• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.5
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• pp.1001-1010
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• 2001

In TLM method, Discrete Green's function ABC have been used when improved the exactness of analyzing in wide frequency band. But this technology has a complicated process to apply absorbing boundary, which means it needs additional numerical analyzing process to obtain discrete Green's function data. so, In this paper, we propose new Green's absorbing layer for simple process to apply absorbing boundary. newly proposed Green's absorbing layer is produced by applying of loss operation, loading discrete Green's function with attenuation. A state of optimum absorbing would be obtained by relation between increasing rate of loss, attenuation constant and length of green's absorbing layer. and then Analysts of waveguide BPF is carried out using Green's absorbing layer within state of optimum absorbing, then this result is in corrective agreement with the result applying traditional discrete Green's function ABC.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.691-699
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• 2017

Data analysts sometimes test the equality of two normal population means by the inspection of the overlapping of two confidence intervals. This method seems simple to use; however, it is a common statistical misconception to suppose that two normal means are not significantly different because of no overlapping. This article will present transforming the confidence interval of the mean difference to individual confidence intervals that are visualized to inspect overlapping. It will also be shown that this technique can be extended when comparing the k normal population means with equal variances.

• Anxiety and mood
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• v.1 no.1
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• pp.14-17
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• 2005

By the influence of the descriptive approach of DSM-III, the anxiety became the same thing as the anxiety disorder to the clinicians. This unfortunate result sacrificed psychodynamic model of symptom formations and simplified the anxiety as one of the disease entity not as the overdetermined symptoms. These phenomenon awakened the psychoanalytic interest which was in sleep. Freud was the first major articulator of the basic significance of anxiety in human behavior. He attributed the particular quality of the anxiety experience to the trauma of birth, and subsequently to the fear of castration. Such classification of the anxiety according to the psychosexual development is helpful for the clinicians in understanding the origin of anxiety which the patient shows during the psychotherapy. The other analytical view of interpersonal psychoanalysis came from Sullivan. A large part of his therapy is taken up with recognizing and correcting parataxic distortions that interfere with realistic self-appraisal of events and of oneself in relation to others. Perhaps no explanation is the 'most basic' explanation for human anxiety. Anxiety is a multifaceted entity consisting of aspects of realm of discourse. Existential anxiety is inescapable in Western culture but it can be transcended by the cultivation of mind in Eastern culture. The analysts need to stay attuned to their own propensities for anxiety and must permit their own experiences with anxiety to be the grist for the psychotherapeutic mill.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.79-92
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• 2020

As the number of systems increases and the network size increases, automated attack prediction systems are urgently needed to respond to cyber attacks. In this study, we developed four types of information gathering sensors for collecting asset and vulnerability information, and developed technology to automatically generate attack graphs and predict attack targets. To improve performance, the attack graph generation method is divided into the reachability calculation process and the vulnerability assignment process. It always keeps up to date by starting calculations whenever asset and vulnerability information changes. In order to improve the accuracy of the attack target prediction, the degree of asset risk and the degree of asset reference are reflected. We refer to CVSS(Common Vulnerability Scoring System) for asset risk, and Google's PageRank algorithm for asset reference. The results of attack target prediction is displayed on the web screen and CyCOP(Cyber Common Operation Picture) to help both analysts and decision makers.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.11a
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• pp.479-484
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• 2002

In this paper consisted of three steps for the research The first, The Database of Biological Resource Information are constructing for species Information and Content Information of based XML. The second, The item of defined from the analysts and must be considered for national GSD(Global Species Database), Supply and Contracture of Input System of based Component for the Efficient Local Information Database. The third Information Service and Interoperability are using the GRM(Global Road Map) of based DADI. These are able to accomplish to Contracture for Database and Service structure of Biological Resources Information.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.23-33
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• 2000

On this study, Among the classification methods of land cover using satellite imagery, we compared the classification accuracy of Neural Network Classifier and that of Maximum Likelihood Classifier which has the characteristics of parametric and non-parametric classification method. In the assessment of classification accuracy, we analyzed the classification accuracy about testing area as well as training area that many analysts use generally when assess the classification accuracy. As a result, Neural Network Classifier is superior to Maximum Likelihood Classifier as much as 3% in the classification of training data. When ground reference data is used, we could get poor result from both of classification methods, but we could reach conclusion that the classification result of Neural Network Classifier is superior to the classification result of Maximum Likelihood Classifier as much as 10%.

• Journal of Korean Society for Geospatial Information Science
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• v.8 no.2 s.16
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• pp.47-60
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• 2000

On this study, Among the classification methods of land cover using satellite imagery, we compared the classification accuracy of Neural Network Classifier and that of Maximum Likelihood Classifier which has the characteristics of parametric and non-parametric classification method. In the assessment of classification accuracy, we analyzed the classification accuracy about testing area as well as training area that many analysts use generally when assess the classification accuracy. As a result, Neural Network Classifier is superior to Maximum Likelihood Classifier as much as 3% in the classification of training data. When ground reference data is used, we could get poor result from both of classification methods, but we could reach conclusion that the classification result of Neural Network Classifier is superior to the classification result of Maximum Likelihood Classifier as much as 10%.

• Korean Management Science Review
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• v.21 no.2
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• pp.61-77
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• 2004

As various methodologies for business process analysis and design have been conducted in many organizations by their own ways, those methodologies are not compatible each other. In order to reduce the cost of analysis for organizations. some mapping methods between different methodologies need to be developed. UMM(UN/CEFACT Modeling Methodology) that has an object-oriented point of view. can overcome the limits of existing bottom-up approaches and make it reasonable. It also simplifies the business and administrative procedures. IDEF( Integrated Definition Language) with a structural point of view that has been widely used as a system analysis and design method, needs to be mapped to UMM in order to reuse the existing IDEF models. In this study, we propose a guideline that deals with procedures of utilizing IDEF models from which we want to derive the UMM models for developing an electronic commerce system including electronic documents exchange. By comparing IDEF and UMM, we analyze the differences between those two methodologies. Based on these differences. we suggest the basic strategies for mapping method from IDEF to UMM. We also propose a mapping guideline that can make UMM results from the modeling results of IDEF. We can take an advantage of the existing IDEF analysis design results when we adopt UMM methodology for electronic business system. Many analysts who are familiar with the IDEF methodology can develop UMM work-flow by utilizing their existing results and skills.

• Korean Management Science Review
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• v.30 no.1
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• pp.43-58
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• 2013

Although analysis of charts, which used in stock trading by distinguishing standardized patterns in the movements of stock prices, is simple and easy to use, there can be problems stemming from specific patterns being distinguished as a result of the subjective perspectives of analysts. In accordance with such problems, through the method of template pattern matching, 4 trend reversal patterns were designed and the fitness of the patterns were quantitatively measured. In cases when a stock is purchased when the template pattern fitness value is within a certain range and held for at least 20-days, the average return ratio was analyzed to be higher-with the difference being statistically significant-than the average return ratio attained from trading a stock according to the same method per the Efficient Market Hypothesis. From the results of stock trades of 2 domestic corporations to which the values of the 4 patterns had been applied based on the 4 strategies, it was possible to ascertain differences in the strategy- and pattern-dependent return ratios. Through this study, along with presenting the exceptions for the Efficient Market Hypothesis in stock trading, the fitness level of quantitative chart patterns was measured and the theoretical basis for application of such fitness level was proposed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.251-257
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• 2020

The study investigates the role of commodity prices and tax purpose recognition on bitcoin prices. Since the introduction of bitcoin in 2008, emphasis has focused on economists, policy-makers and analysts drastically increasing bitcoin's accessibility and commodity values (Dumitrescu & Firică, 2014). This study employs GARCH and EGARCH from ARCH/GARCH family on daily nature data. We measure the volatile behavior of bitcoin by employing auto-regressive conditional heteroscedasticity model with the aim to explore the relationship between major commodities and bitcoin volatility. We focus on major commodities like gold, silver, platinum, and crude oil to be regressed with bitcoin. The daily prices of commodities were retrieved from www.investing.com and bitcoin prices from www.coindesk.com for the period from 29April 2013 to 16 October 2018. Results confirmed the currency's long-term volatile behavior, which is due to its composition and market dynamics, whereas the existence of asymmetric information effect is not confirmed. Tax recognition by other countries may in future help in controlling the volatility as bitcoin is not a country-specific security. But, only silver impacts on volatility in comparison to oil prices and platinum, which is due to its similar features with gold. Eventually, bitcoin can be used for risk diversification and money making.