Proton therapy using the Bragg peak is one of the radiation therapies and can deliver its maximum energy to the tumor with giving least energy for normal tissue. A cross-sectional image of the human body taken with the computed tomography (CT) has been used for radiation therapy planning. The HU values change according to the tube voltage, which lead to the change in the boundary and thickness of the anatomical structure on the CT image. This study examined the changes in the Bragg peak of the brain region according to the thickness variation in the head phantom composed of several materials using the Geant4. In the phantom composed of a single material, the Bragg peak according to the type of media and the incident energy of the proton beams were calculated, and the reliability of Geant4 code was verified by the Bragg peak. The variation of the peak in the brain region was examined when each thickness of the head phantom was changed. When the thickness of the soft tissue was changed, there was no change in the peak position, and for the skin the change in the peak was small. The change of the peak position was mainly changed when the bone thickness. In particular, when the bone was changed only or the bone was changed together with other tissues, the amount of change in the peak position was the same. It is considered that measurement of the accurate bone thickness in CT images is one of the key factors in depth-dose distribution of the radiation therapy planning.
One of the most noteworthy topics in recent corporate management is ESG(Environmental, Social, Governance). Although there are many companies that have declared ESG management, KT has declared full-fledged ESG management in 2021 and is sharing its sustainable management strategy with stakeholders. In addition, KT is strengthening ESG management by issuing ESG bonds for the first time in the domestic ICT industry. At a time when the information technology industry became more important due to COVID-19, this study attempted to examine KT's ESG management goals and strategies by dividing them into environmental, social, and governance areas. KT was aiming to achieve environmental integrity through 'environmental management', 'green competence', 'energy resources', and 'eco-friendly projects' in the environmental field. In addition, in the social field, genuine creating social value was pursued through 'social contribution', 'co-growth', and 'human rights management'. Finally, in the governance area, it was aiming for a transparent corporate management system to pursue economic reliability through 'ethics and compliance' and 'risk management'. In particular, KT was promoting its own ESG management by promoting strategies to solve environmental and social problems using AI and BigData technologies based on the characteristics of a digital platform company. This study aims to derive implications for ESG strategy establishment and ESG management development direction through KT's ESG management case in relation to ESG management, which has emerged as a hot topic.
It is very important to ensure the reliability of dam inflow data, which is critical in planning and managing the supply and demand of water resources in a basin. However, the simple water balance model sometimes results in negative inflows and does not consider the actual inflow characteristics. In this study, to address these issues, the existing water balance formula was modified by considering evaporation which is available for calculation among other outflows. The modified water balance formula was applied to the Soyang Dam. The results showed that the rate of negative inflows decreased in the re-evaluated dam inflow data and it was possible to secure consistency for the total inflow volume. In addition, investigating the water availability in the Soyang Dam watershed based on the water balance concept considering evaporation, it was found that direct water use in the human aspect was about 60%, and the indirect water use in the natural aspect was about 40%. In drought years, it was also confirmed that the proportion of indirect use of water resources increased.
This study is to investigate the perception of domestic appraisers about the possibility of using artificial intelligence (AI) and related risks from the use of AI in the appraisal industry. We conducted a mobile survey of evaluators from February 10 to 18, 2022. We collected survey data from 193 respondents. Frequency analysis and multiple response analysis were performed for basic analysis. When AI is used in the appraisal industry, factor analysis was used to analyze various types of risks. Although appraisers have a positive perception of AI introduction in the appraisal industry, they considered collateral, consulting, and taxation, mainly in areas where AI is likely to be used and replaced, mainly negative effects related to job losses and job replacement. They were more aware of the alternative risks caused by AI in the field of human labor. I was very aware of responsibilities, privacy and security, and the risk of technical errors. However, fairness, transparency, and reliability risks were generally perceived as low risk issues. Existing studies have mainly studied analysis methods that apply AI to mass evaluation models, but this study focused on the use and risk of AI. Understanding industry experts' perceptions of AI utilization will help minimize potential risks when AI is introduced on a large scale.
Journal of Korea Entertainment Industry Association
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v.14
no.7
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pp.95-106
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2020
The study was conducted to investigate the effectiveness of professional volleyball teams' integrated marketing communication(IMC) activities. The subjects of this study were a total of 400 surveys of visitors who visited the stadium to watch mans professional volleyball games from 2019 to 2020, and 385 questionnaires except for invalid or error questionnaires were used for research purposes. For factor analysis and reliability testing, IBM SPSS Statistics Ver 21.0 was used. Frequency analysis was conducted to examine the general characteristics. To verify differences between groups according to demographic and general characteristics, independent sample t-test and one-way ANOVA were performed, and correlation analysis was performed to examine the relationship between variables. In addition, regression analysis was conducted to verify the influence between variables. The results of the study are as follows. First, there was no difference in club image, club reputation, and club loyalty by gender. Second, there was no difference in club image, club reputation, and club loyalty according to age. Third, there was no difference in the club image, club reputation, or club loyalty according to the viewing experience. Fourth, professional volleyball team IMC activities were found to affect the club image. Fifth, professional volleyball team IMC activities were found to have an impact on the club's reputation. Sixth, it was shown that professional volleyball team IMC activities have an effect on club loyalty. Eighth, the club image was found to affect the club loyalty. Finally, it was found that the club reputation influenced the club loyalty.
Journal of the Korea Society of Computer and Information
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v.28
no.1
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pp.17-26
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2023
In this paper, we propose a several smoothing techniques are compared and applied to increase the application of the LSTM-based learning model and its effectiveness. The applied smoothing technique is Savitky-Golay, exponential smoothing, and weighted moving average. Through this study, the LSTM algorithm with the Savitky-Golay filter applied in the preprocessing process showed significant best results in prediction performance than the result value shown when applying the LSTM model to Bitcoin data. To confirm the predictive performance results, the learning loss rate and verification loss rate according to the Savitzky-Golay LSTM model were compared with the case of LSTM used to remove complex factors from Bitcoin price prediction, and experimented with an average value of 20 times to increase its reliability. As a result, values of (3.0556, 0.00005) and (1.4659, 0.00002) could be obtained. As a result, since crypto-currencies such as Bitcoin have more volatility than stocks, noise was removed by applying the Savitzky-Golay in the data preprocessing process, and the data after preprocessing were obtained the most-significant to increase the Bitcoin prediction rate through LSTM neural network learning.
Purpose: With the development of the Internet, consumers can quickly access the electronic word-of-mouth. Consumers seek to reduce uncertainty by referring to the opinions of other consumers about products and services when making purchase decisions. In the food service industry, evaluating a restaurant before an actual visitation is difficult. Therefore, electronic word-of-mouth is important to interact with the customer in restaurants. as it can be used as an exchange of information in which consumers participate and interact with other customers. This study was conducted to verify how online word-of-mouth characteristics (Consensus, Vividness, Neutrality) on attitudes and visit intention from the perspective of social exchange theory. And it was performed to verify the structural relationship between short-term visit intention, mid-term visit and long-term visit intention. Research design, data, and methodology: A survey was conducted on customers who have visited restaurants. Of a total of 312 responses, 306 responses were used, excluding insincere responses and missing values for factors analysis. SPSS 25.0 and AMOS 25.0 were used for statistical analysis, and hypothesis testing was conducted after verifying the validity and reliability of the questionnaire items. Result: The result of the analysis showed that, consensus and neutrality have a positive effect on attitude but not much on vividness. In addition, consensus, vividness, and neutrality have no effect on the short-term visit intention. Finally, the short-term visit intention has a positive effect on mid-term visit intention, and mid-term visit intention has a positive effect on long-term visit intention. Conclusions: Based on the results, this study suggested that it is necessary to have practical implications for marketing and monitoring restaurant reviews in consideration of the characteristics of electronic word-of-mouth. When managing electronic-word-of-mouth, it is necessary to manage the consensus and neutrality is essential to provide sufficient information about the restaurant. The focus should not only be on vividness, such as photos and videos. In addition, restaurants should also provide a good experience for first-time visitors as the short-term visit intention positively affects mid-term and long-term visit intention.
The purpose of this study is to present the direction of employment guidance for long-term service through the analysis of the cause of employment of employed students who graduated from specialized high school. In particular, the purpose is to present student guidance plans for long-term service by analyzing personal reasons for students graduating from commercial high schools and policy factors for individual, school, company, and government service after employment. To this end, a survey was conducted for graduates of commercial high schools nationwide, and the validity, reliability, and causality of the survey data were analyzed by applying Exploratory Factor Analysis, Cronbach's Alpha, and decision tree analysis techniques. We found that personal goal setting for employment is an important factor for working for more than 1 year, personal relationships at work and personal characteristics are important factors for working for more than 3 years. In addition, we found that the reason for getting a job is that personal reasons and school recommendations are great, special lectures on employment, camps, and 'advice from seniors and teachers' programs are helpful in finding a job, and accounting and computer related subjects are helpful for long-term employment. Accordingly, in specialized high schools, it is required to prepare specific instructional measures for education such as setting personal goals and the formation of human relationships that are the basis of social life, and to actively operate the above subjects and programs to help with employment and longevity.
In this study, K-Digital Training program, which is a representative government project of vocational training for new digital technologies in response to the 4th industrial revolution, is analyzed and an improvement model is suggested. The K-Digital training project is rapidly expanding, with the number of training operators increasing by 7.1 times and training course programs by 8.5 times within three years of implementation, but there is a severe problem in that education and training programs are concentrated in the metropolitan. To solve this problem, a shared training model is proposed. This model is a plan to maximize the use of local human and material resources, to respond to new digital technologies through systematic composition and operation, and to enhance the stability and reliability of education and training. In each region, a sharing and cooperation model in the form of a consortium is established that jointly utilizes resources scattered by various training institutions such as instructors, training contents, and training infrastructure related to digital new technology. In addition, a training certification evaluation system is introduced to increase the credibility of the rapidly developing digital new technology training.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.16
no.1
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pp.24-32
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2023
The current Private 5G use procedure goes through the step of application examination, use and usage inspection, and can be divided in to application, examination step as a procedure before frequency allocation, and use, usage inspection step as a procedure after frequency allocation. Various types of documents are required to apply for a Private 5G, and due to the document screening process and radio station inspection for using Private 5G frequencies, the procedure for Private 5G applicants to use Private 5G is complicated and takes a considerable amount of time. In this paper, we proposed Frequency Allocation Process for Private 5G using a blockchain platform, which is fast and simplified than the current procedure. Through the use of a blockchain platform and NFT (Non-Fungible Token), reliability and integrity of the data required in the frequency allocation process were secured, and security of frequency usage information was maintained and a reliable Private 5G frequency allocation process was established. Also by applying the RPA system that minimizes human intervention, fairness was secured in the process of allocating Private 5G. Finally, the frequency allocation process of Private 5G based on the Ethereum blockchain was performed though a simulation.
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