Journal of the Korea Society of Computer and Information
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v.26
no.6
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pp.145-154
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2021
While welcoming the distributing of the powers of the Ministry of Education, which is currently being promoted, to the city and provincial offices of education, I am very concerned that this will expand and amplify the powers concentrated in one central institution to 17 local institutions closer to the field. Until now, the Ministry of Education and the Office of Education have served as co-cause providers as important reasons for hindering school education. The transfer of the authority of the Ministry of Education is highly likely to be deformed as soon as it results in the quantitative reduction of the functions and roles of the existing Ministry of Education and the quantitative expansion of the roles and functions of the city and provincial offices of education. In the reality that no legal device for school autonomy has been established, it is highly likely that emphasizing the principle of school autonomy in our educational climate, which is deeply rooted in the vertical bureaucratic administrative culture, will end with a simple measure or stop at the level of imitation. Therefore, a more stable device is needed to check the authority of the city and provincial office of education and the superintendent of education to take over the authority of the Ministry of Education. This is also a system that is still required even when school autonomy becomes legal. Therefore, it is necessary to revitalize the independent education committee, establish a local education committee in the city and province education office, and activate the resident participation system (resident proposal system, resident voting system, resident litigation system, resident audit request system).
The Journal of the Convergence on Culture Technology
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v.7
no.4
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pp.559-564
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2021
The purpose of this study is to explore the factors that affect the intention to run remote classes after COVID-19 with university professors have fully experienced remote classes due to COVID-19. The research questions are what are the factors and the combinations of factors that affect the intention to run remote classes in the post-COVID-19. Data were collected through a survey of 311 remote classes at S Univ. in Seoul in fall 2020, and individuals and combinations of factors were confirmed through logistic regression analysis and decision tree analysis. As a result, individual factors were quality management, online office hours, quizzes midterm oral exams, video development, and student-student and instructor-student Q&A type between face-to-face and remote class. As combinations of factors, it was found that quality management×quiz×student Q&A and quality management×quiz×voting type had an effect on whether to run remote classes. Based on the results, we proposed to run and support remote classes in the post-COVID-19 era.
Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.
Journal of the Korean BIBLIA Society for library and Information Science
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v.33
no.1
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pp.371-401
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2022
If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.
This study attempts to analyze gender gaps in voter turnout for three different types of elections held since 2017 at the aggregate level using the Central Election Management Commission's turnout data, paying attention to the importance of women's voting. The findings are as follows. First, modern gender gaps in voter turnout at the aggregate level are confirmed in most regions regardless of election types. Second, the gender gap in turnout varies with age. The gender difference is verified in the "widowhood effect," where turnout decreases in the oldest-old. In the new voter group, modern gender gaps appear in most regions. The reversed gender difference in turnout in the late 20s, which reflects the Korean society's characteristics, is confirmed in all elections. Third, it is unclear whether the reverse gender gap in turnout becomes more pronounced in urbanized districts. As urbanization progressed, modern gender differences in voter turnout across age groups are observed at the population-based size level. Paradoxically, the modern gender gap tends to be weak and turns into the traditional gender gap in younger age groups (in the late thirties) in Gangnam-gu and Seocho-gu, the most modernized districts in Seoul. These results show that the modern gender gap in turnout is now a common phenomenon and continues to be strengthened by newly recruited voters in Korea. Thus we should pay more attention to female voters' political behavior and a new approach beyond the developmental theory to understand the causal mechanism to generate the modern gender gap in voter turnout.
In this study, a proposed ensemble learning technique aims to enhance the semantic segmentation performance of images captured by Unmanned Aerial Vehicles (UAVs). With the increasing use of UAVs in fields such as urban planning, there has been active development of techniques utilizing deep learning segmentation methods for land cover segmentation. The study suggests a method that utilizes prominent segmentation models, namely U-Net, DeepLabV3, and Fully Convolutional Network (FCN), to improve segmentation prediction performance. The proposed approach integrates training loss, validation accuracy, and class score of the three segmentation models to enhance overall prediction performance. The method was applied and evaluated on a land cover segmentation problem involving seven classes: buildings,roads, parking lots, fields, trees, empty spaces, and areas with unspecified labels, using images captured by UAVs. The performance of the ensemble model was evaluated by mean Intersection over Union (mIoU), and the results of comparing the proposed ensemble model with the three existing segmentation methods showed that mIoU performance was improved. Consequently, the study confirms that the proposed technique can enhance the performance of semantic segmentation models.
Woo Kyoung Jeong;Hyo-Jin Kang;Sang Hyun Choi;Mi-Suk Park;Mi Hye Yu;Bohyun Kim;Myung-Won You;Sanghyeok Lim;Young Seo Cho;Min Woo Lee;Jeong Ah Hwang;Jae Young Lee;Jung Hoon Kim;Ijin Joo;Jae Seok Bae;So Yeon Kim;Yong Eun Chung;Dong Hwan Kim;Jeong Min Lee
Korean Journal of Radiology
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v.24
no.6
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pp.482-497
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2023
Sonazoid, a second-generation ultrasound contrast agent, was introduced for the diagnosis of hepatic nodules. To clarify the issues with Sonazoid contrast-enhanced ultrasonography for the diagnosis of hepatocellular carcinoma (HCC), the Korean Society of Radiology and Korean Society of Abdominal Radiology collaborated on the guidelines. The guidelines are de novo, evidence-based, and selected using an electronic voting system for consensus. These include imaging protocols, diagnostic criteria for HCC, diagnostic value for lesions that are inconclusive on other imaging results, differentiation from non-HCC malignancies, surveillance of HCC, and treatment response after locoregional and systemic treatment for HCC.
This paper analyzes the macroeconomic effects of elections on the Korean economy and their future ramifications. It measures the shocks to the Korean economy caused by elections by taking the average of sample forecast errors from four major elections held in the 1980s. The seven variables' Bayesian Vector Autoregression Model which includes the Monetary Base, Industrial Production, Consumption, Consumer Price, Exports, and Investment is based on the quarterly time series data starting from 1970 and is updated every quarter before forecasts are made for the next quarter. Because of this updating of coefficients, which reflects in part the rapid structural changes of the Korean economy, this study can capture the shock effect of elections, which is not possible when using election dummies with a fixed coefficient model. In past elections, especially the elections held in the 1980s, $M_2$ did not show any particular movement, but the currency and base money increased during the quarter of the election was held and the increment was partly recalled in the next quarter. The liquidity of interest rates as measured by corporate bond yields fell during the quarter the election and then rose in the following quarter, which is somewhat contrary to the general concern that interest rates will increase during election periods. Manufacturing employment fell in the quarter of the election because workers turned into campaigners. This decline in employment combined with voting holiday produce a sizeable decline in industrial production during the quarter in which elections are held, but production catches up in the next quarter and sometimes more than offsets the disruption caused during the election quarter. The major shocks to price occur in the previous quarter, reflecting the expectational effect and the relaxation of government price control before the election when we simulate the impulse responses of the VAR model, imposing the same shocks that was measured in the past elections for each election to be held in 1992 and assuming that the elections in 1992 will affect the economy in the same manner as in the 1980s elections, 1992 is expected to see a sizeable increase in monetary base due to election and prices increase pressure will be amplified substantially. On the other hand, the consumption increase due to election is expected to be relatively small and the production will not decrease. Despite increased liquidity, a large portion of liquidity in circulation being used as election funds will distort the flow of funds and aggravate the fund shortage causing investments in plant and equipment and construction activities to stagnate. These effects will be greatly amplified if elections for the head of local government are going to be held this year. If mayoral and gubernatorial elections are held after National Assembly elections, their effect on prices and investment will be approximately double what they normally will have been have only congressional and presidential elections been held. Even when mayoral and gubernatorial elections are held at the same time as congressional elections, the elections of local government heads are shown to add substantial effects to the economy for the year. The above results are based on the assumption that this year's elections will shock the economy in the same manner as in past elections. However, elections in consecutive quarters do not give the economy a chance to pause and recuperate from past elections. This year's elections may have greater effects on prices and production than shown in the model's simulations because campaigners' return to industry may be delayed. Therefore, we may not see a rapid recall of money after elections. In view of the surge in the monetary base and price escalation in the periods before and after elections, economic management in 1992 should place its first priority on controlling the monetary aggregate, in particular, stabilizing the growth of the monetary base.
Predicting corporate failure has been an important topic in accounting and finance. The costs associated with bankruptcy are high, so the accuracy of bankruptcy prediction is greatly important for financial institutions. Lots of researchers have dealt with the topic associated with bankruptcy prediction in the past three decades. The current research attempts to use ensemble models for improving the performance of bankruptcy prediction. Ensemble classification is to combine individually trained classifiers in order to gain more accurate prediction than individual models. Ensemble techniques are shown to be very useful for improving the generalization ability of the classifier. Bagging is the most commonly used methods for constructing ensemble classifiers. In bagging, the different training data subsets are randomly drawn with replacement from the original training dataset. Base classifiers are trained on the different bootstrap samples. Instance selection is to select critical instances while deleting and removing irrelevant and harmful instances from the original set. Instance selection and bagging are quite well known in data mining. However, few studies have dealt with the integration of instance selection and bagging. This study proposes an improved bagging ensemble based on instance selection using genetic algorithms (GA) for improving the performance of SVM. GA is an efficient optimization procedure based on the theory of natural selection and evolution. GA uses the idea of survival of the fittest by progressively accepting better solutions to the problems. GA searches by maintaining a population of solutions from which better solutions are created rather than making incremental changes to a single solution to the problem. The initial solution population is generated randomly and evolves into the next generation by genetic operators such as selection, crossover and mutation. The solutions coded by strings are evaluated by the fitness function. The proposed model consists of two phases: GA based Instance Selection and Instance based Bagging. In the first phase, GA is used to select optimal instance subset that is used as input data of bagging model. In this study, the chromosome is encoded as a form of binary string for the instance subset. In this phase, the population size was set to 100 while maximum number of generations was set to 150. We set the crossover rate and mutation rate to 0.7 and 0.1 respectively. We used the prediction accuracy of model as the fitness function of GA. SVM model is trained on training data set using the selected instance subset. The prediction accuracy of SVM model over test data set is used as fitness value in order to avoid overfitting. In the second phase, we used the optimal instance subset selected in the first phase as input data of bagging model. We used SVM model as base classifier for bagging ensemble. The majority voting scheme was used as a combining method in this study. This study applies the proposed model to the bankruptcy prediction problem using a real data set from Korean companies. The research data used in this study contains 1832 externally non-audited firms which filed for bankruptcy (916 cases) and non-bankruptcy (916 cases). Financial ratios categorized as stability, profitability, growth, activity and cash flow were investigated through literature review and basic statistical methods and we selected 8 financial ratios as the final input variables. We separated the whole data into three subsets as training, test and validation data set. In this study, we compared the proposed model with several comparative models including the simple individual SVM model, the simple bagging model and the instance selection based SVM model. The McNemar tests were used to examine whether the proposed model significantly outperforms the other models. The experimental results show that the proposed model outperforms the other models.
Although more priority is given to politicians from the aspect that they represent people and decide the future of country, the current situation is that politicians are not free from terrorism because of insufficient guard-concerned law, negative social recognition and increased crime and terrorism. The measure for politician terrorism shall be handled from the aspect of national security rather than public peace. For the purpose, basic legal foundation shall be prepared and specialized guard technique considering specialty of politician shall be established. Basic solution shall be established by reinforcing law against politician terrorism and establishing new law from the national viewpoint. The guard for politician has two faces that both of safety of guard target and voting intention of voter shall be met at the same time. Although special guard technique is required for guarding politician, current situation is that it is not researched professionally. In relation to the measure to develop the system of protection for politician, First, the study suggested legal foundation for politician guard. Although the 17th National Assembly proposed revised legal plan to protect politician from terrorism, it is suspended, expired and abolished now. The legal plan presented by members of the National Assembly was simply restricted to the scope of public guard. The study divided establishment of legal foundation into two things. The first one is the dispatch type of effective public guard and the second one is the transfer to private guard. Second, the study suggested environmental development method of politician guard. in the environment of politician guard, the study suggested improvement and development method by analyzing social recognition, politician's mind and voter's mind psychologically. After the beginning of human society, if human race is continued, political activity won't disappear. It is obvious that the safety of political leader is very important issue for human race because he plays the role to decide the future of human. In the future, more specialized, effective law shall be prepared and deeper study of scholar shall be performed.
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