• Journal of Dental Rehabilitation and Applied Science
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• v.33 no.3
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• pp.178-188
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• 2017

Purpose: We compared the effects of newly developed diode laser (Bison 808 nm Diode laser) on the treatment of peri-implantitis with conventional products (Picasso 810 nm Diode laser) by comparing the surface temperature of titanium disc and bacterial sterilization according to laser power. Materials and Methods: The titanium disc was irradiated for 60 seconds and 1 - 2.5 W using diode laser 808 nm and 810 nm. The surface temperature of the titanium disc was measured using a temperature measurement module and a temperature measurement program. In addition, in order to investigate the sterilizing effect according to the laser power, 808 nm laser was irradiated after application of bacteria to sandblasted large-grit acid-etched (SLA) and resorbable blast media (RBM) coated titanium discs. The irradiated disks were examined with scanning electron microscopy. Results: Both 808 nm and 810 nm lasers increased disk surface temperature as the power increased. When the 810 nm was irradiated under all conditions, the initial temperature rise rate, the descending rate, and the temperature change before and after was higher than that of 808 nm. Disk surface changes were not observed on both lasers at all conditions. Bacteria were irradiated with 808 nm, and the bactericidal effect was increased as the power increased. Conclusion: When applying these diode lasers to the treatment of peri-implantitis, 808 nm which have a bactericidal effect with less temperature fluctuation in the same power conditions would be considered safer. However, in order to apply a laser treatment in the dental clinical field, various safety and reliability should be secured.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.387-393
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• 2021

In this study, finite element analysis was performed to evaluate a method of increasing the fatigue life of the pipe connection structure commonly used in the topside structure of offshore platforms. MSC Patran/Nastran, a commercial analysis program, was used, and the critical structural model was selected from the global analysis. To realize the stress concentration phenomenon according to the load, modeling using 8-node solid elements was implemented. The main loads were considered to be two lateral loads and a tensile load on a diagonal pipe. To check the hotspot stress at the main location, a 0.01 mm dummy shell element was applied. After calculating the main stress at the 0.5-t and 1.5-t locations, the stress generated in the weld was estimated through extrapolation. In some sections, this stress was observed to be below the fatigue life that should be satisfied, and reinforcement was required. For reinforcement, a bracket was added to reduce the stress concentration factor where the fatigue life was insufficient without changing the thickness or diameter of the previously designed pipe. Regarding the tensile load, the stress in the bracket toe increased by 23 %, whereas the stress inside and outside of the pipe, which was a problem, decreased by approximately 8 %. Regarding the flexural load, the stress at the bracket toe increased by 3 %, whereas the stress inside and outside of the pipe, which was also a problem, decreased by approximately 48 %. Owing to the new bracket reinforcement, the stress in the bracket toe increased, but the S-N curve itself was better than that of the pipe joint, so it was not a significant problem. The improvement method of fatigue life is expected to be useful; it can efficiently increase the fatigue life while minimizing changes to the initial design.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.199-209
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• 2019

The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.60-76
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• 2022

This study presents a software full setup and the following test execution times in a Linux cluster for the United Kingdom Earth System Model (UKESM) and then compares the model results from control and experimental simulations of the UKESM relative to various observations. Despite its low resolution, the latest version of the UKESM can simulate tropospheric chemistry-aerosol processes and the stratospheric ozone chemistry using the United Kingdom Chemistry and Aerosol (UKCA) module. The UKESM with UKCA (UKESM-UKCA) can treat atmospheric chemistryaerosol-cloud-radiation interactions throughout the whole atmosphere. In addition to the control UKESM run with the default CMIP5 SO₂ emission dataset, an experimental run was conducted to evaluate the aerosol effects on meteorology by changing atmospheric SO₂ loading with the newest REAS data over East Asia. The simulation period of the two model runs was 28 years, from January 1, 1982 to December 31, 2009. Spatial distributions of monthly mean aerosol optical depth, 2-m temperature, and precipitation intensity from model simulations and observations over East Asia were compared. The spatial patterns of surface temperature and precipitation from the two model simulations were generally in reasonable agreement with the observations. The simulated ozone concentration and total column ozone also agreed reasonably with the ERA5 reanalyzed one. Comparisons of spatial patterns and linear trends led to the conclusion that the model simulation with the newest SO₂ emission dataset over East Asia showed better temporal changes in temperature and precipitation over the western Pacific and inland China. Our results are in line with previous finding that SO₂ emissions over East Asia are an important factor for the atmospheric environment and climate change. This study confirms that the UKESM can be installed and operated in a Linux cluster-computing environment. Thus, researchers in various fields would have better access to the UKESM, which can handle the carbon cycle and atmospheric environment on Earth with interactions between the atmosphere, ocean, sea ice, and land.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.356-365
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• 2022

Agrivoltaic systems, also called solar sharing, stated from an idea that utilizes sunlight above the light saturation point of crops for power generation using solar panels. The agrivoltaic systems are expected to reduce the incident solar radiation, the consequent surface cooling effect, and evapotranspiration, and bring additional income to farms through solar power generation by combining crops with solar photovoltaics. In this study, to evaluate if agrivoltaic systems are suitable for viticulture, we investigated the microclimatic change, the growth of vines and the characteristics of grape grown under solar panels set by planting lines compared with ones in open vineyards. There was high reduction of wind speed during over-wintering season, and low soil temperature under solar panel compared to those in the open field. There was not significant difference in total carbohydrates and bud burst in bearing mother branches between plots. Despite high content of chlorophyll in vines grown under panels, there is no significant difference in shoot growth of vines, berry weight, cluster weight, total soluble solid content and acidity of berries, and anthocyanin content of berry skins in harvested grapes in vineyards under panels and open vineyards. It was observed that harvesting season was delayed by 7-10 days due to late skin coloration in grapes grown in vineyards under panels compared to ones grown in open vineyards. The results from this study would be used as data required in development of viticulture system under panel in the future and further study for evaluating the influence of agrivoltaic system on production of crops including grapes.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.209-223
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• 2023

This study was conducted to evaluate the effectiveness of a polar literacy education program for elementary and middle school students, and to derive implications for new education to respond to climate change. We developed modular education programs based on the seven principles of polar literacy established by the Polar-ICE team. We divided them into two courses, one emphasizing science concepts and another emphasizing humanities and sociological issues. We then selected and structured detailed programs suitable for the two courses. These two courses were applied to 26 elementary and middle school students for approximately 69 hours in a Saturday science class hosted by the Department of Science Education at a university in Seoul. The 26 students were divided into three groups. Two groups completed the science education program for polar literacy and a humanities and social studies education program for polar literacy, respectively. The third group, the control group, received general science education unrelated to polar literacy. Before and after running the programs, all three groups responded to a polar literacy test and questionnaires that used vocabulary and presented scenes associated with polar regions. The test results were expressed using Wilcoxon signed ranks, which is a non-parametric test method, and improvements made upon completion of the program were analyzed. From a cognitive aspect, all three groups showed improvement after completing the program in the knowledge area; however, the experimental groups showed a greater degree of improvement than the control group, and there was a clear difference in the contents or materials explicitly covered. From an affective aspect, the difference between before and after the program was minor, but the group that focused on humanities and social issues showed a statistically significant improvement. Regarding changes in polar imagery, the two experimental groups tended to diverge from monotonous images to more diverse images compared to the control group. Based on the above results, we suggested methods to increase the effectiveness of polar literacy education programs, the importance of polar literacy as appropriate material for scientific thinking and earth system education, measures to improve attitudes related to the polar region, and the need to link to school curriculums.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.207-221
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• 2012

Air temperature in Korea has increased by $1.5^{\circ}C$ over the last 100 years, which is nearly twice the global average rate during the same period. Moreover, it is projected that such change in temperature will continue in the 21st century. The objective of this study was to evaluate the potential impacts of future climate change on the rice production and adaptation methods in Korea. Climate data for the baseline (1971~2000) and the three future climate (2011~2040, 2041~2070, and 2071~2100) at fifty six sites in South Korea under IPCC SRES A1B scenario were used as the input to the rice crop model ORYZA2000. Six experimental schemes were carried out to evaluate the combined effects of climatic warming, $CO_2$ fertilization, and cropping season on rice production. We found that the average production in 2071~2100 would decrease by 23%, 27%, and 29% for early, middle, and middle-late rice maturing type, respectively, when cropping seasons were fixed. In contrast, predicted yield reduction was ~0%, 6%, and 7%, for early, middle, and middle-late rice maturing type, respectively, when cropping seasons were changed. Analysis of variation suggested that climatic warming, $CO_2$ fertilization, cropping season, and rice maturing type contributed 60, 10, 12, and 2% of rice yield, respectively. In addition, regression analysis suggested 14~46 and 53~86% of variations in rice yield were explained by grain number and filled grain ratio, respectively, when cropping season was fixed. On the other hand, 46~78 and 22~53% of variations were explained respectively with changing cropping season. It was projected that sterility caused by high temperature would have no effect on rice yield. As a result, rice yield reduction in the future climate in Korea would resulted from low filled grain ratio due to high growing temperature during grain-filling period because the $CO_2$ fertilization was insufficient to negate the negative effect of climatic warming. However, adjusting cropping seasons to future climate change may alleviate the rice production reduction by minimizing negative effect of climatic warming without altering positive effect of $CO_2$ fertilization, which improves weather condition during the grain-filling period.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.