检索结果-内蒙古大学图书馆

Pacific Rim International Symposium on Dependable Computing

作者： Jinwoo Kim Jaehyun Nam School of Software Kwangwoon University Department of Computer Engineering Dankook University

Network virtualization (NV) has been widely used today in data centers to meet the multi-tenancy requirement-a key to achieving Infrastructure as a Service (IaaS) in a modern cloud environment. However, even though NV is a popular solution employed by network operators, we argue that most solutions still have challenges in terms of (i) configuration, (ii) management, and (iii) security; all of which hinder the deployment of secure and practical virtual networks that tenants wish to construct. To bridge the gaps, we propose LinkWire, a new NV system that produces secure and reconfigurable virtual networks. For this, LinkWire leverages extended Berkeley Packet Filter (eBPF), the recently-adopted in-kernel programmable networking technology. We also illustrate several use cases to show how our system brings benefits.

关键词： Data centers Cloud computing Buildings Security Virtualization System analysis and design

来源：评论

学校读者我要写书评

暂无评论

An Online Integrated Development Environment for Automated programming Assessment Systems

arXiv

引用

arXiv 2025年

作者： Frankford, Eduard Crazzolara, Daniel Vierhauser, Michael Meißner, Niklas Krusche, Stephan Breu, Ruth University of Innsbruck Department of Computer Science Austria University of Stuttgart Institute of Software Engineering Germany Technical University of Munich School of Computation Information and Technology Germany

The increasing demand for programmers has led to a surge in participants in programming courses, making it increasingly challenging for instructors to assess student code manually. As a result, automated programming assessment systems (APASs) have been developed to streamline this process. These APASs support lecturers by managing and evaluating student programming exercises at scale. However, these tools often do not provide feature-rich online editors compared to their traditional integrated development environments (IDEs) counterparts. This absence of key features, such as syntax highlighting and autocompletion, can negatively impact the learning experience, as these tools are crucial for effective coding practice. To address this gap, this research contributes to the field of programming education by extracting and defining requirements for an online IDE in an educational context and presenting a prototypical implementation of an open-source solution for a scalable and secure online IDE. The usability of the new online IDE was assessed using the Technology Acceptance Model (TAM), gathering feedback from 27 first-year students through a structured survey. In addition to these qualitative insights, quantitative measures such as memory (RAM) usage were evaluated to determine the efficiency and scalability of the tool under varying usage conditions. © 2025, CC BY-NC-ND.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units 39

HiPoser: 3D Human Pose Estimation with Hierarchical Shared L...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Liao, Guorui Zheng, Chunyuan Cheng, Li Xie, Haoyu Huang, Shanshan Liao, Jun Li, Haoxuan Liu, Li School of Big Data & Software Engineering Chongqing University China School of Mathematical Sciences Peking University China Department of Electrical and Computer Engineering University of Alberta Canada Center for Data Science Peking University China

ISBN: (纸本)157735897X

This paper considers the challenging problem of 3D Human Pose Estimation (HPE) from a sparse set of Inertial Measurement Units (IMUs). Existing efforts typically reconstruct a pose sequence by either directly tackling whole-body motions or focusing on distinctive spatio-temporal features of local body parts. Unfortunately, these methods ignore existing interdependent motor synergies amongst body parts, which may lead to pose estimation with ambiguous local parts. This observation motivates us to propose a hierarchical learning-based approach, HiPoser, which utilizes a hierarchical shared structure using Mamba blocks as the backbone to focus on the following estimation tasks, involving: 1) torso pose, 2) lower limbs pose, 3) upper limbs pose, and finally 4) global translation. These tasks selectively incorporate body motion states and are to be carried out sequentially in reconstructing part-based poses, which are amalgamated to estimate the final full-body pose with the global translation that satisfies inter-part consistencies. Our hierarchical structure allows HiPoser the flexibility in prioritizing different aspects of pose estimation, to emphasize more on detail or stability. Empirical evaluations over three benchmark datasets demonstrate the superiority of HiPoser over existing state-of-the-art models, suggesting that analyzing the synergistic movement of body parts is indeed important for advancing IMU-based 3D HPE. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Metric system

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a Web-Based Application for Managing Agricultural Health Products

Design and Implementation of a Web-Based Application for Man...

引用

International Conference on Emerging Trends in Networks and computer Communications (ETNCC)

作者： Olugbenga O. Oluwagbemi Emebo Onyeka Ikashi S. Ishieka Anna Wieclaw Ambrose A. Azeta Department of Computer Science Middlesex University London United Kingdom Department of Computer Science Virginia Tech University Blacksburg United States of America Department of Software Engineering Namibia University of Science and Technology Windhoek Namibia

ISBN: (数字)9798350353266

ISBN: (纸本)9798350353273

Caring for the health of food crops and plants can help boost food production and eradicate hunger according to the second United Nations (UN) Sustainable Development Goal (SDG). The procurement of agricultural health products such as fertilizers, fungicides, pesticides, and herbicides are a major problem for an average Nigerian farmer. This results in low crop yield and negatively impacts on food production which eventually causes hunger in the land. Existing methods of procuring these health products have majorly been through offline platforms such as agricultural stores and other relevant stores. This has its disadvantages such as inaccessible roads to stores where such products can be obtained, varying prices, health products out of stock, ignorance in the application of such products. These barriers deter farmers from procuring these health products. In this paper, a survey was conducted on the needs and problems of farmers. The results of the survey informed the design and implementation of an agricultural health Informatics web application for health product management for food crops. The application was designed using unified modelling language class diagram and implemented using Python. SQLite3 serves as the backend database. The agricultural informatics solution will help farmers in Nigeria to easily procure health products for food crops and get the products delivered without stress and worry when fully deployed. This will boost food production, thus eradicating hunger; it will also help in exporting food crops to other countries.

关键词： Procurement Surveys Food manufacturing Roads Unified modeling language Transforms Pesticides Bioinformatics Sustainable development Stress

来源：评论

学校读者我要写书评

暂无评论

A Robust Methodology for Fruit Quality Prediction and Estimation Using Intelligent Learning Based Image Processing Logic

A Robust Methodology for Fruit Quality Prediction and Estima...

引用

Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES), International Conference on

作者： Malathi K Vunnava Dinesh Babu M. Ramkumar M. Ayyadurai Vivek K Hamzeh J Aljawawdeh Department of CSE Saveetha School of Engineering Saveetha Institute of Science and Technology (SIMATS) Saveetha University Chennai Department of CSE RV Institute of Technology Guntur Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai Chennai Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur Department of software engineering Faculty of information technology Zarqa University Zarqa Jordan University of Business and Technology Jeddah Saudi Arabia

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Fruit quality prediction plays a vital role in agricultural and food industries, ensuring that only high-quality produce reaches the consumer. Traditional methods of assessing fruit quality rely on manual inspection, which is both time-consuming and prone to human error. This paper presents a robust methodology for fruit quality prediction and estimation, utilizing a hybrid deep learning model that integrates DenseN et for feature extraction with LightGBM for efficient classification. The proposed model is designed to automate the process of fruit quality assessment by analyzing key attributes such as color, texture, and shape from high-resolution fruit images. The Fruit360 dataset was used for training and testing, with images classified into categories such as fresh, ripe, overripe, and damaged. A comprehensive comparison with nine existing models, including SVM, Random Forest, and XGBoost, was conducted using performance metrics such as accuracy, precision, recall, and Fl-score. The proposed model achieved an accuracy of 96.78%, significantly outperforming all other models. Furthermore, the model's precision and recall reached 95.33% and 95.67%, respectively, demonstrating its reliability in distinguishing high-quality fruits from low-quality ones.

关键词： Training Support vector machines Accuracy Shape Computational modeling Estimation Predictive models Feature extraction Reliability Testing

来源：评论

学校读者我要写书评

暂无评论

A Lightweight VK-Net Based on Motion Profiles for Hazardous Driving Scenario Identification 23

A Lightweight VK-Net Based on Motion Profiles for Hazardous ...

引用

23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Gao, Zhen Xu, Jingning Zheng, Jiang Yu Fan, Hongfei Yu, Rongjie Zong, Jiaqi Li, Xinyi School of Software Engineering Tongji University Shanghai China Indiana University-Purdue University Department of Computer Science Indianapolis United States Jiangsu China Tongji University Key Laboratory of Road and Traffic Engineering of the Ministry of Education Shanghai China College of Transportation Engineering Tongji University Shanghai China

ISBN: (纸本)9781665494571

Hazardous driving scenarios are critical for the development and testing of highly autonomous vehicles. Recent studies have proposed new approaches for extracting hazardous scenarios from driving videos, which greatly improve the detection accuracy compared with traditional approaches that extract information from structured kinematic data. However, direct processing on driving videos is costly, and the videos need to be uploaded and processed in a centralized manner. In this study, we propose a novel approach for reducing the cost of video analysis while maintaining high accuracy in hazardous scenario identification. Firstly, the videos are significantly compressed into motion profile images that contain motion trajectories of objects. Secondly, a lightweight CNN with attention mechanism has been designed to extract risky trajectory features of the conflicting traffic objects. Furthermore, data augmentation has been applied to increase the generalizability of the model. The proposed approach achieves significantly lightweight network size, and meanwhile, experimental results have demonstrated that the approach achieves high accuracy with sensitivity 0.95, specificity 0.85 and AUC 0.95, which outperforms state-of-the-art hazardous scenario identification approaches. The efficient execution of identification implies that it is suitable to be distributed and deployed at each vehicle, and consequently, videos could be processed via edge computing, which would improve the diversity of hazardous scenarios and the efficiency of scenario collection for further research work. © 2021 IEEE.

关键词： Sensitivity Image coding Smart cities Kinematics Feature extraction Trajectory Data mining

来源：评论

学校读者我要写书评

暂无评论

Analyze, Debug, Optimize: Real-Time Tracing for Perception and Mapping Systems in ROS 2

arXiv

引用

arXiv 2022年

作者： Lajoie, Pierre-Yves Bédard, Christophe Beltrame, Giovanni Department of Computer and Software Engineering Polytechnique Montréal Montreal Canada

Perception and mapping systems are among the most computationally, memory, and bandwidth intensive software components in robotics. Therefore, analysis, debugging, and optimization are crucial to improve perception systems performance in real-time applications. However, standard approaches often depict a partial picture of the actual performance. Fortunately, instrumentation and tracing offer a great opportunity for detailed performance analysis of real-time systems. In this paper, we show how our novel open-source tracing tools and techniques for ROS 2 enable us to identify delays, bottlenecks and critical paths inside centralized, or distributed, perception and mapping systems. Copyright © 2022, The Authors. All rights reserved.

关键词： Real time systems

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Approach to Predict SGPA and CGPA

Machine Learning Approach to Predict SGPA and CGPA

引用

2021 International Conference on Artificial Intelligence and computer Science Technology, ICAICST 2021

作者： Saifuzzaman, Mohd. Parvin, Masuma Jahan, Israt Moon, Nazmun Nessa Narin Nur, Fernaz Shetu, Syeda Farjana Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh Notre Dame University Department of Computer Science and Engineering Dhaka Bangladesh BJIT Limited Software Quality Assurance Department Dhaka Bangladesh

ISBN: (纸本)9781665424042

The prediction of SGPA and CGPA is beneficial to university students. Students will easily get an estimate of their final outcome from this project. As a result, the students will be able to brace themselves for a successful outcome. Students pass the day by participating in a variety of events. Students use social media sites such as Facebook, Instagram, and Twitter. They engage in various hobbies such as playing mobile games, listening to music, among others. As a result, they were able to move several times with these tasks. As a result, if a student spends so much time doing any of those things, she will not be able to achieve a successful grade because of the experiment;students can develop a research routine or guideline that they can apply to their other tasks. Additionally, students' behaviors will forecast their outcomes. The Authors will now see machine learning in Python being used all over the place. After that, The Authors created a smart SGPA and CGPA prediction project, as well as the results on students. The findings are predicted using the Nave Byes algorithm. The Nave Byes algorithm is a simple but effective prediction algorithm. It is a machine learning algorithm as well. As a result, students will be given an estimate of their final exam scores. They can prepare them to make a good result by following the routine of the SGPA CGPA prediction project. © 2021 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Image Captioning Using Novel Multimodal Feature Fusion

SSRN

引用

SSRN 2024年

作者： Zahra, Sabih Iqbal, Muhammad Ur Rehman, Hafeez Nawaz, Shoaib Institute of Computer Science Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan64200 Pakistan Institute of Computer & Software Engineering Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan64200 Pakistan Islamabad44000 Pakistan Department of Computer Science University of South Asia Lahore Pakistan

Image captioning is a challenging task that involves generating natural language descriptions for images. In this research, we propose a novel image captioning model that combines Convolutional Neural Networks (CNNs) for image feature extraction with a Transformer-based text generation component. The objective is to seamlessly integrate visual and textual information to produce coherent and contextually relevant captions for images. The methodology consists of two key components: image feature extraction and Transformer-based text generation. Image feature extraction is achieved using pre-trained CNN models, namely VGG16 and ResNet50. The extracted features are combined into a single feature vector and then processed to reduce dimensionality. For text generation, a Transformer model is employed, specifically "bert-base-uncased" from the Hugging Face Transformers library. It processes tokenized captions using input sequences and attention masks, producing contextual representations of the captions. The textual embeddings are merged with the processed image features, enabling the model to fuse visual and textual context. Caption generation involves an LSTM layer for sequential word generation and a dense layer with a SoftMax activation to predict the next word in the caption. The model is trained using categorical cross-entropy loss and Adam optimization. The model's performance is evaluated using the BLEU-1 and BLEU-2 scores on a validation dataset. Our results demonstrate the effectiveness of the proposed architecture in generating captions that are both linguistically accurate and contextually relevant. The combination of CNN-based image feature extraction and Transformer-based text generation in this image captioning model leverages the strengths of computer vision and natural language processing techniques, offering a promising approach for generating high-quality image captions. © 2024, The Authors. All rights reserved.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Serverless software engineering – and How to Get There. 1

引用

29th European Systems, software and Services Process Improvement, EuroSPI 2022

作者： McAleese, Stephen McLaughlin, Jordan Conway Detyna, Filip Murashev, Andrey Yilmaz, Murat Clarke, Paul M. School of Computing Dublin City University Dublin Ireland Department of Computer Engineering Gazi University Ankara Turkey Lero The Science Foundation Ireland Research Center for Software Dublin Ireland

ISBN: (数字)9783031155598

ISBN: (纸本)9783031155581

Serverless computing is on the rise but developing software to exploit this space involves a deep rethink of software architecture, deployment, and operation (perhaps also, software development processes and team structures). Central to this revolution, we find a compelling argument for distributed, services-based software architectures. But converting a large, established monolith architecture system to microservices is non-trivial and fraught with both cost and risk. For the many firms with established software systems, this architectural system conversion might be considered the first stop-off on the journey to serverless computing. In tandem, software deployment and production monitoring also require reinvention. The focus of this paper involves an examination of the advantages of microservices architectures, include techniques for migrating from monolith architectures. Through application of a Multivocal Literature Review (MLR), we find that migrating from a monolith architecture to a microservices architecture is risky and non-trivial, but that there are techniques that can be employed to support the transition. We find also that monoliths have their advantages which might be overlooked to some extent in the race to serverless computing. © 2022, Springer Nature Switzerland AG.

关键词： software architecture

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：