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GEO-BASED IMAGE ANALYSIS SERVICE IN OPEN SOURCE CLOUD COMPUTING ENVIRONMENT Sanggoo Kang 1 , Guseon Yoon 1 , and Kiwon Lee 2 1 Graduate Student, Department of Information Systems Engineering, Hansung University, Samseon-dong 2-ga, Seongbuk-gu, Seoul, Korea, 136-792 Email: lainer23@naver.com,gxexe3@naver.com 2 Professor, Department of Information Systems Engineering, Hansung University, Samseon-dong 2-ga, Seongbuk-gu, Seoul, Korea, 136-792 Email: kilee@hansung.ac.kr ABSTRACT Globally, cloud computing is one of huge trends in ICT communities, exerting its influence on the most information application fields including geo-spatial domain. In general, cloud computing services are being regarded as commercial or public internet data center or infrastructure of computing resources. However, there is no limitation for applications of cloud computing. Especially, it is on the early developing stage in geo-based applications. This project is to present a practical application for geo-based image processing and analysis on open source cloud environment. OpenStack Juno version was applied for open source cloud computing environment. On this cloud environment, PostgreSQL and Django were used as open source for metadata server and web framework, respectively. For geo-based image processing server, OTB was used with GDAL for image manipulating. Some image processing algorithms were implemented in this cloud environment, and provides as a web service for public users. Web-accessible users in this cloud service do not need any software installation and downloading data sets. This full open source approach is expected to be an element geo-spatial information processing linked with cloud computing service. 1. INTRODUCTION In globally scaled information communication technology (ICT) application, cloud computing leads new paradigm for computing resources uses. The most acceptable one among numerous literal definitions with respect to cloud computing is pay-as-you-go webaccessible computing environment by on-demand typed processing including server hardware, network infrastructure, or software service. Since the early 2010s, cloud computing is widely applied in many application domains, and practical cloud application cases have been reported.In general, cloud-based system shows many advantageous points of economic cost reduction, stability, and scalability (Chou, 2015). Despite of these huge trend, development of geo-based application in cloud environment is rather slow, it is an early stage. Evangelidiset al. (2014) expected that linkage of cloud computing and standards of Open Geo-spatial Consortium, Inc.(OGC) would expand. Thus it is necessary that experiments for linkage of geo-spatial applications and cloud computing technologies and cloud-based application cases. The purpose of this work is to demonstrate a cloud-based geo-spatial system which was newly designed and implemented for satellite image processing by open sources covering geo-processing engine and even cloud environments. This system by open source stack and integration supports cross-browser functionalities and does not need any installation processes by users. Computing resources such as data server, web server, geo-data and geobased image processing engine or client user interface for web mapping are included into FOSS4G Seoul, South Korea | September 14 th – 19 th , 2015 308
cloud environment, so that end-users with accessing account, basically open accessing, just use web browser. But internal processing in the cloud environment is hidden on the stable mode and quite differ from the non-cloud system. As the previous works, Lee and Kang (2013) implemented a real-time processing system of satellite image processing for tablet devices by using Amazon elastic compute cloud (EC2) in Amazon Web Service (AWS). Kang and Lee (2014) performed a test case for geo-data fusion application in AWS and OpenStack cloud, one of open source cloud platform. Lee et al. (2015) developed a prototype for geo-based image analysis system on OpenStack cloud. This work used more advanced development environments and user interface components, and proposes a new system architecture, different from those previous works. OpenStack, open source cloud computing platform for public and private clouds, was used for building cloud computing environment, so that generation of instance servers with various performance capability was possible. It means fast adoption and customization of cloud environment according to application purposes.As for OpenStack, it reduce the risks of lock-in associated with proprietary platforms, and offers target-based flexibility and numerous communities and developers choice (OpenStack, 2015). The OpenStack technologies have been built by interrelated projects which control processing, storage, and networking computing resources, capable of being handled by a web-based dashboard or command-line tools. In many areas of information system business, use cases of OpenStack are increasing every year. But in the geo-spatial field, OpenStack application is a somewhat beginning stage. In spite of current status, integration or linkage of open source cloud computing and geobased application is a prospective approach. Cloud computing environment helps management and manipulation of large volume of various typed geo data sets and geo-based images including satellite image data. 2. SYSTEM IMPLEMENTATION The work was fully implemented by open source basis from operating system (OS) to application service level in Table 1. The operating environment is divided intoserverand client. The server was built with OpenStack cloud computing environment and used the operating system, Ubuntu 12.04. Django was used for web framework of Python-based implementation, and it improves security and reliability of fast implemented products. PostgreSQL/PostGIS, open source database management system, was used for metadata cataloging and query process of geo-based image sets. As for image processing engine, Orfeo ToolBox (OTB) providing a variety of open source satellite image processing algorithms was used. In the client side, Bootstrap was used for user interface framework, taking advantage of optimization for multi-screen devices and consistency for displaying contents. As well, JavaScript libraries such as iCheck and selectric based on jQuery were applied for additional user interfacing components. While, OpenLayerswas used for web mapping library, to online visualize base map, index image and the processed images. Figure 1 shows an architecture of the implemented system, with work flow and system modules. Instance server is divided into 4 operating environments. Processing system and user interface system are basically operated on Apache web server and Django. There are many cloud-based user requesting and responding modules. In the geo-based image management module, an important preprocessing for metadata query and display regarding index image archived in the storage units is performed before the image processing or analysis request management module. For actual image processing, OTB and GDAL are used. Geo-based image analysis service in open source cloud computing environment 309
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PROCEEDINGS Honil Gangni Yeokdae Gu
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C O N T E N T S Welcome Messages Lo
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A Week of Sharing, Learning, and Fu
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ACADEMIC TRACKS 7
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September 17, Thursday 11:00-12:15
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September 16 (Wed) & 18 (Fri) 15:05
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AUTOMATIC IMPROVEMENT OF POINT-OF-I
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In the following, we will list
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and specify their relations manuall
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Conducting a cross-validation on th
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81%. For cuisine=german, the precis
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4.3 Tourism and Leisure Tags We ide
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GENERATING GEOSPATIAL FOOTPRINTS FO
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quality assessment of geocrowdsourc
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Figure 2: The first simple case of
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Figure 5: The footprint of walkways
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say instead “Between 1st Street a
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4. DISCUSSION AND CONCLUSIONS The G
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Performance Analysis of MongoDB Vs.
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2. REVIEW OF SPATIAL DATABASES Simi
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4.2 Point Containment Problem Like
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If we observe the results above we
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esolution data (RapidEye and Landsa
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and used for calibration and coeffi
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scatter plot of RapidEye (Global (C
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is efficient to extrapolate depth f
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DYNAMIC STYLING FOR THEMATIC MAPPIN
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all) datasets on offer or applying
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3.2.1 Data inputs The styler accept
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determine the radius (both in the x
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Figure 5: Map classification of blo
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4.3 Point data Figure 8: Diverging
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4.4 Non-spatial visualisations Figu
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6 ACKNOWLEDGEMENTS The Cooperative
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educational resources (OER) and mod
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workshops have revealed that microc
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300 250 200 150 100 50 0 Figure 4.
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H 27 Male Student Maths / Geography
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5. CONCLUSIONS AND FUTURE WORK We h
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DEVELOPMENT OF DATA ARCHIVING AND D
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2. RELATED WORK Recent developments
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3. Significance and Objectives With
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Figure 3. Map Tiles Grid Selection
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The Ceph architecture comprises of
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Boundless, 2015. GeoExplorer — Ge
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Object-Based Building Boundary Extr
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2.2. A Grid-Based Algorithm A grid-
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3.1 Boundary Extraction The extract
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The Development of Web3D-based Open
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Singh et al.(2012) have utilized op
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Monitoring concept on operating asp
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(a) Mining area (Left:2007, Right:2
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geospatial information open platfor
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open platform utilized in open-pit
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Data Acquisition Methods Acquisitio
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(a) Ecological Restoring Area 1 (Le
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possibility of development of open-
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2. DATA ACQUISITION 2.1 Image gathe
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Hugin Pix4Dmapper Pablo d'Angelo et
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utit may be improved using many ste
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Wójcicka, A., and Wróbel, Z., 201
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platforms, which are easy to use an
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SWE framework proposes the followin
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Steenkamp et al. (2009) state that
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technology and are published under
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Measurement value yes Measurement s
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4.3.1 Explore The explore view allo
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Figure 8. Registration of a generic
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participants completely agree with
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467 - 471. Sohraby, K., Minoli, D.,
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In augmented reality a live view of
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Figure 4. Dwellings in an informal
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1. Gen eral crite ria 1.1. Platform
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matching, 3D engine, image tracking
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1.4. Implemented standards OGC ARML
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2.3. Object events 2.4. Display rad
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instructional videos, and basic exa
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application for addressing, the pre
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Environments, 6(4), 355-385. Carmig
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1. INTRODUCTION Use of landmarks in
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the junctions which made with major
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4. IMPLEMENTATION 4.1 Technology Se
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Figure 3: Linear map output with si
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AN OPEN SOURCE WEB SERVICE FOR REGI
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2. IGSN OVERVIEW Figure 1 shows the
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types (e.g., dateType and relationT
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REST API(Fielding, 2000). The servi
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An Open Source Web Service for Regi
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Research Centre (ARRC) and the Nati
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Developing a land use database of t
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Figure 3. Land use input applicatio
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Paddy 19.4 23.7 Upland field, orcha
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Figure 6. Overlay point based land
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Integrating Open Source GIS Softwar
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Advanced GIS course, we recognized
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for undergraduates. Research take t
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Figure 8 The USDA Foodshed project
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4. Data is sent to the web pages ei
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Advances in Civic Co-management wit
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2. JAKARTA'S DISASTER RISK MANAGEME
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The aim of the system is to improve
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8. REFERENCES Baker, J. L., 2012. (
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EVALUATION OF AN OPEN-SOURCE COLLAB
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therelevant stakeholderswith differ
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at each stage of the exercise: · l
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differentmitigationmeasuresaccordin
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students before the exercise. 5 4 3
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the third stage of the exercise in
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doi:10.1016/j.envsoft.2003.12.019.
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e integrated directly in the Web-GI
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3. Implementation The main features
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Phase 1: Earthquake data Input Data
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Figure 4 . Magnitude 7.8 Earthquake
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After adding all the layer maps, th
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EVALUATING FLOOD HAZARD POTENTIAL I
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σ 0 = 10*log 10 (DN 2 ) + CF (1) W
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Figure 4. The geomorphological feat
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from water class in land cover map
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ANALYSIS OF SPATIAL DENSITY UTILIZI
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demographic data. He also states th
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Table 1. The combination of COUNTRY
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NUMBER OF SUBSCRIBERS 300,000 250,0
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Figure 9. The number of foreign tou
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Figure 16. Spatial call activity pa
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Recently, additional tourist inform
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country. It uses R-Studio, a statis
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Geosocial Big Data Analysis Using P
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AN ON-BOARD VISUAL-BASED ATTITUDE E
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Page 273 and 274: 4. RESULTS Summing up, we should no
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Page 281 and 282: 2. DATA AND METHOD The approach ado
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Page 353 and 354: Table 1: Confusion Matrix Crowd sou
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Most solar radiation models compute
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2. OBJECTIVES, SCOPE, AND LIMITATIO
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Figure 4. BSWM Solar Sensors for Va
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4.2 Site Suitability Analysis Inter
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5. RESULTS AND DISCUSSION 5.1 Month
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Figure 8. Monthly Average Real-sky
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Figure 19. GHI for November Figure
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Figure 26. Non-Resource Criteria Su
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Kryza, M. et al. 2010. “Spatial i
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example coordinates agents, based o
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A benefit of using multiple agents
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A local GeoServer instance was set
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Figure 3. Screen captures of search
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In combination with ranking of resu
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INTRODUCTION TO A NEW GEO-REFERENCE
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Figure 2. ‘Click-to-go’ functio
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Figure 5. The conceptual structure
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Figure 6. Software architecture of
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GIS ORIENTED SERVICE OPTIMIZATION T
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Vehicle Routing Problem (VRP) refer
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So, buffer of 2 meters was created
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log data which was the actual dista
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was being served by three vehicles.
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Analyzing the number of customers,
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PO-17 A Study of the Development an
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MODELING OF TERMINOLOGY DATABASE IN
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3.2 Interpretation of the terms 4 I
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Figure 4 shows the result of SWOT a
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Add terms in the database: Super us
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6. REFERENCES Damdinsuren A., 2013.
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PO-20 Vulnerability Assessment Usin
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LEIGHTWEIGHT URBAN COMPUTATION INTE
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where events are instantly propagat
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not be conceived as responsive by a
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3.5. Remote Services Among a few
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4. USE CASES 4.1. Transition Worksh
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to display the rank of the player i
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PO-23 Development of Opensource-bas
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Author Index Aburizaiza, Ahmad O. 2
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