• Title/Summary/Keyword: DataBases

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Acoustic Metal Impact Signal Processing with Fuzzy Logic for the Monitoring of Loose Parts in Nuclear Power Plang

  • Oh, Yong-Gyun;Park, Su-Young;Rhee, Ill-Keun;Hong, Hyeong-Pyo;Han, Sang-Joon;Choi, Chan-Duk;Chun, Chong-Son
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.1E
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    • pp.5-19
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    • 1996
  • This paper proposes a loose part monitoring system (LPMS) design with a signal processing method based on fuzzy logic. Considering fuzzy characteristics of metallic impact waveform due to not only interferences from various types of noises in an operating nuclear power plant but also complex wave propagation paths within a monitored mechanical structure, the proposed LPMS design incorporates the comprehensive relation among impact signal features in the fuzzy rule bases for the purposes of alarm discrimination and impact diagnosis improvement. The impact signal features for the fuzzy rule bases include the rising time, the falling time, and the peak voltage values of the impact signal envelopes. Fuzzy inference results based on the fuzzy membership values of these impact signal features determine the confidence level data for each signal feature. The total integrated confidence level data is used for alarm discrimination and impact diagnosis purposes. Through the perpormance test of the proposed LPMS with mock-up structures and instrumentation facility, test results show that the system is effective in diagnosis of the loose part impact event(i.e., the evaluation of possible impacted area and degree of impact magnitude) as well as in suppressing false alarm generation.

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Automatic Expansion of ConceptNet by Using Neural Tensor Networks (신경 텐서망을 이용한 컨셉넷 자동 확장)

  • Choi, Yong Seok;Lee, Gyoung Ho;Lee, Kong Joo
    • KIPS Transactions on Software and Data Engineering
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    • v.5 no.11
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    • pp.549-554
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    • 2016
  • ConceptNet is a common sense knowledge base which is formed in a semantic graph whose nodes represent concepts and edges show relationships between concepts. As it is difficult to make knowledge base integrity, a knowledge base often suffers from incompleteness problem. Therefore the quality of reasoning performed over such knowledge bases is sometimes unreliable. This work presents neural tensor networks which can alleviate the problem of knowledge bases incompleteness by reasoning new assertions and adding them into ConceptNet. The neural tensor networks are trained with a collection of assertions extracted from ConceptNet. The input of the networks is two concepts, and the output is the confidence score, telling how possible the connection between two concepts is under a specified relationship. The neural tensor networks can expand the usefulness of ConceptNet by increasing the degree of nodes. The accuracy of the neural tensor networks is 87.7% on testing data set. Also the neural tensor networks can predict a new assertion which does not exist in ConceptNet with an accuracy 85.01%.

A Study on Establishing Urban Spatial Structure through Central Hierarchy Analysis: Focus on Daejeon (중심지 위계 분석을 통한 대전시 도시공간구조 설정에 관한 연구)

  • RYU, KYUNG-SOO;PARK, SOUNG-EUN
    • Journal of the Korean Regional Science Association
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    • v.40 no.2
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    • pp.57-73
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    • 2024
  • The purpose of this study is to establish the central hierarchy and urban spatial structure of Daejeon in 2040 using differentiated analysis indicators. In order to establish a central hierarchy in the future urban space of Daejeon City, three indicators were derived: population density, use of buildings (commercial, office, residential, etc.) and traffic volume data(KTDB). The results of analyzing the center hierarchy using indicators are as follows. First, the primary centers responsible for urban (core) functions are set in three areas, including Dunsan downtown, the original downtown (Daejeon Station area, designated as a special urban convergence zone), and Doan New Town, and the secondary centers corresponding to sub-city centers (regional bases). was set at 9, 10 tertiary centers corresponding to regional centers (living area centers), and a center hierarchy was established with 5 new specialized bases. Second, new secondary and tertiary centers emerged that were different from the center hierarchy in the 2030 Daejeon Urban Basic Plan. The three indicators used in this study yielded meaningful results in establishing urban spatial structure and central hierarchy that can secure urban competitiveness.

USING VIRTUAL OBSERVATORY TOOLS FOR ASTRONOMICAL RESEARCH

  • KIM SANG CHUL;TAYLOR JOHN D.;PANTER BENJAMIN;SOHN SANGMO TONY;HEAVENS ALAN F.;MANN ROBERT G.
    • Journal of The Korean Astronomical Society
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    • v.38 no.2
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    • pp.85-88
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    • 2005
  • Construction of the Virtual Observatory (VO) is a great concern to the astronomical community in the 21st century. We present an outline of the concept and necessity of the va and the current status of various VO projects including the 15 national ones and the International Virtual Observatory Alliance (IVOA). We summarize the possible science cases that could be solved by using the VO data/tools, real science cases which are the results of using current VO tools, and our own work of using AstroGrid, the United Kingdom national VO, for a research on star formation history of galaxies.

A Neural Network-Driven Decision Tree Classifier Approach to Time Series Identification (인공신경망 기초 의사결정트리 분류기에 의한 시계열모형화에 관한 연구)

  • 오상봉
    • Journal of the Korea Society for Simulation
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    • v.5 no.1
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    • pp.1-12
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    • 1996
  • We propose a new approach to classifying a time series data into one of the autoregressive moving-average (ARMA) models. It is bases on two pattern recognition concepts for solving time series identification. The one is an extended sample autocorrelation function (ESACF). The other is a neural network-driven decision tree classifier(NNDTC) in which two pattern recognition techniques are tightly coupled : neural network and decision tree classfier. NNDTc consists of a set of nodes at which neural network-driven decision making is made whether the connecting subtrees should be pruned or not. Therefore, time series identification problem can be stated as solving a set of local decisions at nodes. The decision values of the nodes are provided by neural network functions attached to the corresponding nodes. Experimental results with a set of test data and real time series data show that the proposed approach can efficiently identify the time seires patterns with high precision compared to the previous approaches.

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특허 데이터를 활용한 정보통신 산업혁신체제의 역동성 분석

  • Kim, Jin-Yong;Jeong, Jae-Yong
    • Journal of Technology Innovation
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    • v.11 no.2
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    • pp.283-314
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    • 2003
  • The transformation of sector system in Information and Communications Technology (ICT), a prominent character in sector system, has been paid much attention in innovation theory with rapid change in information technologies and technological environment. In this context, we explore how Sectoral Innovation System (SIS) in ICT has been transformed since 1970 by employing US patent data and Proxy variables which measures the basic elements for SIS and its technological characteristics. By utilizing patent data, it is demonstrated that technological regimes, key links and Schumpeterian patterns of innovation in overall ICT sector have drastically transformed over the last three decades. We also reviewed how changes of knowledge bases and technological characteristics driving forces of dynamics in ICT help heterogeneous agents interact with environmental factors (Industrial structure and institutions), leading to industrial or economic growth and its dynamics in the historical perspective over ICT sector (Telecommunication, Computer and Semiconductor). Consequently, our research shows clearly that Schumpeterian patterns of innovation have shifted from Mark I to Mark II in ICT. Our study also provides a glimpse picture of dynamics patent data.

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Probability-Based Estimates of Basic Design Wind Speeds In Korea (확률에 기초한 한국의 기본 설계풍속 주정)

  • 조효남;백현식;차철준
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1988.10a
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    • pp.7-12
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    • 1988
  • This study presents rational methods for probability-based estimates of basic design wind speeds in Korea and develops a risk-bases nation-wide map of design wind speeds. The paper examines the fitting of the Type-I extreme model to maximum yearly non-typhoon wind data from long-term records based on the conventional method and to maximum monthly nod-typhoon wind data from short-term records following Grigorin's approach. The paper also reviews the applicability of the method using short records of about 5 years. The basic design wind speeds for typhoon and non-typhoon wind at a station are made to be obtained from a mixed model which is given as a product of typhoon and non-typhoon extreme wind distributions. A practical method which is based on the fitting of the Type I model to records or typhoon and non-typhoon mixed wind data at a station is also preposed in this study.

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Estimation of Design Flood by the Determination of Best Fitting Order of LH-Moments ( I ) (LH-모멘트의 적정 차수 결정에 의한 설계홍수량 추정 ( I ))

  • 맹승진;이순혁
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.44 no.6
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    • pp.49-60
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    • 2002
  • This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study. GEV distribution for the flood flow data of the applied watersheds was confirmed as the best one among others by the LH-moments ratio diagram and Kolmogorov-Smirnov test. Best fitting order of LH-moments will be derived by the confidence analysis of estimated design flood in the second report of this study.

A Study on Prediction of Hourly Cooling Load Using Building Area (건물 면적을 이용한 시간별 냉방부하 예측에 관한 연구)

  • Yoo, Seong-Yeon;Han, Kyu-Hyun
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.22 no.11
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    • pp.798-804
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    • 2010
  • New methodology is proposed to predict the hourly cooling load of the next day using maximum/minimum temperature and building area. The maximum and minimum temperature are obtained from forecasted weather data. The cooling load parameters related to building area are set through a database provided from reference buildings. To validate the performance of the proposed method, the predicted cooling loads in hourly bases are calculated and compared with the measured data. The predicted results show fairly good agreement with the measured data for benchmarking building.

CALS oriented design/fabrication information system for steel bridges

  • Isohata, Hiroshi;Fukuda, Masahiko;Watanabe, Sueo
    • Steel and Composite Structures
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    • v.3 no.1
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    • pp.13-32
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    • 2003
  • In this paper design and fabrication information system for steel bridge construction is studied and proposed according to the progress of Construction CALS/EC in the construction industry in Japan. The data exchange in this system bases on the text file as well as CAD data with simplified drawings. The concept of this system is discussed following the analysis on the issues of the conventional system. The application of the product model is also discussed including effects and issues on the inspection system. This paper is based on the study carried out by Special Committee on Construction CALS of JASBC to which author belong.