• The Journal of Korean Academy of Sensory Integration
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• v.17 no.1
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• pp.19-29
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• 2019

Objective : The aim of this study was to verify validity of the Activity Participation Assessment for school-age children. Methods : A questionnaire consisting of 30 items from the APA, 75 items from the PACS, and 55 items from the CAPE was administered to elementary school students. A total of 207 questionnaires were analyzed. Confirmatory factor analysis was performed to confirm the construct validity of the APA. Convergence validity and discriminant validity were verified with the average variance extracted (AVE) and the square of the correlation coefficient. The discriminant validity was the Pearson correlation coefficient of the APA, PACS, and CAPE. Results : The results of the analysis were as follows: 1) For construct validity, the goodness of fit of the modified hierarchical second-order factor model was found to be appropriate (p < .001), 2) For convergent validity, the AVE was higher than .50 for all latent variables, 3) For discriminant validity, the AVE of the latent variable was greater than the square of the correlation coefficient (0.239), 4) For concurrent validity, the correlation between the total sum of the APA and PACS scores showed a positive correlation in all domains, and the correlation coefficient ranged from .303 to .647 at a statistically significant level (p < .01), 5) The correlation coefficient between the total sum of the APA and CAPE scores was .490 for recreational activities, .329 for physical activities, .571 for social activities, .401 for skill-based activities, and .390 for self-improvement activities. All domains showed a positive correlation, and were statistically significant (p < .01). Conclusion : APA can be used as a valid assessment tool to measure the participation of school aged children.

• Smart Media Journal
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• v.12 no.11
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• pp.134-144
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• 2023

Nowadays, Deep Learning (DL) technology is being used in several government departments. South Korea imports a lot of seafood. If the demand for fishery products is not accurately predicted, then there will be a shortage of fishery products and the price of the fishery product may rise sharply. So, South Korea's Ministry of Ocean and Fisheries is attempting to accurately predict seafood imports using deep learning. This paper introduces the solution for the fish import prediction in South Korea using the Long Short-Term Memory (LSTM) method. It was found that there was a huge gap between the sum of consumption and export against the sum of production especially in the case of two species that are Hairtail and Pollock. An import prediction is suggested in this research to fill the gap with some advanced Deep Learning methods. This research focuses on import prediction using Machine Learning (ML) and Deep Learning methods to predict the import amount more precisely. For the prediction, two Deep Learning methods were chosen which are Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM). Moreover, the Machine Learning method was also selected for the comparison between the DL and ML. Root Mean Square Error (RMSE) was selected for the error measurement which shows the difference between the predicted and actual values. The results obtained were compared with the average RMSE scores and in terms of percentage. It was found that the LSTM has the lowest RMSE score which showed the prediction with higher accuracy. Meanwhile, ML's RMSE score was higher which shows lower accuracy in prediction. Moreover, Google Trend Search data was used as a new feature to find its impact on prediction outcomes. It was found that it had a positive impact on results as the RMSE values were lowered, increasing the accuracy of the prediction.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.3
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• pp.280-285
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• 2015

We consider a linear transceiver design method for multi-user multiple-input multiple-output (MIMO) downlink channels where a base station (BS) equipped with a finitely large number of antennas. Although a matched-filter precoder is a capacity-achieving method in massive MIMO downlink systems, it cannot guarantee to achieve the multi-user MIMO capacity in a finitely large number of antennas due to inter-user interferences. In this paper, we propose a two-stage precoder design method that maximizes the sum-rate of cell-edge users when the BS equipped with a finitely large number of antennas. At the first stage, a matched-filter precoder is adopted to exploit both beamforming gain and the reduction of the dimension of effective channels. Then, we derive the second stage precoder that maximizes the sum-rate by minimizing the weighted mean square error (WMSE). From simulation and analysis, we verify the effectiveness of the proposed method.

• Korean journal of applied entomology
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• v.53 no.3
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• pp.311-315
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• 2014

Lantern fly(Lycorma delicatula) is a major invasive pest that causes withering symptom of agricultural crops by sucking tree sap and sooty mold symptom by producing honeydew. This study was conducted to investigate the occurrence pattern of lantern fly in grape orchards in Gyeonggi area and the effect of winter temperature on L. delicatula egg survival during 2010 to 2013. In Gyeonggi areas, overwintered L. delicatula eggs began to hatch from early May and nymphs peaked in mid May. Adults emerged from late July and laid eggs until early November. The survival of L. delicatula eggs during overwintering was largely affected by winter temperatures. The relationship between the number of days below a threshold temperature (x) in January and the survival rate of overwintering L. delicatula eggs (y) was using linear regression model. The best model selected by the lowest RSS (residual sum of square) between predicted and actual survival was y = -1.0486 x + 94.496 ($R^2=0.7067$) with $-11^{\circ}C$ of threshold temperature. These results should be helpful to conduct L. delicatula management programs, since the results provided relivable prediction for the winter survival of L. delicatula eggs and the phenology of egg hatch in the spring.

• Korean journal of applied entomology
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• v.52 no.4
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• pp.415-425
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• 2013

The yellow tea thrips, Scirtothrips dorsalis (Thysanoptera: Thripidae), has been regarded as a minor pest on citrus on Jeju Island. However, the damage of yellow tea thrips has gradually increased since 2007. This study was conducted to develop a forecasting model for generation peak time of S. dorsalis by using degree-days. Simple linear regression analysis was applied to determine the relationship between the generation number (x, dependent variable) and degree-days (y, independent variable). As a result, two regression models were established: citrus-based model (y = 310.9x + 69.0, $r^2$=0.99) and green tea-based model (y = 285.7x + 84.1, $r^2$=0.99). The models was fitted by independent data sets obtained from 2013 and evaluated using the technique of RSS (residual sum of square) and ${\chi}^2$-test. The green tea based-model showed a good fitting ability. The discrepancy between model outputs and actual data, and the practical application of models were discussed.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.25-31
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction. Although PCA has been applied in many areas successfully, it is sensitive to outliers due to the use of sum-square-error. Several variants of PCA have been proposed to resolve the noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA2, however, still can fall into a local optimum due to equal initial membership values for all data points. Another reason comes from the fact that RF-PCA2 is based on sum-square-error although fuzzy memberships are incorporated. In this paper, a variant of RF-PCA2 called RF-PCA3 is proposed. The proposed algorithm is based on the objective function of RF-PCA2. RF-PCA3 augments RF-PCA2 with the objective function of PCA and initial membership calculation using data distribution, which make RF-PCA3 to have more chance to converge on a better solution than that of RF-PCA2. RF-PCA3 outperforms RF-PCA2, which is demonstrated by experimental results.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.292-300
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• 2008

An algorithm for detecting a line segment in an image is presented using incremental pixel extension. We use a different approach from conventional algorithms, such as the Hough transform approach and the line segment grouping approach. The Canny edge is calculated and an arbitrary point is selected among the edge elements. After the arbitrary point is selected, a base line approximating the line segment is calculated and edge pixels within an arbitrary radius are selected. A weighted value is assigned to each edge pixel, which is selected by using the error of the distance and the direction between the pixel and the base line. A line segment is extracted by Jilting a line using the weighted least square method after determining whether selected pixels are linked or delinked using the sum comparison of the weights. The proposed algorithm is compared with two other methods and results show that our algorithm is faster and can detect the real line segment.

• Journal of Korean Society of Forest Science
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• v.88 no.4
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• pp.446-453
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• 1999

In this study, the effects of stand planting density on parameters of stand height and basal area growth models were investigated. We used the Korf equation as the base model in estimating the parameters of the growth models for cryptomeria plantation forest stands. Then, in order to investigate the effects of the change in plantation density on the parameter estimates, the "extra sums of square" principle, which provided a reasonable statistical procedure for a performance test, was used. The results of the test coincide with the understandings that stand height growth is not affected significantly by the planting density and the growth curves of stand basal area approaches a common asymptote regardless of the stand density for a given site. However, the shapes of the basal area growth curves were affected significantly by the planting density. Based on the results of the test, we developed a basal area growth model to account for the effects of initial planting density in cryptomeria plantation forest stands.

• Wind and Structures
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• v.26 no.2
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• pp.99-114
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• 2018

Due to shortage of land and architectural aesthetics, sometimes the buildings are constructed as unconventional in plan. The wind force acts differently according to the plan shape of the building. So, it is of utter importance to study wind force or, more specifically wind pressure on an unconventional plan shaped tall building. To address this issue, this paper demonstrates a comprehensive study on mean pressure coefficient of 'E' plan shaped tall building. This study has been carried out experimentally and numerically by wind tunnel test and computational fluid dynamics (CFD) simulation respectively. Mean wind pressures on all the faces of the building are predicted using wind tunnel test and CFD simulation varying wind incidence angles from $0^{\circ}$ to $180^{\circ}$ at an interval of $30^{\circ}$. The accuracy of the numerically predicted results are measured by comparing results predicted by CFD with experimental results and it seems to have a good agreement with wind tunnel results. Besides wind pressures, wind flow patterns are also obtained by CFD for all the wind incidence angles. These flow patterns predict the behavior of pressure variation on the different faces of the building. For better comparison of the results, pressure contours on all the faces are also predicted by both the methods. Finally, polynomial expressions as the sine and cosine function of wind angle are proposed for obtaining mean wind pressure coefficient on all the faces using Fourier series expansion. The accuracy of the fitted expansions are measured by sum square error, $R^2$ value and root mean square error.

• The Journal of Pediatrics of Korean Medicine
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• v.25 no.3
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• pp.77-84
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• 2011

Objectives: This study was performed to investigate the effect of hot spring therapy on children weight, body composition and heart rate variability. Methods: The study was carried out from 30 children who visited the spa from August 1, 2011 to August 31, 2011. We measured the change of weight, body composition, and heart rate variability after hot spring therapy for an hour per day. Results: The subject was consisted of 13 boys and 17 girls. This study revealed that their weight got lost from a hot spring therapy, which was statistically significant. Their body mass index(BMI) was decreased in from a hot spring therapy, which was not statistically significant. Total body water, muscle, protein, and mineral were decreased from a hot spring therapy, which was statistically significant. We measured HRV(heart rate variability) before and after the hot spring therapy. The mean HRT was increased, which was statistically insignificant. SDNN(standard deviation of the NN interval) and RMSSD(square root of the mean of the sum of the square of differences) were not different before and after the hot spring therapy. ln TP was decreased insignificantly. ln VLF was not affected before and after hot spring therapy. ln LF and ln HF was decreased, LF norm was increased, and HF norm was decreased, which were not statistically significant. Also, LF/HF ratio was increased insignificantly. Conclusions: From these results, we concluded that the weight, total body water, muscle, protein, and mineral got lost from the hot spring therapy. However, the HRV was not affected from the hot spring therapy.