• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1155-1167
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• 2009

We made a new sample design for life and consciousness survey of Kyungpook people in 2007. We used the 10% sample survey data of 2005 population and housing census as a survey population. After stratification, we allocate proportionally samples within strata after examining various characteristics in previous survey, which includes economic activity state, an income level per year, and housing possession. And we calculated weight in a new sample design and derived estimators and a formula of standard error using the weights.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.463-466
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• 2004

본 연구는 조선 LNG선의 탱크를 제작하는 공장의 관리 및 운영을 지원하는 제조실행 시스템(MES : Manufacturing Execution Sys- tem)의 개발에 대한 내용이다. 본 연구대상 공장에는 가공과 조립라인이 있으며, 가공라인에서는 소재를 가공하고, 조립라인에서는 가공된 소재를 가공하고, 조립라인에서는 가공된 소재를 용접으로 최종 조립한다. 본 연구 대상 공장의 주요 관리 및 운영에 대한 관점은 장비의 고장 방지와 효율극대화, 납기 준수 및 최종 용접 후 결함 최소화 등이다. 이에 본 연구에서는 공장을 체계적으로 관리 운영하기 위해 공정관리와 장비관리 기능을 통합한 제조실행 시스템을 개발하였다. 공정관리는 일정계획 수립, 관리에서부터 작업자 배치 및 입${\cdot}$출고 관리 등의 역할을 수행하고, 장비관리는 장비 모니터링, 장비와 작업 이력 데이터 추출 및 집계, 장비보전 관리, 장비별 작업지시 등의 역할을 수행한다. 본 연구의 개발 시스템은 MSSQL Sever 데이터베이스와 Visual Basic, C++ Builder로 개발되었다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Archives of design research
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• v.19 no.5 s.67
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• pp.255-268
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• 2006

This study raised a question about 'how user's psychological value consciousness influences design evaluation and evaluated 14 product samples. Three main categories were chosen to be analyzed; product evaluation by step, value consciousness toward products, and creation of shape image and design evaluation. In order to obtain results, four research hypotheses were established a and case study was conducted as part of 'conclusive research' for verification. 120 university students in their 20s majoring in product design were chosen as testees in a bid to increase the accuracy of data. With data collected, the whole flow was analyzed by simple tabulation and further analysis was carried out in three evaluation items. An analysis method was mainly quantitative, focusing on multivariate analysis like factor analysis, cluster analysis, etc. The empirical analysis of this study was verified at P<.05 significance level and SPSSWIN 12.0 program was used for statistic process. As a result, four conclusions were gained regarding 'user's value consciousness toward products and pattern of design evaluation'.

• Convergence Security Journal
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• v.13 no.1
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• pp.59-70
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• 2013

Along with the rapid development of the wireless network (Wireless Network) technology for secure wireless communications, security problems have emerged as an important issue. In order to operate the wireless network intrusion detection system detects the agent installed on each wireless node should be. Ad-hoc network structures scattered in the AP over a wireless network without the node is a structure that makes it possible to communicate to connect. Intrusion detection agent to be installed on the node, and the corresponding energy consumption occurs when the survival time is reduced. On a node that can monitor a lot of traffic in order to increase the effect of intrusion detection, an intrusion detection agent should be placed. Therefore, in this paper, by taking advantage of the structure of Ad-hoc wireless network, considering the maximum living time of the network, while at the same time, the effectiveness of intrusion detection and intrusion detection by proposing a plan for installing the agent. Also improve the system performance by reducing the network load on each network, a system designed for data aggregation to reduce data redundancy, network energy consumption by reducing.

• Spatial Information Research
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• v.22 no.3
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• pp.35-46
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• 2014

Population data are usually provided at administrative spatial units in Korea, so areal interpolation is needed for fine-grained analysis. This study aims to compare various methods of areal interpolation for population subgroups rather than the total population. We estimated the number of elderly people and single-person households for small areal units from Dong data by the different interpolation methods using 2010 census data of Seoul, and compared the estimates to actual values. As a result, the performance of areal interpolation methods varied between the total population and subgroup populations as well as between different population subgroups. It turned out that the method using GWR (geographically weighted regression) and building type data outperformed other methods for the total population and households. However, the OLS regression method using building type data performed better for the elderly population, and the OLS regression method based on land use data was the most effective for single-person households. Based on these results, spatial distribution of the single elderly was represented at small areal units, and we believe that this approach can contribute to effective implementation of urban policies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.605-610
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• 2008

Through welding fabrication, user can feel unsatisfaction of surface quality because of welded defects, Generally speaking, these are called weld defects. For checking these defects effectively without time loss effectively, weldability estimation system setup is an urgent thing for detecting whole specimen quality. In this study, by laser vision camera, catching a rawdata on welded specimen profiles, treating vision processing with these data, qualitative defects are estimated from getting these information at first. At the same time, for detecting quantitative defects, whole specimen weldability estimation is pursued by multifeature pattern recognition, which is a kind of fuzzy pattern recognition. For user friendly, by weldability estimation results are shown each profiles, final reports and visual graphics method, user can easily determined weldability. By applying these system to welding fabrication, these technologies are contribution to on-line weldability estimation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.612-623
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• 2022

Estimation of the presence of people in real time is extremely useful for businesses in providing better services. Many companies and researchers have attempted various researches in order to count the number of floating population in a specific space. Recently, as part of smart cities and digital twins, commercialization of measuring floating populations using Wi-Fi signals has become active in the public and private sectors. In this paper we present a method of estimating the floating population based on MAC-address values collected from smartphones. By distinguishing Real MAC-address and Random MAC-address values, we compare the estimated number of smartphone devices and the actual number of people caught on CCTV screens to evaluate the accuracy of the proposed method. And it appeared to have a similar correlation between the two datas. As a result, we present a method of estimating the floating population based on analyzing Wi-Fi Probe Requests.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.363-372
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• 2016

Two-stage sample designs are commonly used for household surveys in Korea using as clusters the enumeration districts (EDs). Since clustering decomposes the population variation into within- and between-cluster variations, the sample sizes allocated in stages can affect the overall precision. Alternative clusters are often considered due to diverse reasons such as the EDs' limitation in size, being out-of-date, and in-assessibility to their household lists. In addition, the EDs are currently under development by the Statistics Korea as an joint effort toward their transition from the traditional practice to the register census from 2015. We present an approach for evaluating the difference in the precision of the mean estimators of the sets of the cluster units in between a hierachical and nested form, where the design effect is used to reflect the effect of the clustering and the sample allocation. We also demonstrate our approach using the U.S. Census counts from the year 2000 for Anne Arundel County in Maryland. Our research shows that the within-cluster variance can be significantly different for survey variables and thus the choice of cluster units and the associated sample allocation scheme should reflect the corresponding variance decomposition due to clustering.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.