• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.258-264
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• 2018

This paper presents application of a differential search (DS) meta-heuristic optimization algorithm for optimal operation of a micro grid system. The DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. The micro grid system consists of a wind turbine, a diesel generator, a fuel cell, and a photovoltaic system. The wind turbine generator is modeled by considering the characteristics of variable output. Optimization is aimed at minimizing the cost function of the system, including fuel costs and maximizing fuel efficiency to generate electric power. The simulation was applied to a micro grid system only. This study applies the DS algorithm with excellence and efficiency in terms of coding simplicity, fast convergence speed, and accuracy in the optimal operation of micro grids based on renewable energy resources, and we compared its optimum value to other algorithms to prove its superiority.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.367-372
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• 2013

In Speech recognition system, there is a problem with phoneme in the model training and it cause a stored mode regeneration process which come into being appear time and more costs. In this paper, we propose the methode of likely phoneme model schema using decision tree clustering. Proposed system has a robust and correct sound model which system apply the decision tree clustering methode form generate model, therefore this system reduce the regeneration process and provide a retrieve the phoneme unit in probability model. Also, this proposed system provide a additional likely phoneme model and configured robust correct sound model. System performance as a result of represent vocabulary dependence recognition rate of 98.3%, vocabulary independence recognition rate of 98.4%.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.5
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• pp.53-59
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• 2007

Now, the study is activity that the energy market depending on a fossil fuel tend to change different way. In middle of the study compositive use of renewable energy(fuel cell and wind power, solar cell, etc.) is dispersion power system which concern is increasing. But in the case of generation of electric wind power system is changeable to be turbulence and wind and win speed are changeable in several seconds, so making the best of wind energy the MPPT that role in this case is important. In this paper suggest a MPPT which is making a use of information of wind speed and turning speed, windmill, electric power but it is simpler than former way. We could verify that a proposed controller working at the highest point of electric power when wind speed is regular speed and changable speed through the simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.651-659
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• 2004

The Fast Handover protocol ［1］ provides seameless handover in wireless If networks by minimizing handover latency, which uses anticipation based on layer 2 (L2) trigger information. Therefore, it incurs higher signaling costs compared with the basic Mobile U protocol. Furthermore, since the L2 trigger is based on fluctuating wireless channel states, the handover anticipation may sometimes be incorrect. In the case of incorrect anticipation, unnecessary buffer space may be used for the purpose of providing a smooth handover. Therefore, it is essentical to analyze these overhead costs, in order to evaluate and compare the performance of Fast Handover with that of the basic Mobile U protocol. In this paper, we analyzed the overhead associated with Fast Handover including the signaling cost and the packet delivery cost. We formulated these costs based on a timing diagram and compared Fast Handover with basic Mobile Ipv6 in terms of their packet loss rates and buffer requirements. Also, we studied the impact of the L2 triggering time on the total overhead cost.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.4
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• pp.289-309
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• 2014

A rotor blade is an important device that converts kinetic energy of wind into mechanical energy. Rotor blades affect the power performance, energy conversion efficiency, and loading and dynamic stability of wind turbines. Therefore, considering the characteristics of a wind turbine system is important for achieving optimal blade design. This study examined the general blade design procedure for a wind turbine system and aero-structure design results for a 2-MW class wind turbine blade (KR40.1b). As suggested above, a rotor blade cannot be designed independently, because its ultimate and fatigue loads are highly dependent on system operating conditions. Thus, a reference 2-MW wind turbine system was also developed for the system integrated load calculations. All calculations were performed in accordance with IEC 61400-1 and the KR guidelines for wind turbines.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.137-145
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• 2002

In the method of 3D modeling, stereo matching method which obtains three dimensional depth information from the two images is taken from the different view points. In general, it is very essential work for the 3D modeling from 2D stereo images to estimate the exact disparity through fading the conjugate pair of pixel from the left and right image. In this paper to solve the problems of the stereo image disparity estimation, we introduce a novel approach method to improve the exactness and efficiency of the disparity. In the first place, we perform a wavelet transformation of the stereo images and set the reference points in the image by the feature-based matching method. This reference points have very high probability over 95 %. In the base of these reference points we can decide the size of the variable block searching windows for estimating dense disparity of area based method and perform the ordering constraint to prevent mismatching. By doing this, we could estimate the disparity in a short time and solve the occlusion caused by applying the fried-sized windows and probable error caused by repeating patterns.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.162-162
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• 2017

구글에서 공개한 Tensorflow를 이용한 여러 학문 분야의 연구가 활발하다. 농업 시설환경을 대상으로 한 빅데이터의 축적이 증가함과 아울러 실효적인 정보 획득을 위한 각종 데이터 분석 및 마이닝 기법에 대한 연구 또한 활발한 상황이다. 한편, 타 분야의 성공적인 심층학습기법 응용사례에 비하여 농업 분야에서의 응용은 초기 성장 단계라 할 수 있다. 이는 농업 현장에서 취득한 정보의 난해성 및 완성도 높은 생육/환경 모델링 정보의 부재로 실효적인 전과정 처리 기술 도출에 소요되는 시간, 비용, 연구 환경이 상대적으로 부족하기 때문일 것이다. 특히, 센서 기반 데이터 취득 기술 증가에 따라 비약적으로 방대해진 수집 데이터를 시간 복잡도가 높은 심층 학습 모델링 연산에 기계적으로 단순 적용할 경우 시간 효율적인 측면에서 성공적인 결과 도출에 애로가 있을 것이다. 매우 높은 시간 복잡도를 해결하기 위하여 제시된 하드웨어 가속 기능의 경우 일부 개발환경에 국한이 되어 있다. 일례로, 구글의 Tensorflow는 오픈소스 기반 병렬 클러스터링 기술인 MPICH를 지원하는 알고리즘을 공개하지 않고 있다. 따라서, 본 연구에서는 심층학습 기법 연구에 있어서, 예상 가능한 다양한 자원을 활용하여 최대한 연산의 결과를 빨리 도출할 수 있는 하드웨어적인 접근 방법을 모색하였다. 호스트에서 수행하는 일방적인 학습 알고리즘과 달리 이기종간 심층 학습이 가능하기 위해선 우선, NFS(Network File System)를 이용하여 데이터 계층이 상호 연결이 되어야 한다. 이를 위해서 고속 네트워크를 기반으로 한 NFS의 이용이 필수적이다. 둘째로 제한된 자원의 한계를 극복하기 위한 메모 공유 라이브러리가 필요하다. 셋째로 이기종간 프로세서에 최적화된 병렬 처리용 컴파일러를 이용해야 한다. 가장 중요한 부분은 이기종간의 처리 능력에 따른 작업을 고르게 분배할 수 있는 작업 스케쥴링이 수행되어야 하며, 이는 처리하고자 하는 데이터의 형태에 따라 매우 가변적이므로 해당 데이터 도메인에 대한 엄밀한 사전 벤치마킹이 수행되어야 한다. 이러한 요구조건을 대부분 충족하는 Open-CL ver1.2(https://www.khronos.org/opencl/)를 이용하였다. 최신의 Open-CL 버전은 2.2이나 본 연구를 위하여 준비한 4가지 이기종 시스템에서 모두 공통적으로 지원하는 버전은 1.2이다. 실험적으로 선정된 4가지 이기종 시스템은 1) Windows 10 Pro, 2) Linux-Ubuntu 16.04.4 LTS-x86_64, 3) MAC OS X 10.11 4) Linux-Ubuntu 16.04.4 LTS-ARM Cortext-A15 이다. 비교 분석을 위하여 NVIDIA 사에서 제공하는 Pascal Titan X 2식을 SLI로 구성한 시스템을 준비하였다. 개별 시스템에서 별도로 컴파일 된 바이너리의 이름을 통일하고, 개별 시스템의 코어수를 동일하게 균등 배분하여 100 Hz의 데이터로 입력이 되는 온도 정보와 조도 정보를 입력으로 하고 이를 습도정보에 Linear Gradient Descent Optimizer를 이용하여 Epoch 10,000회의 학습을 수행하였다. 4종의 이기종에서 총 32개의 코어를 이용한 학습에서 17초 내외로 연산 수행을 마쳤으나, 비교 시스템에서는 11초 내외로 연산을 마치는 결과가 나왔다. 기보유 하드웨어의 적절한 활용이 가능한 심층학습 기법에 대한 연구를 지속할 것이다

• Applied Chemistry for Engineering
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• v.29 no.2
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• pp.215-224
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• 2018

Influences of the magnetic field on 5, 10 and 15 wt% (1.5, 3 and 4.5 M) HCl solution behaviour, which has widespread applications in petroleum well acidizing, were investigated in various conditions. Differences in the pH of magnetized hydrochloric acid compared to that of normal hydrochloric acid were measured. Taguchi design of experimental (DoE) method were used to model effects of the magnetic field intensity, concentration, velocity and temperature of acid in addition to the elapsed time. The experimental results showed that the magnetic field decreases [$H^+$] concentration of hydrochloric acid up to 42% after magnetization. Increasing the magnetic field intensity (with 28% contribution), concentration (with 42% contribution), and velocity of acid increases the effect of magnetic treatment. The results also demonstrated that the acid magnetization was-not influenced by the fluid velocity and heating. It was also displayed that the acid preserves its magnetic memory during time. The optimum combination of factors with respect to the highest change of [$H^+$] concentration was obtained as an acid concentration of 10% and an applied magnetic field of 4,300 Gauss. Due to the reduction of HCl reaction rate under the magnetization process, it can be proposed that the magnetized HCl is a cost effective and reliable alternative retarder in the matrix acidizing of hydrocarbon (crude oil and natural gas) wells.

• Analytical Science and Technology
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• v.27 no.2
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• pp.79-91
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• 2014

Solubility data of carbon dioxide ($CO_2$) in 1-butyl-3-methylpiperidinium bis(trifluoromethylsulfonyl)imide ($[bmpip][Tf_2N]$) ionic liquid are presented at pressures up to about 30 MPa and at temperatures between 303 K and 343 K. As far as we know, the data on the $CO_2$ solubility in the $[bmpip][Tf_2N]$ ionic liquid have never been reported in the literature by other investigators. The solubilities of $CO_2$ were determined by measuring the bubble point or cloud point pressures of the $CO_2+[bmpip][Tf_2N]$ mixtures with various compositions using a high-pressure equilibrium apparatus equipped with a variable-volume view cell. To observe the effect of the cation composing the ionic liquid on the $CO_2$ solubility, the $CO_2$ solubilities in $[bmpip][Tf_2N]$ used in this study were compared with those in 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)-imide ($[bmim]Tf_2N]$). As the equilibrium pressure increased, the $CO_2$ solubility in $[bmpip][Tf_2N]$ increased sharply. On the other hand, the $CO_2$ solubility decreased with increasing temperature. The mole fraction-based $CO_2$ solubilities were almost the same for both $[bmpip][Tf_2N]$ and $[bmim][Tf_2N]$, regardless of temperature and pressure. The phase equilibrium data for the $CO_2+[bmpip][Tf_2N]$ systems have been correlated using the Peng-Robinson equation of state.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.111-121
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• 2006

Recently, many studies have been performed to apply airborne LIDAR data to extracting urban models. In order to model efficiently the man-made objects which are the main components of these urban models, it is important to extract automatically planar patches from the set of the measured three-dimensional points. Although some research has been carried out for their automatic extraction, no method published yet is sufficiently satisfied in terms of the accuracy and completeness of the segmentation results and their computational efficiency. This study thus aimed to developing an efficient approach to automatic segmentation of planar patches from the three-dimensional points acquired by an airborne LIDAR system. The proposed method consists of establishing adjacency between three-dimensional points, grouping small number of points into seed patches, and growing the seed patches into surface patches. The core features of this method are to improve the segmentation results by employing the variable threshold value repeatedly updated through a statistical analysis during the patch growing process, and to achieve high computational efficiency using priority heaps and sequential least squares adjustment. The proposed method was applied to real LIDAR data to evaluate the performance. Using the proposed method, LIDAR data composed of huge number of three dimensional points can be converted into a set of surface patches which are more explicit and robust descriptions. This intermediate converting process can be effectively used to solve object recognition problems such as building extraction.