Search results for: data augmentation.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7470

Search results for: data augmentation.

7440 Research of Data Cleaning Methods Based on Dependency Rules

Authors: Yang Bao, Shi Wei Deng, Wang Qun Lin

Abstract:

This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSql), and gives 6 data cleaning methods based on these algorithms.

Keywords: Data cleaning, dependency rules, violation data discovery, data repair.

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7439 Coalescing Data Marts

Authors: N. Parimala, P. Pahwa

Abstract:

OLAP uses multidimensional structures, to provide access to data for analysis. Traditionally, OLAP operations are more focused on retrieving data from a single data mart. An exception is the drill across operator. This, however, is restricted to retrieving facts on common dimensions of the multiple data marts. Our concern is to define further operations while retrieving data from multiple data marts. Towards this, we have defined six operations which coalesce data marts. While doing so we consider the common as well as the non-common dimensions of the data marts.

Keywords: Data warehouse, Dimension, OLAP, Star Schema.

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7438 Mining Big Data in Telecommunications Industry: Challenges, Techniques, and Revenue Opportunity

Authors: Hoda A. Abdel Hafez

Abstract:

Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: Mining Big Data, Big Data, Machine learning, Data Streams, Telecommunication.

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7437 Natural Convection Boundary Layer Flow of a Viscoelastic Fluid on Solid Sphere with Newtonian Heating

Authors: A.R.M. Kasim, N.F. Mohammad, Aurangzaib, S. Sharidan

Abstract:

The present paper considers the steady free convection boundary layer flow of a viscoelastic fluid on solid sphere with Newtonian heating. The boundary layer equations are an order higher than those for the Newtonian (viscous) fluid and the adherence boundary conditions are insufficient to determine the solution of these equations completely. Thus, the augmentation an extra boundary condition is needed to perform the numerical computational. The governing boundary layer equations are first transformed into non-dimensional form by using special dimensionless group and then solved by using an implicit finite difference scheme. The results are displayed graphically to illustrate the influence of viscoelastic K and Prandtl Number Pr parameters on skin friction, heat transfer, velocity profiles and temperature profiles. Present results are compared with the published papers and are found to concur very well.

Keywords: boundary layer flow, Newtonian heating, sphere, viscoelastic fluid.

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7436 Comparative Analysis of Diverse Collection of Big Data Analytics Tools

Authors: S. Vidhya, S. Sarumathi, N. Shanthi

Abstract:

Over the past era, there have been a lot of efforts and studies are carried out in growing proficient tools for performing various tasks in big data. Recently big data have gotten a lot of publicity for their good reasons. Due to the large and complex collection of datasets it is difficult to process on traditional data processing applications. This concern turns to be further mandatory for producing various tools in big data. Moreover, the main aim of big data analytics is to utilize the advanced analytic techniques besides very huge, different datasets which contain diverse sizes from terabytes to zettabytes and diverse types such as structured or unstructured and batch or streaming. Big data is useful for data sets where their size or type is away from the capability of traditional relational databases for capturing, managing and processing the data with low-latency. Thus the out coming challenges tend to the occurrence of powerful big data tools. In this survey, a various collection of big data tools are illustrated and also compared with the salient features.

Keywords: Big data, Big data analytics, Business analytics, Data analysis, Data visualization, Data discovery.

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7435 Frame Texture Classification Method (FTCM) Applied on Mammograms for Detection of Abnormalities

Authors: Kjersti Engan, Karl Skretting, Jostein Herredsvela, Thor Ole Gulsrud

Abstract:

Texture classification is an important image processing task with a broad application range. Many different techniques for texture classification have been explored. Using sparse approximation as a feature extraction method for texture classification is a relatively new approach, and Skretting et al. recently presented the Frame Texture Classification Method (FTCM), showing very good results on classical texture images. As an extension of that work the FTCM is here tested on a real world application as detection of abnormalities in mammograms. Some extensions to the original FTCM that are useful in some applications are implemented; two different smoothing techniques and a vector augmentation technique. Both detection of microcalcifications (as a primary detection technique and as a last stage of a detection scheme), and soft tissue lesions in mammograms are explored. All the results are interesting, and especially the results using FTCM on regions of interest as the last stage in a detection scheme for microcalcifications are promising.

Keywords: detection, mammogram, texture classification, dictionary learning, FTCM

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7434 Multi-labeled Data Expressed by a Set of Labels

Authors: Tetsuya Furukawa, Masahiro Kuzunishi

Abstract:

Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.

Keywords: Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels

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7433 Computation of Global Voltage Stability Margin in a Practical Power Network Incorporating FACTS in the OPF Frame Work

Authors: P. Nagendra, S. Halder nee Dey, S. Paul, T. Datta

Abstract:

This paper presents a methodology to assess the voltage stability status combined with optimal power flow technique using an instantaneous two-bus equivalent model of power system incorporating static var compensator (SVC) and thyristor controlled series compensator (TCSC) controllers. There by, a generalized global voltage stability indicator being developed has been applied to a robust practical Indian Eastern Grid 203-bus system. Simulation results have proved that the proposed methodology is promising to assess voltage stability of any power system at any operating point in global scenario. Voltage stability augmentation with the application of SVC at the weakest bus and TCSC at critical line connected to the weakest bus is compared with the system having no compensation. In the proposed network equivalent model the generators have been modeled more accurately considering economic criteria.

Keywords: Equivalent two-bus model, global voltage security indicator, optimal power flow, SVC, TCSC.

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7432 The Comparison of Data Replication in Distributed Systems

Authors: Iman Zangeneh, Mostafa Moradi, Ali Mokhtarbaf

Abstract:

The necessity of ever-increasing use of distributed data in computer networks is obvious for all. One technique that is performed on the distributed data for increasing of efficiency and reliablity is data rplication. In this paper, after introducing this technique and its advantages, we will examine some dynamic data replication. We will examine their characteristies for some overus scenario and the we will propose some suggestion for their improvement.

Keywords: data replication, data hiding, consistency, dynamicdata replication strategy

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7431 Visual Study on Flow Patterns and Heat Transfer during Convective Boiling Inside Horizontal Smooth and Microfin Tubes

Authors: V.D. Hatamipour, M.A. Akhavan-Behabadi

Abstract:

Evaporator is an important and widely used heat exchanger in air conditioning and refrigeration industries. Different methods have been used by investigators to increase the heat transfer rates in evaporators. One of the passive techniques to enhance heat transfer coefficient is the application of microfin tubes. The mechanism of heat transfer augmentation in microfin tubes is dependent on the flow regime of two-phase flow. Therefore many investigations of the flow patterns for in-tube evaporation have been reported in literatures. The gravitational force, surface tension and the vapor-liquid interfacial shear stress are known as three dominant factors controlling the vapor and liquid distribution inside the tube. A review of the existing literature reveals that the previous investigations were concerned with the two-phase flow pattern for flow boiling in horizontal tubes [12], [9]. Therefore, the objective of the present investigation is to obtain information about the two-phase flow patterns for evaporation of R-134a inside horizontal smooth and microfin tubes. Also Investigation of heat transfer during flow boiling of R-134a inside horizontal microfin and smooth tube have been carried out experimentally The heat transfer coefficients for annular flow in the smooth tube is shown to agree well with Gungor and Winterton-s correlation [4]. All the flow patterns occurred in the test can be divided into three dominant regimes, i.e., stratified-wavy flow, wavy-annular flow and annular flow. Experimental data are plotted in two kinds of flow maps, i.e., Weber number for the vapor versus weber number for the liquid flow map and mass flux versus vapor quality flow map. The transition from wavy-annular flow to annular or stratified-wavy flow is identified in the flow maps.

Keywords: Flow boiling, Flow pattern, Heat transfer, Horizontal, Smooth tube, Microfin tube.

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7430 Implementation of an IoT Sensor Data Collection and Analysis Library

Authors: Jihyun Song, Kyeongjoo Kim, Minsoo Lee

Abstract:

Due to the development of information technology and wireless Internet technology, various data are being generated in various fields. These data are advantageous in that they provide real-time information to the users themselves. However, when the data are accumulated and analyzed, more various information can be extracted. In addition, development and dissemination of boards such as Arduino and Raspberry Pie have made it possible to easily test various sensors, and it is possible to collect sensor data directly by using database application tools such as MySQL. These directly collected data can be used for various research and can be useful as data for data mining. However, there are many difficulties in using the board to collect data, and there are many difficulties in using it when the user is not a computer programmer, or when using it for the first time. Even if data are collected, lack of expert knowledge or experience may cause difficulties in data analysis and visualization. In this paper, we aim to construct a library for sensor data collection and analysis to overcome these problems.

Keywords: Clustering, data mining, DBSCAN, k-means, k-medoids, sensor data.

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7429 Government (Big) Data Ecosystem: Definition, Classification of Actors, and Their Roles

Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

Abstract:

Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: Big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review.

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7428 Heat Transfer and Turbulent Fluid Flow over Vertical Double Forward-Facing Step

Authors: Tuqa Abdulrazzaq, Hussein Togun, M. K. A. Ariffin, S. N. Kazi, A. Badarudin, N. M Adam, S. Masuri

Abstract:

Numerical study of heat transfer and fluid flow over vertical double forward facing step were presented. The k-w model with finite volume method was employed to solve continuity, momentum, and energy equations. Different step heights were adopted for range of Reynolds number varied from 10000 to 40000, and range of temperature varied from 310K to 340 K. The straight side of duct is insulated while the side of double forward facing step is heated. The result shows augmentation of heat transfer due to the recirculation region created after and before steps. Effect of step length and Reynolds number observed on increase of local Nusselt number particularly at recirculation regions. Contour of streamline velocity is plotted to show recirculation regions after and before steps. Numerical simulation in this paper done by used ANSYS FLUENT 14.

Keywords: Turbulent flow, Double forward, Heat transfer, Separation flow.

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7427 Numerical Investigation of Heat Transfer in a Channel with Delta Winglet Vortex Generators at Different Reynolds Numbers

Authors: N. K. Singh

Abstract:

In this study the augmentation of heat transfer in a rectangular channel with triangular vortex generators is evaluated. The span wise averaged Nusselt number, mean temperature and total heat flux are compared with and without vortex generators in the channel at a blade angle of 30° for Reynolds numbers 800, 1200, 1600, and 2000. The use of vortex generators increases the span wise averaged Nusselt number compared to the case without vortex generators considerably. At a particular blade angle, increasing the Reynolds number results in an enhancement in the overall performance and span wise averaged Nusselt number was found to be greater at particular location for larger Reynolds number. The total heat flux from the bottom wall with vortex generators was found to be greater than that without vortex generators and the difference increases with increase in Reynolds number.

Keywords: Heat transfer, channel with vortex generators, numerical simulation, effect of Reynolds number on heat transfer.

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7426 Imputation Technique for Feature Selection in Microarray Data Set

Authors: Younies Mahmoud, Mai Mabrouk, Elsayed Sallam

Abstract:

Analyzing DNA microarray data sets is a great challenge, which faces the bioinformaticians due to the complication of using statistical and machine learning techniques. The challenge will be doubled if the microarray data sets contain missing data, which happens regularly because these techniques cannot deal with missing data. One of the most important data analysis process on the microarray data set is feature selection. This process finds the most important genes that affect certain disease. In this paper, we introduce a technique for imputing the missing data in microarray data sets while performing feature selection.

Keywords: DNA microarray, feature selection, missing data, bioinformatics.

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7425 Analyzing the Plausible Alternatives in Contracting the Societal Fissure Caused by Digital Divide in Sri Lanka

Authors: Manuela Nayantara Jeyaraj

Abstract:

'Digital Divide' is a concept that has existed in this paradigm ever since the discovery of the first-generation technologies. Before the turn of the century, it was basically used to describe the gap between those with telephone communication access and those without it. At present, it is plainly descriptive in itself to illustrate the cavity among those with Internet access and those without. Though the concept of digital divide has been merely lying in sight for as long as time itself, the friction it caused has not yet been fully realized to solve major crisis situations. Unlike well-developed countries, Sri Lanka is still in the verge of moving farther away from a developing country in the race towards reaching a developed state. Access to technological resources varies from region to region, even within the island itself, with one region having a considerable percentage of its community exposed to the Internet and its related technologies, and the other unaware of such. Thus, this paper intends to analyze the roots for the still-extant gap instigated based on the concept of ‘Digital Divide’ and explores the plausible potentials that could be brought about by narrowing this prevailing percentage among the population, specifically entrenching the advantages reaped towards an economic augmentation and culture or lifestyle revolution on the path towards development.

Keywords: Communication, digital divide, society, Sri Lanka.

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7424 Automatic Real-Patient Medical Data De-Identification for Research Purposes

Authors: Petr Vcelak, Jana Kleckova

Abstract:

Our Medicine-oriented research is based on a medical data set of real patients. It is a security problem to share patient private data with peoples other than clinician or hospital staff. We have to remove person identification information from medical data. The medical data without private data are available after a de-identification process for any research purposes. In this paper, we introduce an universal automatic rule-based de-identification application to do all this stuff on an heterogeneous medical data. A patient private identification is replaced by an unique identification number, even in burnedin annotation in pixel data. The identical identification is used for all patient medical data, so it keeps relationships in a data. Hospital can take an advantage of a research feedback based on results.

Keywords: DASTA, De-identification, DICOM, Health Level Seven, Medical data, OCR, Personal data

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7423 Analyzing Multi-Labeled Data Based on the Roll of a Concept against a Semantic Range

Authors: Masahiro Kuzunishi, Tetsuya Furukawa, Ke Lu

Abstract:

Classifying data hierarchically is an efficient approach to analyze data. Data is usually classified into multiple categories, or annotated with a set of labels. To analyze multi-labeled data, such data must be specified by giving a set of labels as a semantic range. There are some certain purposes to analyze data. This paper shows which multi-labeled data should be the target to be analyzed for those purposes, and discusses the role of a label against a set of labels by investigating the change when a label is added to the set of labels. These discussions give the methods for the advanced analysis of multi-labeled data, which are based on the role of a label against a semantic range.

Keywords: Classification Hierarchies, Data Analysis, Multilabeled Data, Orders of Sets of Labels

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7422 Heat Transfer to Laminar Flow over a Double Backward-Facing Step

Authors: Hussein Togun, Tuqa Abdulrazzaq, S. N. Kazi, A. Badarudin, M. K. A. Ariffin

Abstract:

Heat transfer and laminar air flow over a double backward-facing step numerically studied in this paper. The simulations was performed by using ANSYS ICEM for meshing process and using ANSYS fluent 14 (CFD) for solving. The k-ɛ standard model adopted with Reynolds number varied between 98.5 to 512 and three step height at constant heat flux (q=2000 W/m2). The top of wall and bottom of upstream are insulated with bottom of downstream is heated. The results show increase in Nusselt number with increases of Reynolds number for all cases and the maximum of Nusselt number happens at the first step in compared to the second step. Due to increase of cross section area of downstream to generate sudden expansion then Nusselt number decrease but the profile of Nusselt number keep same trend for all cases where increase after the first and second steps. Recirculation region after the first and second steps are denoted by contour of streamline velocity. The higher augmentation of heat transfer rate observed for case 1 at Reynolds number of 512 and heat flux q=2000 W/m2.

Keywords: Laminar flow, Double backward, Separation flow, Recirculation flow.

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7421 Steganalysis of Data Hiding via Halftoning and Coordinate Projection

Authors: Woong Hee Kim, Ilhwan Park

Abstract:

Steganography is the art of hiding and transmitting data through apparently innocuous carriers in an effort to conceal the existence of the data. A lot of steganography algorithms have been proposed recently. Many of them use the digital image data as a carrier. In data hiding scheme of halftoning and coordinate projection, still image data is used as a carrier, and the data of carrier image are modified for data embedding. In this paper, we present three features for analysis of data hiding via halftoning and coordinate projection. Also, we present a classifier using the proposed three features.

Keywords: Steganography, steganalysis, digital halftoning, data hiding.

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7420 Biological Data Integration using SOA

Authors: Noura Meshaan Al-Otaibi, Amin Yousef Noaman

Abstract:

Nowadays scientific data is inevitably digital and stored in a wide variety of formats in heterogeneous systems. Scientists need to access an integrated view of remote or local heterogeneous data sources with advanced data accessing, analyzing, and visualization tools. This research suggests the use of Service Oriented Architecture (SOA) to integrate biological data from different data sources. This work shows SOA will solve the problems that facing integration process and if the biologist scientists can access the biological data in easier way. There are several methods to implement SOA but web service is the most popular method. The Microsoft .Net Framework used to implement proposed architecture.

Keywords: Bioinformatics, Biological data, Data Integration, SOA and Web Services.

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7419 STATISTICA Software: A State of the Art Review

Authors: S. Sarumathi, N. Shanthi, S. Vidhya, P. Ranjetha

Abstract:

Data mining idea is mounting rapidly in admiration and also in their popularity. The foremost aspire of data mining method is to extract data from a huge data set into several forms that could be comprehended for additional use. The data mining is a technology that contains with rich potential resources which could be supportive for industries and businesses that pay attention to collect the necessary information of the data to discover their customer’s performances. For extracting data there are several methods are available such as Classification, Clustering, Association, Discovering, and Visualization… etc., which has its individual and diverse algorithms towards the effort to fit an appropriate model to the data. STATISTICA mostly deals with excessive groups of data that imposes vast rigorous computational constraints. These results trials challenge cause the emergence of powerful STATISTICA Data Mining technologies. In this survey an overview of the STATISTICA software is illustrated along with their significant features.

Keywords: Data Mining, STATISTICA Data Miner, Text Miner, Enterprise Server, Classification, Association, Clustering, Regression.

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7418 Proposal of Data Collection from Probes

Authors: M. Kebisek, L. Spendla, M. Kopcek, T. Skulavik

Abstract:

In our paper we describe the security capabilities of data collection. Data are collected with probes located in the near and distant surroundings of the company. Considering the numerous obstacles e.g. forests, hills, urban areas, the data collection is realized in several ways. The collection of data uses connection via wireless communication, LAN network, GSM network and in certain areas data are collected by using vehicles. In order to ensure the connection to the server most of the probes have ability to communicate in several ways. Collected data are archived and subsequently used in supervisory applications. To ensure the collection of the required data, it is necessary to propose algorithms that will allow the probes to select suitable communication channel.

Keywords: Communication, computer network, data collection, probe.

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7417 Linguistic Summarization of Structured Patent Data

Authors: E. Y. Igde, S. Aydogan, F. E. Boran, D. Akay

Abstract:

Patent data have an increasingly important role in economic growth, innovation, technical advantages and business strategies and even in countries competitions. Analyzing of patent data is crucial since patents cover large part of all technological information of the world. In this paper, we have used the linguistic summarization technique to prove the validity of the hypotheses related to patent data stated in the literature.

Keywords: Data mining, fuzzy sets, linguistic summarization, patent data.

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7416 Metadata Update Mechanism Improvements in Data Grid

Authors: S. Farokhzad, M. Reza Salehnamadi

Abstract:

Grid environments include aggregation of geographical distributed resources. Grid is put forward in three types of computational, data and storage. This paper presents a research on data grid. Data grid is used for covering and securing accessibility to data from among many heterogeneous sources. Users are not worry on the place where data is located in it, provided that, they should get access to the data. Metadata is used for getting access to data in data grid. Presently, application metadata catalogue and SRB middle-ware package are used in data grids for management of metadata. At this paper, possibility of updating, streamlining and searching is provided simultaneously and rapidly through classified table of preserving metadata and conversion of each table to numerous tables. Meanwhile, with regard to the specific application, the most appropriate and best division is set and determined. Concurrency of implementation of some of requests and execution of pipeline is adaptability as a result of this technique.

Keywords: Grids, data grid, metadata, update.

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7415 Optimized Approach for Secure Data Sharing in Distributed Database

Authors: Ahmed Mateen, Zhu Qingsheng, Ahmad Bilal

Abstract:

In the current age of technology, information is the most precious asset of a company. Today, companies have a large amount of data. As the data become larger, access to data for some particular information is becoming slower day by day. Faster data processing to shape it in the form of information is the biggest issue. The major problems in distributed databases are the efficiency of data distribution and response time of data distribution. The security of data distribution is also a big issue. For these problems, we proposed a strategy that can maximize the efficiency of data distribution and also increase its response time. This technique gives better results for secure data distribution from multiple heterogeneous sources. The newly proposed technique facilitates the companies for secure data sharing efficiently and quickly.

Keywords: ER-schema, electronic record, P2P framework, API, query formulation.

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7414 Using Data Clustering in Oral Medicine

Authors: Fahad Shahbaz Khan, Rao Muhammad Anwer, Olof Torgersson

Abstract:

The vast amount of information hidden in huge databases has created tremendous interests in the field of data mining. This paper examines the possibility of using data clustering techniques in oral medicine to identify functional relationships between different attributes and classification of similar patient examinations. Commonly used data clustering algorithms have been reviewed and as a result several interesting results have been gathered.

Keywords: Oral Medicine, Cluto, Data Clustering, Data Mining.

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7413 The Application of Data Mining Technology in Building Energy Consumption Data Analysis

Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

Abstract:

Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: Data mining, data analysis, prediction, optimization, building operational performance.

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7412 Query Algebra for Semistuctured Data

Authors: Ei Ei Myat, Ni Lar Thein

Abstract:

With the tremendous growth of World Wide Web (WWW) data, there is an emerging need for effective information retrieval at the document level. Several query languages such as XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent years to provide faster way of querying XML data, but they still lack of generality and efficiency. Our approach towards evolving a framework for querying semistructured documents is based on formal query algebra. Two elements are introduced in the proposed framework: first, a generic and flexible data model for logical representation of semistructured data and second, a set of operators for the manipulation of objects defined in the data model. In additional to accommodating several peculiarities of semistructured data, our model offers novel features such as bidirectional paths for navigational querying and partitions for data transformation that are not available in other proposals.

Keywords: Algebra, Semistructured data, Query Algebra.

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7411 Simulation Data Summarization Based on Spatial Histograms

Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

Abstract:

In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: Simulation data, data summarization, spatial histograms, exploration and visualization.

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