• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.81-82
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• 2020

Cement paste is the basic material constituting concrete and the most basic data of workability. This study quantitatively evaluated the measured data using a ring flow and a rotary viscometer to estimate the flow of cement paste, and also evaluated the flow and rheology over time. For this, the current work has studied admixtures that affect the fluidity of cement paste. As a result of the experiment, since fluidity and plastic viscosity are inversely proportional to each other, more experimental studies are needed to obtain high fluidity and high viscosity at the same time.

• Journal of Korea Multimedia Society
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• v.22 no.7
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• pp.749-758
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• 2019

This paper proposes a data augmentation algorithm to improve the performance of DNN(Deep Neural Network) based speech enhancement. Many deep learning models are exploring algorithms to maximize the performance in limited amount of data. The most commonly used algorithm is the data augmentation which is the technique artificially increases the amount of data. For the effective data augmentation algorithm, we used a formant enhancement method that assign the different weights to the formant frequencies. The DNN model which is trained using the proposed data augmentation algorithm was evaluated in various noise environments. The speech enhancement performance of the DNN model with the proposed data augmentation algorithm was compared with the algorithms which are the DNN model with the conventional data augmentation and without the data augmentation. As a result, the proposed data augmentation algorithm showed the higher speech enhancement performance than the other algorithms.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.1-16
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• 2023

Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure limit/control. A significant amount of research has been conducted on tools and languages for data generation. However, existing tools and languages have been developed for specific purposes and are unsuitable for other domains. In this article, we propose a regular expression-based data generation language (DGL) for flexible big data generation. To achieve a general-purpose and powerful DGL, we enhanced the standard regular expressions to support the data domain, type/format inference, sequence and random generation, probability distributions, and resource reference. To efficiently implement the proposed language, we propose caching techniques for both the intermediate and database queries. We evaluated the proposed improvement experimentally.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.255-261
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• 2014

Many studies have estimated a mixture of binomial distributions. This paper considers an extension, a mixture of shifted binomial distributions, and the estimation of the distribution. The range of each component binomial distribution is rst evaluated and then for each possible value of shifted parameters, the EM algorithm is employed to estimate those parameters. From a set of possible value of shifted parameters and corresponding estimated parameters of the distribution, the likelihood of given data is determined. The simulation results verify the performance of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.154.2-154
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• 2001

This paper presented a adaptation approach based on maximum model distance (MMD) method. This method shares the same framework as they are used for training speech recognizers with abundant training data. The MMD method could adapt to all the models with or without adaptation data. If large amount of adaptation data is available, these methods could gradually approximate the speaker-dependent ones. The approach is evaluated through the phoneme recognition task on the TIMIT corpus. On the speaker adaptation experiments, up to 65.55% phoneme error reduction is achieved. The MMD could reduce phoneme error by 16.91% even when ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.99.1-99
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• 2001

This paper presented an adaptation approach based on maximum model distance (MMD) method. This method shares the same framework as they are used for training speech recognizers with abundant training data. The MMD method could adapt to all the models with or without adaptation data. If large amount of adaptation data is available, these methods could gradually approximate the speaker-dependent ones. The approach is evaluated through the phoneme recognition task on the TIMIT corpus. On the speaker adaptation experiments, up to 65.55% phoneme error reduction is achieved. The MMD could reduce phoneme error by 16.91% even when only one adaptation utterance is used.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.37
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• pp.21-29
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• 1996

It is very important to select the best alternative for a manufacturing enterprise. However, more often than not this work is carried out unsatisfactorily. In this paper, we will present a new model for evaluating alternatives. Two main results derived from this paper are as follows: 1. A selection model of alternative is suggested that each decision maker's opinion is equally evaluated and the preference of each attribute can also be considered simultaneously. 2. A proposed method is especially effective to analyze a data structure with fuzzy and crisp data.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.439-446
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• 2014

Quantile regression models with errors in variables have received a great deal of attention in the social and natural sciences. Some eorts have been devoted to develop eective estimation methods for such quantile regression models. In this paper we propose an orthogonal distance quantile regression model that eectively considers the errors on both input and response variables. The performance of the proposed method is evaluated through simulation studies.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.155-155
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• 2000

A high performance control and monitoring system for a high speed railway train requires a reliable the real-time communication network. TCN/WTB is designed for the data transmission over the train bus, and UIC556 defines that all the data be transmitted over TCN/WTB. This paper evaluates the performance of the link layer of WTB(Wired Train Bus). The evaluated results can be used for the selection of parameters for the sporadic message data.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.188-200
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• 2002

In this study, a pavement evaluation method is introduced by a case study of the measurement data obtained in Incheon International Airport. Based on the results obtained by both visual inspection and automobile inspection equipments, the pavement surface condition is evaluated and used for maintenance and rehabilitation strategy for pavement. In addition, the special attention was given to the back calculation and solution technique of E-modulus by FWD's deflection data in Pavement.