• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.986-998
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• 2006

There has been an increasing necessity of Semantic Web-based metadata that helps computers efficiently understand and manage an information increased with the growth of Internet. However, it seems inevitable to face some semantically ambiguous information when metadata is generated. Therefore, we need a solution to this problem. This paper proposes a new method for automated metadata generation with the help of a concept of class, in which some ambiguous words imbedded in information such as documents are semantically more related to others, by using probability model of consequent words. We considers ambiguities among defined concepts in ontology and uses the Hidden Markov Model to be aware of part of a named entity. First of all, we constrict a Markov Models a better understanding of the named entity of each class defined in ontology. Next, we generate the appropriate context from a text to understand the meaning of a semantically ambiguous word and solve the problem of ambiguities during generating metadata by searching the optimized the Markov Model corresponding to the sequence of words included in the context. We experiment with seven semantically ambiguous words that are extracted from computer science thesis. The experimental result demonstrates successful performance, the accuracy improved by about 18%, compared with SemTag, which has been known as an effective application for assigning a specific meaning to an ambiguous word based on its context.

• Journal of the Society of Disaster Information
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• v.14 no.3
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• pp.379-386
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• 2018

Purpose: This study was to the fragility evaluation of I-shape curved beam structure subjected to strong ground motions including Gyeongju and Pohang earthquakes Method: In particular, to conduct the analytical model, ABAQUS and ANSYS platform was used in this study. Furthermore, the analytical model using 3D Finite Element Model (FEM) was validated, in comparison to the theoretical solutions at the location of 025L, 05L, and 0.75L in static loading condition. In addition, in order to evaluate the seismic fragility of the curved beam structure, 20 seismic ground motions were selected and Monte-Carlo Simulation was used for the empirical fragility evaluation from 0.2g to 1.5g. Result: It was interesting to find that the probability of the system failure was found at 0.2g, as using 190 MPa limit state and the probability of the failure using 390 MPa limit state was starting from 0.6g. Conclusion: This study showed the comparison of the theoretical solution with analytical solution on I-shaped curved beam structures and it was interesting to note that the system subjected to strong ground motions was sensitive to high frequency earthquake. Further, the seismic fragility corresponding to the curved beam shapes must be evaluated.

• The KIPS Transactions:PartC
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• v.8C no.6
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• pp.793-805
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• 2001

In the recent priority system, high-priority packet will be served first and low-priority packet will be served when there isn\`t any high-priority packet in the system. By the way, even high-priority packet can be blocked by HOL (Head of Line) contention in the input queueing System. Therefore, the whole switching performance can be improved by serving low-priority packet even though high-priority packet is blocked. In this paper, we study the performance of preemptive priority in an input queueing switch for high speed switch system. The analysis of this switching system is taken into account of the influence of priority scheduling and the window scheme for head-of-line contention. We derive queue length distribution, delay and maximum throughput for the switching system based on these control schemes. Because of the service dependencies between inputs, an exact analysis of this switching system is intractable. Consequently, we provide an approximate analysis based on some independence assumption and the flow conservation rule. We use an equivalent queueing system to estimate the service capability seen by each input. In case of the preemptive priority policy without considering a window scheme, we extend the approximation technique used by Chen and Guerin [1] to obtain more accurate results. Moreover, we also propose newly a window scheme that is appropriate for the preemptive priority switching system in view of implementation and operation. It can improve the total system throughput and delay performance of low priority packets. We also analyze this window scheme using an equivalent queueing system and compare the performance results with that without the window scheme. Numerical results are compared with simulations.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.745-758
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• 2017

The copula-based models have been successfully applied to hydrological modeling including drought frequency analysis and time series modeling. However, uncertainty estimation associated with the parameters of these model is not often properly addressed. In these context, the main purposes of this study are to develop the Bayesian inference scheme for bivariate copula functions. The main applications considered are two-fold: First, this study developed and tested an approach to copula model parameter estimation within a Bayesian framework for drought frequency analysis. The proposed modeling scheme was shown to correctly estimate model parameters and detect the underlying dependence structure of the assumed copula functions in the synthetic dataset. The model was then used to estimate the joint return period of the recent 2013~2015 drought events in the Han River watershed. The joint return period of the drought duration and drought severity was above 100 years for many of stations. The results obtained in the validation process showed that the proposed model could effectively reproduce the underlying distribution of observed extreme rainfalls as well as explicitly account for parameter uncertainty in the bivariate drought frequency analysis.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.725-734
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• 2017

The main purpose of this study is to analyze runoff aggregation structure and energy expenditure pattern of Choyang creek basin within the framework of power law distribution. To this end geomorphologic factors of every point in the basin of interest, which define tractive force and stream power as well as drainage area, are extracted based on GIS, and their complementary cumulative distributions are graphically analyzed through fitting them to power law distribution. The results indicate that three distinct behavioral regimes are observed from the complementary cumulative distributions of three geomorphogic factors. Based on the parameter estimation of power law distribution by maximum likelihood drainage area and stream power can be judged as scale invariance factor without finite scale while tractive force as scale dependence factor with finite scale. Furthermore, it is judged that tractive force would not follow power law distribution because it shows limited complex system behaviors only within the small extent of scale. The exponent of power law distribution for drainage area obtained in this study by maximum likelihood is larger than the previous researches due to the difference of parameter estimation methodologies. And the exponent for stream power is smaller than the previous researches due to the scaling property of channel slope for the basin of interest.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.447-454
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• 2015

This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.422-429
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• 2007

Location awareness is one of the key functionalities to build an U-city. Recently, many of works of the location-aware systems are emerging to commercially apply to on-going large-scale apartment complex based on U-city. As dwellers or cars being attached with active tags are moving in the U-city complex, the active tags periodically broadcast their own identifiers and receivers fixed along the street or in building use those information to calculate location of them. There are several issues to be considered for such an environment. The first is that the number of active tags operating in the same region are large as much as tens of thousands, and the second is that the active tags should be alive without change of batteries more than a year, hence low power consumption is very important. In this paper we propose i) a new architecture for location-aware system considering such issues, ii) technical issues to implement it using active tags, and iii) a mathematical analytic model to investigate overall performance and verify it by comparing with actual experimental results. Through the analysis we can show the theoretical boundary of the lowest packet loss rate and the maximum number of tags with acceptable performance for the systems based on active tags. The results can be applied to practical design of location-based systems of U-City projects.

• 한국노년학
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• v.37 no.3
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• pp.727-745
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• 2017

This study purported to examine the effects of precarious employment and social capital on the changes of self-rated health status among the middle aged and the young-old population in South Korea. The study analyzed 12 year follow-up data generated by the Korean Labor and Income Panel Study(KLIPS 6-17), which included 10532 employed subjects aged 55 to 75. Multi-level growth curve modeling was performed by fixed and random effect models using STATA 13.0 program. Afterwards, Hausman test was performed, which resulted in support of the estimation by fixed effect model. The results showed that a day labor position was significant factor affecting the deteriorated changes of self-rated health status over time. In addition, wage, weekly working hours, and private/relational social capitals were also found to be significant factors affecting the changes of the self-rated health status. The results supported the divergence hypothesis as well as the cumulative advantage theory. Efforts should be made to develop and implement various employment support policies and social service programs to alleviate the health inequality of the employed workers over their middle-aged to young-old period.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.5
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• pp.1179-1189
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• 2019

Cyber security evaluation is a series of processes that estimate the level of risk of assets and systems through asset analysis, threat analysis and vulnerability analysis and apply appropriate security measures. In order to prepare for increasing cyber attacks, systematic cyber security evaluation is required. Various indicators for measuring cyber security level such as CWSS and CVSS have been developed, but the quantitative method to apply appropriate security measures according to the risk priority through the standardized security evaluation result is insufficient. It is needed that an Scoring system taking into consideration the characteristics of the target assets, the applied environment, and the impact on the assets. In this paper, we propose a quantitative risk assessment model based on the analysis of existing cyber security scoring system and a method for quantification of assessment factors to apply to the established model. The level of qualitative attribute elements required for cyber security evaluation is expressed as a value through security requirement weight by AHP, threat influence, and vulnerability element applying probability. It is expected that the standardized cyber security evaluation system will be established by supplementing the limitations of the quantitative method of applying the statistical data through the proposed method.

• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.107-116
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• 2019

Korean construction engineering firms want to pave the way for expansion of overseas markets through the World Bank's Official Development Assistance (ODA) projects as a way to improve their overseas project performance. However, since the World Bank project competes with global companies for limited projects, building partnerships with suitable business partners is essential to gain an upper hand in bidding competition and meet the institutional conditions of the recipient country. In this regard, many network studies have been conducted in the past through Social Network Analysis (SNA), but few have been analyzed based on the process of changes in the network. So, This study collected winning data from the three Southeast Asian countries that ended after the World Bank's ODA project performed smoothly, and established a learning-based link prediction model that reflected the dynamic nature of the network. As a result, the 11 main variables acting on building a cooperative relationship between winning companies were derived and the effect of each variables on the probability value of cooperation between individual links was identified.