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Cluster Tree Based Hybrid Semantic Similarity Measure for Social Tagging Systems

Cluster Tree Based Hybrid Semantic Similarity Measure for So...

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The 2010 ieee international conference on progress in informatics and computing

作者： Changli Zhang School of Information Engineering Chang'an University Xi'an 710064,China Jinjin Zhang,Maode Yan School of Electronics & Control Engineering Chang'an University Xi'an 710064,China

As the social tagging systems becoming prevalent,it remains a critical question that how to make explicit the semantics for tags to fully facilitate Web2.0 *** paper establishes a cluster tree based semantic similarity measure for social tagging systems,combines it with traditional statistics based measures into a hybrid one,tailors the hybrid measure according to the effectiveness requirement of intelligent search application,and presents a case study using the empirical data retrieved from *** *** to the traditional statistics based measures,our hybrid measure is capable of evaluating similarities between random tags even not co-occurred,can better reflect the structural influence of the network of tag co-occurrence,and is feasible for applications like intelligent search in user-centric Web2.0 environment.

关键词： social tagging systems semantic similarity measure cluster tree folkosonomy small world intelligent search Web2.0

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Maintaining User Interface Integrity on Android

Maintaining User Interface Integrity on Android

引用

ieee Annual international Computer Software and Applications conference (COMPSAC)

作者： Abeer AlJarrah Mohamed Shehab College of Computing & Informatics University of North Carolina at Charlotte Charlotte North Carolina

The demand of having a multi-window and multitasking option in Android devices has been an emerging topic among Android users, especially with the trends toward larger hand-held screen sizes. One option to meet this demand, is to use floating windows. This feature enables users to perform more than one task at the same time while sharing the same screen. Device screens can be divided into multiple windows that can have different visual features in terms of size, location and transparency. While this feature addresses user complaints about Android on large screen devices, attention must be given to the security implications of such an option. In this work, we demonstrate how the current implementation of floating windows on Android can be abused to compromise user interface integrity through several attacks such as tapjacking, event eavesdropping and event hijacking. Although previous versions of Android have evolved to handle the issue of eventhijacking enabled by Toasts, recent versions fail to address security concerns related to floating windows. We propose and describe two approaches, an application level and a system level, to enable secure apps against possible malicious floating windows. The application level approach aims to detect existence and location of floating windows on top of an app. System level approach not only detects their existence, but also extends the system to include an event handler that notifies apps when floating windows are rendered over the apps' secure regions. We implemented our proposed approaches and performed experiments to evaluate their efficiency.

关键词： Androids Humanoid robots Context Smart phones Security Browsers Mobile communication

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Transformation from Data Flow Diagram to UML2.0 Activity Diagram

Transformation from Data Flow Diagram to UML2.0 Activity Dia...

引用

The 2010 ieee international conference on progress in informatics and computing

作者： Fanchao Meng,Dianhui Chu,Dechen Zhan School of Computer Science and Technology, Harbin Institute of Technology at Weihai Weihai,China

Model transformations are frequently applied in business process modeling to bridge between languages on a different level of abstraction and formality This paper proposes a model transformation from Data Flow Diagrams(DFD) which have been used widely in structure requirement analysis phase to UML Activity Diagrams(UML-AD) which have been used widely in various phases of Object Oriented Development ***, we analyze the elements in DFD and the elements in UML-AD that can be transformed from *** on the corresponding relationships between DFD and UML-AD,the transformation rules from DFD to UML-AD are ***,a case of textbook purchase and sale system is used to verify the feasibility and *** to the proposed method,the business process models that are written by DFD can be easily transformed into the business process modes that are written by UM-AD,which realizes the interoperability between DFD and UML.

关键词： Data Flow Diagram UML Activity Diagram model transforamtion

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Online Machine Learning for Big Data Analytics by Cognitive Robots

Online Machine Learning for Big Data Analytics by Cognitive ...

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2016 ieee international conference of Online Analysis and computing Science(ICOACS 2016)

作者： Yingxu Wang FICIC FWIF Information Systems Lab Stanford University Laboratory for Computational Intelligence Denotational Mathematicsand Software Science Dept.of Electrical and Computer EngineeringSchulich School of Engineering and Hotchkiss Brain InstituteUniversity of Calgary

It is recognized that both sources of and solutions to the big data challenges are human collective *** are an abstract representation of the quantity of realistic entities and perceived *** data play an indispensable role not only in a wide range of engineering applications,but also in the cognitive mechanisms of both humans and cognitive robots such as sensation,quantification,qualification,estimation,memory,and *** keynote lecture presents online big data analytic theories by machine learning as well as knowledge extraction by cognitive ***,information,knowledge,and intelligence are the four hierarchical layers of cognitive objects in the brain and cognitive systems from the bottom *** is discovered by the author that,although the cognitive unit of data is bit,that of knowledge is bir,i.e.,a binary relation.A resent finding towards big data science is that big data systems in nature are a recursive ndimensional typed hyperstructure(RNDTHS).This topological property of big data reveals that the mathematical foundation of big data science is underpinned by big data algebra(BDA),which is a denotational mathematical structure for efficiently dealing with the inherited complexities and unprecedented challenges in big data *** leads to a coherent theory for big data modeling,analyses,mining,information elicitation,knowledge extraction,and intelligent generation for cognitive *** experiments demonstrate that cognitive robots may autonomously transform big data in vast linguistic databases(corpuses) into sophistic knowledge bases by cognitive machine learning.

关键词： Big data big data science denotational mathematics mathematical models recursively hierarchical hyperstructures big data algebra cogniitve machine learning formal concepts knowledge extraction knowledge generation cognitive informatics cognitive computing computational intelligence applications

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Effects of Weighting Schemes on Retrieval Precision

Effects of Weighting Schemes on Retrieval Precision

引用

Symposium of Image, Signal Processing, and Artificial Vision (STSIVA)

作者： Fadi Yamout Youssef Mouallem Department of Computer Science International University of Beirut Beirut Lebanon

ISBN: (数字)9798350363203

ISBN: (纸本)9798350363210

Finding relevant information in a vast and growing amount of data has become significant since the arrival of the internet. An Information Retrieval System is described as searching and retrieving a list of documents, such as web pages or other items, in response to a user query. There are many weighting schemes, such as Boolean, Term Frequency or TF, and Term-Frequency-Inverse-Document-Frequency or TFIDF. In Boolean, a ‘1’ indicates the presence of a term in the document, whereas a ‘0’ indicates its absence. In TF, the term is represented by the number of occurrences in a document. TFIDF is the most popular one. It combines TF with an inverse document frequency IDF; IDF gives less weight to terms that frequently occur in many documents. With reference to the information retrieval system literature, TFIDF gives more accurate results on the computationally expensive expenses. Term Frequency is less expensive than TFIDF, and the least expensive one is the Boolean weighting scheme. In this paper, we investigated the effect of different weighting schemes and found out that, in many cases, Boolean and TF performed the same as TFIDF and, in a few cases, outperformed them. The experiments in this paper were conducted on many datasets of variant sizes and types. The dataset documents were indexed using TFIDF, TF, and Boolean. Then, using the queries that come with the dataset, we computed the precision and recall by comparing the results of different weighting schemes; the queries were also indexed using TFIDF, TF, and Boolean weighting schemes. The objective is to show that the use of the Boolean or TF weighting scheme, which is considered not computationally expensive, instead of TFIDF, which is regarded as very computationally expensive, does not significantly affect the results and, in a few cases, gives better results.

关键词： Accuracy Computational modeling Web pages Information retrieval informatics

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Face Image Illumination Quality Assessment for Surveillance Video Using KPLSR

Face Image Illumination Quality Assessment for Surveillance ...

引用

2016 ieee international conference on progress in informatics and computing

作者： Xiaochen Hu Li Zhuo Jing Zhang Xiaoguang Li Signal & Information Processing Laboratory Beijing University of Technology Collaborative Innovation Center of Electric Vehicles in Beijing

Illumination condition is one of the most important factors that affect the face recognition performance. Face image illumination quality assessment can predict the face recognition performance under various illumination conditions, which will improve the accuracy and efficiency of the face recognition system. However, the quality scores calculated by the existing methods are weakly correlated with the performance of face recognition. Face images with high scores often present bad recognition performance, while face images with low scores unexpectedly present good recognition performance. To predict the recognition performance more accurately, a kernel partial least squares regression(KPLSR) based face image illumination quality assessment method for surveillance video is proposed in this paper. The mapping relationship between illumination conditions and face recognition performance is modeled using KPLSR. Taken the fact that different regions of face image have different importance on face recognition, the features of luminance and contrast of sub-blocks are extracted to reflect the illumination conditions. Matching score of the face recognition system is calculated to measure the recognition performance. Experimental results show that, compared with the existing methods, the quality scores calculated by the proposed method are strong correlated with the recognition performance. The proposed method can also meet the requirements of real time processing.

关键词： face image illumination quality kernel partial least squares regression surveillance video real time

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Vehicle Classification for Traffic Surveillance Videos Based on Spatial Location Information and Sparse Representation-based Classifier

Vehicle Classification for Traffic Surveillance Videos Based...

引用

2016 ieee international conference on progress in informatics and computing

作者： Liying Jiang Li Zhuo Haixia Long Xiaochen Hu Jing Zhang Signal & Information Processing Laboratory Beijing University of Technology Collaborative Innovation Center of Electric Vehicles in Beijing

Vehicle classification plays an important part in Intelligent Transport System(ITS). However, the existing vehicle classification methods are not very robust to various changes such as lighting, weathers, noises, and the classification accuracy has been requiring to be improved. Sparse Representation-based Classifier(SRC) is not sensitive to the shortage and damage of data, the feature selection methods, is robust to lighting changes of the images, and can achieve excellent performance in multiclass classification problems. Therefore, this paper presents a new method based on spatial location information and SRC. Firstly, taken the specific characteristics of vehicles into consideration, the features of HOG(Histogram of Oriented Gradient) and HU moments are extracted to characterize the property of vehicles. In addition, the spatial location information is added to HU moment features in this paper to improve its ability to distinguish and describe vehicles. Then, vehicles are classified into six classes(large bus, car, motorcycle, minibus, truck and van) by SRC. The performance evaluation is carried out on the dataset which consists of 13300 vehicle images extracted from the real highway surveillance videos. The experimental results show that, using the proposed method, the time cost of classification can be speeded up by about 1.57 times and the average classification precision can achieve 96.53%, which is drastically improved by more than 2.7% compared to other existing methods.

关键词： Vehicle classification HOG feature HU moments Spatial location information SRC

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Mass Data Storage Platform for Smart Grid

Mass Data Storage Platform for Smart Grid

引用

2016 ieee international conference on progress in informatics and computing

作者： Huahui Lyu Ping Li Yuning Xiao Hongjie Qian Bin Sheng Ruimin Shen Information Department China Southern Power Grid Department of Mathematics and Information Technology The Education University of Hong Kong Department of Computer Science and Engineering Shanghai Jiao Tong University State Key Lab of Computer Science Institute of Software Chinese Academy of Sciences

With the continuous development of power systems, the scale of power grid is increasingly expanding, and the structure of it is becoming more and more complex. Traditional electrical network management cannot meet the current requirements. In this paper, we use load forecasting as a starting point, carrying on the exploration regarding heterogeneous multi-source data of the smart grid and doing research on shortterm load forecasting. In the process of building the application platform of smart grid, we propose some solutions to solve these problems. In the study of heterogeneous multi-source data fusion, we proposed a fusion method of grid data based on CIM/XML after comparing the current method and do numerical simulation on our application platform of smart grid to test its feasibility. At the same time, we also do a lot research on the current situation of load forecasting. After analyzing the advantage and disadvantage of some normal forecasting methods, for example, the peer-fold ratio method, the ration smoothing method, grey prediction and variation coefficient method, we developed two comprehensive approaches, the method of weighted mean and the ratio method based on grey prediction, which will increase the accuracy, general applicability and stability of load forecasting. Through these studies and efforts, we build a friendly and visually interactive application platform, which will lay the foundation of further development about the application platform of smart grid.

关键词： smart grid load forecasting data fusion CIM XML

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Perceptions and attitudes of clinical staff towards telemedicine acceptance in Saudi Arabia

Perceptions and attitudes of clinical staff towards telemedi...

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ACS/ieee international conference on Computer Systems and Applications

作者： Abdulellah Alaboudi Anthony Atkins Bernadette Sharp Mohammed Alzahrani Ahmed Balkhair Tamara Sunbul School of Computing Staffordshire University Stafford UK Alqwieiah Community College Shaqra University Alqwieiah Saudi Arabia College of Engineering at Al Leith Umm Al-Qura University AL Leith Saudi Arabia EHealth Strategy and Change Management Office Ministry of Health in Saudi Arabia Riyadh Saudi Arabia Health Informatics Department Johns Hopkins Aramco Healthcare Dhahran Saudi Arabia

Regardless of promised benefits of telemedicine and its potential technical superiority, its adoption is often cited as a failed project and the lack of understanding potential user acceptance is one of the most pervasive reasons leading to this failure. More than 40% of Information and Communications Technology (ICT) adoption projects have failed for this reason and any ICT system would not be effective if its potential user were averse to utilising its adoption. To the best of our knowledge, no comprehensive scientific study has investigated the perceptions and attitudes of clinical staff towards telemedicine acceptance and use in the Kingdom of Saudi Arabia (KSA) healthcare system at a national level. The objective of this novel research lies in addressing this gap and is conducted in collaboration with the Saudi Ministry of Health (MOH). The Unified Theory of Acceptance and Use of Technology (UTAUT) is used to underpin this research and a questionnaire to support the objective of this research was conducted in KSA to collect data from a random sample of different categories of clinical staff in KSA. The survey of 1,523 returned questionnaires were selected and the findings of this study show that 67.6% of clinical staff on average expect or extremely expect high performance from using telemedicine in KSA. Also 62.6% of clinical staff agree or extremely agree that the use of telemedicine in KSA will be compatible with culture and society. On the other hand, 38.0% of clinical staff agree or extremely agree that the use of telemedicine will not be compatible with their job role. Furthermore 40.6% of participants stated that using telemedicine would not be easy for clinical staff and 37.4% of them indicated that it will waste a lot of time and require a lot of technical and non-clinical administrative time to complete

关键词： Telemedicine Medical services Technological innovation Bibliographies Cultural differences Instruments Information and communication technology

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Internet of things using publish and subscribe method cloud-based application to NFT-based hydroponic system

Internet of things using publish and subscribe method cloud-...

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ieee international conference on System Engineering and Technology

作者： Muhammad Agus Triawan Hilwadi Hindersah Desta Yolanda Febrian Hadiatna School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9781509050901

The integration Internet of Things (IoT) generally identical with Cloud computing. IoT aims to connect the heterogeneous objects/devices with each other, in order to communicate or exchange data/information. Development of the Cloud IoT system, have challenges to achieve these objectives, such as middleware, interoperability and scalability of system. In this paper, we will discuss the solution of the challenges, by applying the publish and subscriber method, using MQTT protocol. This paper, proposed of architecture model design, which is implemented in the form of system topology. This topology apply to monitor and control the provision of nutrition hydroponics, accessible as a Cloud SaaS. From the test results, average node response time needed to connect and communicate with IoT Cloud system (online) is 7.21 seconds. The time required to declare offline state of a node is 21.55 seconds. The test results of Cloud IoT (broker), obtained that number of nodes for each level QoS, affecting resource usage of CPU and throughput. The highest resource usage of CPU is 19% of 2.0GHz and throughput TX/RX is 34.68KBps/49.4KBps. This result obtained from 1000 nodes scheme testing with 1 messages/node, by using simulation application, on QoS level 2. The average of minimum bandwidth used is ± 0.90Kbps by 1 publisher, to send 1 message with 115 Bytes of payload size, on each 3 levels of QoS MQTT, and approximately ± 0.04Kbps on subscriber to receive that message.

关键词： scalability IoT Cloud broker publish subscribe middleware interoperability MQTT

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