• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.105-112
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• 2021

In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

• Korean Journal of Clinical Pharmacy
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• v.15 no.1
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• pp.41-45
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• 2005

심바스타틴은 cholesterol 생합성 과정에서 속도 조절 효소인 HMG-CoA reductase의 강력한 상경적 길항약으로서 고지혈증 치료에 널리 쓰이는 약물이다. 심바스타틴 제제인 MSD 사의 조코 20 mg정을 대조약으로 하여 시험약인 유영 제약의 엘바스타 20mg정의 생물학적 동등성 평가를 하기 위해 22명의 건강한 지원자를 모집하였다. 지원자를 두 군으로 나누어 2정씩 투여하였고 $2{\times}2$ 교차시험을 실시하였다. 심바스타틴의 혈장 중의 농도를 정량하기 위하여 발리데이션된 LC/MS/MS를 사용하였다. 채혈 시간은 투약 전 및 투약 후 0.5, 1, 1.5, 2, 2.5, 3, 4, 6, 8, 10, 12 시간에 걸쳐 총 12시점에 걸쳐 시행하였다. 생물학적 동등성을 판정하기 위한 파라미터로 12시간까지의 혈장 중 농도곡선 하 면적 ($AUC_{12hr}$)과 최고 혈중 농도($C_{max}$)를 사용하였다. 12시간 까지의 혈중 농도 곡선 하 면적의 기하 평균은 $17.30ng{\cdot}ml/hr$(시험약)과 $17.35ng{\cdot}ml/hr$(대조약)으로 나타났다. 최고 혈중 농도의 경우 각 각 5.08 ng/ml(시험약)과 5.20 ng/ml(대조약)으로 관찰 되었다. $AUC_{12hr}$의 경우 로그변환한 평균치 차의 $90{\%}$ 신뢰구간이 log0.8510 - log1.1694이었고, $C_{max}$의 경우 log0.8176 - log1.1649로 계산되어 두 항목 모두 log0.8-log1.25이어야 한다는 식품의약품 안전청과 FDA의 기준을 모두 만족시켰다. 이상의 결과를 종합하면 시험약 엘바스타 정 20mg은 대조약 조코정 20 mg에 대하여 생물학적 동등한 것으로 판정되었다.트리머 전기비저항 탐사를 수행하였다. 이를 통해 하저에 케이블을 설치하는 방식에 비해 매우 신속하고 경제적으로 하저에 분포하는 이상대의 분포범위와 발달방향을 규명할 수 있었다.대에 대해 가장 효과적이다. 모델과 현장 적용 결과들을 통해 GRM SSM 방법을 이용하여 불규칙한 굴절면을 가진 지층들에 대해 좀 더 신뢰할 수 있는 정밀한 탄성파 속도를 산출할 수 있음을 보여주고 있다.별한 주의를 기울여야 한다.EX>$\alpha/\beta$=10인 경우 $62.0\~121.9\;Gy_{10}$ (중앙값: $93.0\;Gy_{10}$)의 분포를, ${\alpha/\beta}=3$인 경우 $93.6\~187.3\;Gy_3$ (중앙값=$137.6\;Gy_3$ )의 분포를 보였다. MD-BED $Gy_3$는 직장합병증 발생과의 관계는 통계적으로 유의하였고, 방광합병증과는 유의하지 않았다. 직장합병증과의 연관성은 MD-BED $Gy_3$보다 개별 환자의 직장전벽 총 선량 BED값인 R-BED $Gy_3$가 훨씬 더 높았다. 요도카테터 풍선의 후방지점이 대변하는 방광의 총 선량 BED값인 V-BED $Gy_3$도 방광합병증과 경향성 테스트에서 통계적 유의성을 보였다. 하지만, 어떠한 방사선선량도 골반제어율과 의미 있는 상관관계를 보이지 않았다. 본 기관에서 주치의의 선호도에 따라 강내근접치료가 외부방사선치료의 중간에 시행되는 형태인 샌드위치기법과 외부방사선치료 후반부에 시행되는 순차적 기법으로 구분하였을 때, 두 방식간 치료성적 및 합병증의 차이는 없었다. 총 치료기간에 대한 분석에서는 치료기간이 길어질수록 재발 위험이 커지는 경향을 보였으나, 나이 및 병기, 종양의 크기, MD-BED $Gy_{10}$

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.12
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• pp.1141-1153
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• 2010

This paper introduces ONLIS(Overlay Multicast Network for Live IPTV Service), a novel overlay multicast network optimized to deliver live broadcast IPTV stream. We analyzed IPTV reference model of ITU-T IPTV standardization group in terms of network and stream delivery from the source networks to the customer networks. Based on the analysis, we divide IPTV reference model into 3 networks; source network, core network and access network, ION(Infrastructure-based Overlay Multicast Network) is employed for the source and core networks and PON(P2P-based Overlay Multicast Network) is applied to the access networks. ION provides an efficient, reliable and stable stream distribution with very negligible delay while PON provides bandwidth efficient and cost effective streaming with a little tolerable delay. The most important challenge in live P2P streaming is to reduce end-to-end delay without sacrificing stream quality. Actually, there is always a trade-off between delay & stream quality in conventional live P2P streaming system. To solve this problem, we propose two approaches. Firstly, we propose DSPT(Distributed Streaming P2P Tree) which takes advantage of combinational overlay multicasting. In DSPT, a peer doesn't fully rely on SP(Supplying Peer) to get the live stream, but it cooperates with its local ANR(Access Network Relay) to reduce delay and improve stream quality. When RP detects bandwidth drop in SP, it immediately switches the connection from SP to ANR and continues to receive stream without any packet loss. DSPT uses distributed P2P streaming technique to let the peer share the stream to the extent of its available bandwidth. This means, if RP can't receive the whole stream from SP due to lack of SP's uploading bandwidth, then it receives only partial stream from SP and the rest from the ANR. The proposed distributed P2P streaming improves P2P networking efficiency.

• The Transactions of the Korea Information Processing Society
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• v.4 no.3
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• pp.831-845
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• 1997

In this paper,we proposed and developed a compiler and interactive programming enviroments for C++ wich is mostly worth of nitice among the object -oriented languages.To develope the compiler for C++ we took front=end/back-end model using EM virtual machine.In develpoing Front-End,we formailized C++ gram-mar with the context semsitive tokens which must be manipulated by dexical scanner and designed a AST class li-brary which is the hierarchy of AST node class and well defined interface among them,In develpoing Bacik-End,we proposed model for three major components :code oprtimizer,code generator and run-time enviroments.We emphasized the retargatable back-end which can be systrmatically reconfigured to genrate code for a variety of distinct target computers.We also developed terr pattern matching algorithm and implemented target code gen-erator which produce SPARC code.We also proposed the theroy and model for construction interative pro-gramming enviroments. To represent language features we adopt AST as internal reprsentation and propose uncremental analysis algorithm and viseal digrams.We also studied unparsing scheme, visual diagram,graphical user interface to generate interactive environments automatically Results of our resarch will be very useful for developing a complier and programming environments, and also can be used in compilers for parallel and distributed enviroments.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.