• Journal of Institute of Control, Robotics and Systems
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• v.18 no.11
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• pp.997-1004
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• 2012

In enterprise software projects, performance issues have become more critical during recent decades. While developing software products, many performance tests are executed in the earlier development phase against the newly added code pieces to detect possible performance regressions. In our previous research, we introduced the framework to enable automated performance anomaly detection and reduce the analysis overhead for identifying the root causes, and showed Statistical Process Control (SPC) can be successfully applied to anomaly detection. In this paper, we explain the special performance trend in which the existing anomaly detection system can hardly detect the noticeable performance change especially when a performance regression is introduced and recovered again a while later. Within the fixed number of sampling period, the fluctuation gets aggravated and the lower and upper control limit get relaxed so that sometimes the existing system hardly detect the noticeable performance change. To resolve the issue, we apply dynamically tuned sampling window size based on the performance trend, and Fuzzy theory to find an appropriate size of the moving window.

• Journal of KIISE:Software and Applications
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• v.37 no.3
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• pp.161-169
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• 2010

The requirement elicitation is the task of eliciting requirements from needs of stakeholders, and preparing for information for negotiation. However, there are methods for gathering needs, but there is no specific method for classifying them, generating information for negotiation. Therefore, To solve the problems, this paper proposes a method to classify requirement and to generate information for negotiation. The proposed methods use Kano model, statistical technique, and identifying relationship between requirements and problems within scope. Finally, we validate the proposed method on simulations, Rough Set Theory, and case study of model.

• The Korean Journal of Applied Statistics
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• v.24 no.1
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• pp.1-10
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• 2011

This study investigates the dynamic structure of interdependence on the domestic and related major stock markets by employing a statistical framework. Finance theory predicts potential gains by international portfolio diversification if returns from investment in different national stock markets are not perfectly correlated or not cointegrated. The benefit of international diversification is limited when national stock markets are cointegrated because of the limited amount of independent variation by the presence of common factors. The statistical tests suggest that international diversification appears to be favorable after the period of the comovement of the stock prices caused by 1997 Asian financial crisis. The result reflects the increase in overseas investment and purchase of overseas funds after the early 2000's.

• ETRI Journal
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• v.25 no.5
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• pp.401-406
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• 2003

A biometric system determines the identity of a person by measuring physical features that can distinguish that person from others. Since biometric features have many variations and can be easily corrupted by noises and deformations, it is necessary to apply machine learning techniques to treat the data. When applying the conventional machine learning methods in designing a specific biometric system, however, one first runs into the difficulty of collecting sufficient data for each person to be registered to the system. In addition, there can be an almost infinite number of variations of non-registered data. Therefore, it is difficult to analyze and predict the distributional properties of real data that are essential for the system to deal with in practical applications. These difficulties require a new framework of identification and verification that is appropriate and efficient for the specific situations of biometric systems. As a preliminary solution, this paper proposes a simple but theoretically well-defined method based on a statistical test theory. Our computational experiments on real-world data show that the proposed method has potential for coping with the actual difficulties in biometrics.

• Journal of Information Science Theory and Practice
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• v.11 no.2
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• pp.67-81
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• 2023

This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.1-11
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• 2016

PURPOSES : This study estimated the load effect of a single heavy truck to develop a live load model for the design and assessment of bridges located on an expressway with a limited truck entry weight. METHODS : The statistical estimation methods for the live load effect acting on a bridge by a heavy vehicle are reviewed, and applications using the actual measurement data for trucks traveling on an expressway are presented. The weight estimation of a single vehicle and its effect on a bridge are fundamental elements in the construction of a live load model. Two statistical estimation methods for the application of extrapolation in a probabilistic study and an additional estimation method that adopts the extreme value theory are reviewed. RESULTS : The proposed methods are applied to the traffic data measured on an expressway. All of the estimation methods yield similar results using the data measured when the weight limit has been relatively well observed because of the rigid enforcement of the weight regulation. On the other hand, when the estimations are made using overweight traffic data, the resulting values differ with the estimation method. CONCLUSIONS : The estimation methods based on the extreme distribution theory and the modified procedure presented in this paper can yield reasonable values for the maximum weight of a single truck, which can be applied in both the design and evaluation of a bridge on an expressway.

• International Journal of Contents
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• v.5 no.1
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• pp.37-45
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• 2009

This paper empirically tests pecking order theory. Korean listed firms are used as the samples. On the whole we find supportive results for pecking order theory. The fixed effect model on the whole period shows that as pecking order theory suggests that debt ratio decreases as cash flow. ROA, physical assets, and firm size increase. Again, it is shown that corporate debt ratio significantly decreases as cash flow or ROA increases in every sub-sample, which coincides with the prediction of pecking order theory. Corporate debt ratio significantly decreases as physical assets or jinn size increases in case of the whole sample, pre-financial crisis period, and the sub-samples by q-ratio, which also supports the prediction of pecking order theory. Statistical significance of the coefficients of physical assets or firm size completely disappears after Korean financial crisis. Perhaps it is because the role of physical assets or firm size as a mitigator of information asymmetry significantly weakens after the financial crisis as Korean financial market becomes more transparent. For small firms only size variable is negatively and significantly related with debt to assets. It seems that size is an important factor for smaller firms in making financing decision.

• Proceedings of the Korean Geotechical Society Conference
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• 1998.03a
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• pp.329-346
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• 1998

• Journal for History of Mathematics
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• v.17 no.1
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• pp.97-108
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• 2004

There are so many methods in population estimation such as logistic estimation and compound interest estimation. If we have some pieces of information about population of one tribe, we can estimate progenitor chronology of that tribe used by inverse estimation. In this paper, we describe several theory of population estimation, and develop mathematical method for estimation progenitor chronology from prior general data and statistical estimation theory. Several examples are illustrated.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.360-364
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• 2001

The fractal theory is an interesting tool for measuring the soil properties which are irregular and dynamical. A simple example is shown in this paper that (statistical) fractal dimension can be evaluated from the traditional Particle-size distribution(PSD) curve. The results of Wu et al.(1993) and Bittelli el al.(1999) were referred to demonstrate the fractal analysis.