This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

Companies are paying attention to project governance to realize their goal strategies, project success, and project value in a rapid and complex environment due to the development of information technology. This study aims to explore project governance and factors from literature review and practice guides related to project governance and empirically analyze the impact of project governance factors on IT project objective performance. The survey was conducted on project managers, project team members, and project management members with experience in carrying out business IT projects within two years at companies in various industries in Korea. The main conclusion is as follows. Among the project governance factors, disclosure and reporting that uses and reports using appropriate and reliable information about projects related to decision-making activities positively impact the achievement of IT project objectives: business success and stakeholder satisfaction. Among the project governance factors, project sponsorship, a role that effectively connects management and projects, and a project management framework that provides tools, procedures, resources, and techniques for projects positively impact IT project objective performance. This study is of academic and practical significance in that it identifies the definition and factors of project governance through companies in various industries in Korea and the positive impact of project governance factors on IT project objective performance.

This empirical analysis investigates the impact of consultant competency and project manager (PM) competency on business performance. Two hundred and twenty four chief executive officers and executive members at small and medium sized firms in the manufacturing sector were surveyed, yielding several outcomes. First, consultant competency positively affects consulting performance. Second, consultant competency positively affects business performance. Third, PM competency does not have a significant influence on consulting performance. Fourth, PM competency does not have a significant impact on business performance. Fifth, consulting performance does not have a significant effect on business performance. Finally, regarding the mediation effect of consulting performance on the influence of consultant competency and PM competency on business performance, consulting performance had no significant impact. Thus, expertise and insight are crucial for a consulting business to enable the growth of professional consultants. Furthermore, this study is expected to enhance the consulting performance of small and medium sized manufacturing firms by providing useful data to consultants and project managers when carrying out consulting projects.

The air transport industry is experiencing unprecedented fluctuations in aviation demand through the Covid-19 pandemic, and is more focused than ever on maintaining and generating business profitability. During the pandemic, demand for air cargo has soared, and the conversion business from passenger aircrafts to freighters(P2F) is drawing attention as a new business in the aviation maintenance industry. This study derives important factors to be considered in order to successfully carry out the P2F project through a wide range of cases and related literature, and analyzes the relative importance of each factor using the analytic hierarchy process. Through a survey of 33 aviation maintenance experts with more than 20 years of field experience, the importance of main factors and their sub factors was determined and implications were drawn. As a primary result, in order to succeed in the P2F project, the main factors were identified in the order of skill, finance, and location. The most important sub factors for each main factors were identified in order of securing airframe modification skill, securing infrastructure construction cost, and creating P2F business complex and district. The quantified success factors suggested the critical direction for the successful development of Korea's P2F business, and presented viable and specific business strategies and implementation plans for each factors.

The metal bush assembling process is a process of inserting and compressing a metal bush that serves to reduce the occurrence of noise and stable compression in the rotating section. In the metal bush assembly process, the head diameter defect and placement defect of the metal bush occur due to metal bush omission, non-pressing, and poor press-fitting. Among these causes of defects, it is intended to prevent defects due to omission of the metal bush by using signals from sensors attached to the facility. In particular, a metal bush omission is predicted through various data mining techniques using left load cell value, right load cell value, current, and voltage as independent variables. In the case of metal bush omission defect, it is difficult to get defect data, resulting in data imbalance. Data imbalance refers to a case where there is a large difference in the number of data belonging to each class, which can be a problem when performing classification prediction. In order to solve the problem caused by data imbalance, oversampling and composite sampling techniques were applied in this study. In addition, simulated annealing was applied for optimization of parameters related to sampling and hyper-parameters of data mining techniques used for bush omission prediction. In this study, the metal bush omission was predicted using the actual data of M manufacturing company, and the classification performance was examined. All applied techniques showed excellent results, and in particular, the proposed methods, the method of mixing Random Forest and SA, and the method of mixing MLP and SA, showed better results.

Recently, as ESG management has become an important issue, major companies in the automotive parts manufacturing industry are conducting ESG evaluations of their suppliers for the purpose of supply chain management. The results of these evaluations are being incorporated into contractual agreements. However, many small and medium-sized enterprises(SMEs) are lacking in their capacity and resources to effectively respond to ESG evaluations. Furthermore, existing ESG management guidelines do not provide an industry-specific guidance, making it necessary to establish industry-specific guidelines that SMEs can refer to. Therefore, in this study, the evaluation Indicators of ESG supply chain assessments are surveyed, which is conducted by domestic major automotive parts companies and global automobile manufacturers. Then 56 supply chain ESG evaluation Indicators are derived. Also, ESG management indicators for SMEs is analyzed through the Importance-Performance Analysis(IPA), based on an interview of expert groups. Therefore, this study could propose industry-specific ESG guidelines, based on the results of the derived indicators, which reflects the need for SMEs to practice ESG management within certain boundaries.

Recently, there are some outdoor floor advertising lighting devices as one of the active marketing methods. However, for outdoor use, there are many restrictions due to the Outdoor Advertisement Act, according to requiring high-output heat generation, waterproofing, and AC power, etc. The purpose of this study is to develop a Duo Light product optimized for indoor use through publicity and information guidance in normal times and automatic evacuation route guidance display in case of disaster, in conjunction with disaster safety. To that end, patent search and patent association analyses were conducted, and a comparative analysis with commercial products was conducted as a case study. In addition, prototypes were designed and produced through the review of operation principles, where field environment surveys and self-tests were conducted. Also, technology roadmaps were presented by preparing plans for expandability and advancement of products. For the analysis of technology commercialization, the feasibility of technology commercialization was examined through the analysis of Jolly’s Model and Lean Canvas Model. The results of this study will be able to contribute to minimize human damage through the effective response to disasters, which can increase the effect of indoor advertising by using the proposed indoor floor advertising lighting device in advertising and disaster situations.

Recently, the importance of impact-based forecasting has increased along with the socio-economic impact of severe weather have emerged. As news articles contain unconstructed information closely related to the people’s life, this study developed and evaluated a binary classification algorithm about snowfall damage information by using media articles text mining. We collected news articles during 2009 to 2021 which containing ‘heavy snow’ in its body context and labelled whether each article correspond to specific damage fields such as car accident. To develop a classifier, we proposed a probability-based classifier based on the ratio of the two conditional probabilities, which is defined as I/O Ratio in this study. During the construction process, we also adopted the n-gram approach to consider contextual meaning of each keyword. The accuracy of the classifier was 75%, supporting the possibility of application of news big data to the impact-based forecasting. We expect the performance of the classifier will be improve in the further research as the various training data is accumulated. The result of this study can be readily expanded by applying the same methodology to other disasters in the future. Furthermore, the result of this study can reduce social and economic damage of high impact weather by supporting the establishment of an integrated meteorological decision support system.

예이츠는 아일랜드의 음유시적 전통과 당대 유럽의 지식사회에서 강한 영향력을 발휘한 부동의 미학을 연결지어 본인만의 독특한 비극론을 전개한다. 유럽 상징주의 드라마가 자신의 연극론 형성에 갖는 잠재력을 예리하게 간파한 예이츠는 특히 벨기에 극작가 모리스 마테를링크가 주창한 “정적 드라마”에 영향을 받는다. 동시에 그리스비극을 아폴로와 디오니소스적 욕망 사이에 존재하는 긴장의 산물로 바라보는 니체의 비극 철학에 매료된다. 본 연구는 예이츠의 비극 이론을 니체철학과 마테를링크의 극이론의 창의적 수용이라는 관점에서 바라보고 분석하며 그 장단점을 논의한다. 특히 ‘비극적 환희’라는 극적 효과가 극형식과 연계되는 지점에서 발생하는 문제들에 주시한다. 예이츠는 그가 가졌던 사실주의에 대한 강한 반감 때문에 마테를링크의 일상성과 니체의 아폴로적인 욕망에서 보이는 형식의 중요성을 간과하게 된다.

본 연구는 아시아의 국제관계가 변화하는 맥락에서 "아시아 나토"의 실 행 가능성과 잠재적 영향을 검토한다. 아시아 버전 나토의 가능성을 분 석하기 위해 세 가지 목표를 추구한다: (1) 나토의 성격을 조사하고 아시 아에서의 잠재적 적용을 검토한다, (2) 세력균형이론과 위협균형이론의 관점에서 나토의 과거 실패를 검토한다, (3) 정치와 군사적 도전을 고려 한 아시아 나토의 실행 가능성을 평가한다. 이 연구는 미국과 일본을 중 심으로 아시아 나토에 대한 관심이 증가한 지정학적 변화를 탐구한다. 현재 미중 균형과 위협 사이의 균형은 양자 및 삼자 동맹을 설정하는 데 이르렀지만 아시아 나토의 가능성은 여전히 쉽지 않다. 그러나 중국이 지역 패권 추구로 인한 압도적인 외부 위협을 초래하면, 아세안 국가들 은 집단 안보 체제에 가입할 수 있다. 본 논문은 특히 이러한 상황에서 한국이 직면할 수 있는 문제점에 대해서도 지적한다.

The large process plant is currently implementing predictive maintenance technology to transition from the traditional Time-Based Maintenance (TBM) approach to the Condition-Based Maintenance (CBM) approach in order to improve equipment maintenance and productivity. The traditional techniques for predictive maintenance involved managing upper/lower thresholds (Set-Point) of equipment signals or identifying anomalies through control charts. Recently, with the development of techniques for big analysis, machine learning-based AAKR (Auto-Associative Kernel Regression) and deep learning-based VAE (Variation Auto-Encoder) techniques are being actively applied for predictive maintenance. However, this predictive maintenance techniques is only effective during steady-state operation of plant equipment, and it is difficult to apply them during start-up and shutdown periods when rises or falls. In addition, unlike processes such as nuclear and thermal power plants, which operate for hundreds of days after a single start-up, because the pumped power plant involves repeated start-ups and shutdowns 4-5 times a day, it is needed the prediction and alarm algorithm suitable for its characteristics. In this study, we aim to propose an approach to apply the optimal predictive alarm algorithm that is suitable for the characteristics of Pumped Storage Power Plant(PSPP) facilities to the system by analyzing the predictive maintenance techniques used in existing nuclear and coal power plants.

Technology innovation companies are focusing on contributing to business performance by R&D project as a strategic tool. Successful R&D leads to corporate competitiveness enhancement, national industrial development, but there are high uncertainty and risks in R&D. Public and private R&D projects are carried out to achieve various purposes. It was verified how the risk management and benefit management of the R&D project affect the detailed R&D project performance between the Public and private domain. The impact of Project Leadership on R&D performance was also analyzed. Those who have participated in the Public and Private R&D projects at companies or research institutes were surveyed. First, it was found that project risk and benefit management have partially an effect on R&D project performance. Second, Public and private R&D Project Leadership showed partially a interaction effect between project management and project performance.

Recently in Korea, YouTube stock channels increased rapidly due to the high social interest in the stock market during the COVID-19 period. Accordingly, the role of new media channels such as YouTube is attracting attention in the process of generating and disseminating market information. Nevertheless, prior studies on the market forecasting power of YouTube stock channels remain insignificant. In this study, the market forecasting power of the information from the YouTube stock channel was examined and compared with traditional news media. To measure information from each YouTube stock channel and news media, positive and negative opinions were extracted. As a result of the analysis, opinion in channels operated by media outlets were found to be leading indicators of KOSPI market returns among YouTube stock channels. The prediction accuracy by using logistic regression model show 74%. On the other hand, Sampro TV, a popular YouTube stock channel, and the traditional news media simply reported the market situation of the day or instead showed a tendency to lag behind the market. This study is differentiated from previous studies in that it verified the market predictive power of the information provided by the YouTube stock channel, which has recently shown a growing trend in Korea. In the future, the results of advanced analysis can be confirmed by expanding the research results for individual stocks.

This study identified the core competencies of aircraft maintenance quality engineers and compared the importance and retention of core competencies. Through literature research, 21 core competencies were derived in three areas of management technology, elemenal technology and collaboration technology, and a survey was conducted on the importance and retention of core competencies for 42 aircraft maintenance quality engineers. As a result of the survey, the importance of all core competencies of aircraft maintenance quality engineers is 3.95/5 on average, and the retention of all core competencies is 3.99/5 on average. 'Risk Management’, ‘Creating Document’, ‘Honesty/Moral’ were identified as the most important competencies in each area, and ‘Quality Management’, ‘Language’, ‘Honesty/Moral’ were identified as the most possessed competencies in each area. An IPA (Importance-Performance Analysis) was performed to analyze the details. Through IPA, ‘Risk Management’ and ‘Safety Management’ were evaluated as having a low degree of retention compared to a high level of importance. Therefore, they were identified as a core competencies that need to be improved first. In addition, the characteristics of each core competency and the recognition level in the field were also identified. This study will be helpful in defining the roles and functions of aircraft maintenance quality engineers to improve flight quality and prevent aviation accidents.

In the recent era of the fourth industrial revolution, many industries aim to maximize the efficiency of products and services by introducing cutting-edge technologies such as artificial intelligence and big data. In this situation, organizational culture is changing a lot due to the influx of the MZ generation with strong individualistic tendencies and the decreased face-to-face communication between members. However, active communication with colleagues is still essential to maximize performance, and the margins created by simplifying work processes and automating processes must be used for creating work performance. This requires cooperation and commitment through the job immersion of members who have an active attitude. This study analyzed how the organization's autonomous work environment and trust among members, which are creative work performance conditions, affect job immersion using raw data from the Occupational Safety and Health Research Institute. As a result, it was found that both the organization's autonomous working environment and trust among members significantly effected the members' job immersion. in order to achieve productivity and value improvement in companies, efforts are needed to increase workers' job immersion by building an autonomous working environment and trust among members. The results of this study are expected to contribute significantly to the search for ways to increase workers’ job commitment to improve organizational productivity.