• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.400-404
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• 2016

This paper presents experimental results for the vibration characteristics of the small unmanned underwater vehicle (UUV) OPKO 300, which was designed and manufactured by Daewoo ship and Marine Engineering Ltd. The autonomy of UUVs has led to an increase in their use in scientific, military, and commercial areas because their autonomy makes it possible for UUVs to be utilized instead of humans in hazardous missions such as mine countermeasure missions (MCM). Since it is impossible to use devices based on electromagnetic waves to gather information in an underwater environment, only sonar systems, which use sound waves, can be used in underwater environments, and their performance can strongly affect the autonomy of a UUV. Since a thruster system, which combines a motor and propeller in a single structure, is widely used as the propulsion system of a UUV and is mounted on the outside of a UUV’s stern, it can generate vibration, which can be transferred throughout the shell of the UUV from its stern to its bow. The transferred vibration can affect the performance of various sonar systems such as side-scan sonar or forward-looking sonar. Therefore, it is necessary to estimate the effect of the transferred vibration of the UUV on the sonar systems. Even if various numerical methods were used to analyze the vibration problem of a UUV, it would be hard to predict the vibration phenomena of a UUV at the initial design stage. In this work, an experimental study using OKPO 300 and an impact hammer was carried out to analyze the vibration feature of a small real UUV in the air. The frequency response function of the vibration based on the experimental results is presented.

• Journal of Yeungnam Medical Science
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• v.12 no.2
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• pp.393-399
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• 1995

Mandibular retrusion showing the facial problem with a marked maxillarry incisors protrusion and chin deficiency, resulting in a highly convex profile is uncommon in Korea.. The large incisor overjet and deep-bite create functional limitations and unpleasing esthetic result. The majority of theses cases are susceptible to correction by orthodontic therapeutic methods. But severe Class II retrognathic cases in which orthodontic treatment alone has not been capable of achieving good results. Orthognathic surgery offers several approaches. In this case, mandibular advancement by bilateral sagittal split ramus osteotomy and augmentation genioplasty has a special surgical problems. The suprahyoid muscle gorup are lengthened if the body of the mandible is surgically repositioned anteriorly. Instability of results and relapse return to original position shoud predicted during post-surgical muscular readjustment.. To maintain maximum correction with this technique, it is suggested that the mandibular body be well rotated forward at time of surgical intervention and overcorrected anteriory as much as possible. So, the authors report the case with review of concerned literature.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.419-428
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• 2019

This study aims to verify the self-determination motivation and ego resilience on the grit of the preparing students for the secondary school physical education teacher certification examination to provide basic data to improve the level of grit required for them to pass the certification examination and be appointed as physical education teachers. Thus, in order to achieve the objectives of this study, 403 students were verified through one-way ANOVA and correlation analysis and stepwise multiple regression analysis, which resulted in the following conclusions: The higher the level of intrinsic motivation and ego resilience, the higher the level of the grit sub-factors. Self-determination motivation and ego resilience that affect grit the most are found to be intrinsic motivation. Next came positive thinking, emotion regulation, problem solving and identified motivation factors. The results of this study suggest the importance of dealing with self-determination motivation and ego resilience affecting grit, and put forward the limitations of the study and future directions of research.

• Journal of Biomedical Engineering Research
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• v.42 no.6
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• pp.268-276
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• 2021

Functional near-infrared spectroscopy-based brain-computer interface (fNIRS-based BCI) has been receiving much attention. However, we are practically constrained to obtain a lot of fNIRS data by inherent hemodynamic delay. For this reason, when employing machine learning techniques, a problem due to the high-dimensional feature vector may be encountered, such as deteriorated classification accuracy. In this study, we employ an elastic net-based feature selection which is one of the embedded methods and demonstrate the utility of which by analyzing the results. Using the fNIRS dataset obtained from 18 participants for classifying brain activation induced by mental arithmetic and idle state, we calculated classification accuracies after performing feature selection while changing the parameter α (weight of lasso vs. ridge regularization). Grand averages of classification accuracy are 80.0 ± 9.4%, 79.3 ± 9.6%, 79.0 ± 9.2%, 79.7 ± 10.1%, 77.6 ± 10.3%, 79.2 ± 8.9%, and 80.0 ± 7.8% for the various values of α = 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, and 0.5, respectively, and are not statistically different from the grand average of classification accuracy estimated with all features (80.1 ± 9.5%). As a result, no difference in classification accuracy is revealed for all considered parameter α values. Especially for α = 0.5, we are able to achieve the statistically same level of classification accuracy with even 16.4% features of the total features. Since elastic net-based feature selection can be easily applied to other cases without complicated initialization and parameter fine-tuning, we can be looking forward to seeing that the elastic-based feature selection can be actively applied to fNIRS data.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Journal of dental hygiene science
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• v.22 no.2
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• pp.126-129
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• 2022

Background: The problem with current dental hygienist education is that it operates as an education system based on the national examination rather than on a practical basis; thus, graduates have difficulties in practice after obtaining their license. This study aimed to propose a job-oriented curriculum by analyzing the links between the task analysis of Korean dental hygienists and dental hygiene learning goals. Methods: This study performed a relationship analysis based on a second job analysis study of dental hygienists conducted by the Korea Health Personnel Licensing Examination Institute and the learning goals of the Korean Dental Hygiene Faculty Association. Results: Based on the links between the task and learning goals of the dental hygienist, they were classified into six types: 1) tasks listed in the license exam and learning goal, 2) tasks not listed in the license exam but listed in learning goals, 3) tasks not listed in learning goals, 4) learning goals not related to tasks, 5) learning goals listed in a few tasks, and 6) tasks related to several learning goals. The results showed that most of them correspond to the 5th classification, followed by the 3rd and 4th categories, which are mostly basic science learning goals. Tasks without learning goals are not included in the curriculum; thus, the curriculum needs to be supplemented. The overlapping learning goals of several subjects for one job skill must be reduced in job-oriented education. Conclusion: We suggest that the dental hygiene curriculum be developed based on task analysis and reflected in the national dental hygienist exam. The clinical practice performance of dental hygienists will take further leap forward through task-oriented education.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.312-318
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• 2022

Currently, the Republic of Korea is facing the problem of a decrease in military service resources due to the demographic cliff, and is pursuing military restructuring and changes in the military force structure in order to respond to this. In this situation, the Army is pushing forward the deployment of a drone-bot combat system that will lead the future battlefield. The battlefield of the future will be changed into an integrated battlefield concept that combines command and control, surveillance and reconnaissance, and precision strike. According to these changes, unmanned combat system, including dronebots, will be widely applied to combat situations that are high risk and difficult for humans to perform in actual combat. In this paper, as one of the countermeasures to these changes, autonomous behavior software with a BDI architecture-based decision-making system was developed. The autonomous behavior software applied a framework structure to improve applicability to multiple models. Its function was verified in a PC-based environment by assuming that the target UAV is a battalion-level surveillance and reconnaissance UAV.

• Journal of Korea Trade
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• v.24 no.4
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• pp.34-48
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• 2020

Purpose - The rapid rise of e-commerce enterprises has led to the development of the logistics industry. At the same time, some enterprises are motivated by the interests to start reducing costs and inputs, which on the contrary leads to low quality of service, thus reducing customer satisfaction. In recent years, vicious competition, violent express delivery and lack of professionalism in the logistics market have led to high annual customer complaint rate, which has resulted in the company losing many loyal customers, but also unable to obtain new customers. Therefore, to pay attention to and understand the psychological needs of customers and improve the quality of logistics distribution service has become a pressing problem for Every express company. Design/methodology - By analyzing the problems existing in logistics distribution of express companies, this paper explores various factors affecting customer satisfaction and takes consumer sentiment as a mediating variable. Through questionnaires to collect relevant data, put forward hypotheses for empirical analysis, use two different software including SPSS 21.0 and AMOS 21.0 to analyze the information, draw conclusions and make recommendations. Findings - According to the above research results, the reliability, convenience, efficiency, professional can have a positive impact on customer satisfaction through the mediating effect of their sentiment, convenience and professional on consumer sentiment and satisfaction are more significant. Originality/value - This paper the establishment of distribution service indicators related to customer satisfaction and empirical analysis can not only enrich and supplement the distribution service quality indicator system studied by the former, but also provide a theoretical basis for future research.

• Journal of Korea Trade
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• v.25 no.2
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• pp.58-74
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• 2021

Purpose - This paper research on the embodied carbon emission in Sino-Korea trade. It calculates and analyzes the carbon emission coefficient and specific carbon emissions in Sino-Korea trade from 2005 to 2014. Design/methodology - This paper conducted an empirical analysis for embodied carbon emission in Sino-Korea trade during the years 2005-2014, using a multi-region input-output model. First, direct and complete CO2 emission coefficient of the two countries were calculated and compared. On this basis, combined with the world input-output table, the annual import and export volume and sector volume of embodied carbon emission are determined. Then through the comparative analysis of the empirical results, the reasons for the carbon imbalance in Sino-Korea trade are clarified, and the corresponding suggestions are put forward according to the environmental protection policies being implemented by the two countries. Findings - The results show that South Korea is in the state of net trade export and net embodied carbon import. The carbon emission coefficient of most sectors in South Korea is lower than that of China. However, the reduction of carbon emission coefficient in China is significantly faster than that in South Korea in this decade. The change of Korea's complete CO2 emission coefficient shows that policy factors have a great impact on environmental protection. The proportion of intra industry trade between China and South Korea is relatively large and concentrated in mechanical and electrical products, chemical products, etc. These sectors generally have large carbon emissions, which need to be noticed by both countries. Originality/value - To the best knowledge of the authors, this study is the first attempt to research the embodied carbon emission of ten consecutive years in Sino-Korea Trade. In addition, In this paper, some mathematical methods are used to overcome the error problem caused by different statistical caliber in different databases. Finally, the accurate measurement of carbon level in bilateral trade will provide some reference for trade development and environmental protection.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.511-518
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• 2022

Supervised learning based on deep learning has made a leap forward in various application fields. However, many supervised learning methods work under the common assumption that training and test data are extracted from the same distribution. If it deviates from this constraint, the deep learning network trained in the training domain is highly likely to deteriorate rapidly in the test domain due to the distribution difference between domains. Domain adaptation is a methodology of transfer learning that trains a deep learning network to make successful inferences in a label-poor test domain (i.e., target domain) based on learned knowledge of a labeled-rich training domain (i.e., source domain). In particular, the unsupervised domain adaptation technique deals with the domain adaptation problem by assuming that only image data without labels in the target domain can be accessed. In this paper, we explore the unsupervised domain adaptation techniques.