• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.347-357
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• 2003

This paper describes on the suppression of sea clutter on marine radar display using a cell-averaging CFAR(constant false alarm rate) technique, and on the analysis of radar echo signal data in relation to the estimation of ARPA functions and the detection of the shadow effect in clutter returns. The echo signal was measured using a X -band radar, that is located on the Pukyong National University, with a horizontal beamwidth of $$3.9^{\circ}$$, a vertical beamwidth of $20^{\circ}$, pulsewidth of $0.8 {\mu}s$ and a transmitted peak power of 4 ㎾ The suppression performance of sea clutter was investigated for the probability of false alarm between $l0-^0.25;and; 10^-1.0$. Also the performance of cell averaging CFAR was compared with that of ideal fixed threshold. The motion vectors and trajectory of ships was extracted and the shadow effect in clutter returns was analyzed. The results obtained are summarized as follows；1. The ARPA plotting results and motion vectors for acquired targets extracted by analyzing the echo signal data were displayed on the PC based radar system and the continuous trajectory of ships was tracked in real time. 2. To suppress the sea clutter under noisy environment, a cell averaging CFAR processor having total CFAR window of 47 samples(20+20 reference cells, 3+3 guard cells and the cell under test) was designed. On a particular data set acquired at Suyong Man, Busan, Korea, when the probability of false alarm applied to the designed cell averaging CFAR processor was 10$^{-0}$.75/ the suppression performance of radar clutter was significantly improved. The results obtained suggest that the designed cell averaging CFAR processor was very effective in uniform clutter environments. 3. It is concluded that the cell averaging CF AR may be able to give a considerable improvement in suppression performance of uniform sea clutter compared to the ideal fixed threshold. 4. The effective height of target, that was estimated by analyzing the shadow effect in clutter returns for a number of range bins behind the target as seen from the radar antenna, was approximately 1.2 m and the information for this height can be used to extract the shape parameter of tracked target..

• 대한공업교육학회지
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• v.39 no.1
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• pp.164-188
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• 2014

The purpose of this study is to investigate the perception of undergraduates of the college of education on the importance of certification areas and factors suggested by the certification system at each department level as well as the college as a whole, in order to come up with measures for further improvement. The specific objectives of this study are first, verifying different perception on the importance of certification areas and factor per department, second, verifying different perception on the importance of certification areas and factor per grade. The population of this study is undergraduates of the college of education at A University, and the survey on the different perception on the importance was conducted on 758 students of 10 departments. Total 800 copies of survey were distributed, and 299 copies or 37.3% were retrieved. First, it was found that undergraduates of the college of education at A University highly recognize the necessity of a new system to produce excellent teachers. when it comes to different department, in the area of teaching personalities, there is difference in the importance of teaching aptitude test and completion of social intelligence development program. In the area of teaching expertise, there is different perception in the importance of completion of curriculum education subjects per major, completion of curriculum contents per major, and participation in teaching demonstration contest. In the area of student guidance expertise, there is difference by department in completion of creative character development related education programs and "teaching practice" course. In the area of communication skills in the information society, minimum score requirement for a second foreign language is considered less important than others. Second, as for grade, freshmen highly recognize the importance of validity of teaching training course, integrity of the course, validity of the teaching training course in producing excellent teachers, graduates' job performing ability development as a teacher, appropriacy of curriculum of the college of education in producing excellent teachers, compared to other grades. In particular, seniors consider the necessity of a new system to produce excellent teachers the most.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.337-347
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• 2021

This study is a qualitative study conducted to provide basic data for therapists working in long-term care hospitals to improve their countermeasure strategies for new infectious diseases and improvement of the treatment room infection management system, and to help therapists understand their infection management work. Colaizzi's phenomenological research method was applied as the research method. Telephone interviews were conducted with nine occupational therapists and physical therapists working in nursing hospitals. The contents of the interview were recorded with the consent of the study subjects, and additional confirmation was received by email. The recorded content was analyzed after transcription, and the meaning and nature of the experience coping with COVID-19 were described. The content was organized into 6 themes, 17 main meaning and 49 meaning units. In accordance with the COVID-19 situation, the infection control system has been strengthened by reinforcing infection control education in nursing hospitals, practicing infection control, and supervising infection control outside business hours. It was found that the treatment environment was changed due to the restriction of treatment activities by practicing distancing in the treatment room, adjusting rest and meal times during working hours, and strengthening infection control. In addition, the therapist's role has been expanded and the paradigm of treatment has changed, such as considering the untact intervention, and they have experienced cohort quarantine, pre-tested for COVID-19, vaccinations, and side effects from COVID-19. However, due to the infection work, the therapist's work burden is increased, and the person is experiencing fear, depression, and work stress from the spread of COVID-19. They were also aware of the need for nursing hospital care personnel support, such as guaranteeing rest after vaccination and providing infection control tools and equipment. The results of this study are expected to be used as basic data for human and physical support for the development of infectious disease response strategy programs in nursing hospital treatment rooms and for infection control in nursing hospitals.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.52-61
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• 2023

The use of ultra-high-resolution (UHR) seismic surveys to preceisly characterize coastal and shallow structures have increased recently. UHR surveys derive a spatial resolution of 3.125 m using a high-frequency source (80 Hz to 1 kHz). A digital streamer system is an essential module for acquiring high-quality UHR seismic data. Localization studies have focused on reducing purchase costs and decreasing maintenance periods. Basic performance verification and application tests of the developed streamer have been successfully carried out; however, a comparative analysis with the existing benchmark model was not conducted. In this study, we characterized data obtained by using a developed streamer and a benchmark model simultaneously. Tamhae 2 and auxiliary equipment of the Korea Institute of Geoscience and Mineral Resources were used to acquire 2D seismic data, which were analyzed from different perspectives. The data obtained using the developed streamer differed in sensitivity from that obtained using benchmark model by frequency band.However, both type of data had a very high level of similarity in the range corresponding to the central frequency band of the seismic source. However, in the low frequency band below 60 Hz, data obtained using the developed streamer showed a lower signal-to-noise ratio than that obtained using the benchmark model.This lower ratio can hinder the quality in data acquisition using low-frequency sound sources such as cluster air guns. Three causes for this difference were, and streamers developed in future will attempt to reflect on these improvements.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.4
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• pp.257-267
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• 2023

Purpose. The purpose of the study was to fabricate a prototype robotic simulator for dental education, to test whether it could simulate mandibular movements, and to assess the possibility of the stimulator responding to stimuli during dental practice. Materials and methods. A virtual simulator model was developed based on segmentation of the hard tissues using cone-beam computed tomography (CBCT) data. The simulator frame was 3D printed using polylactic acid (PLA) material, and dentiforms and silicone face skin were also inserted. Servo actuators were used to control the movements of the simulator, and the simulator's response to dental stimuli was created by pressure and water level sensors. A water level test was performed to determine the specific threshold of the water level sensor. The mandibular movements and mandibular range of motion of the simulator were tested through computer simulation and the actual model. Results. The prototype robotic simulator consisted of an operational unit, an upper body with an electric device, a head with a temporomandibular joint (TMJ) and dentiforms. The TMJ of the simulator was capable of driving two degrees of freedom, implementing rotational and translational movements. In the water level test, the specific threshold of the water level sensor was 10.35 ml. The mandibular range of motion of the simulator was 50 mm in both computer simulation and the actual model. Conclusion. Although further advancements are still required to improve its efficiency and stability, the upper-body prototype simulator has the potential to be useful in dental practice education.

• Journal of Nutrition and Health
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• v.57 no.1
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• pp.53-64
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• 2024

Purpose: Mitochondria play a crucial role in preserving skeletal muscle mass, and damage to mitochondria leads to muscle mass loss. This study investigated the effects of oxypeucedanin hydrate, a furanocoumarin isolated from Angelica dahurica radix, on myogenesis and mitochondrial function in vitro and in zebrafish models. Methods: C2C12 myotubes cultured in media containing 0.1, 1, 10, or 100 ng/mL oxypeucedanin hydrate were immunostained with myosin heavy chain (MHC), and then multinucleated MHC-positive cells were counted. The expressions of markers related to muscle differentiation, muscle protein degradation, and mitochondrial function were determined by quantitative reverse transcription polymerase chain reaction. To investigate the effects of oxypeucedanin hydrate on mitochondrial dysfunction, Tg(Xla.Eef1a1:mito-EGFP) zebrafish embryos were treated with 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI) with or without oxypeucedanin hydrate and analyzed for mito-EGFP intensity and mitochondrial length. Results: Oxypeucedanin hydrate significantly increased MHC-positive multinucleated myotubes (≥ 3 nuclei) and increased the expression of the myogenic marker myosin heavy chain 4. However, it decreased the expressions of muscle-specific RING finger protein 1 and muscle atrophy f-box (markers of muscle protein degradation). Furthermore, oxypeucedanin hydrate enhanced the expressions of markers of mitochondrial biogenesis (peroxisome proliferator-activated receptor-gamma coactivator 1 alpha, transcription factor a mitochondrial, succinate dehydrogenase complex flavoprotein subunit A, and cytochrome c oxidase subunit 1) and mitochondrial fusion (optic atrophy 1). However, it reduced the expression of dynamin-related protein 1 (a mitochondrial fission regulator). Consistently, oxypeucedanin hydrate reduced FOLFIRI-induced mitochondrial dysfunction in the skeletal muscles of zebrafish embryos. Conclusion: The study indicates that oxypeucedanin hydrate promotes myogenesis by improving mitochondrial function, and thus, suggests oxypeucedanin hydrate has potential use as a nutritional supplement that improves muscle mass and function.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Radiation Oncology Journal
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• v.25 no.4
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• pp.242-248
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• 2007

Purpose: To study the effect of recombinant human epidermal growth factor (rhEGF) on oral mucositis induced by cisplatin and radiotherapy in a mouse model. Materials and Methods: Twenty-four ICR mice were divided into three groups-the normal control group, the no rhEGF group (treatment with cisplatin and radiation) and the rhEGF group (treatment with cisplatin, radiation and rhEGF). A model of mucositis induced by cisplatin and radiotherapy was established by injecting mice with cisplatin (10 mg/kg) on day 1 and with radiation exposure (5 Gy/day) to the head and neck on days $1{\sim}5$. rhEGF was administered subcutaneously on days -1 to 0 (1 mg/kg/day) and on days 3 to 5 (1 mg/kg/day). Evaluation included body weight, oral intake, and histology. Results: For the comparison of the change of body weight between the rhEGF group and the no rhEGF group, a statistically significant difference was observed in the rhEGF group for the 5 days after day 3 of. the experiment. The rhEGF group and no rhEGF group had reduced food intake until day 5 of the experiment, and then the mice demonstrated increased food intake after day 13 of the of experiment. When the histological examination was conducted on day 7 after treatment with cisplatin and radiation, the rhEGF group showed a focal cellular reaction in the epidermal layer of the mucosa, while the no rhEGF group did not show inflammation of the oral mucosa. Conclusion: These findings suggest that rhEGF has a potential to reduce the oral mucositis burden in mice after treatment with cisplatin and radiation. The optimal dose, number and timing of the administration of rhEGF require further investigation.