• Smart Media Journal
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• v.11 no.3
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• pp.9-17
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• 2022

Algorithmic trading, which uses algorithms to trade financial products, has a problem in that the results are not stable due to many factors in the market. To alleviate this problem, ensemble techniques that combine trading algorithms have been proposed. However, there are several problems with this ensemble method. First, the trading algorithm may not be selected so as to satisfy the minimum performance requirement (more than random) of the algorithm included in the ensemble, which is a necessary requirement of the ensemble. Second, there is no guarantee that an ensemble model that performed well in the past will perform well in the future. In order to solve these problems, a method for selecting trading algorithms included in the ensemble model is proposed as follows. Based on past data, we measure the contribution of the trading algorithms included in the ensemble models with high performance. However, for contributions based only on this historical data, since there are not enough past data and the uncertainty of the past data is not reflected, the contribution distribution is approximated using the Dirichlet distribution, and the contribution values are sampled from the contribution distribution to reflect the uncertainty. Based on the contribution distribution of the trading algorithm obtained from the past data, the Transformer is trained to predict the future contribution. Trading algorithms with high predicted future contribution are selected and included in the ensemble model. Through experiments, it was proved that the proposed ensemble method showed superior performance compared to the existing ensemble methods.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.189-212
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• 2021

The purpose of this study is to analyze an usage behavior for the public library website through web traffic. For this purpose, using Google Analytics and growth hacking technique, the data of A public library website log was analyzed for three months from August 1, 2021 to October 31, 2021. As a result of the study, the young age group of 18-24 years old and 25-34 years old recorded a high rate of new member registration, & it was found that the inflow rate through SNS was high for external inflows. As a result of analysis for the access rate by time, it was found that the time with the highest inflow rate was between 10 am and 11 am both on Wednesday and Friday. As a access channel, the access rate using mobile (64.90%) was quite high, but at the same time, the bounce rate (27.20%) was higher than the average (24.93%), & the rate of duration time (4 minutes 33 seconds) was lower than thee average (5 minutes 22 seconds). Finally, it was found that the utilization rate of reading program events and online book curation service, which the library focuses on producing and promoting, is very low. These research results can be used as basic data for future improvement of public library websites.

• Journal of the Korean Geotechnical Society
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• v.38 no.10
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• pp.49-60
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• 2022

Underground urbanization appears to be a promising solution in response to the shortage of construction sites in the above-ground space. In this context, an accurate evaluation of a construction site ensures the long-term performance of geosystems. This study characterizes potential sites for complex plants built in underground space using geophysical methods (i.e., seismic refraction exploration and electrical resistivity survey) and in situ tests (i.e., standard penetration tests (SPTs) and downhole tests). SPTs are conducted in nine boreholes BH-1-BH-9 to estimate the groundwater level and vertical distribution of geological structures. The seismic refraction method enables us to obtain the elastic wave velocity and thickness of each soil layer for each cross-sectional area. An electrical resistivity survey conducted using the dipole array method provides the electrical resistivity profiles of the cross-sectional area. Data obtained using geophysical techniques are used to assess the classification of the soil layer and bedrock, particularly the fracture zone. This study suggests that geotechnical information using in situ tests and geophysical methods are useful references to design an underground complex plant construction.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.360-366
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• 2022

This paper presents a AI model structure for restoring Korean traditional palace photographs, which remain only black-and-white photographs, to color photographs using Pix2Pix, one of the adversarial generative neural network techniques. Pix2Pix consists of a combination of a synthetic image generator model and a discriminator model that determines whether a synthetic image is real or fake. This paper deals with an artificial intelligence model by adjusting a receptive field of the discriminator, and analyzes the results by considering the characteristics of the ancient palace photograph. The receptive field of Pix2Pix, which is used to restore black-and-white photographs, was commonly used in a fixed size, but a fixed size of receptive field is not suitable for a photograph which consisting with various change in an image. This paper observed the result of changing the size of the existing fixed a receptive field to identify the proper size of the discriminator that could reflect the characteristics of ancient palaces. In this experiment, the receptive field of the discriminator was adjusted based on the prepared ancient palace photos. This paper measure a loss of the model according to the change in a receptive field of the discriminator and check the results of restored photos using a well trained AI model from experiments.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.492-499
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• 2022

This study experimentally investigates the effect of dimensionality reduction of vibration signal on fault diagnosis of a marine engine. By using the principal component analysis, a vibration signal having the dimension of 513 is converted into a low-dimensional signal having the dimension of 1 to 15, and the variation in fault diagnosis accuracy according to the dimensionality change is observed. The vibration signal measured from a full-scale marine generator diesel engine is used, and the contribution of the dimension-reduced signal is quantitatively evaluated using two kinds of variable importance analysis algorithms which are the integrated gradients and the feature permutation methods. As a result of experimental data analysis, the accuracy of the fault diagnosis is shown to improve as the number of dimensions used increases, and when the dimension approaches 10, near-perfect fault classification accuracy is achieved. This shows that the dimension of the vibration signal can be considerably reduced without degrading fault diagnosis accuracy. In the variable importance analysis, the dimension-reduced principal components show higher contribution than the conventional statistical features, which supports the effectiveness of the dimension-reduced signals on fault diagnosis.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.223-235
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• 2020

The purpose of this study is to verify the effect of golf exercise through rehabilitation training for middle-aged women and to suggest the right golf activities. To achieve the purpose of this study, the subjects were 40-50 year old middle-aged women in Jinju, Gyeongnam Province in February 2020. The subjects of this study were 8 women who were controlled by the subjects who needed to be corrected in golf swing orbit. For the accurate measurement test, the program was conducted for 10 days after explaining the purpose and utilization plan of the study. The data collected by testing level of physical strength and distance before and after the experiment were finally analyzed and used. The statistical processing of the collected data was conducted using SPSS win18.0 program, and the statistical techniques were calculated by means of frequency analysis, average(M) and standard deviation(sd), and t-test, one-way ANOVA and multiple regression analysis were conducted. The results of this study through these methods and procedures are as follows. First, rehabilitation training of general characteristics showed a high difference in golf exercise. Second, there was a high difference in the level of rehabilitation training and physical fitness in swing orbit and distance. Third, rehabilitation training and physical fitness level had a high effect on swing orbit and distance.

• Journal of Conservation Science
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• v.38 no.2
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• pp.154-165
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• 2022

The color appearance of cultural heritage are essential factors for manufacturing technique interpretation, conservation treatment usage, and condition monitoring. Therefore, this study systematically established color reproduction procedures based on the digital color management system for the portrait of Gwon Eungsu. Moreover, various application strategies for recording and conserving the cultural heritage were proposed. Overall color reproduction processes were conducted in the following order: photography condition setting, standard color measurements, digital photography, color correction, and color space creation. Therefore, compared with the color appearance, the digital image applied to a camera maker profile indicated an average color difference of 𝜟10.1. However, the digital reproduction result based on the color management system exhibits an average color difference of 𝜟1.1, which is close to the color appearance. This means that although digital photography conditions are optimized, recording the color appearance is difficult when relying on the correction algorithm developed by the camera maker. Therefore, the digital color reproduction of cultural heritage is required through color correction and color space creation based on the raw digital image, which is a crucial process for documenting the color appearance. Additionally, the recording of color appearance through digital color reproduction is important for condition evaluation, conservation treatment, and restoration of cultural heritage. Furthermore, standard data of imaging analysis are available for discoloration monitoring.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.49-57
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• 2022

The government is making great efforts to prevent crimes such as missing children by using public CCTVs. However, there is a shortage of operating manpower, weakening of concentration due to long-term concentration, and difficulty in tracking. In addition, applying real-time object search, re-identification, and tracking through a deep learning algorithm showed a phenomenon of increased parameters and insufficient memory for speed reduction due to complex network analysis. In this paper, we designed the network to improve speed and save memory through the application of Yolo v4, which can recognize real-time objects, and the application of Batch and TensorRT technology. In this thesis, based on the research on these advanced algorithms, OSNet re-ranking and K-reciprocal nearest neighbor for re-identification, Jaccard distance dissimilarity measurement algorithm for correlation, etc. are developed and used in the solution of CCTV national safety identification and tracking system. As a result, we propose a solution that can track objects by recognizing and re-identification objects in real-time within situation of a Korean public multi-CCTV environment through a set of algorithm combinations.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.19-31
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• 2022

In Machine learning, we usually divide the entire data into training data and test data, train the model using training data, and use test data to determine the accuracy and generalization performance of the model. In the case of models with low generalization performance, the prediction accuracy of newly data is significantly reduced, and the model is said to be overfit. This study is about a method of generating training data based on central limit theorem and combining it with existed training data to increase normality and using this data to train models and increase generalization performance. To this, data were generated using sample mean and standard deviation for each feature of the data by utilizing the characteristic of central limit theorem, and new training data was constructed by combining them with existed training data. To determine the degree of increase in normality, the Kolmogorov-Smirnov normality test was conducted, and it was confirmed that the new training data showed increased normality compared to the existed data. Generalization performance was measured through differences in prediction accuracy for training data and test data. As a result of measuring the degree of increase in generalization performance by applying this to K-Nearest Neighbors (KNN), Logistic Regression, and Linear Discriminant Analysis (LDA), it was confirmed that generalization performance was improved for KNN, a non-parametric technique, and LDA, which assumes normality between model building.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.227-233
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• 2022

The 3D-printing technique is used for manufacturing objects by adding multiple layers, and it is relatively easy to manufacture objects with complex shapes. The 3D concrete printing technique, which incorporates 3D printing into the construction industry, does not use a formwork when placing concrete, and it requires less workload and labor, so economical construction is possible. However, 3D-printed concrete is expected to have a lower strength than that of molded concrete. In this study, the properties of 3D-printed concrete were analyzed. To fabricate the 3D-printed concrete samples, the extrusion path and shape of the samples were designed with Ultimaker Cura. Based on this, G-codes were generated to control the 3D printer. The optimal concrete mixing proportion was selected considering such factors as extrudability and buildability. Molded samples with the same dimensions were also fabricated for comparative analysis. The properties of each sample were measured through a three-point bending test and uniaxial compression test, and a comparative analysis was performed.