• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6C
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• pp.367-377
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• 2008

As part of study to develop LRFD (Load and Resistance Factor Design) codes for foundation structures in Korea, resistance factors for static bearing capacity of driven steel pipe piles were calibrated in the framework of reliability theory. The 57 data sets of static load tests and soil property tests conducted in the whole domestic area were collected and these load test piles were sorted into two cases: SPT N at pile tip less than 50, SPT N at pile tip equal to or more than 50. The static bearing capacity formula and the Meyerhof method using N values were applied to calculate the expected design bearing capacities of the piles. The resistance bias factors were evaluated for the two static design methods by comparing the representative measured bearing capacities with the expected design values. Reliability analysis was performed by two types of advanced methods: the First Order Reliability Method (FORM), and the Monte Carlo Simulation (MCS) method using resistance bias factor statistics. The target reliability indices are selected as 2.0 and 2.33 for group pile case and 2.5 for single pile case, in consideration of the reliability level of the current design practice, redundancy of pile group, acceptable risk level, construction quality control, and significance of individual structure. Resistance factors of driven steel pipe piles were recommended based on the results derived from the First Order Reliability Method and the Monte Carlo Simulation method.

• Journal of the Korean GEO-environmental Society
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• v.17 no.12
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• pp.55-64
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• 2016

In this paper bearing capacity and safety margin of shallow foundation on weathered soil ground against shear failure by using current design method of allowable stress design (ASD), load resistance factor design (LRFD) based on reliability analysis and partial safety factor design (PSFD) in Eurocode were estimated and compared to each other. Results of the plate loading test used in construction and design were collected and analysis of probability statistics on soil parameters affecting the bearing capacity of shallow foundation was performed to quantify the uncertainty of them and to investigate the resistance bias factor and covalence of ultimate bearing capacity. For the typical sections of shallow foundation in domestic field as examples, reliability index was obtained by reliability analysis (FORM) and the sensitivity analysis on soil parameters of probability variables was performed to investigate the effect of probability variable on shear failure. From stability analysis for these sections by ASD, LRFD with the target reiability index corresponding to the safety factor used in ASD and PSDF, safety margins were estimated respectively and compared.

• Journal of KIISE:Information Networking
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• v.31 no.3
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• pp.335-346
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• 2004

In this paper, we present a high-performance fault-tolerant switching networks using a deflection self-routing scheme, and present fault-diagnosis method for the network. We use the facts: 1) Each stage of the Banyan network is arrayed as the sequences of a Cyclic group of SEs. 2) There is the homomorphism between adjacent stages from a view of self-routing, so that all of each Cyclic group is the subgroup of the Cyclic group in the next stage, and there are factor groups due to such subgroup and homomorphism. We provide high-performance fault-tolerant switching networks of which the all links including augmented links are used as the alternate links detouring faulty links. We also present the fault diagnosis scheme for the proposed switching network that provide multiple paths for each input-output pair.

• Journal of the Korean Data and Information Science Society
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• v.23 no.3
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• pp.495-504
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• 2012

In this study, we propose a statistical model based on projection that generates interview scores. In this model, each interviewee's true score and its related variable are viewed as X, Y values respectively in the two dimensional plane, and each interviewer's score is the projected score of true score X to the axis rotated by some angle, which reflects the interviewer's perspective. Each interviewer's observed interview score is obtained by adding personal bias and observed error to this projected score. We compared commonly used standardizing methods of interview scores such as trimmed mean method, rank method, and z-score method based on the proposed statistical model. In this simulation, two types of interview methods, two numbers of interviewers, two degrees of interviewers' expertise and two distributions and three correlations between actual score and its related variable are all considered.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.72-77
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• 2024

Recently, the necessity for sound source localization has grown significantly across various industrial sectors. Among the sound source localization methods, sound intensimetry has the advantage of having high accuracy even with a small microphone array. However, the increase in localization error at high Helmholtz numbers have been pointed out as a limitation of this method. The study proposes a method to compensate for the bias error of the measured sound intensity vector according to the Helmholtz numbers by applying deep learning. The method makes it possible to estimate the accurate direction of arrival of the source by applying a dense layer-based deep learning model that derives compensated sound intensity vectors when inputting the sound intensity vectors measured by a tetrahedral microphone array for the Helmholtz numbers. The model is verified based on simulation data for all sound source directions with 0.1 < kd < 3.0. One can find that the deep learning-based approach expands the measurement frequency range when implementing the sound intensimetry-based sound source localization method, also one can make it applicable to various microphone array sizes.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.2
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• pp.112-121
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• 2013

The calibration of resistance factor in reliability theory for limit state design of gravel compaction piles (GCP) requires a reliable estimate of ultimate bearing capacity. The static load test is commonly used in geotechnical engineering practice to predict the ultimate bearing capacity. Many graphical methods are specified in the design standard to define the ultimate bearing capacity based on the load-settlement curve. However, it has some disadvantages to ensure reliability to obtain an uniform ultimate load depend on engineering judgement. In this study, a well-fitting nonlinear regression model is proposed to estimate the ultimate bearing capacity, for which a nonlinear regression analysis is applied to estimate the ultimate bearing capacity of GCP and the results are compared with those calculated using previous graphical method. Affect the resistance factor of the estimate method were analyzed. To provide a database in the development of limit state design, the load test conditions for predicting the ultimate bearing capacity from static load test are examined.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.417-427
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• 2015

Measures in response rate used to measure the representativeness of the sample (the more high response rate) better explain the representativeness of the sample. However, we cannot often explain the representativeness of the sample because there is nonresponse even in the high response rate. Therefore, Schouten et al. (2009) presented a new R-indicator measure that can be described as a representative of the sample. We research the new estimator of the R-indicator in this paper because there are parameters that require estimations. We describe the meanings as representative of the R-indicator; consequently, the bias and efficiency of the proposed estimator for R-indicator are compared to the existing estimator under various simulations. The representativeness of the sample is also explained by applying the proposed estimators in the actual data.

• Journal of Labour Economics
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• v.33 no.2
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• pp.135-164
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• 2010

This paper compares the earnings effect of inter-industry technology differences between the self-employed and wage earners. It is assumed that primary skills utilized by the self-employed and paid workers differ in nature, and thus the earnings effect of technology differences and its skill-biasness also differ for each type of workers. For the empirical analysis. Heckman's two-stage method and quantile regressions are fitted to Korean panel data. The earnings effect of technology differences turns skill- biased for wage earners (job-specific skills), but prevails for all self-employed workers (entrepreneurial skills) regardless of their schooling level. This sectoral difference holds for each different quantile of earnings distribution.

• 한국HCI학회:학술대회논문집
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• 2007.02b
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• pp.728-736
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• 2007

P2P 파일공유는 1999년 처음 등장한 이래 저작권 침해로 디지털 콘텐츠 시장을 파괴하는 '해적'으로 간주 되어왔다. 하지만 최근 들어 P2P 시장의 산업적 가능성을 새롭게 주목하는 움직임이 나타나고 있다. 아울러 학계에서는 P2P의 경제적 영향력을 공급자 편향의 시각이 아닌 소비자 측면을 포함한 균형적 관점으로 바라보기 시작했다. 본 연구 역시 균형적 관점에서 P2P를 바라보려는 접근법의 일환으로, P2P 영화파일 공유 이용자들의 영화소비패턴을 실증적으로 살펴보고자 하였다. 실제 P2P 영화파일 공유 이용자들에 대한 설문결과, 이용자들은 단일한 영화소비성향을 가지고 있지 않았으며 다운로드와 극장 관람빈도가 모두 높은 이른바 '얼리어답터'형과 다운로드를 극장관람의 대체재로 여기는 소위 '해적'형이 공존하고 있었다. 이 중 그간 산업계에서 우려하던 해적형의 비율은 10% 정도로 낮았고, 대부분의 P2P 이용자들은 오히려 일반 극장 관람객보다 더 적극적으로 극장소비를 하는 사람들로 영화산업에 긍정적인 기여를 하는 것으로 밝혀졌다. 이러한 소비자 분석결과는 향후 본격화되고 있는 P2P 다운로드 유료화 시장에 대한 전망을 밝게 하는 것으로, 현재 유료화에 있어 가장 중시해야 할 것은 불법 무료 다운로드에 대한 경계가 아니라, 소비자 편의적인 시스템의 개발임을 시사한다.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.83-91
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• 1997

A reactor vibration monitoring has been performed using neutron noise obtained from excore detectors for the safety operation, Traditionally, the spectral estimator based on Fourier analysis has been widely used in the noise analysis of the reactor system. If the bias is too severe, the resolution would not be adequate for a given application. One major motivation for the current interests in the parametric approach to spectral estimation is the apparent higher resolution achievable with these modern techniques. In considering an unbias, a consistency, an efficency, and a minimum lower bound of the statictic estimation, an AR model is appropriate for noise spectral estimation with sharp peaks but not deep valley. In order to select an appropriate model order, the lag value of autocorrleaton function is applied. Burg method to trace the vibration mode of RPV internal is the most sucuessful.