• Communications for Statistical Applications and Methods
• /
• v.2 no.1
• /
• pp.145-154
• /
• 1995

Empirical Bayes approach is applied to estimation of the binomial parameter when there is a cost for observations. Both the sample size and the decision rule for estimating the parameter are determined stochastically by the data, making the result more useful in applications. Our empirical Bayes problems with non-iid components are compared to the usual empirical Bayes problems with iid components. The asymptotic optimal procedure with a computer simulation is given.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10c
• /
• pp.712-714
• /
• 2003

과거 우리는 장비에 대한 제어 및 모니터링 소프트웨어의 효율적인 생성을 위한 프레임웍[1][2]을 제안하였다. 제안한 프레임웍은 세가지의 XML 문서(IID, MAP, CMIML), VI Wizard, Generator로 구성되었다. 본 논문에서는 제안한 프레임웍의 핵심이라고 할 수 있는 VI Wizard에 대한 설계와 구현을 보인다. VI Wizard는 장비의 인터페이스 정보를 기술하고 있는 IID(Instrument Interface Description) 문서를 이용해서 GUI 기반으로 VI(Virtual Instrument)를 구성하고, 새롭게 구성된 VI를 이용하여 장비의 제어정보, 사용자 인터페이스 정보, 모니터링 정보, 통신 정보, 스케줄 정보 등을 기술하는 CMIML(Control & Monitoring Instrument Markup Language)문서를 생성한다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.722-723
• /
• 2023

연합학습은 중앙 서버에서 데이터를 수집하는 방식이 아닌 로컬 디바이스 또는 클라이언트에서 학습을 진행하고 중앙 서버로 모델 업데이트만 전송하는 분산 학습 기법으로 데이터 보안 및 개인정보보호를 강화하는 동시에 효율적인 분산 학습을 수행할 수 있다. 그러나, 연합학습 대부분의 시나리오는 클라이언트의 서로 다른 분포 형태인 non-IID 데이터를 대상으로 학습함에 따라 중앙집중식 모델에 비하여 낮은 성능을 보이게 된다. 이에 본 연구에서는 연합학습 모델의 성능을 개선하기 위하여 non-IID 의 환경에서 참여 후보자 중에서 적합한 클라이언트 선택의 최적화 기법을 분석한다.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.1
• /
• pp.26-38
• /
• 2020

A statistical test was carried out on the IID (Independently and Identically Distributed) assumption of the AM (Annual Maxima) data used to estimate the design wave height. The test was divided into independence (randomness) test and homogeneity test, and each test was conducted on AM data of 210 and 310 stations in coastal and inner coastal grids in typhoon and non-typhoon (monsoon) conditions. As a result of the independence test, the rejection ratios of the test are in the range of 1.8~5.3% and 1.4~6.0% for the non-typhoon and typhoon data sets, respectively. On the other hand, in the distribution difference test of typhoon data and nontyphoon data, the same distribution hypothesis was found to be rejected in the range of 47~79% according to the test method for both coastal grid and inner coastal grid. Therefore, in estimating design wave height by extreme value analysis, the estimation process by dividing the typhoon and non-typhoon data is appropriate.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.11
• /
• pp.13-18
• /
• 2022

In this paper, we proposed VW-FedAVG(Validation based Weighted FedAVG) which updates the global model by weighting according to performance verification from the models of each device participating in the training. The first method is designed to validate each local client model through validation dataset before updating the global model with a server side validation structure. The second is a client-side validation structure, which is designed in such a way that the validation data set is evenly distributed to each client and the global model is after validation. MNIST, CIFAR-10 is used, and the IID, Non-IID distribution for image classification obtained higher accuracy than previous studies.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.4
• /
• pp.21-34
• /
• 2023

Federated Learning is divided into synchronous federated learning and asynchronous federated learning. Asynchronous federated learning has a time advantage over synchronous federated learning, but asynchronous federated learning still has some challenges to obtain better performance. In particular, preventing performance degradation in non-IID training datasets, selecting appropriate clients, and managing stale gradient information are important for improving model performance. In this paper, we deal with K-asynchronous federated learning by using non-IID datasets. In addition, unlike traditional method using static K, we proposed an algorithm that adaptively adjusts K and we can reduce the learning time. Additionally, the we show that model performance is improved by using stale gradient handling method. Finally, we use a method of judging model performance to obtain strong model stability. Experiment results show that overall algorithm can obtain advantages of reducing training time, improving model accuracy, and improving model stability.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2003.05b
• /
• pp.1177-1180
• /
• 2003

본 논문에서는 자동화 장비들의 제어 및 모니터링 소프트웨어에 대한 쉬운 개발과 유지보수성을 향상시킬 수 있는 프레임워크를 제안한다. 본 논문에서 제안하는 프레임워크는 XML기반의 세 가지 표준 문서 형식(IID, MAP. CMIML), VI Wizard, Generator로 구성된다. VI Wizard는 표준문서형식(IID, MAP, CMIML)을 내장하고. 입력받은 IID와 MAP파일을 이용해서 GUI기반으로 VI(Virtual Instrument)를 구성한다. 새롭게 구성된 VI를 이용하여 장비의 제어정보, 사용자 인터페이스 정보 모니터링 정보, 통신 방법 등에 대한 정보를 기술하는 CMIML을 생성한다. Generator는 VI Wizard에서 생성한 CMIML문서와 실제 장비 드라이버에 대한 API를 입력으로 장비에 대한 제어 및 모니터링 소프트웨어를 자동 생성하게 된다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.537-537
• /
• 2015

In recent decades, the independence and identical distribution (iid) assumption for extreme events has been shown to be invalid in many cases because long-term climate variability resulting from phenomena such as the Pacific decadal variability and El Nino-Southern Oscillation may induce varying meteorological systems such as persistent wet years and dry years. Therefore, in the current study we propose a new parameter estimation method for probability distribution models to more accurately predict the magnitude of future extreme events when the iid assumption of probability distributions for large-scale climate variability is not adequate. The proposed parameter estimation is based on a metaheuristic approach and is derived from the objective function of the rth power probability-weighted sum of observations in increasing order. The combination of two distributions, gamma and generalized extreme value (GEV), was fitted to the GEV distribution in a simulation study. In addition, a case study examining the annual hourly maximum precipitation of all stations in South Korea was performed to evaluate the performance of the proposed approach. The results of the simulation study and case study indicate that the proposed metaheuristic parameter estimation method is an effective alternative for accurately selecting the rth power when the iid assumption of extreme hydrometeorological events is not valid for large-scale climate variability. The maximum likelihood estimate is more accurate with a low mixing probability, and the probability-weighted moment method is a moderately effective option.

• Journal of Korean Institute of Industrial Engineers
• /
• v.23 no.4
• /
• pp.755-767
• /
• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1996.04a
• /
• pp.714-718
• /
• 1996

The interference phenomenonof a dynamic crack propagation in a inclined DEN(double edge notched) specimen has been investigated by using the dynamic photoelasticity. One crack initiated by static loading is propagated dynamically and experiences a mixed mode condition(interference) as the crack approaches to the inclined edge notch. We use the overdeterministic least-square method to extract dynamic $K_{Id}$ K sub IId/and .sigma. $_{ox}$from the recorded dynamic photoelastic pattern surounding a running crack. The evaluated $K_{Id}$ $K_{IId}$and .sigma. $_{ox}$together with the crack propagation velocity estimate the dynamic crack interference phenomenonenonon