• Journal of Ocean Engineering and Technology
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• v.33 no.3
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• pp.222-228
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• 2019

An extreme value analysis (EVA) is essential to obtain a design value for highly nonlinear variables such as long-term environmental data for wind and waves, and slamming or sloshing impact pressures. According to the extreme value theory (EVT), the extreme value distribution is derived by multiplying the initial cumulative distribution functions for independent and identically distributed (IID) random variables. However, in the position mooring of DNVGL, the sampled global maxima of the mooring line tension are assumed to be IID stochastic variables without checking their independence. The ITTC Recommended Procedures and Guidelines for Sloshing Model Tests never deal with the independence of the sampling data. Hence, a design value estimated without the IID check would be under- or over-estimated because of considering observations far away from a Weibull or generalized Pareto distribution (GPD) as outliers. In this study, the IID sampling data are first checked in an EVA. With no IID random variables, an automatic resampling scheme is recommended using the block maxima approach for a generalized extreme value (GEV) distribution and peaks-over-threshold (POT) approach for a GPD. A partial autocorrelation function (PACF) is used to check the IID variables. In this study, only one 5 h sample of sloshing test results was used for a feasibility study of the resampling IID variables approach. Based on this study, the resampling IID variables may reduce the number of outliers, and the statistically more appropriate design value could be achieved with independent samples.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.43-55
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• 2006

In this paper, we present a framework which is used to develop, modify, maintain and extend a control and monitoring software easily for any kind of automatic instruments. The proposed framework is composed of three XML documents (IID, MAP, CMIML) and two tools (Virtual Instrument Wizard, Generator). Interface information of behaviors and states of instrument is written on IID. Mapping information between the interface information in IID and API of a real instrument driver is written on MAP Final information of the control and monitoring software is written on CMIML, IID, MAP and CMIML are written by XML format to provide a common usage and platform independence of the proposed framework. Vl Wizard generates CMIML intermediate platform independent document using IID and existing CMIML, and Generator generates the source code of a control and monitoring software platform dependent code automatically using CMIML and MAP. The suggested framework provides an easy development and maintenance because it automatically generates a control and monitoring software in GUI environment and it also provides common usage and platform independence in virtue of using description document of XML format. Also, reusability can be increased by reusing platform independent software description document and not reusing platform dependent software code.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.932-935
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• 2004

In this paper, we present a framework that is easy to develop, modify, maintain and extend a control and monitoring software for any kinds of instruments. The presented framework is composed of three XML documents (IID, MAP, and CMIML) and two tools (Virtual Instrument Wizard, Generator). Interface information about behaviors and states of instruments is written on IID. Mapping information between the interface information in IID and API of a real instrument driver is written on MAP. Finally information about control and monitoring software is written on CMIML. IID, MAP and CMIML are written with XML format to provide common usage and platform independence of the suggested framework. VI Wizard generates CMIML (platform independent intermediate document) using IID and existing CMIML, and Generator generates source code of a control and monitoring software (platform dependent code) automatically using CMIML and MAP. The suggested framework that automatically generates control and monitoring software based on GUI provides easy development and maintenance. Also, reusability can be increased by reusing platform independent software description documents.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.3
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• pp.1255-1259
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• 2016

Background: Oral physiotherapy or mouth exercise is considered to be an adjunct but mandatory treatment modality for oral submucous fibrosis (OSMF). This study planned to evaluate the clinical efficacy of a newly designed mouth exercising device (MED) in OSMF patients receiving local ointment, intra-lesional drugs and surgical treatment. Materials and Methods: A total of 231 OSMF patients were selected and treated with basic regime including topical corticosteroids, oral antioxidants and the icecream-stick exercise regime and allotted randomly to two equal groups A and B. Group-A patients were additionally given MED. Subgroups A1 and B1 patients with an inter-incisal distance (IID) 20-35mm were not given any additional therapy; subgroup A2 and B2 patients (IID 20-35mm) were treated additionally with intra-lesional injections. Subgroups A3 and B3 with IID<20mm were managed surgically. IID was measured at baseline and at 6 months recall. The change in IID measurements was calculated and statistically analyzed using 2-way ANOVA and Tukeys multiple post hoc analysis. Results: Average improvement in IID after six months of recall visits was observed to be 8.4 mm in subgroup-A1 (n-53) compared to 5.5 mm in B1(n-50) (p<0.01). The IID improvement in subgroup-A2 was found to be 9.3mm (n-46) compared to 5.1 mm in B2 (n-48) (p<0.01). In the surgery group, mouth opening improvement was observed to be 9.6 mm in subgroup A3 (n-18) compared to 4.8 mm for B3 (n-16) (p<0.01). Conclusions: Use of the MED appears to be effective for increasing oral opening in OMSF patients in conjunction with local, injection and/or surgical treatment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.5
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• pp.1017-1025
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• 2000

The human auditory system has been shown to posses remarkable abilities in the localization and tracking of sound sources. The localization is the result of processing two primary acoustics cues. These are the interaural time difference(ITD) cues and interaural intensity difference(IID) cues at the two ears. In this paper, we propose TEPILD(Time Energy Previous Integration Location Detector) model. TEPILD model is constructed with time function generator, energy function generator, previous location generator and azimuth detector. Time function generator is to process ITD and energy function generator is to process IID. Total average accuracy rate is 99.2%. These result are encouraging and show that proposed model can be applied to the sound source location detector.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.533-534
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• 2023

본 논문에서는 불균형하게 분포된(Non-IID) 데이터를 소유하고 있는 데이터 소유자(클라이언트)들을 가정하고, 데이터 소유자들 간 원본 데이터의 직접적인 이동 없이도 딥러닝 학습이 가능하도록 연합학습을 적용하였다. 실험 환경 구성을 위하여 MNIST 손글씨 데이터 세트를 하나의 숫자만 다량 보유하도록 분할하고 각 클라이언트에게 배포하였다. 연합학습을 적용하여 손글씨 분류 모델을 학습하였을 때 정확도는 85.5%, 중앙집중식 학습모델의 정확도는 90.2%로 연합학습 모델이 중앙집중식 모델 대비 약 95% 수준의 성능을 보여 연합학습 시 성능 하락이 크지 않으며 특수한 상황에서 중앙집중식 학습을 대체할 수 있음을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1892-1902
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• 2016

NIST SP 800-90B is developed to evaluate the security of entropy sources. As SP 800-90B was updated to Second Draft, Estimators with predictors were added at Non-IID track. Though the predictors are known as detecting periodic property of noise sources, periodic properties which are detected by predictor are not clearly known. In this paper, we experiment to find properties of predictors. Once, by experiments we have a result that the min-entropy of Non-IID noise sources is generally determined by tests except for estimators with predictors. And then through presenting various experimental results for clarifying periodic properties detected by predictor, we experimentally analyze on its meaning and role of predictor estimation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.309-316
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• 2011

In this paper, equalization zone of two crosstalk cancellation (CC) schemes, which are the one based on only head related transfer function (HRTF) and the other one based on interaural intensity/time difference (ITD/IID) as well as HRTF is studied. To do this, the condition numbers and ITD/IID levels of two schemes are shown.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.1-11
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• 2023

Federated learning (FL) is a ground breaking machine learning paradigm that allow smultiple participants to collaboratively train models in a cloud environment, all while maintaining the privacy of their raw data. This approach is in valuable in applications involving sensitive or geographically distributed data. However, one of the challenges in FL is dealing with heterogeneous and non-independent and identically distributed (non-IID) data across participants, which can result in suboptimal model performance compared to traditionalmachine learning methods. To tackle this, we introduce FedGCD, a novel FL algorithm that employs Graph Neural Network (GNN)-based community detection to enhance model convergence in federated settings. In our experiments, FedGCD consistently outperformed existing FL algorithms in various scenarios: for instance, in a non-IID environment, it achieved an accuracy of 0.9113, a precision of 0.8798,and an F1-Score of 0.8972. In a semi-IID setting, it demonstrated the highest accuracy at 0.9315 and an impressive F1-Score of 0.9312. We also introduce a new metric, nonIIDness, to quantitatively measure the degree of data heterogeneity. Our results indicate that FedGCD not only addresses the challenges of data heterogeneity and non-IIDness but also sets new benchmarks for FL algorithms. The community detection approach adopted in FedGCD has broader implications, suggesting that it could be adapted for other distributed machine learning scenarios, thereby improving model performance and convergence across a range of applications.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.1
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• pp.25-39
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• 2018

NIST(National Institute of Standards and Technology) has recently published SP 800-90B second draft which is the document for evaluating security of entropy source, a key element of a cryptographic random number generator(RNG), and provided a tool implemented on Python code. In SP 800-90B, the security evaluation of the entropy sources is a process of estimating min-entropy by several estimators. The process of estimating min-entropy is divided into IID track and non-IID track. In IID track, the entropy sources are estimated only from MCV estimator. In non-IID Track, the entropy sources are estimated from 10 estimators including MCV estimator. The running time of the NIST's tool in non-IID track is approximately 20 minutes and the memory usage is over 5.5 GB. For evaluation agencies that have to perform repeatedly evaluations on various samples, and developers or researchers who have to perform experiments in various environments, it may be inconvenient to estimate entropy using the tool and depending on the environment, it may be impossible to execute. In this paper, we propose high-speed implementations and an efficient memory usage technique for min-entropy estimation algorithm of SP 800-90B. Our major achievements are the three improved speed and efficient memory usage reduction methods which are the method applying advantages of C++ code for improving speed of MultiMCW estimator, the method effectively reducing the memory and improving speed of MultiMMC by rebuilding the data storage structure, and the method improving the speed of LZ78Y by rebuilding the data structure. The tool applied our proposed methods is 14 times faster and saves 13 times more memory usage than NIST's tool.