• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권4호
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• pp.1307-1329
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• 2022

This paper proposes an improved Pseudorandom Sequence Generator (PRSG) based on the concept of modular arithmetic systems with non-integral numbers. The generated random sequence use in various cryptographic applications due to its unpredictability. Here the mathematical model is designed to solve the problem of the non-uniform distribution of the sequences. In addition, PRSG has passed the standard statistical and empirical tests, which shows that the proposed generator has good statistical characteristics. Finally, image encryption has been performed based on the sort-index method and diffusion processing to obtain the encrypted image. After a thorough evaluation of encryption performance, there has been no direct association between the original and encrypted images. The results show that the proposed PRSG has good statistical characteristics and security performance in cryptographic applications.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.301-317
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• 2022

In this paper, we propose a change point detection procedure based on the modified information criterion in a generalized lambda distribution (GLD) model. Simulations are conducted to obtain empirical critical values of the proposed test statistic. We have also conducted simulations to evaluate the performance of the proposed methods comparing to the log-likelihood method in terms of power, coverage probability, and confidence sets. Our results indicate that, under various conditions, the proposed method modified information criterion (MIC) approach shows good finite sample properties. Furthermore, we propose a new goodness-of-fit testing procedure based on the energy distance to evaluate the asymptotic null distribution of our test statistic. Two real data applications are provided to illustrate the use of the proposed method.

• 한국정밀공학회지
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• 제13권10호
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• pp.130-138
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• 1996

In general, the scattler is observed in fatigue test data due to the nonhomogeneity of a material. Consequently. It is necessary to use the statistical method to describe the fatigue crack growth process precisely. Bogdanoff and Kozin suggested and developed the B-model which is the probabilistic models of cumulative damage using the Markov process in order to describe the damage process. But the B-model uses only constant probability ratior(r), so it is not consistent with the actual damage process. In this study, the r-decreasing model using a monotonic decreasing function is introduced to improve the B-model. To verify the model, thest data of fatigue crack growth of A12024-T351 and A17075-T651 are used. Compared with the empirical distribution of test data, the distribution from the r-decreasing model is satisfactory and damage process is well described from the probabilistic and physical viewpoint.

• 한국정밀공학회지
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• 제14권11호
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• pp.147-153
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• 1997

Fault diagnosis technique in machining system which is one of engineering techniques absolutely necessary to automation of manufacturing system has been proposed. As a whole, diagnosis process is explained by two steps: sensor data acquisition and reasoning current state of system with the given sensor data. Flexible disk grinding process implemented in milling machine was employed in order to obtain empirical manufacturing process information. Resistance force data during machining were acquired using tool dynamometer known as sensor which is comparably accurate and reliable in operation. Tool status during the process was analyzed using influnece diagram assigning probability from the statistical analysis procedure.

• Pediatric Infection and Vaccine
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• 제18권2호
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• pp.109-116
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• 2011

목 적 : 폐구균은 소아의 비인두에 상재하면서 다양한 국소 및 침습성 감염을 일으키며, 특히 2세 이하의 소아에서 발병 빈도가 높다. 2008년 미국 CLSI의 기준이 개정되면서 국내 폐구균의 페니실린 감수성률이 증가하였고 이에 따라 국내 경증 폐구균 감염증의 경험적 치료로서 경구 페니실린 및 amoxicillin의 사용이 가능하다. 최근 약력동학적 모델을 이용하여 항생제의 치료 효과를 평가하는 연구들이 보고되고 있으며, 본 연구는 이러한 모델 분석을 통해 국내 소아에서의 폐구균 감염증 치료시, 경험적 항생제로서 amoxicillin의 적절한 용량 결정에 도움이 되는 기초 자료를 얻고자 한다. 방 법: 2008년 9월부터 10월까지 서울에 위치한 어린이집을 방문하여 건강한 무증상 소아로부터 분리한 폐구균 23균주를 대상으로, 베타락탐 및 마크로라이드 항생제에 대한 MIC 값을 측정하였다. 베타락탐 항생제의 경우 각 균주의 MIC 값에서 fT>MIC가 50% 이상 되는것을 목표치로 정하고 목표치 획득 확률(PTA)이 90% 이상일 경우 적절한 항생제 요법으로 간주하였다. 소아의 상기도내에 보균된 폐구균 균주가 중이염 등의 폐구균 감염증의 원인 균주가 될 가능성이 높다는 전제하에, 이러한 Monte Carlo simulation 모델에서 구해진 PTA값에 본 연구에 포함된 폐구균 균주의 MIC 값을 적용하여 분석하였다. 결 과:건강한 소아의 인후에서 분리된 23개 폐구균균주중 베타락탐 항생제인 정주용 penicillin, amoxicillin 및 cefotaxime에 대한 감수성 균주의 분율은 각각 78.3%, 82.6% 및 82.6%였고, 마크로라이드 항생제인 erythromycin에 대한 감수성 균주는 단 한 개였다. Fallon등19)이 제시한 Monte Carlo simulation 모델에서 약10 kg의 소아에게 amoxicillin을 40 mg/kg/일의 용량으로 투여 시 $MIC{\leq}1.0{\mu}g$/mL인 폐구균의 경우 PTA 값이 90%였으나, MIC 값이 2 ${\mu}g$/mL로 증가되면 PTA 값이 52%로 감소하였다. 그러나 amoxicillin을 90 mg/kg/일의 용량으로 투여 시 MIC 값이 2 ${\mu}g$/mL인 폐구균의 경우에도 PTA가 97%로 좋은 치료 반응이 예상된다. 이 모델에 국내의 건강한 소아의 인두에서 분리된 폐구균 균주의 MIC 값을 적용하여 약력동학적인 면을 고려한 적절한 항생제 용법을 판단하였다. 본 연구에서 분리된 23개의 폐구균 균주 중 amoxicillin에 대한 MIC 값이${\leq}1.0 {\mu}g$/mL인 경우는 7 균주(30.4%), ${\leq}2 {\mu}g$/mL인 경우는 19 균주(82.6%)로, 국내 소아의 급성 중이염과 같은 폐구균 감염증에서 경구용 amoxicillin을 90 mg/kg/일의 용량으로 투여시 80% 이상에서 좋은 치료 성적을 기대할 수 있었다. 결 론 : 국내 소아의 폐구균 감염증에서 경험적 항생제로 amoxicillin을 투여할 경우, 약력동학적 모델을 이용하면 90 mg/kg/day의 고용량이 더욱 효과적일 것으로 생각되며, 저용량의 amoxicillin 또는 마크로라이드 처방은 치료 실패의 확률이 높을 것으로 추정된다.

• 콘크리트학회논문집
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• 제21권2호
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• pp.187-197
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• 2009

본 논문은 진동수에 따른 취약도 곡선과 손상확률을 제시하였다. 취약도곡선과 손상확률은 주어진 지진동에 의해 임의의 구조물이 견딜 수 있는 손상의 정도를 나타낸다. 지진에 의한 피해는 지진이 가지는 불확실성으로 인하여 확률적으로 예측하여야 한다. 기존 연구와 달리 본 연구에서는 비선형 동적 해석과 실험 결과를 이용하였다. 본 연구에서는 프리스트레스트 콘크리트 교량에 대한 수치적 시뮬레이션을 통하여 주어진 최대지반가속도에 따른 5단계의 손상 단계별 손상확률을 구하였다. 취약도 곡선을 산출하기위해 해석적 연구를 수행하였다. 이를 위해 지반조건에 따라 각각 100개의 인공지진파를 생성하고 비선형 시간이력해석을 수행하였다. 손상단계는 기존의 실험 결과에 기초한 성능기반에 따라 정의하였으며 RC 교각의 지진거동을 변위연성도로 나타내었다. 손상단계 및 지반가속도를 이용하여 PSC교량의 지반조건에 따른 손상곡선을 도출하여 비교분석하였다. 연구 결과에 따르면 지반조건 및 구속철근량에 따른 손상확률의 차이를 확인할 수 있다.

• 유통과학연구
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• 제15권6호
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• pp.77-96
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• 2017

Purpose - This study aims to develop correspondence strategies to the environment change in domestic retail store types. Recently, new types of retails have emerged in retail industries. Therefore, trade area platform has developed focusing on the speed of data, no longer trade area from district border. Besides, 'trade area smart' brings about change in retail types with the development of giga internet. Thus, context shopping is changing the way of consumers' purchase pattern through data capture, technology capability, and algorithm development. For these reasons, the sales estimation model has been shown to be flawed using the notion of former scale and time, and it is necessary to construct a new model. Research design, data, and methodology - This study focuses on measuring retail change in large multi-shopping mall for the outlook for retail industry and competition for trade area with the theoretical background understanding of retail store types and overall domestic retail conditions. The competition among retail store types are strong, whereas the borders among them are fading. There is a greater need to analyze on a new model because sales expectation can be hard to get with business area competition. For comprehensive research, therefore, the research method based on the statistical analysis was excluded, and field survey and literature investigation method were used to identify problems and propose an alternative. In research material, research fidelity has improved with complementing research data related with retail specialists' as well as department stores. Results - This study analyzed trade area survival and its pattern through sales estimation and empirical studies on trade areas. The sales estimation, based on Huff model system, counts the number of households shopping absorption expectation from trade areas. Based on the results, this paper estimated sales scale, and then deducted modified probability model. Conclusions - In times of retail store chain destruction and off-line store reorganization, modified Huff model has problems in estimating sales. Transformation probability model, supplemented by the existing problems, was analyzed to be more effective in competitiveness business condition. This study offers a viable alternative to figure out related trade areas' sale estimation by reconstructing new-modified probability model. As a result, the future task is to enlarge the borders from IT infrastructure with data and evidence based business into DT infrastructure.

• 한국정보과학회논문지:소프트웨어및응용
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• 제30권3_4호
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• pp.326-338
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• 2003

신경회로망 설계 및 모델선택의 목표는 최적의 구조를 가지는 일반화 성능이 우수한 네트워크를 구성하는 것이다. 하지만 학습데이타에는 노이즈(noise)가 존재하고, 그 수도 충분하지 않기 때문에 최종적으로 표현하고자 하는 진확률 분포와 학습 데이타에 의해 표현되는 경험확률분포(empirical probability density) 사이에는 차이가 발생한다. 이러한 차이 때문에 신경회로망을 학습데이타에 대하여 과다하게 적합(fitting)시키면, 학습데이타만의 확률분포를 잘 추정하도록 매개변수들이 조정되어 버리고, 진확률 분포로부터 멀어지게 된다. 이러한 현상을 과다학습이라고 하며, 과다학습된 신경회로망은 학습데이타에 대한 근사는 우수하지만, 새로운 데이타에 대한 예측은 떨어지게 된다. 또한 신경회로망의 복잡도가 증가 할수록 더 많은 매개변수들이 노이즈에 쉽게 적합되어 과다학습 현상은 더욱 심화된다. 본 논문에서는 통계적인 관점을 바탕으로 신경회로망의 일반화 성능을 향상시키는 신경회로 망의 설계 및 모델 선택의 통합적인 프로세스를 제안하고자 한다. 먼저 학습의 과정에서 적응적 정규화가 있는 자연기울기 학습을 통해 수렴속도의 향상과 동시에 과다학습을 방지하여 진확률 분포에 가까운 신경회로망을 얻는다. 이렇게 얻어진 신경회로망에 자연 프루닝(natural pruning) 방법을 적용하여 서로 다른 크기의 후보 신경회로망 모델을 얻는다. 이러한 학습과 복잡도 최적화의 통합 프로세스를 통하여 얻은 후보 모델들 중에서 최적의 모델을 베이시안 정보기준에 의해 선택함으로써 일반화 성능이 우수한 최적의 모델을 구성하는 방법을 제안한다. 또한 벤치마크 문제를 이용한 컴퓨터 시뮬레이션을 통하여, 제안하는 학습 및 모델 선택의 통합프로세스의 일반화 성능과 구조 최적화 성능의 우수성을 검증한다.

• 한국정보시스템학회지:정보시스템연구
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• 제27권1호
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

• 보건행정학회지
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• 제19권3호
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• pp.109-124
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• 2009

Background: This study aimed to examine whether cases of punishing false claimants threat general physicians to check their medical cost claims with care to avoid being suspected, and identify empirically general deterrence effects of the on-site investigation system in the Korean National Health Insurance. Methods: 800 clinics were selected among a total of 15,443 clinics that had no experience of on-site investigation until June 2007 using a stratified proportional systematic sampling method. We conducted logistic multiple regression to examine the association between factors related to provider's perception of on-site investigation and high level of perceived deterrence referring to fear of punishment after adjusting provider's service experiences and general characteristics. Results: The probability of high perceived deterrence was higher 1.7 times (CI: 1.13-2.56), 2.73 times (CI: 1.68-4.45) each among clinics exchanging the information once or more per year or once or more for 2-3 months than among clinics no exchanging the information about on-site investigation. Also, the probability of high perceived deterrence was higher 2.27 times (CI: 1.28-4.45) among clinics that knows more than 3 health care institutions having experienced an on-site investigation than among clinics knowing no case. Conclusion: A clinic knowing more punishment cases by onsite investigation and exchanging more frequently information about on-site investigation is likely to present high perceived deterrence. This result will provide important information to enlarge preventive effects of on-site investigation on fraud and abuse claims.