• Journal of Korea Water Resources Association
• /
• v.52 no.5
• /
• pp.361-372
• /
• 2019

The purpose of this study is to develop a two-dimensional land surface flood analysis model based on uniform square grid using the governing equations except for the convective acceleration term in the momentum equation. Finite volume method and implicit method were applied to spatial and temporal discretization. In order to reduce the execution time of the model, parallel computation techniques using CPU were applied. To verify the developed model, the model was compared with the analytical solution and the behavior of the model was evaluated through numerical experiments in the virtual domain. In addition, inundation analyzes were performed at different spatial resolutions for the domestic Janghowon area and the Sebou river area in Morocco, and the results were compared with the analysis results using the CAESER-LISFLOOD (CLF) model. In model verification, simulation results were well matched with the analytical solution, and the flow analyses in the virtual domain were also evaluated to be reasonable. The results of inundation simulations in the Janghowon and the Sebou river area by this study and CLF model were similar with each other and for Janghowon area, the simulation result was also similar to the flooding area of flood hazard map. The different parts in the simulation results of this study and the CLF model were compared and evaluated for each case. The results of this study suggest that the model proposed in this study can simulate the flooding well in the floodplain. However, in case of flood analysis using the model presented in this study, the characteristics and limitations of the model by domain composition method, governing equation and numerical method should be fully considered.

• Journal of Korea Water Resources Association
• /
• v.49 no.6
• /
• pp.469-480
• /
• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.168-168
• /
• 2017

ICT 융합 스마트팜 내의 환경계측 센서, 영상 및 사양관리 시스템의 증가에도 불구하고 이들 장비에서 확보되는 데이터를 적절히 유효하게 활용하는 기술이 미흡한 실정이다. 돈사의 경우 가축의 복지수준, 성장 변화를 실시간으로 모니터링 및 예측할 수 있는 데이터 분석 및 모델링 기술 확보가 필요하다. 이를 위해선 가축의 생리적 변화 및 행동적 변화를 조기에 감지하고 가축의 복지수준을 실시간으로 감시하고 분석 및 예측 기술이 필요한데 이를 위한 대표적인 정보 통신 공학적 접근법 중에 하나가 Data mining 이다. Data mining에 대한 연구 수행에 필요한 다양한 소프트웨어 중에서 Open source로 제공이 되는 4가지 도구를 비교 분석하였다. 스마트 돈사 내에서 열환경 모델링을 목표로 한 데이터 분석에서 고려해야할 요인으로 데이터 분석 알고리즘 도출 시간, 시각화 기능, 타 라이브러리와 연계 기능 등을 중점 적으로 분석하였다. 선정된 4가지 분석 도구는 1) R(https://cran.r-project.org), 2) OpenCV(http://opencv.org), 3) OpenNN (http://www.opennn.net), 4) Orange(http://orange.biolab.si) 이다. 비교 분석을 수행한 운영체제는 Linux-Ubuntu 16.04.4 LTS(X64)이며, CPU의 클럭속도는 3.6 Ghz, 메모리는 64 Gb를 설치하였다. 개발언어 측면에서 살펴보면 1) R 스크립트, 2) C/C++, Python, Java, 3) C++, 4) C/C++, Python, Cython을 지원하여 C/C++ 언어와 Python 개발 언어가 상대적으로 유리하였다. 데이터 분석 알고리즘의 경우 소스코드 범위에서 라이브러리를 제공하는 경우 Cross-Platform 개발이 가능하여 여러 운영체제에서 개발한 결과를 별도의 Porting 과정을 거치지 않고 사용할 수 있었다. 빌트인 라이브러리 경우 순서대로 R 의 경우 가장 많은 수의 Data mining 알고리즘을 제공하고 있다. 이는 R 운영 환경 자체가 개방형으로 되어 있어 온라인에서 추가되는 새로운 라이브러리를 클라우드를 통하여 공유하기 때문인 것으로 판단되었다. OpenCV의 경우 영상 처리에 강점이 있었으며, OpenNN은 신경망학습과 관련된 라이브러리를 소스코드 레벨에서 공개한 것이 강점이라 할 수 있다. Orage의 경우 라이브러리 집합을 제공하는 것에 중점을 둔 다른 패키지와 달리 시각화 기능 및 망 구성 등 사용자 인터페이스를 통합하여 운영한 것이 강점이라 할 수 있다. 열환경 모델링에 요구되는 시간 복잡도에 대응하기 위한 부가 정보 처리 기술에 대한 연구를 수행하여 스마트팜 열환경 모델링을 실시간으로 구현할 수 있는 방안 연구를 수행할 것이다.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.161-161
• /
• 2017

스마트 시설환경의 제어 요소는 난방기, 창 개폐, 수분/양액 밸브 개폐, 환풍기, 제습기 등 직접적으로 시설환경의 조절에 관여하는 인자와 정보 교환을 위한 통신, 사용자 인터페이스 등 간접적으로 제어에 관련된 요소들이 복합적으로 존재한다. PID 제어와 같이 하는 수학적 논리를 바탕으로 한 제어와 전문 관리자의 지식을 기반으로 한 비선형 학습 모델에 의한 제어 등이 공존할 수 있다. 이러한 다양한 요소들을 복합적으로 연동시키기 위해선 기존의 시퀀스 기반 제어 방식에는 한계가 있을 수 있다. 관행의 방식과 같이 시계열 상에서 획득한 충분한 데이터를 이용하여 제어의 양과 시점을 결정하는 방식은 예외 상황에 충분히 대처하기 어려운 단점이 있을 수 있다. 이러한 예외 상황은 자연적인 조건의 변화에 따라 불가피하게 발생하는 경우와 시스템의 오류에 기인하는 경우로 나뉠 수 있다. 본 연구에서는 실시간으로 변하는 시설환경 내의 다양한 환경요소를 실시간으로 분석하고 상응하는 제어를 수행하여 수학적이며 예측 가능한 논리에 의해 준비된 제어시스템을 보완할 방법을 연구하였다. 과거의 고성능 컴퓨팅(HPC; High Performance Computing)은 다수의 컴퓨터를 고속 네트워크로 연동하여 집적적으로 연산능력을 향상시킨 기술로 비용과 규모의 측면에서 많은 투자를 필요로 하는 첨단 고급 기술이었다. 핸드폰과 모바일 장비의 발달로 인해 소형 마이크로프로세서가 발달하여 근래 2 Ghz의 클럭 속도에 이르는 어플리케이션 프로세서(AP: Application Processor)가 등장하기도 하였다. 상대적으로 낮은 성능에도 불구하고 저전력 소모와 플랫폼의 소형화를 장점으로 한 AP를 시설환경의 실시간 제어에 응용하기 위한 방안을 연구하였다. CPU의 클럭, 메모리의 양, 코어의 수량을 다음과 같이 달리한 3가지 시스템을 비교하여 AP를 이용한 마이크로 클러스터링 기술의 성능을 비교하였다.1) 1.5 Ghz, 8 Processors, 32 Cores, 1GByte/Processor, 32Bit Linux(ARMv71). 2) 2.0 Ghz, 4 Processors, 32 Cores, 2GByte/Processor, 32Bit Linux(ARMv71). 3) 1.5 Ghz, 8 Processors, 32 Cores, 2GByte/Processor, 64Bit Linux(Arch64). 병렬 컴퓨팅을 위한 개발 라이브러리로 MPICH(www.mpich.org)와 Open-MP(www.openmp.org)를 이용하였다. 2,500,000,000에 이르는 정수 중 소수를 구하는 연산에 소요된 시간은 1)17초, 2)13초, 3)3초 이었으며, $12800{\times}12800$ 크기의 행렬에 대한 2차원 FFT 연산 소요시간은 각각 1)10초, 2)8초, 3)2초 이었다. 3번 경우는 클럭속도가 3Gh에 이르는 상용 데스크탑의 연산 속도보다 빠르다고 평가할 수 있다. 라이브러리의 따른 결과는 근사적으로 동일하였다. 선행 연구에서 획득한 3차원 계측 데이터를 1초 단위로 3차원 선형 보간법을 수행한 경우 코어의 수를 4개 이하로 한 경우 근소한 차이로 동일한 결과를 보였으나, 코어의 수를 8개 이상으로 한 경우 앞선 결과와 유사한 경향을 보였다. 현장 보급 가능성, 구축비용 및 전력 소모 등을 종합적으로 고려한 AP 활용 마이크로 클러스터링 기술을 지속적으로 연구할 것이다.

• The KIPS Transactions:PartB
• /
• v.12B no.6 s.102
• /
• pp.671-678
• /
• 2005

In this paper, we suggest an algorithm that allows us to extract the important obbject from motion pictures and then replace the background with arbitrary images. The suggested technique can be used not only for protecting privacy and reducing the size of data to be transferred by removing the background of each frame, but also for replacing the background with user-selected image in video communication systems including mobile phones. Because of the relatively large size of image data, digital image processing usually takes much of the resources like memory and CPU. This can cause trouble especially for mobile video phones which typically have restricted resources. In our experiments, we could reduce the requirements of time and memory for processing the images by restricting the search area to the vicinity of major object's contour found in the previous frame based on the fact that the movement of major object is not wide or rapid in general. Specifically, we detected edges and used the edge image of the initial frame to locate candidate-object areas. Then, on the located areas, we computed the difference image between adjacent frames and used it to determine and trace the major object that might be moving. And then we computed the contour of the major object and used it to separate major object from the background. We could successfully separate major object from the background and replate the background with arbitrary images.

• Geophysics and Geophysical Exploration
• /
• v.2 no.1
• /
• pp.17-25
• /
• 1999

A traveltime tomography has been carried out by transforming electromagnetic data in frequency domain to wave-like domain. The transform uniquely relates a field satisfying a diffusion equation to an integral of the corresponding wavefield. But direct transform of frequency domain magnetic fields to wave-field domain is ill-posed problem because the kernel of the integral transform is highly damped. In this study, instead of solving such an unstable problem, it is assumed that wave-fields in transformed domain can be approximated by sum of ray series. And for further simplicity, reflection and refraction energy compared to that of direct wave is weak enough to be neglected. Then first arrival can be approximated by calculating the traveltime of direct wave only. But these assumptions are valid when the conductivity contrast between background medium and the target anomalous body is low enough. So this approach can only be applied to the models with low conductivity contrast. To verify the algorithm, traveltime calculated by this approach was compared to that of direct transform method and exact traveltime, calculated analytically, for homogeneous whole space. The error in first arrival picked by this study was less than that of direct transformation method, especially when the number of frequency samples is less than 10, or when the data are noisy. Layered earth model with varying conductivity contrasts and inclined dyke model have been successfully imaged by applying nonlinear traveltime tomography in 30 iterations within three CPU minutes on a IBM Pentium Pro 200 MHz.

• Journal of Korea Spatial Information System Society
• /
• v.8 no.2 s.17
• /
• pp.91-107
• /
• 2006

To handling the extreme situation that must manage positional information of a very large volume, at least millions of moving objects. A cluster-based sealable distributed computing system architecture, called the GALIS which consists of multiple data processors, each dedicated to keeping records relevant to a different geographical zone and a different time zone, was proposed. In this paper, we proposed a valid time management and time-zone shifting scheme, which are essential in realizing the long-term location data subsystem of GALIS, but missed in our previous prototype development. We explain how to manage valid time of moving objects to avoid ambiguity of location information. We also describe time-zone shifting algorithm with three variations, such as Real Time-Time Zone Shifting, Batch-Time Zone Shifting, Table Partitioned Batch-Time Zone Shifting, Through experiments related with query processing time and CPU utilization, we show the efficiency of the proposed time-zone shifting schemes.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.1 s.39
• /
• pp.71-85
• /
• 2006

The environment of computational grid is composed of the LAN/WAN each of which has different efficiency and heterogeneous network conditions, and where various programs are running. In this environment, the role of the resource selection broker is very important because the work of each node is performed by considering heterogeneous network environment and the computing power of each node according to the characteristics of a program. In this paper, a new resource selection broker is presented that decides the number of work processes to be allocated at each node by considering network state information and the performance of each node according to the characteristics of a program in the environment of computational grid. The proposed resource selection broker has three steps as follows. First, the performance ratio of each node is computed using latency-bandwidth-cpu mixture information reflecting the characteristics of a program, and the number of work processes that will be performed at each node are decided by this ratio. Second, RSL file is automatically made based on the number of work processes decided at the previous step. Finally, each node creates work processes by using that RSL file and performs the work which has been allocated to itself. As experimental results, the proposed method reflecting characteristics of a program, compared with the existing (uniformity) and latency-bandwidth method is improved $278%\sim316%,\;524%\sim595%,\;924%\sim954%$ in the point of work amount, work process number, and node number respectively.

• Journal of Software Engineering Society
• /
• v.28 no.1
• /
• pp.1-6
• /
• 2019

Google released an initial version of Android that runs Dex(Dalvik Executable) through the Dalvik Runtime. Since Dalvik Runtime is based on interpreter, JIT(Just-in-time) compilation has been applied to improve performance. After Lollipop(Android 5.0) Dalvik Runtime has replaced with ART Runtime which support AOT (Ahead-of-time) compilation of Dex into Native Code. The late st Android has a problem that the application execution speed is slow until the AOT compilation is completed according to the actual usage record after the installation of the app. To improve the problem we have investigate the characteristics of profile that can improve the execution speed of the application and generate the profile automatically. Finally we propose a method that can optimize the application at install time. With the proposed method we can optimize selectively at install time and can help improving the execution speed of the app from the initial execution.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.26 no.4D
• /
• pp.687-693
• /
• 2006

Image co-registration is the process of overlaying two images of the same scene, one of which represents a reference image, while the other is geometrically transformed to the one. In order to improve efficiency and effectiveness of the co-registration approach, the author proposed a pre-qualified area matching algorithm which is composed of feature extraction with canny operator and area matching algorithm with cross correlation coefficient. For refining matching points, outlier detection using studentized residual was used and iteratively removes outliers at the level of three standard deviation. Throughout the pre-qualification and the refining processes, the computation time was significantly improved and the registration accuracy is enhanced. A prototype of the proposed algorithm was implemented and the performance test of 3 Landsat images of Korea. showed: (1) average RMSE error of the approach was 0.435 pixel; (2) the average number of matching points was over 25,573; (3) the average processing time was 4.2 min per image with a regular workstation equipped with a 3 GHz Intel Pentium 4 CPU and 1 Gbytes Ram. The proposed approach achieved robustness, full automation, and time efficiency.