检索结果-内蒙古大学图书馆

2023 Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2023

作者： Sun, Chen Tian, Xiaolin Macau University of Science and Technology Faculty of Innovation Engineering School of Computer Science and Engineering China

Lunar domes have always been one of the important windows to understand lunar volcanic activities, but traditional geological dome identification methods are costly. This study attempts to establish an automatic identification method for lunar volcanic domes through FSOD (Few-Shot Object Detection). Since our previous research has been trying to automatically identify lunar volcanic hills using traditional recognition algorithms, our team will try Few-Shot Object Detection this time. In this study, the researchers first obtained the dome coordinates from the list of known lunar domes and intercepted the data this research need from the corresponding coordinates on the DEM moon images. Subsequently, this research used the existing data to train six traditional recognition algorithms and FSOD and compared their performance to verify the feasibility of this study. This research use AP50 and AP75 to evaluate the performance of the model. Finally, this research found that the AP50 of FSOD can reach 0.76, and the AP75 can reach 0.43. However, although FSOD does perform better than other traditional identification methods, this research believe its accuracy is still far from our expectations. Admittedly, compared with YOLO v5, the performance of FSOD has not been significantly improved, but this study still verifies that it is feasible to apply FSOD to the identification of lunar volcanic domes. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Access Management in IoT: Implementing a Secure Access Control System 15

Access Management in IoT: Implementing a Secure Access Contr...

引用

15th International Conference on Communications, COMM 2024

作者： Neculai, Razvan-Sebastian Bogdan, Ioana-Corina Alexandru, Marian Robu, Dan-Nicolae Transilvania University of Brasov & Eviden Faculty of Electrical Engineering and Computer Science Department of Cybersecurity Braşov Romania Transilvania University of Brasov Faculty of Electrical Engineering and Computer Science Department of Electronics and Computers Braşov Romania

ISBN: (纸本)9798350355956

This paper aims to implement and use the Spring Security framework to secure and authenticate the connection between a web application and the ESP32 device. In the context of a web application, by analyzing the integration of the Spring Security framework, it investigates the ways in which it manages the complex process of authentication and authorization, thus providing a secure and protected connection to an IoT device. Additionally, this study investigates the integration and use of the RTOS operating system to manage physical access in an IoT environment, in particular by implementing the opening of a door using tags. The mechanism described above leads to an additional level of security and control over physical access in an IoT ecosystem. © 2024 IEEE.

关键词： Radio frequency identification (RFID)

来源：评论

学校读者我要写书评

暂无评论

Learning of Multimodal Point Descriptors in Radar and LIDAR Point Clouds

Learning of Multimodal Point Descriptors in Radar and LIDAR ...

引用

2024 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems, MFI 2024

作者： Rottter, Jan M. Cohrs, Simon Blume, Holger Wagner, Bernardo Leibniz University of Hannover Realtime Systems Group The Faculty of Electrical Engineering and Computer Science Hannover30167 Germany Institute of Microelectronic Systems The Faculty of Electrical Engineering and Computer Science Leibniz University of Hannover Hannover30167 Germany

ISBN: (纸本)9798350368031

Registration of point clouds is a fundamental task in robotic SLAM pipelines. Typically this task is performed only on point clouds of the same sensor or at least the same sensing modality. However, robots designed for challenging environments are often equipped with redundant sensors for the same task where some sensors are more accurate and others are more robust against disturbing environmental conditions. Being able to register the data across the modalities is an important step to more fault-tolerant localization and mapping. We therefore propose a learning framework, which describes the points in the point cloud invariant of their modality. This description is then used in a transformer-like model to find point matches for the registration process. We demonstrate our results using a scanning lidar and radar sensor on our own and publicly available datasets. © 2024 IEEE.

关键词： SLAM robotics

来源：评论

学校读者我要写书评

暂无评论

Wideband Slot Antenna Array with Stable Low Sidelobe Performance

引用

IEEE Antennas and Wireless Propagation Letters 2025年第5期24卷 1248-1252页

作者： Zhang, Fengyuan Zhang, Hanlin You, Qingchun Huang, Jifu Ningbo University Faculty of Electrical Engineering and Computer Science Zhejiang Ningbo315211 China University of Birmingham School of Engineering B15 2TT United Kingdom

This letter presents a dispersion compensation method that integrates a comb-shaped slow-wave structure with a defected ground structure (DGS) to achieve wideband low-sidelobe performance. This method effectively ensures phase balance within the feed network, achieving a stable low sidelobe level over a wide frequency range. A prototype planar array antenna operating in the 21.6-30.8 GHz range was designed, fabricated, and measured. The experimental results demonstrate that the antenna achieves a fractional bandwidth (FBW) of 35.1%, with the first sidelobe level maintained below -21 dB across the entire band and a fluctuation confined within ±1.3 dB. © 2002-2011 IEEE.

关键词： Defected ground structures

来源：评论

学校读者我要写书评

暂无评论

A Lightweight Multidendritic Pyramidal Neuron Model With Neural Plasticity on Image Recognition

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4415-4427页

作者： Zhang, Yu Cai, Pengxing Sun, Yanan Zhang, Zhiming Lei, Zhenyu Gao, Shangce University of Toyama Faculty of Engineering Toyama-shi930-8555 Japan Sichuan University Department of Artificial Intelligence College of Computer Science Chengdu610065 China

Simulating the method of neurons in the human brain that process signals is crucial for constructing a neural network with biological interpretability. However, existing deep neural networks simplify the function of a single neuron without considering dendritic plasticity. In this article, we present a multidendrite pyramidal neuron model (MDPN) for image classification, which mimics the multilevel dendritic structure of a nerve cell. Unlike the traditional feedforward network model, MDPN discards premature linear summation integration and employs a nonlinear dendritic computation such that improving the neuroplasticity. To model a lightweight and effective classification system, we emphasized the importance of single neuron and redefined the function of each subcomponent. Experimental results verify the effectiveness and robustness of our proposed MDPN in classifying 16 standardized image datasets with different characteristics. Compared to other state-of-the-art and well-known networks, MDPN is superior in terms of classifica-tion accuracy. © 2020 IEEE.

关键词： computer architecture

来源：评论

学校读者我要写书评

暂无评论

An Empirical Study of Unanswered Python-Related Questions on Stack Overflow

An Empirical Study of Unanswered Python-Related Questions on...

引用

2024 International Conference on Information Technology Research and Innovation, ICITRI 2024

作者： Nugroho, Yusuf Sulistyo Halim, Salsabil Aisyah Abdul Islam, Syful Kurniawan, Yogiek Indra Erlina, Tati Universitas Muhammadiyah Surakarta Informatics Engineering Faculty of Communication and Informatics Surakarta Indonesia BSMRSTU Computer Science and Engineering Faculty of Engineering Gopalganj Bangladesh Universitas Jenderal Soedirman Informatics Engineering Faculty of Engineering Purwokerto Indonesia Universitas Andalas Computer Engineering Faculty of Information Technology Padang Indonesia

ISBN: (纸本)9798350376210

As a high-level programming language, Python supports user-friendly coding and system integration. It is not only used for data analytics but is also applied in software development. Although it has several benefits, users have various issues while running Python code. When programmers face issues, they often use Stack Overflow (SO) to get assistance for their problems. However, many Pythonrelated questions on SO are not responded to and remain unanswered. Thus, in this paper, we analyzed these unanswered questions to identify potential weaknesses of user and discussion characteristics. We applied a mixed-methods approach, including quantitative and qualitative analysis of user reputation, question types, and discussion topics. Our analysis shows that unanswered questions are mostly from low-reputation users (72.52%), followed by mid-reputation users (17.93%), and high-reputation users (9.5 5%). The distribution of the unanswered question types shows that low-reputation users ask more 'how' type of question (38.90%) followed by mid and high-reputation users. In contrast, the 'what' and 'why' questions are mostly posted by high-reputation users, followed by mid and low-reputation users. Our word-cloud analysis suggests a correlation between user reputation and the question topics. We acknowledge that there are limitations in our study, include potential misclassifications due to the time of posting and biases in manual labeling, which may affect the accuracy of our findings. This study provides insights into unanswered questions posted by the community, open up potential areas for future work such as improving support mechanisms and community engagement. © 2024 IEEE.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

YOLOv8n-CGW: A novel approach to multi-oriented vehicle detection in intelligent transportation systems

引用

Multimedia Tools and Applications 2025年第7期84卷 3809-3840页

作者： Berwo, Michael Abebe Fang, Yong Sarwar, Nadeem Mahmood, Jabar Aljohani, Mansourah Elhosseini, Mostafa School of Information and Engineering Chang’an University Shaanxi Xi’an710064 China Department of Computer Science Bahria University Lahore Campus Punjab Lahore54600 Pakistan Department of Information Technology Faculty of Computing and Information Technology University of Sialkot Punjab Sialkot51040 Pakistan College of Computer Science and Engineering Taibah University Yanbu46421 Saudi Arabia Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt

In the context of Intelligent Transportation Systems (ITS), the role of vehicle detection and classification is indispensable for streamlining transportation management, refining traffic control, and conducting in-depth accident analyses. However, the intricate task of accurately detecting multi-oriented vehicles in diverse scenarios remains a challenge, even with the advancements in ITS. Factors such as vehicle morphology, design, road conditions, structural details, and climatic variables provide a significant part in the detection. To address this, our study introduces an advanced YOLOv8n model, specifically the YOLOv8n-CGW, which is built upon pre-trained deep learning frameworks. This model is meticulously tailored to enhance the detection capabilities for multi-oriented vehicles. Comprehensive evaluations on esteemed datasets like MtV, MERGED, Custom dataset, DAWN, WEDGE, and UA-DETRAC underscore the superiority of our approach over existing models. Notably, our YOLOv8n-CGW model achieves a remarkable mAP of 83.3% and boasts a swift inference time of 0.0019s, setting a new benchmark in the domain. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

MOCBOA:Multi-Objective Chef-Based Optimization Algorithm Using Hybrid Dominance Relations for Solving engineering Design Problems

引用

computer Modeling in engineering & sciences 2025年第4期143卷 967-1008页

作者： Nour Elhouda Chalabi Abdelouahab Attia Abdulaziz S.Almazyad Ali Wagdy Mohamed Frank Werner Pradeep Jangir Mohammad Shokouhifar Computer Science Department University of M’silaIchebiliaM’sila28000Algeria Computer ScienceDepartment Mohamed El Bachir El IbrahimiUniversity of Bordj BouArreridjBordj BouArreridj34000Algeria Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Faculty of Mathematics Otto-von-Guericke UniversityMagdeburg39016Germany University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Electrical and Computer Engineering Shahid Beheshti UniversityTehran14399Iran DTU AI and Data Science Hub(DAIDASH) Duy Tan UniversityDa Nang550000Vietnam

Multi-objective optimization is critical for problem-solving in engineering,economics,and *** study introduces the Multi-Objective Chef-Based Optimization Algorithm(MOCBOA),an upgraded version of the Chef-Based Optimization Algorithm(CBOA)that addresses distinct *** approach is unique in systematically examining four dominance relations—Pareto,Epsilon,Cone-epsilon,and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto *** comparison investigation,which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering,mechanical design,and power systems,reveals that the dominance approach used has a considerable impact on the key optimization measures such as the hypervolume *** paper provides a solid foundation for determining themost effective dominance approach and significant insights for both theoretical research and practical applications in multi-objective optimization.

关键词： Multi-objective optimization chef-based optimization algorithm(CBOA) pareto dominance epsilon dominance cone-epsilon dominance strengthened dominance

来源：评论

学校读者我要写书评

暂无评论

Virtual Twin Analytics: Advancing IoT Security through AI-Powered Software Informatics 1

Virtual Twin Analytics: Advancing IoT Security through AI-Po...

引用

1st International Conference on Software, Systems and Information Technology, SSITCON 2024

作者： Nanthini, S. Jain, Upma Arora, Renuka Bhatia, Rishu Sutaria, Kruti Patil, Harshal Saveetha School of Engineering Department of Computer Science and Engineering Chennai India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Jagannath University Department of Computer Science and Engineering Haryana India Ganga Institute of Technology and Management Department of Electronics and Communication Engineering Haryana India Parul Institute of Engineering and Technology Faculty of Engineering and Technology Gujarat India School of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798350352931

The Internet has grown in importance and impact over the years, causing people to become more reliant on it. The Internet has evolved into a major vector for cybercrime because to its ever-increasing user base. Over the last decade, the number of these computing systems - including desktops, laptops, smartphones, and the Internet of Things (IoT) - has skyrocketed. Among them, cell phones are practically integral to modern life. The popularity of web-based assaults has skyrocketed with the exponential growth in the number of individuals using the Internet. These web-based assaults are increasingly being combatted by security corporations. Unfortunately, new forms of these assaults are appearing all the time, making it hard for older security measures to stay up. Artificial intelligence (AI) is a source of optimism in the current cybersecurity landscape, offering a potential solution to the ever-changing digital dangers. The fast development of AI over the last decade has given rise to this optimism, because it is now impacting the expansion of every industry. With AI bringing so many advantages in every field, online security is one sector that just cannot afford to ignore it. This planned effort's work represents an advance in that direction. Critical online security issues have been the focus of this proposed work's study, which aims to address these issues using AI. Web security issues for desktop and mobile devices have been addressed in the proposed work. The planned work's contributions to online security are as follows: The 'MalCrawler' web crawler is a targeted tool for finding and exploring the web. This crawler makes it easy to gather websites, particularly ones that are harmful. It does a better job of collecting dangerous websites than a typical crawler. Additionally, it is built to circumvent the evasion strategies used by rogue websites. The crawler's ability to gather webpages - particularly dangerous ones - in order to provide datasets for ML-based an

关键词： Web crawler

来源：评论

学校读者我要写书评

暂无评论

High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

引用

Tsinghua science and Technology 2024年第4期29卷 1118-1137页

作者： Azam Fazel-Najafabadi Mahdi Abbasi Hani H.Attar Ayman Amer Amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster

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：