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检索条件"任意字段=14th Symposium on Large Data Analysis and Visualization"

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A Novel Verifiable and Dynamic Fuzzy Keyword Search Scheme over Encrypted data in Cloud Computing 15

A Novel Verifiable and Dynamic Fuzzy Keyword Search Scheme o...

引用

15th IEEE Int Conf on Trust, Security and Privacy in Comp and Commun / 10th IEEE Int Conf on Big data Science and Engineering / 14th IEEE Int symposium on Parallel and Distributed Proc with Applicat (IEEE Trustcom/BigdataSE/ISPA)

作者： Zhu, Xiaoyu Liu, Qin Wang, Guojun Cent South Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China Hunan Univ Sch Comp Sci & Elect Engn Guangzhou 510006 Guangdong Peoples R China Guangzhou Univ Sch Comp Sci & Educ Software Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9781509032051

In recent years, cloud computing becomes more and more popular. Users outsource large amount of encrypted documents to the cloud in order to avoid information leakage. Searchable encryption technique is a desirable service to enable users search on encrypted data. In most existing searchable encryption schemes, they only provide exact keyword search. Fuzzy keyword search improves the system usability because it allows users to make spelling errors or format inconsistencies. Besides, verifiable encryption schemes usually consider a semi-trusted server and verify the authenticity of the search results. However, the server may be malicious, which may modify/delete some encrypted files or forge erroneous results in order to save its storage space or computation ability. In this paper, we investigate the searchable encryption problem in the presence of a malicious server, the verifiable searchability is needed to provide users the ability to detect the potential misbehavior. We propose a verifiable and dynamic fuzzy keyword search (VDFS) scheme to offer secure fuzzy keyword search, update the outsourced document collection and verify the authenticity of the search result. Our scheme is proved universally composable (UC) security by rigorous security analysis.

关键词： Cloud computing Searchable encryption Malicious server Verifiable search Dynamic fuzzy search

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Enabling patient remote rehabilitation through motion monitoring and analysis

Enabling patient remote rehabilitation through motion monito...

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International symposium on Computational Intelligence and Informatics

作者： Miklos Kozlovszky John von Neumann Faculty of Informatics Obuda University Budapest Hungary

Accurate motion monitoring can provide detailed information through qualitative and quantitative analysis of patient movements in the field of rehabilitation and thus can become an effective tool set for treatment of motion problems. Normally patients are doing rehabilitation training programs under the guidance of their supervisor only during some small fragment (1-2 hours) of the day. Remote motion monitoring can enable skilled medical staff to monitor closely patient's training activities at home during the whole day, thus multi-part (morning, afternoon, evening) training sessions can be included easily into the daily life and in certain cases (e.g.: stroke rehabilitation) this can enhance the healing process significantly and can lead to better restoration results. Accurate movement/motion monitoring can enable medical experts to introduce individual (patient specific) rehabilitation programs, and assess the value of the training program at any time with high granularity level. the MOVANDIS framework is a novel, generic, vendor independent motion data collector and movement visualizer software solution. this paper focuses mainly its internal architecture, and its usage scenarios within the field of telerehabilitation.

关键词： Monitoring Training Sensors data visualization Hardware Software Biomedical monitoring

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Efficient and Realistic visualization of Cloth

Efficient and Realistic Visualization of Cloth

引用

14th Eurographics Workshop on Rendering Techniques, EGSR 2003

作者： Sattler, Mirko Sarlette, Ralf Klein, Reinhard Institute of Computer Science II University of Bonn Germany

ISBN: (纸本)3905673037

Efficient and realistic rendering of cloth is of great interest especially in the context of e-commerce. Aside from the simulation of cloth draping, the rendering has to provide the "look and feel" of the fabric itself. In this paper we present a novel interactive rendering algorithm to preserve this "look and feel" of different fabrics. this is done by using the bidirectional texture function (BTF) of the fabric, which is acquired from a rectangular probe and after synthesis, mapped onto the simulated geometry. Instead of fitting a special type of bidirectional reflection distribution function (BRDF) model to each texel of our BTF, we generate view-dependent texture-maps using a principal component analysis of the original data. these view-dependent texture maps are then illuminated and rendered using either point-light sources or high dynamic range environment maps by exploiting current graphics hardware. In both cases, self-shadowing caused by geometry is taken into account. For point light sources, we also present a novel method to generate smooth shadow boundaries on the geometry. Depending on the geometrical complexity and the sampling density of the environment map, the illumination can be changed interactively. To ensure interactive frame rates for denser samplings or more complex objects, we introduce a principal component based decomposition of the illumination of the geometry. the high quality of the results is demonstrated by several examples. the algorithm is also suitable for materials other than cloth, as far as these materials have a similar reflectance behavior. © the Eurographics Association 2003.

关键词： Distribution functions

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Exposing the Attraction of data- An Examination and Application of Teaching data visualization in Multimedia Learning Mode From theory to Practice

Exposing the Attraction of Data- An Examination and Applicat...

引用

IEEE International symposium on Information (IT) in Medicine and Education, ITME

作者： Yue Wang Mingyou Liu Yingxue Zhu Sitong Liu School of Biology and Engineering(Health Medicine Modern Industry College) Guizhou Medical University Guizhou China University of Nottingham Ningbo China

ISBN: (数字)9798350356670

ISBN: (纸本)9798350356687

With the advent of the big data era, data visualization technology has grown in significance and become an essential core technology in the fields of statistical analysis and decision support. However, the current approaches of teaching the data visualization course tend to downplay the significance of theoretical knowledge in favor of developing students' practical skills with various information visualization technologies. When students are faced with complex facts, this teaching style, which prioritizes practice over theory, may result in a lack of deep analytical skills and creative thinking. Meanwhile, in order to reveal the charm of data, the process of transforming data information into visual form can significantly improve the presentation effect of data, and observe and browse the data in an intuitive and interactive way, so that it is easier to find the hidden features, relationships, and patterns in the data, which can provide powerful support for data analysis and *** order to create a naturally occurring combination of knowledge and application and better prepare students for the difficulties of the big data era, teaching data visualization educational programs using a blended learning approach requires maintaining a balance between the two.

关键词： visualization Educational programs data analysis Statistical analysis data visualization Big data Hybrid learning Information technology

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Filter large-scale engine data using apache spark

Filter large-scale engine data using apache spark

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Donato Pirozzi Vittorio Scarano Steven Begg Guillaume De Sercey Andrew Fish Andrew Harvey Dipartimento di Informatica Università degli Studi di Salerno IT School of Computing Engineering and Mathematics University of Brighton UK

ISBN: (纸本)9781509028719

this paper introduces a minimum viable software product to filter large datasets of engine data recorded during laboratory experiments of combustion engines. the aim is to support analysts in the identification and analysis of specific physical phenomenon within hours of recorded engine experimental data. Specifically, the tool has been designed considering the use case of identifying Low Speed Pre-Ignition events. this work describes the tool's graphical user interface and its scalable architecture based on mainstream web and big-data technologies as well as the practical application to pre-ignition events identification. the paper provides details on the architecture's performance, providing evidence of its scalability by increasing the number of available computing workers.

关键词： Engines Combustion Graphical user interfaces data visualization Sparks Bars Industries

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A prediction method for multi-class systems based on limited data [clinical trials]

A prediction method for multi-class systems based on limited...

引用

Annual IEEE symposium on Computer-Based Medical Systems

作者： V.A. Kuznetsov G.D. Knott Laboratory Integrative and Medicine Biophysics National Institute of Child Health and Human Development Bethesda MD USA Civilized Software Inc. Silver Spring MD USA

In many clinical trials, the prediction of patient outcome following therapy requires the analysis of two or more small groups of responders having a large number of simultaneously measured covariates, some of whose values may be absent. Prediction of individual outcomes in these groups is a severe statistical problem. this has motivated us to develop a suitable approach for inference from such limited data. A new statistically-oriented prediction method, called optimized independent segment voting (OISV), is presented for constructing a class-membership prediction function for such data sets. this "voting" prediction function is constructed based on the most informative and robust discrete segments of all covariate ranges, which are thus discretized.

关键词： Prediction methods Voting Clinical trials Laboratories Biophysics Silver Springs Medical treatment Logistics Regression analysis

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Analyzing the relation between heart rate, problem behavior, and environmental events using data mining system LERS

Analyzing the relation between heart rate, problem behavior,...

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Annual IEEE symposium on Computer-Based Medical Systems

作者： R.L. Freeman J.W. Grzymala-Busse L.A. Riffel S.R. Schroeder Bureau of Child Research Institute for Life Span Studies University of Kansas Lawrence KS USA Department of Electrical Engineering and Computer Science University of Kansas Lawrence KS USA

the relation between physiological events, environmental factors and the occurrence of problem behavior in natural settings was analyzed using the data mining system LERS (Learning from Examples based on Rough Sets). Heart-rate data were linked to environmental and behavioral data coded from videotapes of one adult subject diagnosed with severe mental retardation and who engaged in problem behavior. the results of the analysis suggest that using data mining system LERS will be a valuable strategy for exploring large data sets that include heart rate, environmental and behavioral measures.

关键词： Heart rate data mining Environmental factors Pediatrics Computer science data analysis Rough sets Problem-solving Transmitters Belts

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ZO-AdaMU Optimizer: Adapting Perturbation by the Momentum and Uncertainty in Zeroth-Order Optimization 38

ZO-AdaMU Optimizer: Adapting Perturbation by the Momentum an...

引用

38th AAAI Conference on Artificial Intelligence (AAAI) / 36th Conference on Innovative Applications of Artificial Intelligence / 14th symposium on Educational Advances in Artificial Intelligence

作者： Jiang, Shuoran Chen, Qingcai Pan, Youcheng Xiang, Yang Lin, Yukang Wu, Xiangping Liu, Chuanyi Song, Xiaobao Harbin Inst Technol Shenzhen Shenzhen Peoples R China Peng Cheng Lab Shenzhen Peoples R China Harbin Inst Technol Shenzhen Inst Data Secur Shenzhen Peoples R China

ISBN: (纸本)1577358872

Lowering the memory requirement in full-parameter training on large models has become a hot research area. MeZO fine-tunes the large language models (LLMs) by just forward passes in a zeroth-order SGD optimizer (ZO-SGD), demonstrating excellent performance with the same GPU memory usage as inference. However, the simulated perturbation stochastic approximation for gradient estimate in MeZO leads to severe oscillations and incurs a substantial time overhead. Moreover, without momentum regularization, MeZO shows severe over-fitting problems. Lastly, the perturbation-irrelevant momentum on ZO-SGD does not improve the convergence rate. this study proposes ZO-AdaMU to resolve the above problems by adapting the simulated perturbation with momentum in its stochastic approximation. Unlike existing adaptive momentum methods, we relocate momentum on simulated perturbation in stochastic gradient approximation. Our convergence analysis and experiments prove this is a better way to improve convergence stability and rate in ZO-SGD. Extensive experiments demonstrate that ZO-AdaMU yields better generalization for LLMs fine-tuning across various NLP tasks than MeZO and its momentum variants.

关键词： Momentum

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A Visual Exploration Process for the analysis of Internet Routing data 03

A Visual Exploration Process for the Analysis of Internet Ro...

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Proceedings of the 14th IEEE visualization 2003 (VIS'03)

作者： Soon Tee Teoh Kwan-Liu Ma S. Felix Wu University of California Davis

ISBN: (纸本)9780769520308

the Internet pervades many aspects of our lives and is becoming indispensable to critical functions in areas such as commerce, government, production and general information dissemination. To maintain the stability and efficiency of the Internet, every effort must be made to protect it against various forms of attacks, malicious uses, and errors. A key component in the Internet security effort is the routine examination of Internet routing data, which unfortunately can be too large and complicated to browse directly. We have developed an interactive visualization process which proves to be very effective for the analysis of Internet routing data. In this application paper, we show how each step in the visualization process helps direct the analysis and glean insights from the data. these insights include the discovery of patterns, detection of faults and abnormal events, understanding of event correlations, formation of causation hypotheses, and classification of anomalies. We also discuss lessons learned in our visual analysis study.

关键词： homeland security

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Better IT services by means of data mining

Better IT services by means of data mining

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International symposium on Applied Machine Intelligence and Informatics (SAMI)

作者： M. Vadovský P. Michalik I. Zolotová J. Paralič Department of Cybernetics and Artificial Intelligence Technical University of Košice Košice Slovakia

this article contains description how to create prediction models for more efficient utilization of running IT resources. Prediction model creation is presented as one of the most important steps within the process of the knowledge discovery. Presented models were created based on real data from a local IT company by means of the programming language R. this article also marginally covers the steps, which are to be carried out before the actual modelling. the steps to mention are the following: available data understanding and their subsequent preprocessing for further work, individual attributes analysis using data visualization by means of graphs and tracking certain behavior and correlations in data. First of all, designing models using linear and multiple regression will be followed in detail. then, the methods of new values prediction will be described using the R language. Finally, the different types of prediction models will be considered using appropriate indicators. the results obtained should assist and simplify the methods of the knowledge discovery in certain enterprises based on the available databases, and also help to choose the most suitable prediction models learning method.

关键词： Predictive models Biological system modeling data models Correlation Knowledge discovery data mining Servers

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