检索结果-内蒙古大学图书馆

Proceedings of the 29th Australasian Computer Science Conference - Volume 48

作者： Audun Jøsang Ross Hayward Simon Pope School of Software Engineering and Data Communications Queensland University of Technology Brisbane Australia CRC for Enterprise Distributed Systems Technology (DSTC Pty Ltd) The University of Queensland Brisbane Australia

ISBN: (纸本)9781920682309

Trust networks consist of transitive trust relationships between people, organisations and software agents connected through a medium for communication and interaction. By formalising trust relationships, e.g. as reputation scores or as subjective trust measures, trust between parties within the community can be derived by analysing the trust paths linking the parties together. This article describes a method for trust network analysis using subjective logic (TNA-SL). It provides a simple notation for expressing transitive trust relationships, and defines a method for simplifying complex trust networks so that they can be expressed in a concise form and be computationally analysed. Trust measures are expressed as beliefs, and subjective logic is used to compute trust between arbitrary parties in the network. We show that TNA-SL is efficient, and illustrate possible applications with examples.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Topic-oriented mining and reasoning

Topic-oriented mining and reasoning

引用

Proceedings of the International Conference on Active Media Technology, AMT

作者： Y. Li N. Zhong Y.Y. Yao School of Software Engineering and Data Communications Queensland University of Technology Brisbane QLD Australia Department of Systems and Information Engineering Maebashi Institute of Technology Japan Department of Computer Science University of Regina Canada

The discovery of the association between terms and a specified topic is a difficult task. A new data mining technique, topic-oriented mining and reasoning, is presented for this task. The technique consists of two threads: pattern mining and pattern reasoning. Pattern mining means the automatic discovery of interesting user topic models. A novel topic structure is presented for this thread. Pattern reasoning means the utilization and maintenance of the interesting user topic models to determine if an input data is relevant to the specified topic. The innovation for this thread is the use of meta-knowledge for the discovered knowledge. In this way the system can trace errors to update inadequate subtopics in the user topic model. The experimental results show that all objectives we expect for the topic-oriented model are achievable.

关键词： data mining Yarn Technological innovation Web mining Web pages Clustering methods software engineering data communication Australia Error correction

来源：评论

学校读者我要写书评

暂无评论

Comparing XML-IR query formation interfaces

Proceedings of the Eleventh Australasian Document Computing ...

引用

Proceedings of the Eleventh Australasian Document Computing Symposium, ACDS 2006 2006年

作者： Woodley, Alan Geva, Shlomo Edwards, Sylvia Lauretta School of Software Engineering and Data Communications Faculty of Information Technology Queensland University of Technology QLD 4000 Australia School of Information Systems Faculty of Information Technology Queensland University of Technology QLD 4000 Australia

XML information retrieval (XML-IR) systems differ from traditional information retrieval systems by using structure of XML documents to retrieve more specific units of information than the documents themselves. Users interact with XML-IR systems via structured queries that express their content and structural requirements. Historically, it has been common belief within the XML-IR community that structured queries will perform better than traditional keyword-only queries. However, recent system-orientated analysis has show that this assumption may be incorrect when system performance is averaged over a set of queries. Here, we test this assumption with users via a simulated work task experiment. We compare a keyword only interface with two user friendly XML-IR interfaces: NLPX, a natural language interface and Bricks, a query-bytemplate interface. This is the first time that a XML-IR natural language interface has been tested in user experiments. We compare the retrieval performance of all three interfaces and the usability of the two structured interfaces. Our results correspond to those of the system-orientated evaluation and indicate that structured queries do not aid retrieval performance. They also show that in terms of retrieval performance and usability the structured interfaces are comparable.

关键词： XML

来源：评论

学校读者我要写书评

暂无评论

What types of events provide the strongest evidence that the stock market is affected by company specific news?

Conferences in Research and Practice in Information Technolo...

引用

Conferences in Research and Practice in Information Technology Series 2006年 61卷 145-153页

作者： Robertson, Calum Geva, Shlomo Wolff, Rodney School of Software Engineering and Data Communications Faculty of Information Technology Queensland University of Technology Level 7 S Block 2 George Street Brisbane QLD 4000 Australia School of Economics and Finance Faculty of Business Queensland University of Technology Brisbane QLD 4000 Australia

The efficient market hypothesis states that an efficient market immediately incorporates all available information into the price of the traded entity. It is well established that the stock market is not an efficient market as it consists of numerous traders with differing strategies and interpretations of information. However there is substantial evidence to suggest that the stock market does incorporate new information into prices. Unfortunately little research has focussed on the high frequency effect of real time news, across a broad base of assets. This paper investigates how the US, UK, and Australian markets incorporate all real time news, not just Press Announcements, Annual Reports, etc. We find that there is strong evidence to suggest that the markets do incorporate news quickly.

关键词： Financial markets

来源：评论

学校读者我要写书评

暂无评论

Queuing Packets in Communication Networks for Networked Control Systems

Queuing Packets in Communication Networks for Networked Cont...

引用

World Congress on Intelligent Control and Automation (WCICA)

作者： Yu-Chu Tian D. Levy M.O. Tade Tianlong Gu C. Fidge School of Software Engineering and Data Communications Queensland University of Technology Brisbane QLD Australia Department of Electrical and Information Engineering University of Sydney Sydney NSW Australia Department of Chemical Engineering Curtin University of Technology Perth WA Australia School of Computer Science Guilin University of Electronic and Technology Guilin China

We propose a queuing communication architecture for real-time applications of networked control systems (NCSs). Simple strategies are developed to deal with packet dropouts. Typical scenarios are modelled, simulated, and analysed to demonstrate how a TCP/IP based NCS is configured for realtime control of a middle-scale process or multiple small-scale processes

关键词： Intelligent networks Communication networks Networked control systems Communication system control Control systems Electrical equipment industry Industrial control Process control Real time systems TCPIP

来源：评论

学校读者我要写书评

暂无评论

Weighted Linear Multiple Kernel Learning for Saliency Detection 2nd

Weighted Linear Multiple Kernel Learning for Saliency Detect...

引用

2nd EAI International Conference on Robotic Sensor Networks, ROSENET 2018

作者： Zhou, Quan Wu, Jinwen Fan, Yawen Zhang, Suofei Wu, Xiaofu Zheng, Baoyu Jin, Xin Lu, Huimin Latecki, Longin Jan National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China College of Information Engineering China University of Geosciences Wuhan China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China National Engineering Research Center of Communications and Networking Nanjing University of Posts and Telecommunications Nanjing China Department of Cyber Security Beijing Electronic Science and Technology Institute Beijing China CETC Big Data Research Institute Co. Ltd. Guizhou Guiyang China Department of Mechanical and Control Engineering Kyushu Institute of Technology Kitakyushu Japan Department of Computer and Information Sciences Temple University PhiladelphiaPA United States

ISBN: (纸本)9783030177621

This paper presents a novel saliency detection method based on weighted linear multiple kernel learning (WLMKL), which is able to adaptively combine different contrast measurements in a supervised manner. Three commonly used bottom-up visual saliency operations are first introduced, including corner-surround contrast (CSC), center-surround contrast (CESC), and global contrast (GC). Then these contrast measures are fed into our WLMKL framework to produce the final saliency map. We show that the assigned weights for each contrast feature maps are always normalized in our WLMKL formulation. In addition, the proposed approach benefits from the advantages of the contribution of each individual contrast operation, and thus produces more robust and accurate saliency maps. The extensive experimental results show the effectiveness of the proposed model, and demonstrate the combination is superior to individual subcomponent. © 2020, Springer Science and Business Media Deutschland GmbH. All rights reserved.

关键词： Center-surround contrast Corner-surround contrast Global contrast Multiple kernel learning Saliency detection

来源：评论

学校读者我要写书评

暂无评论

Prioritizing Test Cases Through Dual-Uncertainty Evaluating for Road Disease Detection System

Prioritizing Test Cases Through Dual-Uncertainty Evaluating ...

引用

Asia-Pacific Conference on software engineering

作者： Chenxu Niu Huijun Liu Ao Li Tianhao Xiao Zhimin Ruan Ling Xu Yongxin Ge College of Computer Science Chongqing University Chongqing China School of Big Data & Software Engineering Chongqing University Chongqing China China Merchants Chongqing Communications Technology Research&Design Institute Co. Ltd. Chongqing China

ISBN: (数字)9798331534011

ISBN: (纸本)9798331534028

Road damage detection system based on deep learning models has been extensively researched, capable of intelligently detecting damages in roads. However, to ensure reliability, a large number of images usually need to be collected and annotated to test the model. Collecting images is often a straightforward work, but annotating them is both time-consuming and costly. To minimize annotation costs during the testing phase, we can evaluate images using Test Prioritization method to select more meaningful samples for system testing. Yet, most mainstream work currently only evaluates cases based on classification result, neglecting the impact of localization. At the same time, these methods do not provide higher evaluation results to complex images that may detect errors or images where targets cannot be detected at all. To address these issues, we propose a new Test Prioritization tool, Dual-u, to evaluate road damage cases. It consists of two components: (1) Localization Uncertainty Evaluation, which evaluates the localization of damages while considering the value of the image, ensuring that complex images and images where targets cannot be detected also have higher priority; (2) Classification Uncertainty Evaluation, which evaluates the classification of damages. To evaluate Dual-u, we conduct extensive experiments using two object detection model architectures on multiple road disease datasets, and the results demonstrate that Dual-u outperforms existing methods in evaluating cases. Moreover, Dual-u can also be used to improve the accuracy and robustness of road disease detection models.

关键词： Location awareness Deep learning System testing Uncertainty Costs Roads Object detection Robustness Diseases software engineering

来源：评论

学校读者我要写书评

暂无评论

Heterogeneous window Transformer for image denoising

arXiv

引用

arXiv 2024年

作者： Tian, Chunwei Zheng, Menghua Lin, Chia-Wen Li, Zhiwu Zhang, David School of Software Northwestern Polytechnical University National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China School of Software Northwestern Polytechnical University Xi’an710129 China Department of Electrical Engineering the Institute of Communications Engineering National Tsing Hua University 300 Taiwan School of Elector-Mechanical Engineering Xidian University Xi’an710071 China Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China

Deep networks can usually depend on extracting more structural information to improve denoising results. However, they may ignore correlation between pixels from an image to pursue better denoising performance. Window Transformer can use long- and short-distance modeling to interact pixels to address mentioned problem. To make a tradeoff between distance modeling and denoising time, we propose a heterogeneous window Transformer (HWformer) for image denoising. HWformer first designs heterogeneous global windows to capture global context information for improving denoising effects. To build a bridge between long and short-distance modeling, global windows are horizontally and vertically shifted to facilitate diversified information without increasing denoising time. To prevent the information loss phenomenon of independent patches, sparse idea is guided a feed-forward network to extract local information of neighboring patches. The proposed HWformer only takes 30% of popular Restormer in terms of denoising time. Its codes can be obtained at https://***/hellloxiaotian/HWformer. © 2024, CC BY-NC-ND.

关键词： Image denoising

来源：评论

学校读者我要写书评

暂无评论

Multi-operator network sharing for massive IoT

arXiv

引用

arXiv 2020年

作者： Xiao, Yong Krunz, Marwan Shu, Tao School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan430074 China Department of Electrical and Computer Engineering the University of Arizona TucsonAZ85721 United States School of Electrical and Data Engineering University of Technology Sydney UltimoNSW2007 Australia Department of Computer Science and Software Engineering Auburn University AuburnAL36849 United States

A recent study predicts that by 2020, up to 50 billion Internet-of-Things (IoT) devices will be connected to the Internet, straining the capacity of the wireless infrastructure, which has already been overloaded with data-hungry mobile applications. How to accommodate the demand for both massivescale IoT devices and high-speed cellular services in the physically limited spectrum without significantly increasing the operational and infrastructure costs is one of the main challenges for operators. In this article, we introduce a new multi-operator network sharing framework that supports the coexistence of IoT and high-speed cellular services. Our framework is based on the radio access network (RAN) sharing architecture recently introduced by 3GPP as a promising solution for operators to improve their resource utilization and reduce system roll-out cost. We evaluate the performance of our proposed framework using real base station location data in the city of Dublin collected from two major operators in Ireland. Numerical results show that our proposed framework can almost double the total number of supported IoT devices and simultaneously coexist with other cellular services. Copyright © 2020, The Authors. All rights reserved.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Brain tumor segmentation from multispectral MRIs using sparse representation classification and markov random field regularization

International Journal of Signal Processing, Image Processing...

引用

International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第9期8卷 229-238页

作者： Zhan, Tianming Gu, Shenghua Feng, Can Zhan, Yongzhao Wang, Jin School of Computer Science & communications Engineering Jiangsu University Zhenjiang China Jiangsu Key Laboratory of Big Data Analysis Technology Nanjing University of Information Science and Technology Nanjing China Center of software China North Industries Group Corporation Co. Ltd Nanjing China

Automatic brain tumor segmentation from multispectral magnetic resonance imaging (MRI) data is an important but a challenging task because of the high diversity in the appearance of tumor tissues among different patients and in many cases similarity with the normal tissues. In this paper, we propose a fully automatic technique for brain tumor segmentation from multispectral human brain MRIs. We first use the intensities of different patches in multispectral MRIs to represent the features of both normal and abnormal tissues and generate a dictionary for following tissue classification. Then, the sparse representation classification (SRC) is applied to classify the brain tumor and normal brain tissue in the whole image. At last, the Markov random field (MRF) regularization introduces spatial constraints to the SRC to take into account the pair-wise homogeneity in terms of classification labels and multispectral voxel intensities. Our method was evaluated on 20 multi-modality patient datasets with competitive segmentation results. ©, 2015 SERSC.

关键词： Magnetic resonance imaging

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：