• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.601-609
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• 2014

The most widely used data mining technique for big data analysis is to generate meaningful association rules. This method has been used to find the relationship between set of items based on the association criteria such as support, confidence, lift, etc. Among them, confidence is the most frequently used, but it has the drawback that we can not know the direction of association by it. The attributably pure confidence was developed to compensate for this drawback, but the value was changed by the position of two item sets. In this paper, we propose four symmetrically and attributably pure confidence measures to compensate the shortcomings of confidence and the attributably pure confidence. And then we prove three conditions of interestingness measure by Piatetsky-Shapiro, and comparative studies with confidence, attributably pure confidence, and four symmetrically and attributably pure confidence measures are shown by numerical examples. The results show that the symmetrically and attributably pure confidence measures are better than confidence and the attributably pure confidence. Also the measure NSAPis found to be the best among these four symmetrically and attributably pure confidence measures.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.235-243
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• 2011

The most widely used data mining technique is to explore association rules. This technique has been used to find the relationship between each set of items based on the association thresholds such as support, confidence, lift, etc. There are many interestingness measures as the criteria for evaluating association rules. Among them, confidence is the most frequently used, but it has the drawback that it can not determine the direction of the association. The net confidence measure was developed to compensate for this drawback, but it is useless in the case that the value of positive confidence is the same as that of negative confidence. This paper propose a attributably pure confidence to evaluate association rules and then describe some properties for a proposed measure. The comparative studies with confidence, net confidence, and attributably pure confidence are shown by numerical example. The results show that the attributably pure confidence is better than confidence or net confidence.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.523-532
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• 2013

Generally, data mining is the process of analyzing big data from different perspectives and summarizing it into useful information. The most widely used data mining technique is to generate association rules, and it finds the relevance between two items in a huge database. This technique has been used to find the relationship between each set of items based on the interestingness measures such as support, confidence, lift, etc. Among many interestingness measures, confidence is the most frequently used, but it has the drawback that it can not determine the direction of the association. The attributably pure confidence and compared confidence are able to determine the direction of the association, but their ranges are not [-1, +1]. So we can not interpret the degree of association operationally by their values. This paper propose a compared and attributably pure confidence to compensate for this drawback, and then describe some properties for a proposed measure. The comparative studies with confidence, compared confidence, attributably pure confidence, and a proposed measure are shown by numerical example. The results show that the a compared and attributably pure confidence is better than any other confidences.

• Journal of the Korean Data and Information Science Society
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• v.22 no.3
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• pp.495-503
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• 2011

The most widely used data mining technique is to find association rules. Association rule mining is the method to quantify the relationship between each set of items in very huge database based on the association thresholds. There are some basic association thresholds to explore meaningful association rules ; support, confidence, lift, etc. Among them, confidence is the most frequently used, but it has the drawback that it can not determine the direction of the association. The net confidence and the attributably pure confidence were developed to compensate for this drawback, but they have other drawbacks.In this paper we consider some predictive similarity measures for binary data in cluster analysis and multi-dimensional analysis as association threshold to compensate for these drawbacks. The comparative studies with net confidence, attributably pure confidence, and some predictive similarity measures are shown by numerical example.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.939-948
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• 2012

The most widely used data mining technique is to explore association rules. This technique has been used to find the relationship between items in a massive database based on the interestingness measures such as support, confidence, lift, etc. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control.In general, association rule technique generates the rule, 'If A, then B.', whereas negative association rule technique generates the rule, 'If A, then not B.', or 'If not A, then B.'. We can determine whether we promote other products in addition to promote its products only if we add negative association rules to existing association rules. In this paper, we proposed the negatively attributable and pure confidence to overcome the problems faced by negative association rule technique, and then we checked three conditions for interestingness measure. The comparative studies with negative confidence, negatively pure confidence, and negatively attributable and pure confidence are shown by numerical examples. The results show that the negatively attributable and pure confidence is better than negative confidence and negatively pure confidence.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.619-630
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• 2019

Dyslipidemia is a representative chronic disease affecting Koreans that requires continuous management. It is also a known risk factor for cardiovascular disease such as hypertension and diabetes. However, it is difficult to diagnose vascular disease without a medical examination. This study identifies risk factors for the recognition and prevention of dyslipidemia. By integrating them, we construct a statistical instrumental nomogram that can predict the incidence rate while visualizing. Data were from the Korean National Health and Nutrition Examination Survey (KNHANES) for 2013-2016. First, a chi-squared test identified twelve risk factors of dyslipidemia. We used a naïve Bayesian classifier model to construct a nomogram for the dyslipidemia. The constructed nomogram was verified using a receiver operating characteristics curve and calibration plot. Finally, we compared the logistic nomogram previously presented with the Bayesian nomogram proposed in this study.

• KOREAN POULTRY JOURNAL
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• v.37 no.3 s.425
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• pp.103-105
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• 2005

옛부터 국내 재래닭은 우리나라 국민들의 식성에 알맞는 독특한 맛과 육질로 인하여 가든이나 토속 음식점 등에서 고가로 판매되면서 입지를 굳혀오고 있다. 일부 지역에서는 지역 특성에 맞는 브랜드를 상품등록하여 소비자들로부터 신뢰를 받는 농가들도 늘어가고 있다. 이런 가운데 축산연구소(소장 윤상기)에서는 빠르면 금년말 국내 순수 혈통을 자랑하는 재래닭이 상품등록을 마치고 공식 탄생할 예정이다. 축산연구소 가금과(과장 이덕수)는 이미 10년에 걸친 재래닭 복원작업을 마치고 3월중 특허청에 재래닭 3개 계통(흑색, 황갈색, 적갈색)에 대해 등록출원 준비를 마친 상태이다. 상표등록이 이루어질 경우 철저한 가계선발과 사양관리를 통해 고정된 국내 유일의 재래닭을 국제적으로 알리고 국내 소비자들에게 재래닭의 참맛을 전달하게 될 것으로 기대를 모으고 있다.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.209-215
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• 2018

The level of cultural enjoyment in Korea has improved every year, but the culture that the general public possesses artworks has not developed so much. Most artwork trading systems, from traditional ones to the latest blockchain-based ones, are designed for expensive artwork trading and are hardly accessible to the general public. In this paper, we propose a blockchain-based artwork trading system that can improve the culture of the general public's art collection and contribute to the popularization of fine art. The proposed system consists of three interacted blockchains for identification, artwork registration and smart contract. The proposed system utilizes the advantages of the blockchain system for users to provide trust to each other, and introduces the concept of art notebook for artists to build trust in their own artwork. Since the proposed system builds a trust system through participants rather than experts or external organizations, it can reduce the cost of trading and deal with artworks that can be owned by the general public.

• Journal of Radiation Protection and Research
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• v.8 no.2
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• pp.36-40
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• 1983

Uranium radionuclides are electrodeposited on inexpensive stainless steel cathode from a mixed oxalate-chloride electrolyte. The factors affecting the optimum condition for the deposition are determined by studying the effects of deposition time, initial current, electrode spacing, pH of electrolyte and uranium concentration in the electrolyte at fixed cathode area. The experiment which was repeated 3 times at each uranium concentration with 60 minutes of deposition time, gave an error of less than 4% standard deviation at the 90% confidence level with average yield greater than 99%.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.205-212
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• 1999

When we want to observe and record a patient's EEG in an operating room, the operation of electrosurgical unit(ESU) causes undesirable artifacts with high frequency and high voltage. These artifacts make the amplifiers of the conventional EEG system saturated and prevent the system from measuring the EEG signal. This paper describes a high-performance bipolar EEG amplifier for a CSA (compressed spectral array ) system with reduced ESU artifacts. The designed EEG amplifier uses a balanced filter to reduce the ESU artifacts, and isolates the power supply and the signal source of the preamplifier from the ground to cut off the current from the ESU to the amplifier ground. To cancel the common mode noise in high frequency, a high CMRR(common mode rejection ratio) diffferential amplifier is used. Since the developed bipolar EEG amplifier shows high gain, low noise, high CMRR, high input impedance, and low thermal drift, it is possible to observe and record more clean EEG signals in spite of ESU operation. Therefore the amplifier may be applicable to a high-fidelity CSA system.