检索结果-内蒙古大学图书馆

IEEE EUROCON-International Conference on Computer As A Tool

作者： Pajares, Gonzalo Guijarro, Maria Herrera, P. Javier Dept. Software Engineering and Artificial Intelligence Faculty of Informatics University Complutense of Madrid Madrid Spain Dept. Architecture of Computers and Automatic Faculty of Informatics University Complutense of Madrid Madrid Spain

ISBN: (纸本)9781424474868

We propose a procedure for applying a teaching-learning methodology, where the student's interest is considered a relevant issue. This procedure is based on: a) resources and material available;b) specific classroom, activities;c) external classroom activities, linking the learning process with the real world;d) continuous evaluation. The full process is evaluated from both points of view: teaching and learning. The results obtained allow us verifying the appropriateness of this strategy. © 2011 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Research on Handover Strategy Based on Greedy Algorithm in Vehicle Edge Computing 3rd

Research on Handover Strategy Based on Greedy Algorithm in V...

引用

3rd International Conference on Wireless Communications and Applications,ICWCA 2019

作者： Zhao, Hongzhuan Zheng, Lina Li, Wenyong Zhou, Dan Li, Wenhao School of Architecture and Transportation Engineering Guilin University of Electronic Technology GuilinGuangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology GuilinGuangxi541004 China

ISBN: (纸本)9789811556968

Due to the mobility of the vehicle, the communication link between the vehicle and the edge server changes dynamically in the vehicle edge computing, leading to the increase of task completion time, transmission energy consumption, and execution cost. In order to solve the problem, this paper studies the computational handover strategy in the vehicle edge computing environment. Considering the three indicators of completion time, transmission energy consumption, and execution cost, two handover strategies based on greedy weighted of simple additivity (SAW) algorithm and greedy expectation–maximization (EM) algorithm are proposed. The experimental results show that the two handoff strategies proposed in this paper can shorten the task completion time, reduce the energy consumption of vehicle transmission, and reduce the task execution cost. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

software Defect Prediction via Deep Belief Network

引用

Chinese Journal of Electronics 2019年第5期28卷 925-932页

作者： WEI Hua SHAN Chun HU Changzhen ZHANG Yu YU Xiao School of Computer Science and Technology Beijing Institute of Technology China Information Technology Security Evaluation Center Beijing Key Laboratory of Software Security Engineering Technology Beijing Institute of Technology School of Electrical and Information Engineering and Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture State Key Laboratory in China for Geomechanics and Deep Underground Engineering (Beijing) China University of Mining and Technology School of Computer Science and Technology Shandong University of Technology

Defect distribution prediction is a meaningful topic because software defects are the fundamental cause of many attacks and data loss. Building accurate prediction models can help developers find bugs and prioritize their testing efforts. Previous researches focus on exploring different machine learning algorithms based on the features that encode the characteristics of *** problem of data redundancy exists in software defect data set, which has great influence on prediction *** propose a defect distribution prediction model(Deep belief network prediction model, DBNPM), a system for detecting whether a program module contains defects. The key insight of DBNPM is Deep belief network(DBN)technology, which is an effective deep learning technique in image processing and natural language processing,whose features are similar to defects in source *** results show that DBNPM can efficiently extract and process the data characteristics of source program and the performance is better than Support vector machine(SVM), Locally linear embedding SVM(LLE-SVM), and Neighborhood preserving embedding SVM(NPE-SVM).

关键词： Defect prediction software security Deep belief network(DBN)

来源：评论

学校读者我要写书评

暂无评论

1st Workshop on VAriability for QUalIties in software architecture (VAQUITA): Workshop Introduction 15

1st Workshop on VAriability for QUalIties in SofTware Archit...

引用

Proceedings of the 2015 European Conference on software architecture Workshops

作者： Azadeh Alebrahim Stephan Faßbender Martin Filipczyk Michael Goedicke Maritta Heisel Uwe Zdun paluno - The Ruhr Institute for Software Technology Working group Software Engineering University of Duisburg-Essen Germany paluno - The Ruhr Institute for Software Technology Working group Specification of Software Systems University of Duisburg-Essen Germany Research Group Software Architecture University of Vienna

No abstract available.

ISBN: (纸本)9781450333931

No abstract available.

关键词： quality attributes software architecture variability

来源：评论

学校读者我要写书评

暂无评论

Research on the Application of Visualization Computer Technology in the Design of Architectural Decoration

Research on the Application of Visualization Computer Techno...

引用

2013 International Conference on Vehicle and Mechanical engineering and Information Technology, VMEIT 2013

作者： Zhou, Jun Zhou, Jian Ma, Xiao Li Architecture and Art College Shijiazhuang Tiedao University Shijiazhuang China Digital Media Department Hebei Software Institute Baoding China Microsoft IT Department Shijiazhuang Information Engineering Vocational College Shijiazhuang China

ISBN: (纸本)9783037858202

With the advances of computer science and technology, the visualization computer technology profoundly affects and changes people's understanding of the traditional visual language and promotes the continuous progress of the building decoration design. Its function of repeatedly revised not only can improve the quality of design but also can shorten the design cycle. The characteristics of building decoration design and the advantages of application of visual computer technology were first analyzed;based on analyses, the article explores the reliabilities of visualization computer technology in architectural decoration design. Linear model provides a theoretical basis and practical support for the development of architectural decoration design in a certain extent. © (2013) Trans Tech Publications, Switzerland.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

software Curriculum Transformation at the University Level 4

Software Curriculum Transformation at the University Level

引用

4th IEEE World engineering Education Conference, EDUNINE 2020

作者： Dorin, Michael Chong, Mario Machuca, Juan University of St. Thomas Graduate Programs in Software St. PaulMinnesota United States Universidad Del Pacífico Faculty of Engineering Lima Peru Universidad de Lima Faculty of Engineering and Architecture Lima Peru

ISBN: (数字)9781728166384

ISBN: (纸本)9781728166384

Many software-related degrees exist, and a diversity of programs makes it difficult for candidates to choose where they wish to study. Selecting the wrong program costs students time, money, and considerable effort. Though several institutions have created curriculum guidelines for data science related programs, an overall consensus on program content does not exist at either the undergraduate or graduate levels. This paper examines the most common course requirements, such as data mining, machine learning, mathematics, software engineering, data analysis, and data visualization. We then compare the requirement analysis against the specifics of data science related programs offered at the Universidad de Lima, the Universidad Pacifico, and the University of St. Thomas. The results show that all three universities have active programs worth consideration and give students a model of what to look for when selecting their programs. © 2020 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

An Exploratory Analysis of Effect of Adversarial Machine Learning Attack on IoT-enabled Industrial Control Systems

An Exploratory Analysis of Effect of Adversarial Machine Lea...

引用

2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Trivedi, Sandeep Anh Tran, Tien Faruqui, Nuruzzaman Hassan, Md. Maruf Deloitte Consulting Llp Houston United States Seoul National University Department of Naval Architecture and Ocean Engineering Seoul City Korea Republic of Daffodil International University Daffodil Smart City Department of Software Engineering Dhaka Bangladesh

ISBN: (纸本)9798350347050

Machine Learning (ML)-based Intrusion Detection Systems (IDS) is an effective technology to automatically detect cyber attacks in the Internet of Things (IoT) dependent Industrial Control Systems (ICS). It is faster, more efficient, and can detect attacks without human intervention. However, ML-based IDSs have introduced another security threat called Adversarial Machine Learning (AML). An AML attack may cause severe industrial infrastructural and production damage resulting in substantial financial loss. This paper presents an exploratory analysis of initiating an AML attack using adversarial samples created using a Fast Gradient Sign Method (FGSM). The research presented in this paper has been conducted from a dataset generated from a full-fledged singular module of a power distribution industry controlled by IoT-enabled ICSs. We explored the AML attack on Gradient Boosting (GB) and Iterative Dichotomiser 3 (ID3) model and discovered the average classification accuracy, precision, recall, and F1-scores are 87%, 88%, 87.5%, and 87%, respectively. The AML attack reduces the average precision, recall, and F1-score by 20.5%, 20.5%, and 22.5%, respectively, when 50% perturbations are added to 10% samples. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Automatic Adaptation of Reliability and Performance Trade-Offs in Service- and Cloud-Based Dynamic Routing architectures

Automatic Adaptation of Reliability and Performance Trade-Of...

引用

IEEE International Conference on software Quality, Reliability and Security (QRS)

作者： Amirali Amiri Uwe Zdun André van Hoorn Schahram Dustdar Software Architecture Research Group University of Vienna Software Engineering and Construction Methods University of Hamburg Distributed Systems Group Technical University of Vienna

ISBN: (纸本)9781665458146

Many different dynamic routing architectures are available, including sidecar-based routing, routing through a central entity such as an event store or gateway, or architectures with multiple routers. These architectures are currently based on vastly different implementation concepts, such as API Gateways, Message Brokers, or Service Proxies. We propose a new approach that abstracts all these architecture patterns using one Adaptive Dynamic Routers architecture. We hypothesize that a dynamic self-adaptation of the routing architecture is beneficial over any fixed architecture selections for reliability and performance trade-offs. That is, if encountered with traffic and load changes, our approach dynamically self-adapts between more central or distributed routing to optimize system reliability and performance. We evaluate our approach by analyzing our previously-measured data during an experiment of 1200 hours of runtime. Our extensive systematic evaluation with 1089 cases confirms that our hypothesis holds and our approach is beneficial in terms of reliability and performance. Moreover, we empirically validate our results on Google Cloud Platform infrastructure.

关键词： Systematics Runtime Conferences Computer architecture software quality Logic gates Routing

来源：评论

学校读者我要写书评

暂无评论

Individual Characteristics Analytical Models based on Deep Learning, Trajectory and Social Network Data

Individual Characteristics Analytical Models based on Deep L...

引用

作者： Dechang Wang Buyang Cao Zhenfang Chu School of Software Engineering Tongji University College of Architecture and Urban Planning Tongji University

The analysis of individual characteristics in this paper refers to analyze the individual characteristics in a certain field to draw the relevant conclusions such as classification, scoring and so on. The main purpose of this study is to apply deep learning, trajectory and social network data to enhance the process of individual characteristics analysis. We developed an algorithm for extracting features from trajectory data based on LSTM and an algorithm for retrieving features from social network data based on the network structural characteristics. A series of computational experiments were conducted by employing the features extracted by our algorithms. According the experimental results and the comparisons with some existing classification models, we can conclude that our approach can improve the accuracy of individual feature classification by 5% on average.

关键词： Deep Learning LSTM Social Network Ensemble Learning Classification

来源：评论

学校读者我要写书评

暂无评论

Prediction of Office Building Rental upon Spatiotemporal Data

Prediction of Office Building Rental upon Spatiotemporal Dat...

引用

作者： Zhihong Wang Buyang Cao School of Software Engineering Tongji University College of Architecture And Urban Planning Tongji University

This paper presents a study on effectively predicting office building rentals based on the surrounding spatiotemporal data. During the planning, development, and construction stages of an office building, the stakeholders of the building may have one question to be answered, i.e., what the potential value of the office building *** potential value of office buildings may be hard to be measured directly, however, it can be reflected in the rental after the office is put into operation. An accurate prediction of the office building rental will provide the solid base for the corresponding stakeholders to make business decisions. The rental of office buildings is affected by many factors, such as its location, floors, number of parking spots, the convenience of transportation, as well as the activities of the surrounding business. To support the rental prediction, we collect the datasets from different data sources in Shanghai. The linear regression, the decision tree, and the random forest models are employed in the computational experiments to predict the office building rentals and the most suitable prediction methodology for predicting the office building rental is suggested upon the experiments.

关键词： Commercial estate Prediction Regression model Machine learning Parameter optimization

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：