• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.187-193
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• 2017

Government has established and operated GIS Data Base in such fields as land-use, road, and underground facilities since 1995. Based on these circumstances, the importance of spatial information industry began to emerge and accordingly MLIT (Ministry of Land, Infrastructure and Transport) established "National Spatial Information Policy Master Plan" and "National Spatial Information Policy Action Plan". However, compared to other fields of transportation, the spatial information data base for railway facilities are not established and provided systematically. As shown in 'Korea National Spatial Data Infrastructure System', only 'transportation information' as an related information and 'transportation' field as an administrative information are included in the system. Detailed information for railway and its facilities are not included in the system. The reason why detailed information for railway facilities are not included in the system is that regulations for establishing and utilizing the spatial information of railway and its facilities are imperfect. In this study, trend of establishing spatial information and regulations related to railway and its facilities are reviewed. Through this review, improvement items such as complementing existent laws and establishing organization for managing spatial information data of railway are deduced and suggested. Based on this research 'Korea National Spatial Data Infrastructure System' could set a legal fundament and both integrated maintenance and operation of railway facilities could be possible.

• Korean Journal of Social Welfare
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• v.59 no.1
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• pp.199-221
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• 2007

This study examines the conditions and causes of income inequality and seeks assignments for mitigating income inequality. An analysis of the conditions and causes of income inequality is summarized as follows. First, income inequality, which rapidly increased after the economic crisis, increased and reduced repeatedly during 1999-2004, and remained a level in 2005 as high as that of the year directly after the economic crisis. Second, an analysis of the causes of income inequality by utilizing the long-term data(1985-2004) shows that unemployment rate, nonstandard employment rate, and the rising rate of land prices positively affect income inequality. Third, an analysis of the causes of income inequality by utilizing the data before and after the economic crisis(1995-2004) demonstrates that unemployment rate, nonstandard employment rate, and the workers' income ratio between large enterprises and small enterprises positively affect income inequality. Fourth, the rising rate of land prices which significantly affects income inequality in the data of 1985-2004 does not affect income equality in the data of 1995-2004, and the workers' income ratio between large enterprises and small enterprises which does not affect income inequality in the data of 1985-2004 significantly affect income equality in the data of 1995-2004. These results suggest several implications for mitigating income inequality. First, alternative plans to reduce unemployment rate must be prepared. Second, policies to reduce nonstandard employment rate should be established. Third, programs to stabilize or lower the land prices must be deliberated. Fourth, a master-plan to support small to medium enterprises must be carried out in order to reduce the wage differentials between large enterprises and small to medium enterprises.

• Restorative Dentistry and Endodontics
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• v.36 no.3
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• pp.231-237
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• 2011

Objectives: The purpose of this study was to determine the optimal master apical file size with minimal transportation and optimal efficiency in removing infected dentin. We evaluated the transportation of the canal center and the change in untouched areas after sequential preparation with a #25 to #40 file using 3 different instruments: stainless steel K-type (SS K-file) hand file, ProFile and LightSpeed using microcomputed tomography (MCT). Materials and Methods: Thirty extracted human mandibular molars with separated orifices and apical foramens on mesial canals were used. Teeth were randomly divided into three groups: SS K-file, Profile, LightSpeed and the root canals were instrumented using corresponding instruments from #20 to #40. All teeth were scanned with MCT before and after instrumentation. Cross section images were used to evaluate canal transportation and untouched area at 1-, 2-, 3-, and 5- mm level from the apex. Data were statistically analyzed according to 'repeated nested design' and Mann-Whitney test (p = 0.05). Results: In SS K-file group, canal transportation was significantly increased over #30 instrument. In the ProFile group, canal transportation was significantly increased after preparation with the #40 instrument at the 1- and 2- mm levels. LightSpeed group showed better centering ability than ProFile group after preparation with the #40 instrument at the 1 and 2 mm levels. Conclusions: SS K-file, Profile, and LightSpeed showed differences in the degree of apical transportation depending on the size of the master apical file.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of Christian Education in Korea
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• v.71
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• pp.181-210
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• 2022

The purpose of this study was to investigate the research trends related to the children's department of church schools. The purpose of this study is to present basic data for the study of the children's department of church schools by analyzing the research period, research contents, research methods, and subjects of research related to the children's department of church schools. For this study, 50 domestic master's and doctoral dissertations searched through the National Assembly Library and the Research Information Sharing Service(RISS) were extracted with the keywords of 'church school' and 'children's department'. The frequency and percentage were calculated by analyzing the research related to the children's department of the church school according to four criteria: research period, research content, research method, and research subject. As a result of the study, first, the research trend of research papers in the children's department of church schools was found to be 49 articles (98%) for master's degrees and 1 article (2%) for doctoral degrees from 1980 to 2022. Trends by research period are focused on master's degrees. Second, the trend by research content was 27 practical studies (54%) and 23 theory studies (46%). In the research related to the children's department of church schools, the practical research accounted for a relatively high percentage compared to the theory research. Third, the trends by research method were in the order of 30 literature studies (60%), 19 quantitative studies (38%), and 1 qualitative study (2%). Research related to children's departments in church schools is being actively conducted with a focus on literature research. Fourth, as for the trends by study subject, the study was conducted focusing on physical subjects, with 35 subjects (70%) and 15 subjects (30%) of personal subjects. As research is conducted from physical objects to church schools and media, it is necessary to study the connection between church schools and families. As the research on church school kindergarten is focused on adults (teachers, parents, and educational preachers), in-depth research on children in church schools and qualitative research with voices from the field of children's department in church schools are required.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of Cadastre & Land InformatiX
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• v.48 no.1
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• pp.153-167
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• 2018

Despite many criticisms that topographic survey data for the official land price appraising collected annually using field survey method might be inaccurate, there is only few concrete research on it. This paper investigated whether the topographic survey data collected by a local government using field survey method is consistent with the data analyzed using the digital elevation model to examine its accuracy. The accuracy analysis indicated that 324 out of 1537 lots of land have inconsistent results which means the ratio of inconsistency is 17.36%. Among 11 areas studied, five had the inconsistency ratio above 20% while the worst one had 38.71%. The inconsistency ratio is generally higher for the rough terrain with irregular slope and high altitude while it is relatively lower for the terrain with smooth landform. The analysis results imply that there are limitations in investigating the topology by field survey method. Therefore, the official land price appraising policy should set precise criterion and change over to highly accurate geographic information analysis method to effectively and accurately examine topology, given the fact that the topology of the Republic of Korea has complicated features with irregular slope and altitude.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.235-243
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• 2021

River surveying is conducted to acquire basic geographic data for river master plans and various river maintenance, and it is also used to predict changes after river maintenance construction. ABL (Airborne Bathymetric LiDAR) system is a cutting-edge surveying technology that can simultaneously observe the water surface and river bed using a green laser, and has many advantages in river surveying. In order to use the ABL data for river surveying, it is prerequisite step to segment and extract the water surface and river bed points from the original point cloud data. In this study, point cloud segmentation was performed by applying the ground filtering technique, ATIN (Adaptive Triangular Irregular Network) to the ABL data and then, the water surface and riverbed point clouds were extracted sequentially. In the Gokgyocheon river area, Chungcheongnam-do, the experiment was conducted with the dataset obtained using the Leica Chiroptera 4X sensor. As a result of the study, the overall classification accuracy for the water surface and riverbed was 88.8%, and the Kappa coefficient was 0.825, confirming that the ABL data can be effectively used for river surveying.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.451-461
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• 2016

The purpose of this study was to identify relationship among critical thinking, nursing process competency and evidence based practice competency of nurses working in middle sized hospitals. A descriptive correlational study design was used. The data were collected from 262 nurses working in the three hospitals located in G and P city using self-administered questionnaires. Data were analyzed using descriptive statistic, independent t-test, one-way ANOVA with scheffe, Pearson's correlation coefficient, and hierarchical multiple linear regression using SPSS Statistics 21.0 program. Nurses' evidence-based practice competency had positive correlation with critical thinking disposition (r=.42, p <.001) and nursing process competency (r=.58, p <.001). Full model accounted for 65.1% of evidence-based practice competency by nursing process competency (${\beta}=.57$, p <.001), critical thinking disposition (${\beta}=.34$, p <.001), critical thinking educational experience (${\beta}=.11$, p=.004), Master's degree (${\beta}=.09$, p=.032). Conclusion: o increase evidence-based practice competency of nurses, it is required to develop critical thinking disposition and nursing process competency of nurses.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.98-111
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• 2019

This study suggests a proper studying direction of research on relationship addiction problem. And it presents fundamental research data by analysing domestic research trends of relationship addiction among various crises of people have addiction problem. For analysis of trends on relationship addiction, I searched almost all master's and doctoral dissertations and academic journals which were studied on "addiction", "relationship addiction", "addiction relationship" from 2005 to 2019 in Korea. Also I have surveyed various publications in the data base of Research Information Sharing Service, academic research data base, the National Assembly Library and the National Central Library in Korea. And for the reasonable results, I have studied the research according to 4 steps such as "collecting data and analyzing precedent research", "building analysis criterion", "cording and analysis", "making conclusion and suggesting the development direction" The results of this study are like these. The total number of researches on relationship addiction is 67. The object of those studies were limited adult's or undergraduate students's relationship addiction. So it is necessary that the fields of relationship addiction research are expanding gradually. And the research shows that the relationship addiction problem is directly related with sexual prostitution. Therefore, there are enough needs to study more in diverse, different point of view. Also it is suggested that the proper analyses methodology of relationship addiction shoud be used and new analysis criterions should be developed. In this study, the necessity of further more study is proposed in various ways of methodology about the relation of social problem and relationship addiction. And from this study, it is proved that expending the objects and fields of the study on relationship addiction, the factors analysis on addiction, study models of addiction must be necessary to be studied.