• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5A
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• pp.737-746
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• 2008

Recently, NDTs (Non-Destructive Techniques) using electromagnetic(EM) properties are applied to the performance evaluation for RC (Reinforced Concrete) structures. Since nonmetallic materials which are cement-based system have their unique dielectric constant and conductivity, they can be characterized and changed with different mixture conditions like W/C (water to cement) ratios and unit cement weight. In a room condition, cement mortar is generally dry so that porosity plays a major role in EM properties, which is determined at early-aged stage and also be affected by curing condition. In this paper, EM properties (dielectric constant and conductivity) in cement mortar specimens with 4 different W/C ratios are measured in the wide region of 0.2 GHz~20 GHz. Each specimen has different submerged curing period from 0 to 28 days and then EM measurement is performed after 4 weeks. Furthermore, porosity at the age of 28 days is measured through MIP (Mercury Intrusion Porosimeter) and saturation is also measured through amount of water loss in room condition. In order to evaluate the porosity from the initial curing stage, numerical analysis based on the modeling for the behavior in early-aged concrete is performed and the calculated results of porosity and measured EM properties are analyzed. For the convenient comparison with influencing parameters like W/C ratios and curing period, EM properties from 5 GHz to 15 GHz are averaged as one value. For 4 weeks, the averaged dielectric constant and conductivity in cement mortar are linearly decrease with higher W/C ratios and they increase in proportion to the square root of curing period regardless of W/C ratios.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.363-374
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• 2008

Intensity-Duration-Frequency (IDF) curve that is essential to calculate rainfall quantiles for designing hydraulic structures in Korea is generally formulated by regression analysis. In this study, IDF curve derived by the cumulative distribution function ("IDF by CDF") of the proper probability distribution function (PDF) of each site is suggested, and the corresponding parameters of IDF curve are computed using genetic algorithm (GA). For this purpose, IDF by CDF and the conventional IDF derived by regression analysis ("IDF by REG") were computed for 22 Korea Meteorological Administration (KMA) rainfall recording sites. Comparisons of RMSE (root mean squared error) and RRMSE (Relative RMSE) of rainfall intensities computed from IDF by CDF and IDF by REG show that IDF by CDF is more accurate than IDF by REG. In order to accommodate the effect of the recent intensive rainfall of Korea, the rainfall intensities computed by the two IDF curves are compared with that by at-site frequency analysis using the rainfall data recorded by 2006, and the result from IDF by CDF show the better performance than that from IDF by REG. As a result, it can be said that the suggested IDF by CDF curve would be the more efficient IDF curve than that computed by regression analysis and could be applied for Korean rainfall data.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.719-726
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• 2009

In this study, a series of push-off tests for lean concrete, aggregate, asphalt subbases mainly used in Korea were performed to investigate the friction characteristics between the slab and subbase layers. Use of separation membrane and wet condition of subbase were other parameters in the tests. Horizontal displacements of the slabs and friction coefficients were measured at 1st loading, stable condition (2nd and 3rd loadings), and wet condition (4th loading) by applying 40mm/hour horizontal loadings. Larger maximum friction coefficients were measured in order of the lean concrete, asphalt, aggregate, and subbases using the separation membrane at 1st loading, and in order of the asphalt, aggregate, lean concrete, and subbases using the separation membrane at stable and wet conditions. The friction coefficients of the aggregate and asphalt subbases which did not used the separation membrane decreased by the wet condition while the subbases using the separation membrane were not affected. Additional push-off tests for effects of slab thickness and temperature sensitivity of asphalt will be performed. And, effects of the friction characteristics between the slab and subbase layers on behavior and performance of concrete pavements will be investigated by structural analyses using the test results.

• 한국노년학
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• v.39 no.2
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• pp.241-259
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• 2019

The purpose of this study was to study the performance of volunteer work for the elderly from the perspective of self-efficacy and self-extension of the elderly, not from successful aging or productive aging. Through this, the research aims to confirm the expansion of internal growth and self-sufficiency that can occur in old age, and to provide an opportunity to re-examine one's life in old age. In order to verify the purpose of this research, questionnaires were distributed to 300 senior citizens who participated in volunteer activities at the City Hall and the District Office of Busan Metropolitan City over a period of three months from September to November 2018 and used the data from 266 questionnaires for the study, excluding the 34questionnaire answered unfaithfully. The results of the study are as follows. First, the motivation for volunteering activities (value function, social function, understanding function) of the elderly has a positive effect on self-efficacy. Second, the motivation for volunteering activities (value functions, social functions, understanding functions) have a positive effect on self-extension. Third, it has been shown that the elderly's sense of self-efficacy (self-regulation efficacy, confidence) has a positive effect on their self-extension. Fourth, it was found that self-efficacy has a mediated effect on the motivation of the elderly to participate in volunteer activities and the relationship of self-extension. This study identified the relevance of the motivation for volunteering activities of the elderly to influence their effectiveness and self-extension. In particular, the research suggests practical and policy measures for the revitalization of volunteer activities of the elderly by providing a new perspective on the welfare of the elderly by utilizing parameters of self-efficacy, a psychological and social concept for the elderly.

• Tunnel and Underground Space
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• v.33 no.5
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• pp.348-372
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• 2023

In relation to the high-level radioactive waste disposal project in deep fractured rock aquifer environments, it is essential to evaluate hydrogeological characteristics for evaluating the suitability of the site and operational stability. Such subsurface hydrogeological data is obtained through in-situ tests using boreholes excavated at the target site. The accuracy and reliability of the investigation results are directly related to the selection of appropriate test methods, the performance of the investigation system, standardization of the investigation procedure. In this report, we introduce the detailed procedures for the representative test method, the constant pressure injection test (CPIT), which is used to determine the key hydrogeological parameters of the subsurface fractured rock aquifer, namely hydraulic conductivity and storativity. This report further refines the standard test method suggested by the KSRM in 2022 and includes practical field application case conducted in volcanic rock aquifers where this investigation procedure has been applied.

• Advanced Industrial SCIence
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• v.3 no.2
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• pp.8-16
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• 2024

This paper shows the system of drug classification, the goal of this is to foretell the apt drug for the patients based on their demographic and physiological traits. The dataset consists of various attributes like Age, Sex, BP (Blood Pressure), Cholesterol Level, and Na_to_K (Sodium to Potassium ratio), with the objective to determine the kind of drug being given. The models used in this paper are K-Nearest Neighbors (KNN), Logistic Regression and Random Forest. Further to fine-tune hyper parameters using 5-fold cross-validation, GridSearchCV was used and each model was trained and tested on the dataset. To assess the performance of each model both with and without hyper parameter tuning evaluation metrics like accuracy, confusion matrices, and classification reports were used and the accuracy of the models without GridSearchCV was 0.7, 0.875, 0.975 and with GridSearchCV was 0.75, 1.0, 0.975. According to GridSearchCV Logistic Regression is the most suitable model for drug classification among the three-model used followed by the K-Nearest Neighbors. Also, Na_to_K is an essential feature in predicting the outcome.

• The Journal of the Acoustical Society of Korea
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• v.28 no.2
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• pp.155-163
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• 2009

In text-to-speech systems, the conversion of text into prosodic parameters is necessarily composed of three steps. These are the placement of prosodic boundaries. the determination of segmental durations, and the specification of fundamental frequency contours. Prosodic boundaries. as the most important and basic parameter. affect the estimation of durations and fundamental frequency. Break prediction is an important step in text-to-speech systems as break indices (BIs) have a great influence on how to correctly represent prosodic phrase boundaries, However. an accurate prediction is difficult since BIs are often chosen according to the meaning of a sentence or the reading style of the speaker. In Japanese, the prediction of an accentual phrase boundary (APB) and major phrase boundary (MPB) is particularly difficult. Thus, this paper presents a method to complement the prediction errors of an APB and MPB. First, we define a subtle BI in which it is difficult to decide between an APB and MPB clearly as a variable break (VB), and an explicit BI as a fixed break (FB). The VB is chosen using the classification and regression tree, and multiple prosodic targets in relation to the pith and duration are then generated. Finally. unit-selection is conducted using multiple prosodic targets. In the MOS test result. the original speech scored a 4,99. while proposed method scored a 4.25 and conventional method scored a 4.01. The experimental results show that the proposed method improves the naturalness of synthesized speech.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.392-400
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• 2009

In this paper, we propose an effective speech reinforcement technique base on ITU-T G.729A CS-ACELP codec under the near-end background noise environments. In general, since the intelligibility of the far-end speech for the near-end listener is significantly reduced under near-end noise environments, we require a far-end speech reinforcement approach to avoid this phenomena. In contrast to the conventional speech reinforcement algorithm, we reinforce the excitation signal of the codec's parameters received from the far-end speech signal based on the G.729A speech codec under various background noise environments. Specifically, we first estimate the excitation signal of ambient noise at the near-end through the encoder of the G.729A speech codec, reinforcing the excitation signal of the far-end speech transmitted from the far-end. we specially propose a novel approach to directly reinforce the excitation signal of far-end speech signal based on the decoder of the G.729A. The performance of the proposed algorithm is evaluated by the CCR (Comparison Category Rating) test of the method for subjective determination of transmission quality in ITU-T P.800 under various noise environments and shows better performances compared with conventional SNR Recovery methods.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.201-214
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• 2023

This study attempted to analyze the impact of individual entrepreneurial capabilities on entrepreneurial intention targeting small and medium-sized business employees, and sought to confirm the mediating effect of entrepreneurial efficacy and entrepreneurial mentoring between entrepreneurial capabilities and entrepreneurial intention. The sub-variables of entrepreneurship competency were analyzed separately into creativity, problem solving, communication, and marketing. 368 questionnaires collected from employees at small and medium-sized manufacturing companies located across the country were used for empirical analysis. A parallel dual mediation model with no causal relationship between parameters was used for empirical analysis using SPSS v26.0 and PROCESS macro v4.2. As a result of the analysis, first, among the start-up competencies, creativity, communication, and marketing were confirmed to have a significant positive (+) effect on start-up efficacy. Second, among the start-up competencies, creativity, communication, and marketing were tested to have a significant positive influence on start-up mentoring. Third, both startup efficacy and startup mentoring were found to have a significant positive influence on startup intention. Fourth, among start-up capabilities, creativity and marketing were confirmed to have a significant positive (+) effect on start-up intention. Fifth, startup efficacy and startup mentoring were found to have a mediating effect on startup intention except for problem solving among startup competencies. As a result, it was confirmed that in order to strengthen the intention to start a business among small and medium-sized business employees, start-up efficacy and start-up mentoring are important factors, and that marketing and creativity have an important influence among individual start-up capabilities, so education and prior preparation for these are necessary. As follow-up research, it will be necessary to apply multivariate models, analyze time series data, research considering external environmental factors, and test the difference between start-up capabilities and performance considering detailed population characteristics.