• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.51 no.4
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• pp.504-511
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• 2015

In this paper, the results of evaluating the passenger comfort due to the standard deviation of acceleration in vertical and lateral direction regarding the ship response in irregular wave by ordinary strip method in regular wave and energy spectrum using linear superposition theory in order to evaluate the motion of experimental ship are as follows. According to the results of ship response, it was possible to find that, in order to reduce the motion of ship, a ship operating in bow sea was more stable than in quartering sea. In the results of analyzing the standard deviation of acceleration in vertical direction according to each component wave pattern, when there was a wave length of 56m and an average wave period of 6 sec, most of cases showed the peak value. And among them, the standard deviation was 0.35 which was the highest in head sea. And in case of lateral direction, the maximum value was shown in a wave length of 100m and an average wave period of 8 sec. And it was 0.16 in beam sea and ${\chi}=150^{\circ}$. In the evaluation of passenger comfort due to standard acceleration in vertical and lateral direction, it was 80% in head and bow sea. On the other hand, it was shown to be 15% in follow sea. Accordingly, when the expected wave height in a sea area where a training ship was intended to operate was known, it was possible to predict the routing of ship. And altering her course could reduce the passenger comfort by approximately 50%.

• Korean Journal of Acupuncture
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• v.36 no.1
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• pp.44-51
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• 2019

Objectives : Teaching the standardized acupuncture point locations and improving the accuracy of acupoint locations through objective evaluation is a very important part of Korean medicine education. The aim of this study is to develop a dummy system for evaluation and support of teaching acupoint location in meridian and acupoints classes and to introduce the developed system. Methods : We established a protocol for the development of the system. The protocol included definition of usage purpose, definition of its essential performance, and set of scope. The system compares the amount of light at the target acupoint with the amount of light at the other sites to determine whether the target acupoint is properly specificated. Results : A prototype of the system was built according to the protocol and consists of light emitter, dummy, control/operation, input part and output part. The light emitter projects laser beam passing through the skin of the dummy. Light sensors were attached inside the acupoints of the dummy. Three types of light sensors were selected depending on the location of the acupoints. The arithmetic, input, and output parts were constructed using Arduino and Raspberry pi boards. The developed system was applied in class. Conclusions : It is thought that the dummy system for evaluation and support of teaching acupoint location can be used as a training model in order to help teach standardized acupoint locations and objective evaluation.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.2
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• pp.105-120
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• 2019

The species composition and abundance variations of fishery resources in the adjacent marine ranching area, Tongyeong, Korea, were investigated by shrimp trawl, gill net, and longline during the period of July, September, and October in 2016. During the study period, the total catch were 8,522.9 kg with 34 species from the shrimp trawl, 32 species from the gill net, and nine species from the longline. The dominant species were different by gear, which were Hypodytes rubripinnis and Parapercis sexfasciata in the shrimp trawl, Platycephalus indicus and Raja kenojei in the gill net, and Conger myriaster and Scomber Japonicus in the longline. In terms of spatial distribution, Yongchodo showed the highest total catch in number as well as of in weight while Jukdo showed the lowest total catch in number and Bijindo showed the lowest total catch in weight. The amount of demersal fish resources in the survey area estimated as 301 ha, was 99,396 individuals which was converted to be 8,552.9 kg. The amount of demersal fish resources by gear were of trawling area, which area is 127 ha, were 76,251 and 3,489.5 kg, 74 ha in the gill net and longline survey area was 16,213 and 3,457.3 kg, and the other 100 ha area was 6,932 and 1,606.1 kg. In this study, the minimum resources for demersal fish is 61,687 and 4,265.2 kg, and the maximum is 149,439 and 14,197.9 kg.

• The Journal of Advanced Prosthodontics
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• v.14 no.5
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• pp.285-293
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• 2022

PURPOSE. This study evaluated the relationship among translucency, crystalline phase, grain size, and fracture toughness of zirconia. MATERIALS AND METHODS. Four commercial zirconia - Prettau^®Anterior^® (PA), Prettau^® (P), InCorisZI (ZI), and InCorisTZI (TZI)- were selected for this study. The bar specimens were prepared to determine fracture toughness by using chevron notched beam method with four-point bending test. The grain size was evaluated by a mean linear intercept method using a scanning electron microscope. X-ray diffraction and Rietveld refinement were performed to evaluate the amount of tetragonal and cubic phases of zirconia. Contrast ratio (CR) was measured to investigate the level of translucency. RESULTS. PA had the lowest fracture toughness among other groups (P < .05). In addition, the mean fracture toughness of P was significantly less than that of ZI, but there was no difference compared with TZI. Regarding grain size measurement, PA had the largest average grain size among the groups. P obtained larger grain size than ZI and TZI (P < .05). However, there was no significant difference between ZI and TZI. Moreover, PA had the lowest CR value compared with the other groups (P < .05). This means PA was the most translucent material in this study. Rietveld refinement found that PA presented the greatest percentage of cubic phase, followed by TZI, ZI, and P, respectively. CONCLUSION. The different approaches are used by manufacturers to fabricate various types of translucent zirconia with different levels of translucency and mechanical properties, which should be concerned for material selection for successful clinical outcome.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.641-648
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• 2022

This paper is a study to find out the factors affecting the defects that occur during the use of Electron Beam Melting (EBM), one of the 3D printer output methods, through data analysis. By referring to factors identified as major causes of defects in previous studies, log files occurring between processes were analyzed and related variables were extracted. In addition, focusing on the fact that the data is time series data, the concept of a window was introduced to compose variables including data from all three layers. The dependent variable is a binary classification problem with the presence or absence of defects, and due to the problem that the proportion of defect layers is low (about 4%), balanced training data were created through the SMOTE technique. For the analysis, I use XGBoost using Gridsearch CV, and evaluate the classification performance based on the confusion matrix. I conclude results of the stuy by analyzing the importance of variables through SHAP values.

• Computers and Concrete
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• v.28 no.6
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• pp.533-547
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• 2021

Calculating the shear capacity of slender reinforced concrete beams without shear reinforcement was the subject of numerous studies, where the eternal problem of developing a single relationship that will be able to predict the expected shear capacity is still present. Using experimental results to extrapolate formulae was so far the main approach for solving this problem, whereas in the last two decades different research studies attempted to use artificial intelligence algorithms and available data sets of experimentally tested beams to develop new models that would demonstrate improved prediction capabilities. Given the limited number of available experimental databases, these studies were numerically restrained, unable to holistically address this problem. In this manuscript, a new approach is proposed where a numerically generated database is used to train machine-learning algorithms and develop an improved model for predicting the shear capacity of slender concrete beams reinforced only with longitudinal rebars. Finally, the proposed predictive model was validated through the use of an available ACI database that was developed by using experimental results on physical reinforced concrete beam specimens without shear and compressive reinforcement. For the first time, a numerically generated database was used to train a model for computing the shear capacity of slender concrete beams without stirrups and was found to have improved predictive abilities compared to the corresponding ACI equations. According to the analysis performed in this research work, it is deemed necessary to further enrich the current numerically generated database with additional data to further improve the dataset used for training and extrapolation. Finally, future research work foresees the study of beams with stirrups and deep beams for the development of improved predictive models.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.715-727
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• 2024

During fast neutron imaging, besides the dark current noise and readout noise of the CCD camera, the main noise in fast neutron imaging comes from high-energy gamma rays generated by neutron nuclear reactions in and around the experimental setup. These high-energy gamma rays result in the presence of high-density gamma white spots (GWS) in the fast neutron image. Due to the microscopic quantum characteristics of the neutron beam itself and environmental scattering effects, fast neutron images typically exhibit a mixture of Gaussian noise. Existing denoising methods in neutron images are difficult to handle when dealing with a mixture of GWS and Gaussian noise. Herein we put forward a deep learning approach based on the Swin Transformer UNet (SUNet) model to remove high-density GWS-Gaussian mixture noise from fast neutron images. The improved denoising model utilizes a customized loss function for training, which combines perceptual loss and mean squared error loss to avoid grid-like artifacts caused by using a single perceptual loss. To address the high cost of acquiring real fast neutron images, this study introduces Monte Carlo method to simulate noise data with GWS characteristics by computing the interaction between gamma rays and sensors based on the principle of GWS generation. Ultimately, the experimental scenarios involving simulated neutron noise images and real fast neutron images demonstrate that the proposed method not only improves the quality and signal-to-noise ratio of fast neutron images but also preserves the details of the original images during denoising.

• Journal of the Korean earth science society
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• v.27 no.4
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• pp.390-400
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• 2006

The purpose of this study is to propose an improvement plan based on an analysis of the current earth science teacher education curriculum in the department of education in the four fields of teaching profession theory: student-teacher practice, subject lesson education, and subject content education. The following are the conclusions and suggestions of this study. In case of teaching profession theory, too much emphasis is put on pedagogical theory over practical issues, and a problem arises upon completion. Therefore, it is sugguest that teaching profession theory might be completed before subject lesson education to ensure more authentic subjects performing teaching profession. The current term for student-teacher training is too short to understand the whole school system. Current school system does not have any off-job training course or internship system. Therefore, student-teacher training term should be increased by at least $3{\sim}6$ months to play a vital role in the current system. The credit number of subject lesson education is too small compared with subject content education. Consequently, the credit number of subject lesson education should be increased, and more professor majored in subject lesson education should be recruited. Significant deviation between the content of subject content education and that of middle school grade exists, and there is also much difference in the ratio of subject according to university. To get rid of these problems, subject content education should be connected with subject lesson education and appropriate number of credit needs to be assigned to each subject domain.

• Journal of Practical Agriculture & Fisheries Research
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• v.16 no.1
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• pp.193-206
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• 2014

The objectives of the project are to increase farmers' income through GAP and to reduce the loss of agricultural produce, for which the Korean partner takes a role of transferring needed technologies to the project site. To accomplish the project plan, it is set to implement the project with six components: construction of buildings, installation of agricultural facilities, establishment of demonstration farms, dispatching experts, conducting training program in Korea and provision of equipments. The Project Management Committee and the Project Implementation Team are consisted of Korean experts and senior officials from Department of Agriculture, Myanmar that managed the project systematically to ensure the success of the project. The process of the project are; the ceremony of laying the foundation and commencing the construction of training center in April, 2012. The Ribbon Cutting Ceremony for the completion of GAP Training Center was successfully held under PMC (MOAI, GAPI/ARDC) arrangement in SAl, Naypyitaw on June 17, 2012. The Chairman of GAPI, Dr. Sang Mu Lee, Director General U Kyaw Win of DOA, officials and staff members from Korea and Myanmar, teachers and students from SAl attended the ceremony. The team carried out an inspection and fixing donors' plates on donated project machineries, agro-equipments, vehicles, computers and printer, furniture, tools and so forth. Demonstration farm for paddy rice, fruits and vegetables was laid out in April, 2012. Twenty nine Korean rice varieties and many Korean vegetable varieties were introduced into GAP Project farm to check the suitability of the varieties under Myanmar growing conditions. Paddy was cultivated three times in DAR and twice in SAl. In June 2012, vinyl houses were started to be constructed for raising seedlings and finished in December 2012. Fruit orchard for mango, longan and dragon fruit was established in June, 2012. Vegetables were grown until successful harvest and the harvested produce was used for panel testing and distribution in January 2013. Machineries for postharvest handling systems were imported in November 2012. Setting the washing line for vegetables were finished and the system as run for testing in June 2013. New water tanks, pine lines, pump house and electricity were set up in October 2013.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.30-39
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• 2003

In this paper, we carried out the performance evaluation of HM-Net(Hidden Markov Network) speech recognition system for Korean speech databases. We adopted to construct acoustic models using the HM-Nets modified by HMMs(Hidden Markov Models), which are widely used as the statistical modeling methods. HM-Nets are carried out the state splitting for contextual and temporal domain by PDT-SSS(Phonetic Decision Tree-based Successive State Splitting) algorithm, which is modified the original SSS algorithm. Especially it adopted the phonetic decision tree to effectively express the context information not appear in training speech data on contextual domain state splitting. In case of temporal domain state splitting, to effectively represent information of each phoneme maintenance in the state splitting is carried out, and then the optimal model network of triphone types are constructed by in the parameter. Speech recognition was performed using the one-pass Viterbi beam search algorithm with phone-pair/word-pair grammar for phoneme/word recognition, respectively and using the multi-pass search algorithm with n-gram language models for sentence recognition. The tree-structured lexicon was used in order to decrease the number of nodes by sharing the same prefixes among words. In this paper, the performance evaluation of HM-Net speech recognition system is carried out for various recognition conditions. Through the experiments, we verified that it has very superior recognition performance compared with the previous introduced recognition system.