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Tangpattanakul P.,Geo Informatics and Space Technology Development Agency Public Organization
2015 4th International Conference on Informatics, Electronics and Vision, ICIEV 2015

This paper presents two algorithms, which are a nondominated sorting genetic algorithm II (NSGA-II) and an indicator-based multi-objective local search (IBMOLS), for solving a bi-objective p-Median problem. The bi-objective p-Median problem is a problem of finding p location points to install facilities from a set of m candidates. This problem considers two objectives: minimizing the sum of the distances from each customer to the nearest facility and minimizing the sum of the costs to install each facility in the selected location points. NSGA-II and IBMOLS are efficient algorithms in the area of multi-objective optimization. Experiments are conducted on generated instances. Hypervolume values of the approximate Pareto fronts are computed and the obtained results from IBMOLS and NSGA-II are compared. © 2015 IEEE. Source

Jitkajornwanich K.,Geo Informatics and Space Technology Development Agency Public Organization | Elmasri R.,University of Texas at Arlington
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Large amounts of "big data" are generated every day, many in a "raw" format that is difficult to analyze and mine. This data contains potential hidden meaningful concepts, but much of the data is superfluous and not of interest to the domain experts. Thus, dealing with big raw data solely by applying a set of distributed computing technologies (e.g., MapReduce, BSP [Bulk Synchronous Parallel], and Spark) and/or distributed storage systems, namely NoSQL, is generally not sufficient. Extracting the full knowledge that is hidden in the raw data is necessary to efficiently enable analysis and mining. The data needs to be processed to remove the superfluous parts and generate the meaningful domainspecific concepts. In this paper, we propose a framework that incorporates conceptual modeling and EER principle to effectively extract conceptual knowl‐ edge from the raw data so that mining and analysis can be applied to the extracted conceptual data. © Springer International Publishing Switzerland 2015. Source

Tawala J.,Geo Informatics and Space Technology Development Agency Public Organization
34th Asian Conference on Remote Sensing 2013, ACRS 2013

Car robbery is one the serious problems in a large city like Bangkok, the capital of Thailand, and statistics showed that one or two vehicles were stolen every day. The objective of this study is to identify risk area for car robbery in Lat Phrao district of Bangkok, The excel file of 5-year period car stolen records collected during 2005 - 2009 by Lat Phrao police station were converted into GIS format, to identify and describe spatial and temporal distribution of the incident. Next, the data were spatially interpolated using various algorithms, and the outputs were compared to select the most appropriate output. The result showed that the kernel density estimation described spatial distribution of the robbery very well, and Bang Kapi and Happy Land sub districts had the highest risk for car robbery. To make the output more understandable for general users, the kernel density estimation was overlaid on high resolution satellite imageries in Google Earth. The results provide a basis for further study on risk areas for the car robbery, analysis of factors leading to the risk, and help law enforcement administrators in making better decisions. Source

Phodee P.,Chulalongkorn University | Trisirisatayawong I.,Chulalongkorn University | Aobpaet A.,Geo Informatics and Space Technology Development Agency Public Organization
Engineering Journal

In this study, we investigate the March 24th 2011 Mw=6.8 Tarlay earthquake, Myanmar using Interferometric Synthetic Aperture Radar (InSAR) and inversion analysis. We firstly invert InSAR coseismic displacement from our previous study. The inversions are carried out in both single and multi-patch model. The coseismic slip of 2.5 meter from single-patch solution is then combined with long-term slip rate from geomorphological study, resulting in an estimate of 1,140-4,160 years recurrence period. Then, coulomb stress changes on nearby faults in northern Thailand are calculated. It is found that stress in western and middle segments of Mae Chan fault decreases significantly while stress increase in eastern segment of Mae Chan, Mae Ing and Chiang Kham fault. Finally, the results from PSInSAR of 29 Radarsat-2 images reveal postseismic displacement rates between-24.4.6 to 34.5 millimeters per year. © 2014, Engineering Journal. All right reserved. Source

Sritarapipat T.,Geo Informatics and Space Technology Development Agency Public Organization | Rakwatin P.,Geo Informatics and Space Technology Development Agency Public Organization | Kasetkasem T.,Kasetsart University
Sensors (Basel, Switzerland)

Rice crop height is an important agronomic trait linked to plant type and yield potential. This research developed an automatic image processing technique to detect rice crop height based on images taken by a digital camera attached to a field server. The camera acquires rice paddy images daily at a consistent time of day. The images include the rice plants and a marker bar used to provide a height reference. The rice crop height can be indirectly measured from the images by measuring the height of the marker bar compared to the height of the initial marker bar. Four digital image processing steps are employed to automatically measure the rice crop height: band selection, filtering, thresholding, and height measurement. Band selection is used to remove redundant features. Filtering extracts significant features of the marker bar. The thresholding method is applied to separate objects and boundaries of the marker bar versus other areas. The marker bar is detected and compared with the initial marker bar to measure the rice crop height. Our experiment used a field server with a digital camera to continuously monitor a rice field located in Suphanburi Province, Thailand. The experimental results show that the proposed method measures rice crop height effectively, with no human intervention required. Source

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