• The Journal of the Acoustical Society of Korea
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• v.21 no.3
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• pp.221-229
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• 2002

In thin paper, error tolerance of each array element which satisfies error tolerance of beam pattern is decided by using the Monte-Carlo method. Conventional deterministic method decides the error tolerance of each element from the acceptance pattern by testing all cases, but this method is not suitable for the analysis of large number of array elements because the computation resources increase exponentially as the number of array elements increases. To alleviate this problem, we applied new algorithm which reduces the increment of calculation time increased by the number of the array elements. We have validates the determined error tolerance region through several simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.1
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• pp.26-32
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• 2013

Blind algorithms based on Information potential of output samples and a set of symbols generated in random order at the receiver go through performance degradation when biased impulsive noise is added to the channel since the cost function composed of information potentials has no variable to deal with biased signal. Aiming at the robustness against biased impulsive noise, we propose, in this paper, a modified information potential, and derived related blind algorithms based on augmented filter structures and a set of random-order symbols. From the simulation results of blind equalization for multipath channels, the blind algorithm based on the proposed information potential produced superior convergence performance in the environments of strong biased impulsive noise.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1951-1956
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• 2013

Distribution-matching type algorithms based on a set of symbols generated in random order provide a limited performance under biased impulsive noise since the performance criterion for the algorithms has no variables for biased signal. For the immunity against biased impulsive noise, we propose, in this paper, a modified performance criterion and derived related blind algorithms based on augmented filter structures and the distribution-matching method using a set of random symbols. From the simulation results, the proposed algorithm based on the proposed criterion yielded superior convergence performance undisturbed by the strong biased impulsive noise.

• The Korean Journal of Applied Statistics
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• v.30 no.6
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• pp.809-825
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• 2017

The number of TV entertainment shows is increasing. Competition among programs in the entertainment market is intensifying since cable channels air many entertainment TV shows. There is now a need for research on program ratings and the number of episodes. This study presents predictive models for entertainment TV show ratings and number of episodes. We use various data mining techniques such as linear regression, logistic regression, LASSO, random forests, gradient boosting, and support vector machine. The analysis results show that the average program ratings before the first broadcast is affected by broadcasting company, average ratings of the previous season, starting year and number of articles. The average program ratings after the first broadcast is influenced by the rating of the first broadcast, broadcasting company and program type. We also found that the predicted average ratings, starting year, type and broadcasting company are important variables in predicting of the number of episodes.

• Phonetics and Speech Sciences
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• v.12 no.4
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• pp.91-98
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• 2020

This study investigated the acoustic characteristics of sustained vowel /a/ and sentence utterance produced by patients with muscle tension dysphonia (MTD) using cepstrum-based acoustic variables. 36 women diagnosed with MTD and the same number of women with normal voice participated in the study and the data were recorded and measured by ADSVTM. The results demonstrated that cepstral peak prominence (CPP) and CPP_F0 among all of the variables were statistically significantly lower than those of control group. When it comes to the GRBAS scale, overall severity (G) was most prominent, and roughness (R), breathiness (B), and strain (S) indices followed in order in the voice quality of MTD patients. As these characteristics increased, a statistically significant negative correlation was observed in CPP. We tried to classify MTD and control group using CPP and CPP_F0 variables. As a result of statistic modeling with a Random Forest machine learning algorithm, much higher classification accuracy (100% in training data and 83.3% in test data) was found in the sentence reading task, with CPP being proved to be playing a more crucial role in both vowel and sentence reading tasks.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.791-794
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• 1998

칩의 집적도에 비레한 테스트 문제의 원초적인 해결은 VHDL등으로 기술되는 상위기능 수준에서부터 고려되어야 한다. 본 논문에서는 상위수준의 기능정보에서 테스트점을 삽입 제어흐름(control flow)를 변경하여 고집적 회로의 고장점검도를 증진시키는 기술을 소개한다. while 푸프와 if-then-else 제어문에 AND 및 OR 타입 등의 테스점을 삽입하여 내부 신호의 조정도를 최적화시킨다. 랜덤패턴 시뮬레이션을 벤치마크 회로에 적용 각 변수의 조정도를 산출하여 테스트점의 종류 및 삽입할 위치를 결정하였다. 본 연구에서 제안하는 상대적 랜덤도에 의하여 VHDL 코드에 단일 테스트점을 삽입 합성한 결과 게이트 수준회로에 대한 고장점검도가 최대 30% 까지 증진됨을 알 수 있었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.350-350
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• 2023

SCE-UA(Shuffled Complex Evolution-University Arizona)기법은 최적해 탐색 알고리즘으로 개념적 강우유출 모형(conceptual rainfall runoff model)의 보정을 위한 도구로 개발되었다. SCE-UA기법은 메타휴리스틱 방법의 일종으로 최적해를 구하기 위하여 여러번 목적함수 값을 계산해야 한다. 이 때 목적함수 계산 횟수와 해의 수렴과 관련된 제어 매개변수가 존재하며, 사용자가 적절한 값을 입력해주어야 한다. 이 연구에서는 SCE-UA와 관련된 제어 매개변수의 기능에 대해서 검토하였다. 그리고 집합체 수의 변화에 따라서 검사함수인 Ackley function의 전역해를 얼마나 잘 탐색하는지 검토하였다. 검토 결과 랜덤 시드에 따라서 전역해 탐색 결과가 달라졌으며, 집합체의 수가 증가할수록 목적함수 계산 횟수는 증가하는 경향을 나타내었다. 검사함수의 차원(결정 변수의 수)이 증가하면 전역해의 탐색률이 감소하며, 집합체의 수가 많아지면 전역해를 더 잘 찾는 경향이 나타나지만, 목적함수 계산 횟수는 더 많아지게 되는 것을 확인할 수 있었다. 2차원인 경우 집합체의 수가 7개 이상일 때 탐색 성공률은 90% 이상이 되었지만, 10차원인 경우 집합체의 수가 시험 최대값인 20개일 때의 전역해 탐색률은 37%에 그쳤다. 이 연구의 결과는 SCE-UA 기법의 설정 매개변수에 관한 기본 개념을 이해하고, 사용자가 설정 매개변수 선정 시에 활용할 수 있을 것이다.

• Journal of the Korean Geotechnical Society
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• v.27 no.10
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• pp.93-104
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• 2011

In this paper, a numerical procedure of probabilistic steady seepage analysis that considers the spatial variability of soil permeability is presented. The procedure extends the deterministic analysis based on the finite element method to a probabilistic approach that accounts for the uncertainties and spatial variation of the soil permeability. Two-dimensional random fields are generated based on a Karhunen-Lo$\grave{e}$ve expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty due to the spatial heterogeneity on the seepage behavior of soil foundation beneath water retaining structure with a single sheet pile wall. The results showed that the probabilistic framework can be used to efficiently consider the various flow patterns caused by the spatial variability of the soil permeability in seepage assessment for a soil foundation beneath water retaining structures.

• Tunnel and Underground Space
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• v.22 no.3
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• pp.196-204
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• 2012

Quantification of roughness plays an important role in modeling strength deformability and fluid flow behaviors of rock joints. A procedure was suggested to simulate joint roughness, and characteristics of the roughness was investigated in this study. Stationary fractional Brownian profiles with known input values of the fractal parameter and other profile properties were generated based on random midpoint displacement method. Also, a procedure to simulate three dimensional roughness surface was suggested using the random midpoint displacement method. Selected statistical roughness parameters were calculated for the generated self-affine profiles to investigate the attribute of roughness. Obtained results show that statistical parameters applied in this study were able to consider correlation structure and amplitude of the profiles. However, effect of data density should be tackled to use statistical parameters for roughness quantification.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.899-904
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• 2022

As the world becomes an aging society due to a decrease in the birth rate and an increase in life expectancy, a system for health management of the elderly population is needed. Among them, various studies on occupancy and activity types are being conducted for smart home care services for indoor health management. In this paper, we propose a random forest model that classifies activity type as well as occupancy status through indoor temperature and humidity, CO2, fine dust values and UWB radar positioning for smart home care service. The experiment measures indoor environment and occupant positioning data at 2-second intervals using three sensors that measure indoor temperature and humidity, CO2, and fine dust and two UWB radars. The measured data is divided into 80% training set data and 20% test set data after correcting outliers and missing values, and the random forest model is applied to evaluate the list of important variables, accuracy, sensitivity, and specificity.