• 경영과학
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• 제19권1호
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• pp.189-196
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• 2002

Data clustering is often one of the first steps in data mining analysis. It Identifies groups of related objects that can be used as a starling point for exploring further relationships. This technique supports the development of population segmentation models, such as demographic-based customer segmentation. This paper Purpose to present the development of two phase hierarchical clustering algorithm for group formation. Applications of the algorithm for product-customer group formation in customer relationahip management are also discussed. As a result of computer simulations, suggested algorithm outperforms single link method and k-means clustering.

• Journal of Computing Science and Engineering
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• 제10권1호
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.

• 제어로봇시스템학회논문지
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• 제20권2호
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• pp.126-131
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• 2014

This paper is concerned with a track management method for a naval combat system which receives the tracks information from multi-sensors and multi-tactical datalinks. Since the track management of processing the track information from diverse sources can be formulated as a data fusion problem, this paper will deal with the data fusion architecture, track association and track information determination algorithm for the track management of naval combat systems.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 가을학술발표대회논문집
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• pp.265-266
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• 2023

Recently, many disasters have occurred due to poor management of construction site. In addition, as legal regulations on safety management at construction sites are strengthened, its importance is being further emphasized. In relation to smart safety management technology, a study was introduced to build an analysis model through various safety-related data collected within construction companies. This model derives quantitative disaster risk about the site level through information related to past disasters and near misses. However, construction work is performed separately by work group of each partner company. There is a limitation in that individual workers cannot directly experience this analysis information. In this study, we propose a method to derive the safety disaster risk of individual work units from disaster risk of the site level. We expect that this study to be helpful for smart safety management technology of construction sites.

• Journal of Information Science Theory and Practice
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• 제9권4호
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• pp.35-49
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• 2021

In a situation where there are multiple diverse datasets, it is essential to have an efficient method to provide users with the datasets they require. To address this suggestion, necessary datasets should be selected on the basis of the relationships between the datasets. In particular, in order to discover the necessary datasets for disaster resolution, we need to consider the disaster resolution stage. In this paper, in order to provide the necessary datasets for each stage of disaster resolution, we constructed a disaster type and disaster management process ontology and designed a method to determine the necessary datasets for each disaster type and disaster management process step. In addition, we introduce a method to determine relationships between datasets necessary for disaster response. We propose a method for discovering datasets based on minimal relationships such as "isA," "sameAs," and "subclassOf." To discover suitable datasets, we designed a knowledge exploration model and collected 651 disaster-related datasets for improving our method. These datasets were categorized by disaster type from the perspective of disaster management. Categorizing actual datasets into disaster types and disaster management types allows a single dataset to be classified as multiple types in both categories. We built a knowledge exploration model on the basis of disaster examples to ensure the configuration of our model.

• 한국측량학회지
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• 제37권2호
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• pp.81-89
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• 2019

As the need for the integration of administrative datasets and address information increases, there is also growing interest in POI (Point of Interest) data as a source of location information across applications and platforms. The purpose of this study is to develop an alias database management method for efficient POI searching, based on POI data representing position. First, we determine the attributes of POI alias data as it is used variously by individual users. When classifying aliases of POIs, we excluded POIs in which the typo and names are all in English alphabet. The attributes of POI aliases are classified into four categories, and each category is reclassified into three classes according to the strength of the attributes. We then define the quality of POI aliases classified in this study through experiments. Based on the four attributes of POI defined in this study, we developed a method of managing one POI alias through and integrated method composed of word embedding and a similarity measurement. Experimental results of the proposed POI alias management method show that it is possible to utilize the algorithm developed in this study if there are small numbers of aliases in each POI with appropriate POI attributes defined in this study.

• 한국산학기술학회논문지
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• 제10권11호
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• pp.3207-3212
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• 2009

반도체 산업이 발전함에 따라 생산 효율을 높이기 위해 무인 자동 생산 공정이 요구되고 있다. 이러한 무인자동화 생산 관리 시스템은 생산성 향상을 위해 생산 공정에서 발생하는 대량의 실시간 데이터 분석 및 관리를 필요로 한다. 따라서 실시간으로 발생하는 대용량 데이터를 저장하기 위한 저장 관리 시스템이 요구된다. 기존의 저장 관리 시스템으로 오라클, MY-SQL, MS-SQL 등의 디스크 기반 DBMS가 있다. 하지만 기존의 디스크 기반 DBMS는 반도체 장비로부터 실시간으로 발생하는 대용량 데이터 처리에 한계가 있다. 본 논문에서는 대용량 데이터를 저비용으로 실시간 저장하기 위해 블록 단위 삽입 트랜잭션을 이용한 압축-합병 저장 기법을 제안한다. 제안 기법은 블록 단위 트랜잭션을 이용하여 실시간 데이터를 빠르게 저장하며 데이터를 압축하고 압축된 데이터를 합병하여 저장하기 때문에 보다 적은 디스크 공간을 사용하여 저장할 수 있다. 따라서 반도체 공정에서 빠르게 발생하는 대용량 데이터를 기존 DBMS보다 빠르게 저장이 가능하고 저장 공간 비용을 감소시킨다.

• 품질경영학회지
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• 제48권3호
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• pp.511-520
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• 2020

Purpose: The purpose of this study was to devise an accurate machine learning model for predicting silica concentrations following the addition of impurities, through time series analysis of mining data. Methods: The mining data were preprocessed and subjected to time series analysis using the machine learning model. Through correlation analysis, valid variables were selected and meaningless variables were excluded. To reflect changes over time, dependent variables at baseline were treated as independent variables at later time points. The relationship between independent variables and the dependent variable after n point was subjected to Pearson correlation analysis. Results: The correlation (R2) was strongest after 3 hours, which was adopted as a dependent variable. According to root mean square error (RMSE) data, the proposed method was superior to the other machine learning methods. The XGboost algorithm showed the best predictive performance. Conclusion: This study is important given the current lack of machine learning studies pertaining to the domestic mining industry. In addition, using time series analysis in mining data will show further improvement. Before establishing a predictive model for the proposed method, predictions should be made using data with time series characteristics. After doing this work, it should also improve prediction accuracy in other domains.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.119-126
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• 2004

Location management is very important issue in wireless communication system to trace mobile users' exact location. In this study, we propose a dynamic location area management scheme which determines the size of dynamic location area considering each user's characteristic. In determining the optimal location area size, we consider the measurement data as well as the historical data, which contains call arrival rate and average speed of each mobile user. In this mixture of data, the weight of historical data is derived by linear searching method which guarantees the minimal cost of location management. We also introduce the regularity index which can be calculated by using the autocorrelation of historical data itself. Statistical validation shows that the regularity index is the same as the weight of measurement data. As a result, the regularity index is utilized to incorporate the historical data into the measurement data. By applying the proposed scheme, the location management cost is shown to decrease. Numerical examples illustrate such an aspect of the proposed scheme.

• 한국농공학회지
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• 제44권3호
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• pp.101-110
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• 2002

Most of the agricultural structures are in shortage of feasible facility management because these structures are small in size and spacially distributed in rural area. Inspection tools based on visual inspections are generally used for agricultural structures in most of the countries, including Korea. It is necessary to survey data of the irrigation structures to maintain records, and to develop the interface program by constructing database of inspection data. This study was conducted to develop a system for safe appraisal and repair works on agricultural irrigation structures. Repair and rehabilitation method can be chosen from an optimum viewpoint if the information between the method and life-cycle management cost of agricultural structures is constructed in the database. In this study, the system assisting onsite field investigation and determining the typical rehabilitation method of typical agricultural structural problems such as fractures and cracks of members was developed.