarity loss via class-centered labels to optimize the spatial distribution of global samples, which can encourage hash codes with similar semantics to cluster around centroids and reduce distribution shift. Meanwhile, we incorporate a central intensive loss into the Hamming space to shorten intra-class Hamming distances, generating more compact and discriminative hash codes. Extensive experiments demonstrate the superiority of our CIDH method compared with current state-of-the-art deep hashing methods. © 2008-2012 IEEE.

关键词： Hamming distance

来源：评论

学校读者我要写书评

暂无评论

Implications of the forthcoming forensic sciences standard ISO/IEC 21043 for forensic biometrics 12

Implications of the forthcoming forensic sciences standard I...

引用

12th International Workshop on Biometrics and Forensics, IWBF 2024

作者： Meuwly, Didier University of Twente Faculty of Electrical Engineering Mathematics and Computer Science Enschede Netherlands

ISBN: (纸本)9798350354478

The forthcoming forensic sciences standard ISO/IEC 21043 is a methodological and technical standard, currently at the stage of Draft International Standard. When adopted, it will apply to all forensic disciplines, including forensic biometrics. This standard has been designed by forensic, legal, and standardisation professionals to ensure that forthcoming forensic services, products, and systems are safe, reliable, and consistently perform as intended. The aim of this contribution is to present to the forensic biometric community some of the implications of adopting ISO/IEC 21043 for the forensic biometric *** an introduction (§ I) and a review of the existing international standards applied in forensic science (§ II), the five-part structure of ISO/IEC 21043 is described: 1. Terms and definitions, 2. Recovery, 3. Analysis, 4. Interpretation and 5. Reporting, (§ III). Then a selection of requirements and recommendations of this five-part standard are highlighted, and their implication for forensic biometric research, development, implementation, and practice is discussed (§ IV).The conclusion is that the adoption and use of ISO/IEC 21043 will help forensic laboratories to reach accreditation and to enhance their existing quality management systems. It will also make it easier for forensic biometric researchers to develop, deliver, and implement more relevant, more reliable, and safer services, products, and systems to the forensic biometric examiners performing casework (§ V). © 2024 IEEE.

关键词： Forensic science

来源：评论

学校读者我要写书评

暂无评论

Energy-Efficient Scheduling Based on Task Migration Policy Using DPM for Homogeneous MPSoCs

引用

computers, Materials & Continua 2023年第1期74卷 965-981页

作者： Hamayun Khan Irfan Ud din Arshad Ali Sami Alshmrany Department of Electrical Engineering Faculty of Engineering&Technology Superior University Lahore54000Pakistan Department of Computer Science Faculty of Computer Science&IT Superior University Lahore54000Pakistan Faculty of Computer and Information Systems Islamic University of MadinahAl Madinah Al Munawarah42351Saudi Arabia

Increasing the life span and efficiency of Multiprocessor System on Chip(MPSoC)by reducing power and energy utilization has become a critical chip design challenge for multiprocessor *** the advancement of technology,the performance management of central processing unit(CPU)is *** densities and thermal effects are quickly increasing in multi-core embedded technologies due to shrinking of chip *** energy consumption reaches a threshold that creates a delay in complementary metal oxide semiconductor(CMOS)circuits and reduces the speed by 10%–15%because excessive on-chip temperature shortens the chip’s life *** this paper,we address the scheduling&energy utilization problem by introducing and evaluating an optimal energy-aware earliest deadline first scheduling(EA-EDF)based technique formultiprocessor environments with task migration that enhances the performance and efficiency in multiprocessor systemon-chip while lowering energy and power *** selection of core andmigration of tasks prevents the system from reaching itsmaximumenergy utilization while effectively using the dynamic power management(DPM)*** in the execution of tasks the temperature and utilization factor(u_(i))on-chip increases that dissipate more *** proposed approach migrates such tasks to the core that produces less heat and consumes less power by distributing the load on other cores to lower the temperature and optimizes the duration of idle and sleep times across multiple *** performance of the EA-EDF algorithm was evaluated by an extensive set of experiments,where excellent results were reported when compared to other current techniques,the efficacy of the proposed methodology reduces the power and energy consumption by 4.3%–4.7%on a utilization of 6%,36%&46%at 520&624 MHz operating frequency when particularly in comparison to other energy-aware methods for *** are running and accurately scheduled to make an energy-efficient

关键词： Dynamic power management dynamic voltage&frequency scaling dynamic thermal management multiprocessor system on chip complementary metal oxide semiconductor reliability

来源：评论

学校读者我要写书评

暂无评论

A comprehensive review of effective parameters to improve the performance of the Savonius turbine using a computational model and comparison with practical results

引用

Water-Energy Nexus 2024年第1期7卷 266-274页

作者： Jebelli, Ali Lotfi, Nafiseh Saeid Zare, Mohammad Yagoub, Mustapha C.E. Department of Engineering and Design Robotic Century Inc Alberta Canada Faculty of New Science and Technologies Tehran University Tehran Iran School of Electrical Engineering and Computer Science University of Ottawa ON Canada

Amidst growing global concerns over climate change and escalating greenhouse gas emissions from fossil fuels, the pursuit of renewable energy sources has become critical. This study focuses on harnessing hydropower using Savonius turbines, which are known for their efficiency in generating energy at lower flow rates. However, the intrinsic low efficiency of these turbines necessitates precise optimization tailored to specific river or channel conditions. In this research, we optimized the performance of Savonius turbines by analyzing key parameters such as the height-to-diameter ratio, blade twist, and the integration of multi-stage configurations with deflectors. Our findings reveal significant efficiency improvements through strategic modifications. Specifically, by reducing the height-to-diameter ratio from 1.2 to 0.8 and maintaining a Tip Speed Ratio (TSR) of 0.6, the power coefficient increased by 15%, from 0.33 to 0.38. Further optimization was achieved by adjusting the blade twist angle, with an increase in power coefficient up to an optimal angle of 45°, beyond which efficiency declined. Implementing a two-stage turbine setup with a 90-degree phase difference between stages further improved the power coefficient to 0.51 at the same TSR. Additionally, the use of deflectors, particularly at a 90° angle, significantly boosted the power coefficient, highlighting their effectiveness in optimizing water flow impact on the turbine. This comprehensive study not only advances the understanding of Savonius turbine optimization but also contributes to broader renewable energy applications. The research offers critical insights into sustainable hydroelectric power generation, providing practical solutions to enhance turbine performance for real-world applications. © 2024

关键词： Clean energy

来源：评论

学校读者我要写书评

暂无评论

Implementation of human-following robot system applying virtual delay to posture of a leader 3

Implementation of human-following robot system applying virt...

引用

3rd International Conference on Image Processing and Robotics, ICIPRoB 2024

作者： Takemori, Fumiaki Tottori University Faculty of Engineering Dept. of Electrical Engineering and Computer Science Tottori Japan

ISBN: (纸本)9798350374766

This paper develops an implementation of a measurement and control system in which a vehicle follows its predecessor while maintaining a certain distance. First, we construct a model that virtually delays the reference coordinates of the leading target backwards, and propose a control law that follows the steering angle of the following vehicle to that virtual delay point. Next, a range sensor is used to detect the position and orientation of the leader, and the position and orientation is estimated using a template matching method based on the person's body contour point group measured by the sensor. Finally, the effectiveness (including robustness) of the proposed system is demonstrated in some simulations and human tracking experiments. © 2024 IEEE.

关键词： Template matching

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：