• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.309-311
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• 2014

Despite increasing demands for big data application based on the analysis of scattered unstructured data, few relevant studies have been reported. Accordingly, the present study suggests a technique enabling a sentence-based semantic analysis by extracting objects from collected web information and automatically analyzing the relationships between such objects with collective intelligence and language processing technology. To be specific, collected information is stored in DBMS in a structured form, and then morpheme and feature information is analyzed. Obtained morphemes are classified into objects of interest, marginal objects and objects of non-interest. Then, with an inter-object attribute recognition technique, the relationships between objects are analyzed in terms of the degree, scope and nature of such relationships. As a result, the analysis of relevance between the information was based on certain keywords and used an inter-object relationship extraction technique that can determine positivity and negativity. Also, the present study suggested a method to design a system fit for real-time large-capacity processing and applicable to high value-added services.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.360-363
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• 2022

According to the 2018 Kaggle ML & DS Survey, among the proportions of frameworks for machine learning and data science, TensorFlow and Keras each account for 41.82%. It was found to be 34.09%, and in the case of development programming, it is confirmed that about 82% use Python. A significant number of machine learning and deep learning structures utilize the Keras framework and Python, but in the case of Python, distribution and execution are limited to the Python script environment due to the script language, so it is judged that it is difficult to operate in various environments. This paper implemented a machine learning and deep learning system using C# and Keras running in Visual Studio 2019. Using the Mnist dataset, 100 tests were performed in Python 3.8,2 and C# .NET 5.0 environments, and the minimum time for Python was 1.86 seconds, the maximum time was 2.38 seconds, and the average time was 1.98 seconds. Time 1.78 seconds, maximum time 2.11 seconds, average time 1.85 seconds, total time 37.02 seconds. As a result of the experiment, the performance of C# improved by about 6% compared to Python, and it is expected that the utilization will be high because executable files can be extracted.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.167-171
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• 2007

Application areas of Knowledge Discovery in Database (KDD) have been expanded into many R&D management processes including technology trends analysis, forecasting and evaluation etc. Established research field such as informetrics (or scientometrics) has recently fully utilized techniques or methods of KDD. Various systems have been developed to support works of analyzing large-scale R&D related databases such as patent DB or bibliographic DB by a few researchers or institutions. But extant systems have some problems for korean users to use. Their prices is not cheap, korean language process not available, and user's demands not reflected. To solve these problems, Korea Institute of Science and Technology Information (KISTI) developed stand-alone type information analysis system named as KnowledgeMatrix. KnowledgeMatrix system offer various functions to analyze retrieved data set from databases. Knowledge Matrix main operation unit is composed of user-defined lists and matrix generation, cluster analysis, visualization, data pre-processing. KnowledgeMatrix show better performances and offer more various functions than extant systems.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.31-31
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• 2023

During December 2022, the northeast monsoon, which dominates the south and the Gulf of Thailand, had significant rainfall that impacted the lower southern region, causing flash floods, landslides, blustery winds, and the river exceeding its bank. The Golok River, located in Narathiwat, divides the border between Thailand and Malaysia was also affected by rainfall. In flood management, instruments for measuring precipitation and water level have become important for assessing and forecasting the trend of situations and areas of risk. However, such regions are international borders, so the installed measuring telemetry system cannot measure the rainfall and water level of the entire area. This study aims to predict 72 hours of water level and evaluate the situation as information to support the government in making water management decisions, publicizing them to relevant agencies, and warning citizens during crisis events. This research is applied to machine learning (ML) for water level prediction of the Golok River, Lan Tu Bridge area, Sungai Golok Subdistrict, Su-ngai Golok District, Narathiwat Province, which is one of the major monitored rivers. The eXtreme Gradient Boosting (XGBoost) algorithm, a tree-based ensemble machine learning algorithm, was exploited to predict hourly water levels through the R programming language. Model training and testing were carried out utilizing observed hourly rainfall from the STH010 station and hourly water level data from the X.119A station between 2020 and 2022 as main prediction inputs. Furthermore, this model applies hourly spatial rainfall forecasting data from Weather Research and Forecasting and Regional Ocean Model System models (WRF-ROMs) provided by Hydro-Informatics Institute (HII) as input, allowing the model to predict the hourly water level in the Golok River. The evaluation of the predicted performances using the statistical performance metrics, delivering an R-square of 0.96 can validate the results as robust forecasting outcomes. The result shows that the predicted water level at the X.119A telemetry station (Golok River) is in a steady decline, which relates to the input data of predicted 72-hour rainfall from WRF-ROMs having decreased. In short, the relationship between input and result can be used to evaluate flood situations. Here, the data is contributed to the Operational support to the Special Water Resources Management Operation Center in Southern Thailand for flood preparedness and response to make intelligent decisions on water management during crisis occurrences, as well as to be prepared and prevent loss and harm to citizens.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.555-559
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• 2006

This paper will intend to contribute to extracting and storing various form of information on user interests by using structural rules user makes and XML-based word document converting techniques. The system named PPE consists of three essential element. One is converting element which converts word documents like HWP, DOC into XML documents, another is extracting element to prepare structural rules and extract concerned information from XML document by structural rules, and the other is storing element to make final XML document or store it into database system. For word document converting, we developed OCX based word converting daemon. Helping user to extracting information, we developed script language having native function/variable processing engine extended from XSLT. This system can be used in the area of constructing word document contents DB or providing various information service based on RAW word documents. We really applied it to project management system and project result management system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.277-280
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• 2015

Smishing, Phishing personal privacy caused by Incident accidents such as Phishing information security has become a hot topic. Such incidents have privacy in personal information management occurs due to a lack of user awareness. This paper is based on the existing structure of the XML Tag question bank used a different Key-Value Structure-based JSON. JSON is an advantage that does not depend on the language in the text-based interchange format. The proposed system is divided into information security sector High, Middle and Low grade. and Provides service to the user through the free space and the smart device and the PC to the constraints of time. The use of open source Apache Load Balancing technology for reliable service. It also handles the user's web page without any training sessions Require server verification result of the training(training server). The result is sent to the training server using jQuery Ajax. and The resulting data are stored in the database based on the user ID. Also to be used as a training statistical indicators. In this paper, we design a level training system to enhance the user's information security awareness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.875-878
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• 2015

In this paper, we propose an intra prediction hardware architecture with less processing time, computations and reduced hardware area for a high performance HEVC encoder. The proposed intra prediction hardware architecture uses common operation units to reduce computational complexity and uses $4{\times}4$ block unit to reduce hardware area. In order to reduce operation time, common operation unit uses one operation unit to generate predicted pixels and filtered pixels in all prediction modes. Intra prediction hardware architecture introduces the $4{\times}4$ PU design processing to reduce the hardware area and uses intemal registers to support $32{\times}32$ PU processmg. The proposed hardware architecture uses ten common operation units which can reduce execution cycles of intra prediction. The proposed Intra prediction hardware architecture is designed using Verilog HDL(Hardware Description Language), and has a total of 41.5k gates in TSMC $0.13{\mu}m$ CMOS standard cell library. At 150MHz, it can support 4K UHD video encoding at 30fps in real time, and operates at a maximum of 200MHz.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.166-171
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• 2000

밀티빔 음향 측심기 (Multibeam Echo Sounder)는 탐사선에 수직방향으로 해저면을 주사(Swath)하여, 한번의 송수신(Ping)으로 다중의 빔자료를 얻을 수 있는 측심기로, 해저면에 반사되어 되돌아오는 음파의 음압을 기록하고, 사이드 스캔 소나 자료도 동시에 취득하는 기능을 가지고 있으므로, 측심된 해저 지형(Bathymetry)과 해저 지형을 덮고 있는 해저면의 퇴적 상황(Sediment Environment)도 동시에 얻을 수 있는 다목적 측심기이다. 본 논문에서는 L3사의 Sea Beam 2100 멀티빔 음향 측심기를 통해 얻은 자료를 처리하여, 3차원 공간 데이터인 DEM(Digital Elevation Model)을 생성하고, VRML을 이용한 웹상에서의 해저 지형 가시화를 통해, 세계 어느 곳에서나 웹을 통하여 쉽게 정보를 공유할 수 있는 3차원 해저 지리 정보 시스템의 구현을 목적으로 한다. 멀티빔 음향 측심기를 통해 얻어진 자료는 항해 자료 보정, 음속 보정, 빔 좌표 계산과 분리, 오측심 자료 제거, 조석 보정 등의 단계를 거쳐 측심자료의 정확도 및 신뢰도를 높이는 과정을 거치게 된다. 보정된 멀티빔 음향 측심자료는 무작위 점 사상(Point Topology)으로 산재 되어 있는 빔 자료를 임의의 단위영역으로 변환하는 과정을 거쳐야 하는데, 이 과정을 격자화라고 한다. 자료의 격자화를 통해 3차원 공강 데이터인 DEM 파일을 제작하고, 이 DEM 파일과 음압 영상을 이용해 웹상에서의 3차원 해저 지형의 가시화를 실현한다. 웹상에서의 3차원 지형 가시화에서 방대한 양의 지형 데이터는 데이터 전송 시간과 렌더링 시간에 치명적인 문제이다. 따라서, 렌더링 시간과 데이터 전송 시간을 단축시키기 위한, 지형 자료의 LOD(Level of Detail)를 통해, VRML을 이용한 보다 효과적인 웹상에서의 3차원 해저 지형의 가시화를 실현한다.면 기업은 고객으로 공간적인 제약으로 인한 불신을 불식시키는 신뢰감을 주게 된다. 이러한 고객서비스 향상과 물류비용 절감은 사이버 쇼핑몰이 전국 어디서나 우리의 안방에서 자연스럽게 점할 수 있는 상황을 만들 것이다.SP가 도입되어, 설계업무를 지원하기위한 기본적인 시스템 구조를 구상하게 된다. 이와 함께 IT Model을 구성하게 되는데, 객체지향적 접근 방법으로 Model을 생성하고 UML(Unified Modeling Language)을 Tool로 사용한다. 단계 4)는 Software Engineering 관점으로 접근한다. 이는 최종산물이라고 볼 수 있는 설계업무 지원 시스템을 Design하는 과정으로, 시스템에 사용될 데이터를 Design하는 과정과, 데이터를 기반으로 한 기능을 Design하는 과정으로 나눈다. 이를 통해 생성된 Model에 따라 최종적으로 Coding을 통하여 실제 시스템을 구축하게 된다.the making. program and policy decision making, The objectives of the study are to develop the methodology of modeling the socioeconomic evaluation, and build up the practical socioeconomic evaluation model of the HAN projects including scientific and technological effects. Since the HAN projects consists of 18 subprograms, it is difficult In evaluate all the subprograms simultaneously. Despite, each program is being performed under the category of HAN projects, so the common soci

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.349-352
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• 2004

4D system has applied to construction project as a management tool after the late 1990's. Various 4D systems have been developed, however they have some problems that should be improved. Especially, the 4D system for civil engineering project needs synthesized 3D model between natural ground condition and physical facility type. It is a different problem comparing with the system for building project. 1'his study suggests an automatically synthesizing methodology between ground triangulate network and design triangulate network. Furthermore the study develops an application methodology of multi-texturing technique defined in virtual reality modeling language (VRML) for skipping the 3D model synthesizing process from the 4D model development processes. The suggested methodology is applied to the prototype of real 4D system. The proposed technique for 3D modeling may be used as an essential methodology for developing 4D system for civil engineering projects.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2006.04a
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• pp.166-170
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• 2006

본 연구에서는 폐광산 주변에 산재되어 있는 광미/광폐석을 처리하기 위하여 고형화 실증 실험을 수행하였다. 고형화 공정에서 흔히 사용하는 포틀랜드 시멘트와 MSG-E, MSG-N을 고화제로 사용하였으며 현장 광미 및 광폐석을 대상으로 고화체를 양생하고 고화체의 압축강도 및 중금속 용출 정도를 측정하였다. 고화체의 물리/화학적 특성을 비교하기 위해 광미/고화제 비율, 배합수/고화제 비율 그리고 고화체 양생기간을 실험인자로 설정하였다. 실험 결과 광미/고화제의 비율 1:1 만을 고려하더라도 중금속 용출의 급격한 감소가 이루어지는 것을 확인할 수 있었으며 광미/고화제의 비율을 3:1 이하로 유지시키는 경우, 고화체의 압축강도가 현행 폐기물 관리법(20조 관련)에서 규정하고 있는 차단형 매립시설 내부막의 압축강도 기준인 $0.21kgf/mm^2$ 보다 높은 것으로 나타났다. 다양한 pH를 갖는 수용액에 대하여 시간에 따른 고화체의 중금속 용출률을 측정한 결과, 수용액의 pH가 1과 13인 강산/강염기 용액에서 일부 중금속의 용출 농도가 지하수 생활용수 기준치를 초과하였으나, pH와 3 - 11인 경우에는 중금속 용출률이 급격히 감소하여 모두 기준치 이하를 나타내었다. 또한, pH가 1과 13인 수용액의 경우에도 고화체와 반응하는 시간이 증가할수록 고화체의 buffering 효과에 의해 수용액의 pH가 감소하였다. 이러한 결과는 현장에서 접촉수의 pH가 강산이나 강염기라 하여도, 고화체의 buffering 효과에 의해 시간이 지남에 따라 수용액의 pH가 낮아져 고화체로부터의 중금속 용출은 매우 감소할 것임을 의미한다.ss of an active application defined using the model. The technique is developed in a platform- and language-independent way, and it is algorithmic and can be automated by computer program. We give an example dealing with network auction to illustrate the use of the model and the verification technique.품으로 내부 온도분포를 측정하였으며, 유한차분법 프로그램으로 대류열전달계수를 결정하였다. 대류열전달계수는 792에서 2,107 W/m$^2$로 분석되었다. 대류열전달 계수는 액상식품과의 상대속도가 증가함에 따라서 증가하였고, 점도가 증가함에 따라서는 감소하였다.ce of precision/recall of 90.99%/92.52%, and 93.39%/93.41% respectively. 의한 변성에 부분적으로 보호 작용을 나타 낼 것으로 추정된다.경(製麴72時間頃)의 활성(活性)은 보리쌀국(麴), 밀가루국(麴), 찹쌀국(麴), 고구마국(麴)의 순이었다.험 결과 오전용 사료는 관행적인 산란계 배합사료에서 Ca공급제를 제외한 것을 급여하고, 오후용 사료는 Ca공급제를 3배 첨가한 T2처리로 15:00~16:00시에 교체급여를 하면 사료섭취량 감소와 사료비 절감면에서 바람직할 것으로 사료되며, 고에너지-고단백질-저Ca의 분말사료와 저에너지-저단백질-고Ca의 펠렛사료를 혼합급여하면 산란계의 사료