• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.84-94
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• 2011

In this paper, we propose a method to provide the distribution of option price under local volatility model when market-provided implied volatility data are given. The local volatility model is one of the most widely used smile-consistent models. In local volatility model, the volatility is a deterministic function of the random stock price. Before estimating local volatility surface (LVS), we need to estimate implied volatility surfaces (IVS) from market data. To do this we use local polynomial smoothing method. Then we apply the Dupire formula to estimate the resulting LVS. However, the result is dependent on the bandwidth of kernel function employed in local polynomial smoothing method and to solve this problem, the proposed method in this paper makes use of model averaging approach by means of bandwidth priors, and then produces a robust local volatility surface estimation with a confidence interval. After constructing LVS, we price barrier option with the LVS estimation through Monte Carlo simulation. To show the merits of our proposed method, we have conducted experiments on simulated and market data which are relevant to KOSPI200 call equity linked warrants (ELWs.) We could show by these experiments that the results of the proposed method are quite reasonable and acceptable when compared to the previous works.

• 한국정보통신학회논문지
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• 제24권1호
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• pp.134-137
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• 2020

Recently, there are emphasized to support the maintenance and management system of vessels using acquired data from engine part equipment. But, there are limitations for data exchange and management. To solve the problem, the ISO published ISO 19847 and 19848. In this paper, we analyze the ISO 19848 requirements related to identify data channel ID for ship equipment, and propose the examples for applying encoding techniques. In addition, we suggest the proposed technique for applying of managing the failure and maintenance type of the ship's engine part facilities by examples. If this method is applied, the vessel's equipment can exchange data through the sharing of the code table, and express what response is needed or acted, including where the failure occurred.

• Journal of Information Technology Applications and Management
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• 제26권1호
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• 한국경영과학회지
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• 제33권3호
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• pp.93-105
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• 2008

Semi-supervised learning uses a small amount of labeled data to predict labels of unlabeled data as well as to improve clustering performance, whereas unsupervised learning analyzes only unlabeled data for clustering purpose. We propose a new clustering-based semi-supervised learning method by reflecting the initial predicted labels of unlabeled data on the objective function. The initial prediction should be done in terms of a discrete probability distribution through a classification method using labeled data. As a result, clusters are formed and labels of unlabeled data are predicted according to the Information of labeled data in the same cluster. We evaluate and compare the performance of the proposed method in terms of classification errors through numerical experiments with blinded labeled data.

• 한국안전학회지
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• 제28권1호
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• 디지털산업정보학회논문지
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• 제12권3호
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• pp.75-85
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• 2016

MANET is a network composed only mobile network having limited resources and has dynamic topology characteristics. Therefore, every mobile node acts as a route and delivers data by using multi-hop method. In particular, group communication such as multicast is desperately needed because of characteristics such as battery life of limited wireless bandwidth and mobile nodes. However, the multicast technique can have different efficient of data transmission according to configuring method of a virtual topology by the movement of the nodes and the performance of a multicast can be significantly degraded. In this paper, the region based security multicast technique is proposed in order to increase the efficiency of data transmission by maintaining an optimal path and enhance the security features in data transmission. The group management node that manages the state information of the member nodes after the whole network is separated to area for efficient management of multicast member nodes is used. Member node encrypts using member key for secure data transmission and the security features are strengthened by sending the data after encrypted using group key in group management node. The superiority of the proposed technique in this paper was confirmed through experiments.

• 지식경영연구
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• 제5권1호
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• pp.69-82
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• 2004

Prior research on knowledge management focused more on the experiential knowledge based on individual's experience or knowhow than on the analytical knowledge extracted from corporate data. This study examines the effects of the data warehouse technology, especially OLAP(on line analytical processing) and data mining techniques, on the analytical knowledge creation in organizations, linking analytical knowledge creation to data analysis method through real world case studies.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 추계학술발표회 논문집
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• pp.343-347
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• 2004

Landuse information is used to plan land use, urban and environmental management as base data. And, demand for landuse information is rising due to ecological consideration in urban area. But existing method to extract landuse information from aerial photographs or satellite images is difficulte to describe sufficient urban landuses. Also landuse information need to be linked with statistical data because statistical data is used to make decision for urban planning and management with landuse. Therefore this study aims to examine the landuse classification method using statistical unit data and 1:1,000 digital topographic data. for the purpose, the method was applied to a part of metropolitan Seoul. The results of study shows that total accuracy is 95%. For the future, the method will be effectively applicable for the city maintenance.

• 한국신뢰성학회지:신뢰성응용연구
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• 제17권3호
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• pp.213-223
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• 2017

Purpose: The purpose of this study is to arrange the life data analysis literatures based on the Bayesian method quantitatively and provide it as tables. Methods: The Bayesian method produces a more accurate estimates of other traditional methods in a small sample size, and it requires specific algorithm and prior information. Based on these three characteristics of the Bayesian method, the criteria for classifying the literature were taken into account. Results: In many studies, there are comparisons of estimation methods for the Bayesian method and maximum likelihood estimation (MLE), and sample size was greater than 10 and not more than 25. In probability distributions, a variety of distributions were found in addition to the distributions of Weibull commonly used in life data analysis, and MCMC and Lindley's Approximation were used evenly. Finally, Gamma, Uniform, Jeffrey and extension of Jeffrey distributions were evenly used as prior information. Conclusion: To verify the characteristics of the Bayesian method which are more superior to other methods in a smaller sample size, studies in less than 10 samples should be carried out. Also, comparative study is required by various distributions, thereby providing guidelines necessary.

• Journal of Information Science Theory and Practice
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• 제11권3호
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• pp.79-91
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• 2023

The storage of data documentation for Myanmar pagodas has various issues, and its retrieval method causes problems for users and libraries. This study utilized a mixed-methods approach, combining qualitative and quantitative methods to investigate pagoda data management in Myanmar libraries. The study aims to achieve the following objectives: to study the library collection management of pagodas in Myanmar, to investigate the management of pagoda data in Myanmar libraries, and to identify the pagoda data requirements for metadata development from the library professional perspective. The study findings revealed several challenges facing librarians and library users in accessing and managing Myanmar pagoda data, including limited stocks and retrieval tools, difficulty in accessing all available data online, and a lack of a centralized database or repository for storing and retrieving pagoda data. The study recommends the establishment of metadata criteria for managing a set of pagoda data and improving access to technology to address these challenges.