• Journal of the Korean Society for information Management
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• v.30 no.3
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• pp.7-21
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• 2013

The study examines two aspects that relate to undergraduates' selection and use of information sources for their academic assignments: (1) sources perceived useful vs. sources frequently used, and (2) source characteristics considered important as selection criteria vs. selection criteria used as reflected in characteristics of frequently used sources. A survey of 251 undergraduate students attempted to address the gaps between what students think they should do and what they actually do with regard to source selection. Characteristics of frequently used sources were analyzed to find out the criteria used for source selection. Friends/family were among the frequently used sources although they were not perceived as useful. Unlike other sources suffering gaps between the perceived usefulness and the use behavior, Web sources were the ones not only perceived most useful but also used most frequently. When the important selection criteria were compared with the characteristic of sources used often, students did not seem to actually use the selection criteria they thought important. While students considered some characteristics related to information quality (e.g., accuracy, comprehensiveness) as important criteria for source selection, the actual criteria they applied for choosing information sources could be described as 'convenient' or 'accessible' (e.g., efficient/time saving, easy to use, familiar, accessible). Based on the findings, suggestions were made to help bridge such gaps through information literacy programs and information systems design.

• Journal of Korea Water Resources Association
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• v.44 no.3
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• pp.199-208
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• 2011

The objective of this study is to develop real-time river flow forecast model by linking continuous rainfall-runoff model with ensemble Kalman filter technique. Andong dam basin is selected as study area and the model performance is evaluated for two periods, 2006. 7.1~8.18 and 2007. 8.1~9.30. The model state variables for data assimilation are defined as soil water content, basin storage and channel storage. This model is designed so as to be updated the state variables using measured inflow data at Andong dam. The analysing result from the behavior of the state variables, predicted state variable as simulated discharge is updated 74% toward measured one. Under the condition of assuming that the forecasted rainfall is equal to the measured one, the model accuracy with and without data assimilation is analyzed. The model performance of the former is better than that of the latter as much as 49.6% and 33.1% for 1 h-lead time during the evaluation period, 2006 and 2007. The real-time river flow forecast model using rainfall-runoff model linking with data assimilation process can show better forecasting result than the existing methods using rainfall-runoff model only in view of the results so far achieved.

• CRM연구
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• v.2 no.2
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• pp.53-70
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• 2009

Understanding consumer behavior based on the analysis of the customer data is one essential part of analytic CRM. To do this, the analytic skills for data extraction and data processing are required to users. As a user has various kinds of questions for the consumer data analysis, the user should use database language such as SQL. However, for the firm's user, to generate SQL statements is not easy because the accuracy of the query result is hugely influenced by the knowledge of work-site operation and the firm's database. This paper proposes a natural language based database search framework finding relevant database elements. Specifically, we describe how our TableRank method can understand the user's natural query language and provide proper relations and attributes of data records to the user. Through several experiments, it is supported that the TableRank provides accurate database elements related to the user's natural query. We also show that the close distance among relations in the database represents the high data connectivity which guarantees matching with a search query from a user.

• Journal of the Korean Geotechnical Society
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• v.29 no.2
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• pp.35-45
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• 2013

The void ratio is an important parameter for reflecting the soil behavior including physical property, compressibility, and relative density. The void ratio can be obtained by laboratory test with extracted soil samples. However, the specimen has a possibility to be easily disturbed due to the stress relief when extracting, vibration during transportation, and error in experimental process. Thus, the theoretical equations have been suggested for obtaing the void ratio based on the elastic wave velocities. The objective of this paper is to verify the accuracy of the proposed analytical solution through the error norm. The paper covers the theoretical methods of Wood, Gassmann and Foti. The elastic wave velocity is determined by the Field Velocity Probe in the southern part of Korean Peninsular. And the rest parameters are assumed based on the reference values. The Gassmann method shows the high reliability on determining the void ratio. The error norm is also analyzed as substitution of every parameter. The results show every equation has various characteristics. Thus, this paper may be widely applied for obtaining the void ratio according to the field condition.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.96-110
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• 2018

As the development of ICT has made it easier to collect various traffic information, research on creating new traffic attributes is drawing attention. Estimation and forecasts of demand and traffic volume are one of the main indicators that are essential to traffic operation, assuming that the traffic pattern at a particular node or link is repeated. Traditionally, a survey method was used to demonstrate this similarity on trip behavior. However, the method was limited to achieving high accuracy with high costs and responses that relied on the respondents' memory. Recently, as traffic data has become easier to gather through ETC system, smart card, studies are performed to identify the regularity of trip in various ways. In, this study, route-level trip data collected in Daegu metropolitan city were analyzed to confirm that individual traveler forms a spatially similar trip chain over several days. For this purpose, we newly define the concept of spatial trip regularity and assess the spatial difference between daily trip chains using the sequence alignment algorithm, Dynamic Time Warping. In addition, we will discuss the applications as the indicators of fixed traffic demand and transportation services.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.27-35
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• 2021

With the development of the Internet, various IT technologies such as IoT, Cloud, etc. have been developed, and various systems have been built in countries and companies. Because these systems generate and share vast amounts of data, they needed a variety of systems that could detect threats to protect the critical data contained in the system, which has been actively studied to date. Typical techniques include anomaly detection and misuse detection, and these techniques detect threats that are known or exhibit behavior different from normal. However, as IT technology advances, so do technologies that threaten systems, and these methods of detection. Advanced Persistent Threat (APT) attacks national or companies systems to steal important information and perform attacks such as system down. These threats apply previously unknown malware and attack technologies. Therefore, in this paper, we propose a hybrid intrusion detection system that combines anomaly detection and misuse detection to detect unknown threats. Two detection techniques have been applied to enable the detection of known and unknown threats, and by applying machine learning, more accurate threat detection is possible. In misuse detection, we applied Classification based on Association Rule(CBA) to generate rules for known threats, and in anomaly detection, we used One-Class SVM(OCSVM) to detect unknown threats. Experiments show that unknown threat detection accuracy is about 94%, and we confirm that unknown threats can be detected.

• Journal of the Korean Geotechnical Society
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• v.25 no.4
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• pp.19-29
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• 2009

In this study, a numerical analysis was performed to predict the sequential behavior of anchored retaining wall where the failure accident took place, and verified accuracy of prediction through the comparisons between prediction and field measurement. The emphasis was given to the wall behaviors and the variation of sliding surface based on the two different methods of elasto-plastic and finite element (shear strength reduction technique). Through the comparison study, it is shown that the bending moment and the soil pressure at construction stages produce quite similar results in both the elasto-plastic and finite element method. However, predicted wall deflections using elasto-plastic method show underestimate results compared with measured deflections. This demonstrates that the elasto-plastic method does not clearly consider the influence of soil-wall-reinforcement interaction, so that the tension force (anchor force and earth pressure) on the wall is overestimated. Based on the results obtained, it is found that finite element method using shear strength reduction method can be effectively used to perform the back calculation analysis in the anchored retaining wall, whereas elasto-plastic method can be applicable to the preliminary design of retaining wall with suitable safety factor.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.167-175
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• 2024

Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.4
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• pp.348-356
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• 2018

Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behavior and its spread. Thus, meteorological factors as well as topographical and forest factors were considered in the fire danger rating systems. This study aims to develop an advanced national integrated daily weather index(DWI) using weather data in the spring and fall to support forest fire prevention strategy in South Korea. DWI represents the meteorological characteristics, such as humidity (relative and effective), temperature and wind speed, and we integrated nine logistic regression models of the past into one national model. One national integrated model of the spring and fall is respectively $[1+{\exp}\{-(2.706+(0.088^*T_{mean})-(0.055^*Rh)-(0.023^*Eh)-(0.014^*W_{mean}))\}^{-1}]^{-1}$, $[1+{\exp}\{-(1.099+(0.117^*T_{mean})-(0.069^*Rh)-(0.182^*W_{mean}))\}^{-1}]^{-1}$ and all weather variables significantly (p<0.01) affected the probability of forest fire occurrence in the overall regions. The accuracy of the model in the spring and fall is respectively 71.7% and 86.9%. One integrated national model showed 10% higher accuracy than nine logistic regression models when it is applied weather data with 66 random sampling in forest fire event days. These findings would be necessary for the policy makers in the Republic of Korea for the prevention of forest fires.

• Tunnel and Underground Space
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• v.16 no.1 s.60
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• pp.50-57
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• 2006

Development of structures such as slope and tunnel, waste disposal, oil and LPG storages, and underground power house and so on, is increasing with the year. The method for appropriate estimation of rock state such as fresh or damaged rocks is also requested with increasing structural development. On these purposes, seismic logging system, which is a simple and easy way for handling as well as small and light, has been developed. Seismic logging method is one of logging tests, which is able to evaluate the state of rock mass with various shapes and is possible to obtain the relatively accuracy data at situ state. In addition, seismic logging method is at to apply to estimate structural behavior, before and after support installed. According to the results obtained from this study, firstly, it is clear that the extent of damage in rock slope due to blasting is able to be evaluated with quantity using seismic logging method, moreover to decide the damage zone in rock slope reasonably. Secondly, it is expected that installing depth of support is able to be decided more effectively and economically, using the results of seismic logging data. Finally, seismic logging method is also able to be applied safety supervision of structures, before and after support installed.