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International conference on Information and Communication Technology Convergence

作者： Mary Jane Samonte Tristan Gabriel Bal Zeus Nisael Recio Randall Mark San Jose School of InformationTechnology Mapúa University Makati City Philippines

The Philippine Conditional Cash Transfer (CCT) of the Philippines has started since 2007. This Philippine government program and human development measure provides conditional cash grants to the poorest of the poor, to improve the health, nutrition, and the education of children aged 0-18. This study provides a framework of state-of-the-art visualization tool in presenting data that provides significant reports that will aid government decision making that involves poor Filipino families. With the vast rising of technology and never-ending growth of government data in the Philippines, it is a big possibility that the data generated by the tool can give solutions and amendments to future management policies and improves administration tasks. This research shows a framework for the development of a web application of a decision support system to support the National Advisory Committee (NAC) and NAC Technical Working Group (NAC-TWG) of the Department of Social Welfare and Development of the Philippines. The data analyses reports produced on this interactive data visualization tool can be used as a basis for program and action recommendation of government offices. The framework includes descriptive and diagnostic analysis after data cleansing and simulation. It also features forecasting and prediction functionalities.

关键词： data visualization Tools data analysis Government Urban areas Correlation Big data

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Precise 3D documentation - between the need of a high resolution and the limit of visualization possibilities

Precise 3D documentation - between the need of a high resolu...

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14th Annual IS&T Archiving conference 2017 (ARCHIVING 2017)

作者： Bunsch, Eryk Sitnik, Robert Museum King Jan IIIs Palace Wilanow Lab Documentat 3D Warsaw Poland Warsaw Univ Technol Inst Micromech & Photon Warsaw Poland

ISBN: (纸本)9780892083268

Since 2007 Museum of King Jan III's Palace at Wilanow and Warsaw University of Technology, Faculty of Mechatronics are together developing precise, structured light-based scanning methods. This cooperation was established in order to elaborate solutions allowing documenting characteristics of the sutface of different cultural heritage objects. The gathered data are intended to support the processes of conservation, education, historical analysis as well as the sharing of the visualizations of the especially fragile objects. In order to fulfill those requirements for most of the historic artifacts, scanning with a spatial resolution of at least 2500 points per square millimeter is needed. As a result of those assumptions, files of a very large size are produced. Today's software environments for such a huge data processing and applications to visualize those data are very limited. Consequently, this raises the need for either a significant simplification of visualization process or a reduction of the shared results of measurements (by showing data concerning only a small parts of the heritage objects). Which path would be most suitable for the end users? Should this insufficiency of the visualization software cause a reduction of the quality of the measurement processes?

关键词： visualization

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Prettycloud Visualizing Weighted and Grouped Genomic Context with Mathematical Curves 2

Prettycloud Visualizing Weighted and Grouped Genomic Context...

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2nd IEEE International conference on Cloud Computing and Big data analysis (ICCCBDA)

作者： Miao, Peng Sablok, Gaurav Zhang, Qinglei Tao, Mingxin Zhu, BeiBei Feng, Gang Sun, Xiaoyong Shandong Agr Univ Coll Informat Sci & Engn Agr Big Data Res Ctr Tai An Shandong Peoples R China Univ Technol Sydney Plant Funct Biol & Climate Change Cluster C3 POB 123 Broadway NSW 2007 Australia Northwestern Univ Prevent Med Hlth & Biomed Informat Chicago IL 60611 USA

ISBN: (纸本)9781509044993

Biological networks and visualization of the frequent terms in networks offers a key scenario to visualize and link the biological terms, which are representative of the physiological experiment. Plethora of the publications recently using the RNA-Seq has widely elucidated the organismal biology. However, the embedded annotations are dispersed across representative publications and present end-user a cumbersome task of visually looking at annotations files for the over-represented categories. In the present paper, we present an R package for the visualization of the most frequent annotation terms using math curve functions. The developed pack-age allows for the visualization of the abundant terms in clustered way using weighted indices and present the visualization of the abundance of the terms in relation to word size, font and coloring as per the frequency of the observed word. prettycloud is implementegd in R, and is supported on Windows, Linux and MAC OSX, and freely available at https://***/projects/prettycloud/or http://***/research/software/*** (Figure 1).

关键词： component R package embedded annotations visualization

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Real-Time Gender Detection in the Wild Using Deep Neural Networks

Real-Time Gender Detection in the Wild Using Deep Neural Net...

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Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI)

作者： Luis Felipe de Araujo Zeni Claudio Rosito Jung Informatics Institute Federal University of Rio Grande do Sul Porto Alegre Brazil

Gender recognition can be used in many applications, such as video surveillance, human-computer interaction and customized advertisement. Current state-of-the-art gender recognition methods are detector-dependent or region-dependent, focusing mostly on facial features (a face detector is typically required). These limitations do not allow an end-to-end training pipeline, and many features used in the detection phase must be re-learned in the classification step. Furthermore, the use of facial features limits the application of such methods in the wild, where the face might not be present. This paper presents a real-time end-to-end gender detector based on deep neural networks. The proposed method detects and recognizes the gender of persons in the wild, meaning in images with a high variability in pose, illumination an occlusions. To train and evaluate the results a new annotation set of Pascal VOC 2007 and CelebA were created. Our experimental results indicate that combining both datasets during training can increase the mAp of our gender detector. We also visually analyze which parts leads our network to make mistakes and the bias introduced by the training data.

关键词： Face Feature extraction Detectors Training visualization Facial features Task analysis

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A data-Driven Approach for Discovering the Recent Research Status of Diabetes in China 1

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6th International conference on Health Information Science (HIS)

作者： Chen, Xieling Weng, Heng Hao, Tianyong Jinan Univ Sch Econ Guangzhou Peoples R China Guangzhou Univ Chinese Med Affiliated Hosp 2 Guangzhou Peoples R China Guangdong Univ Foreign Studies Sch Informat Sci & Technol Guangzhou Peoples R China

ISBN: (数字)9783319691824

ISBN: (纸本)9783319691824;9783319691817

This paper aims at discovering the recent research status of diabetes in China through a data-driven bibliometrics and knowledge mapping analysis method on diabetes-related literature. With the basis of 24,561 publication documents from CNKI during 2007-2016, the quantitative analysis are conducted in three aspects: (1) descriptive statistical method for acquiring literature distribution characteristics;(2) hierarchical clustering, k-means clustering analysis, and multidimensional scaling analysis based on a keyword co-occurrence matrix for discovering research hotspots;and (3) network analysis for revealing cooperation relationships among authors and affiliations. The result shows some findings about the recent diabetes research in China. It also demonstrates the close cooperation of diabetes research among productive authors and affiliations through network generation and visualization.

关键词： Diabetes Distribution characteristics Research hotspots Cooperation network

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analysis of the socio-economic impact of renewable energy hybrid electricity utilization for rural community development (case study: Pantai Anyar, Yogyakarta special region, Indonesia)

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IOP conference Series: Earth and Environmental Science 2019年第1期383卷

作者： D Rachmawatie E Rustiadi Aad Fauzi Bambang Juanda Universitas Muhammadiyah Yogyakarta Department of Regal Development Faculty of Agriculture Bogor Agricultural University Department of Resource Economics and Environment Faculty of Economy and Management Bogor Agricultural University Department of Economic Science Faculty of Economy and Management Bogor Agricultutal University

The aim of this research were to: (1) study on socio-economics from Renewable Energy Hybrid Power Plant (PLTH) electricity development for rural communities, (2) find out information related to average households beneficiaries of electricity (pre and post the utilization of electrical energy hybrid electricity at Baru Beach. The research was conducted at Baru Beach, Yogyakarta Special Region on November – December, 2017. The data used were primary and secondary data. The research was conducted by surveying 68 respondents who are direct beneficiaries of hybrid electric energy utilization activities in Baru Beach. The analytical method used in this part of the study is the visualization analysis of the Baru Beach map area for 20072017, analysis of household income, and Paired Sample T-test. The results showed that: (1) based on changes in the map of Pantai Baru area in 2007-2017, changes in road changes, the access and connectivity of this region to other regions have become much better. In the analysis of income obtained, post PLTH was developed at Baru Beach. The income analysis was found that, post PLTH was developed in Baru Beach, there was an increase in the average income in the non-agricultural sector and household income for PLTH electricity beneficiaries, but there was a decrease in the average income value in the agricultural sector, (2) based on Paired Sample T-Test analysis show there is a significant difference the average household income post PLTH developed at Baru Beach with a significance level of 0.041. Thus the results of this research conclude that there is any a socio-economic impact from the utilization of renewable electricity not only for the beneficiaries of electricity in rural communities, but also for the development of local area.

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2D Approach Measuring Multidimensional data Pattern in Big data visualization

2D Approach Measuring Multidimensional Data Pattern in Big D...

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IEEE International conference on Big data analysis (ICBDA)

作者： Zhang, Jinson Huang, Mao Lin Univ Technol Sydney Fac Engn & IT Sch Software Sydney NSW 2007 Australia Tianjin Univ Sch Comp Software Tianjin Peoples R China

ISBN: (纸本)9781467395915

Big data, structured and unstructured data, contains millions attributes in multiple dimensions. This has arisen threeissues: 1) how to measure the structured and unstructured multidimensional data patterns for Big data analysis;2) how to display multidimensional data patterns in normal size of screen;3) how to optimize the data attributes in Big data visualization. In this work, we have visual analyzed Big datavariety based on the complexity of multidimensional data. Firstly, we introduce2D dimension which divided the multidimensional dataset into 2D data pattern subsets, and then establish 2D-Ratio algorithm to measure 2D dimension in multiple data patterns. Second, we createtwo additional parallel axes by using 2D-Ratio to compare 2D dimensional patterns for visualization. Third, the dimension clustering and shrunk attribute have been introduced in 2D-Ratio parallel coordinates to reduce the data over-crowed. The experiment shows that our model can be efficiently and accurately used for Big data analysis and visualization.

关键词： Big data multidimensional dataset 2D-Ratio data visual analytics parallel coordinates

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Design for intelligence analysis of complex systems: Evolution of criminal networks 7

Design for intelligence analysis of complex systems: Evoluti...

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7th European Intelligence and Security Informatics conference, EISIC 2016

作者： Seidler, Patrick Haider, Johanna Kodagoda, Neesha William Wong, B.L. Pohl, Margit Adderley, Richard Middlesex University London United Kingdom Vienna University of Technology Vienna Austria Ltd. Badsey United Kingdom

ISBN: (纸本)9781509028566

Intelligence analysts are at the forefront to provide decision makers with a greater picture of current situational context. Their main task is to identify relevant pieces of information from disparate systems and growing amounts of data while often lacking the appropriate tools. We propose a visual analytics approach to support analysts in monitoring and reasoning about the dynamics in a complex system. In our approach, we systematically map relations onto the user interface and support both overview and provenance over temporal dynamics. We further map explicitly otherwise tacit organisational knowledge. Our use case is based on a crime system taking the perspective of criminal network analysis tasks. Our analytics extract force-prioritised, weighted co-offender networks, which are represented through both a graph and a matrix visualisation, incorporating the evolution of relationships between offenders. The developed tools were evaluated in a study with domain experts, with the goal to assess tool utility and to investigate the appropriateness of the tool with the end user. © 2016 IEEE.

关键词： visualization

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Codebook enhancement of vlad representation for visual recognition

Codebook enhancement of vlad representation for visual recog...

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International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhe Wang Yali Wang Limin Wang Yu Qiao Shenzhen key lab of Comp. Vis. & Pat. Rec. Shenzhen Institutes of Advanced Technology CAS China

ISBN: (纸本)9781479999897

Recent studies demonstrate the effectiveness of super vector representation in a number of visual recognition tasks. One popular approach along this line is the Vector of Locally Aggregated Descriptor (VLAD) where the super vector is encoded with a codebook generated by k-means. However, the effectiveness of the codebook is often limited, due to the poor clustering solution, the high dimensionality of visual descriptors and the global PCA for data preprocessing. To circumvent these problems, we propose three approaches for codebook enhancement, (i) partition of data, (ii) partition of feature, and (iii) local PCA. Moreover, all these approaches can be effectively integrated together to further boost the recognition performance. In our experiments, we evaluate our enhancement approaches on two challenging visual tasks, i.e., action recognition (HMDB51) and object recognition (PASCAL VOC2007). The results show that our approaches and the fusion versions significantly outperform the baselines.

关键词： Principal component analysis visualization Videos Training Standards data preprocessing Feature extraction

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analysis of hydrodynamic force acting on commercialized rowing blades using computational fluid dynamics

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AIP conference Proceedings 2017年第1期1831卷

作者： A. M. Y. Aziz M. N. Harun Ardiyansyah Syahrom A. H. Omar 1Faculty of Bioscience and Medical Engineering Universiti Teknologi Malaysia Johor Baharu Malaysia 2Sports Innovation and Technology Centre (SITC) Institute of Human Centered Engineering (IHCE) Universiti Teknologi Malaysia Johor Baharu Malaysia

This paper presents a study of the hydrodynamics of several rowing blade designs. The study was done using Computational Fluid Dynamics (CFD) which enabled the investigation to be done similar to the experimental study, but with additional hydrodynamic visualization for further analysis and understanding. The CFD method was validated using quasi-static experimental data from Caplan (2007). Besides that, the proposed CFD analyses have improved the precious CFD results with the percentage of error of 6.58 percent of lift and 0.69 percent of drag force compared to 33.65 and 18.75 percent obtained by Coppel (2010). Consequent to the successful validation, the study then proceeded with the real size of Macon, Big balde and Fat blade. It was found that the hydrodynamic performance of the Fat blade was the highest due to the area, aspect ratio and the shape of the blade. Besides that, distribution of pressure for all models were also investigated which deepened the understanding of the blade fluid mechanics of rowing.

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