• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.3
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• pp.127-143
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• 2022

Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.42-55
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• 2023

A methodology to predict the carbon performance of newly created urban greening plans is required as policies based on quantifying carbon performance are rapidly being introduced in the face of the climate crisis caused by global warming. This study developed a tree carbon calculator that can be used for carbon reduction designs in landscaping and attempted to verify its effectiveness in landscape design. For practical operability, MS Excel was selected as a format, and carbon absorption and storage by tree type and size were extracted from 93 representative species to reflect plant design characteristics. The database, including tree unit prices, was established to reflect cost limitations. A plantation experimental design to verify the performance of the tree carbon calculator was conducted by simulating the design of parks in the central region for four landscape design, and the causal relationship was analyzed by conducting semi-structured interviews before and after. As a result, carbon absorption and carbon storage in the design using the tree carbon calculator were about 17-82% and about 14-85% higher, respectively, compared to not using it. It was confirmed that the reason for the increase in carbon performance efficiency was that additional planting was actively carried out within a given budget, along with the replacement of excellent carbon performance species. Pre-interviews revealed that designers distrusted data and the burdens caused by new programs before using the arboreal carbon calculator but tended to change positively because of its usefulness and ease of use. In order to implement carbon reduction design in the landscaping field, it is necessary to develop it into a carbon calculator for trees and landscaping performance. This study is expected to present a useful direction for ntroducing carbon reduction designs based on quantitative data in landscape design.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.41-61
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• 2023

The universal form of life in the era of the 4th industrial revolution can probably be summarized as the keyword "non-face-to-face". In particular, in terms of consumption activities, face-to-face contact is gradually changing to a system that minimizes, and offline stores are rapidly changing to non-contact services through kiosks and robots. The social structure is also changing with the passage of time, and most fundamentally, our dietary consumption patterns are changing. In particular, the increase in single-person households and the aging population are having a great impact on changes in the food service industry, which is closely related to dietary life. The HMR (Home Meal Replacement) market has grown significantly as the labor of cooking at home has decreased and the use of substitute foods has increased. As the size of the market has grown, the types of businesses that provide products have also diversified. The development of technology, non-face-to-face culture, and corporate management efficiency are intertwined, and unmanned stores are spreading recently. In this study, service quality attributes of HMR unmanned stores, where competition is gradually intensifying, are classified, and service quality classification using the Kano model and Timko's customer satisfaction coefficient are calculated to provide implications for service management based on customer satisfaction. As a result of the analysis, 'products with short cooking time' and 'variety of products (menu)' were classified as attractive qualities, and 'cleanliness inside/outside of the store' and 'products at reasonable prices' were classified as unified quality. In addition, 'convenience of self-checkout process' was classified as a natural quality, and 'convenience of in-store passage' was classified as an indifferent quality. Furthermore, when the service factor was satisfied within the HMR unmanned store, the factor with the highest satisfaction coefficient was 'product (menu) variety', and the factor with the highest dissatisfaction factor was 'convenience of self-checkout process'. Through the results of this study, it is intended to derive priorities in service quality management of HMR unmanned stores and provide strategic implications for related businesses.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.181-198
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• 2023

This study aims to analyze the influence of organizational support perception of workers in medical institutions on intrinsic job motivation, and to check whether there is significance in the mediating effect of work-family conflict and work-family balance factors in this process. The results of empirical analysis through the questionnaire are as follows. First, it was confirmed that organizational support recognition had a significant positive effect on work-family balance as well as intrinsic job motivation, and work-family balance had a significant positive effect on intrinsic job motivation. Second, it was confirmed that organizational support recognition had a significant negative effect on work-family conflict, but work-family conflict had no significant influence on intrinsic job motivation. Third, in order to reduce job stress for medical institution workers, it is necessary to reduce job intensity, assign appropriate workload for ability. And in order to improve manpower operation and job efficiency, Job training and staffing in the right place are needed. Fourth, in order to improve positive organizational support perception and intrinsic job motivation, It is necessary to induce long-term service by providing support and institutional devices to increase attachment to the current job and recognize organizational problems as their own problems with various incentive systems. The limitations of this study and future research directions are as follows. First, it is believed that an expanded analysis of medical institution workers nationwide by region, gender, medical institution, academic, and income will not only provide more valuable results, but also evaluate the quality of medical services. Second, it is necessary to reflect the impact of the work-life balance support system on each employee depending on the environmental uncertainty or degree of competition in the hospital to which medical institution workers belong. Third, organizational support perception will be recognized differently depending on organizational culture and organizational type, and organizational size and work characteristics, working years, and work types, so it is necessary to reflect this. Fourth, it is necessary to analyze various new personnel management techniques such as hospital's organizational structure, job design, organizational support method, motivational approach, and personnel evaluation method in line with the recent change in the government's medical institution policy and the global business environment. It is also considered important to analyze by reflecting recent and near future medical trends.

• Journal of Public Diplomacy
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• v.3 no.2
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• pp.35-52
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• 2023

Korea has developed as an influential country over Asia and all over the world based on remarkable economic development. And the background of this development was possible due to the existence of those who sacrificed precious lives and contributed to the nation's existence in the past crisis. Every year, Korea holds an annual commemorative event with people of national merit, Korean War veterans, and their families, expressing gratitude for sacrifices and contributions at home and abroad, and providing economic support. The tragedy of the Korean War and the pro-democracy movement in Korea over the past half century will one day become a history of the distant past over time. As generations change and the purpose and method of exchange by region change, the tragic situation that occurred earlier and the way people sacrificed for the country are expected to be different from before. In particular, it is true that the number of Korean War veterans and their families is gradually decreasing as they are now old. In addition, due to the outbreak of global infectious diseases such as COVID-19, it is difficult to plan and conduct face to face events as well as before. Currently, Korea's digital technology is introducing various methods. 5G communication networks, smart-phones, tablet PCs, and smart devices that can experience virtual reality are already used in our real lives. Business meetings are held in a metaverse environment, and concerts by famous singers are held in an online environment. Artificial intelligence technology has also been introduced in the field of human resource recruitment and customer response services, improving the work efficiency of companies. And it seems that this technology can be used in the field of veterans. In particular, there is a metaverse technology that can vividly show the situation during the Korean War, and a way to digitalize the voices and facial expressions of currently surviving veterans to convey their memories and lessons to future generations in the long run. If this digital technology method is realized on an online platform to hold a veterans' celebration event, veterans and their families on the other side of the world will be able to participate in the event more conveniently.

• Clean Technology
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• v.29 no.4
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• pp.255-261
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• 2023

Power semiconductors are semiconductors used for power conversion, transformation, distribution, and control. Recently, the global demand for high-voltage power semiconductors is increasing across various industrial fields, and optimization research on high-voltage IGBT components is urgently needed in these industries. For high-voltage IGBT development, setting the resistance value of the wafer and optimizing key unit processes are major variables in the electrical characteristics of the finished chip. Furthermore, the securing process and optimization of the technology to support high breakdown voltage is also important. Etching is a process of transferring the pattern of the mask circuit in the photolithography process to the wafer and removing unnecessary parts at the bottom of the photoresist film. Ion implantation is a process of injecting impurities along with thermal diffusion technology into the wafer substrate during the semiconductor manufacturing process. This process helps achieve a certain conductivity. In this study, dry etching and wet etching were controlled during field ring etching, which is an important process for forming a ring structure that supports the 3.3 kV breakdown voltage of IGBT, in order to analyze four conditions and form a stable body junction depth to secure the breakdown voltage. The field ring ion implantation process was optimized based on the TEG design by dividing it into four conditions. The wet etching 1-step method was advantageous in terms of process and work efficiency, and the ring pattern ion implantation conditions showed a doping concentration of 9.0E13 and an energy of 120 keV. The p-ion implantation conditions were optimized at a doping concentration of 6.5E13 and an energy of 80 keV, and the p+ ion implantation conditions were optimized at a doping concentration of 3.0E15 and an energy of 160 keV.

• Journal of the Korean Institute of Gas
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• v.27 no.3
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• pp.52-58
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• 2023

With the increasing awareness of the importance of carbon neutrality in response to global climate change, the utilization of hydrogen as a carbon-free fuel source is also growing. Hydrogen is commonly used in fuel cells (FC), but it can also be utilized in internal combustion engines (ICE) that are based on combustion. Particularly, ICEs that already have established infrastructure for production and supply can greatly contribute to the expansion of hydrogen energy utilization when it becomes difficult to rely solely on fuel cells or expand their infrastructure. However, a disadvantage of utilizing hydrogen through combustion is the potential generation of nitrogen oxides (NOx), which are harmful emissions formed when nitrogen in the air reacts with oxygen at high temperatures. In particular, for the EURO-7 exhaust regulation, which includes cold start operation, efforts to reduce exhaust emissions during the warm-up process are required. Therefore, in this study, the characteristics of nitrogen oxides and fuel consumption were investigated during the warm-up process of cooling water from room temperature to 88℃ using a 2-liter direct injection spark ignition (SI) engine fueled with hydrogen. One advantage of hydrogen, compared to conventional fuels like gasoline, natural gas, and liquefied petroleum gas (LPG), is its wide flammable range, which allows for sparser control of the excessive air ratio. In this study, the excessive air ratio was varied as 1.6/1.8/2.0 during the warm-up process, and the results were analyzed. The experimental results show that as the excessive air ratio becomes sparser during warm-up, the emission of nitrogen oxides per unit time decreases, and the thermal efficiency relatively increases. However, as the time required to reach the final temperature becomes longer, the cumulative emissions and fuel consumption may worsen.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.17-32
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• 2023

In recent years, the need for social ventures that aim to grow while solving social problems through the efficiency and effectiveness of commercial organizations in the market has increased, while there is a limit to how much the government and the public can do to solve social problems. Against this background, the number of social venture startups is increasing in the domestic startup ecosystem, and interest in impact investors, which are investors in social ventures, is also increasing. Therefore, this research utilized judgment analysis technology to objectively analyze the validity and weight of judgment information based on the cognitive process and decision-making environment in the investment decision-making of impact investors. We proceeded with the research by constructing three classifications; first, investment priorities at the initial investment stage for financial benefit and return on investment as an investor, second, the political skills of the entrepreneurs (teams) for the social impact and ripple power, and social venture coexistence and solidarity, third, the social mission of a social venture that meets the purpose of an impact investment fund. As a result of this research, first of all, the investment decision-making priorities of impact investors are the expertise of the entrepreneur (team), the potential rate of return when the entrepreneur (team) succeeds, and the social mission of the entrepreneur (team). Second, impact investors do not have a uniform understanding of the investment decision-making factors, and the factors that determine investment decisions are different, and there are differences in the degree of the weighting. Third, among the various investment decision-making factors of impact investment, "entrepreneur's (team's) networking ability", "entrepreneur's (team's) social insight", "entrepreneur's (team's) interpersonal influence" was relatively lower than the other four factors. The practical contribution through this research is to help social ventures understand the investment determinant factors of impact investors in the process of financing, and impact investors can be expected to improve the quality of investment decision-making by referring to the judgment cases and analysis of impact investors. The academic contribution is that it empirically investigated the investment priorities and weighting differences of impact investors.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.89-114
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• 2008

Most of the extant studies on communication effects have been devoted to the typical issue, "what types of communication activities are more effective for brand awareness or brand attitudes?" However, little research has addressed another question on communication decisions, "what makes communication activities less effective?" Our study focuses on factors negatively influenced on the efficiency of communication activities, especially of Advertising. Some studies have introduced concepts closely related to our topic such as consumer confusion, brand confusion, or belief confusion. Studies on product belief confusion have found some factors misleading consumers to misunderstand the physical features of products. Studies on brand confusion have uncovered factors making consumers confused on brand names. Studies on advertising confusion have tested the effects of ad models' employed by many other firms for different products on communication efficiency. We address a new concept, Ad noises, which are any factors interfering with consumers exposed to a particular advertisement in understanding messages provided by advertisements. The objective of this study is to understand the effects of ad noises caused by ad models on brand awareness and brand attitude. There are many different types of AD noises. Particularly, we study the effects of AD noises generated from ad model selection decision. Many companies want to employ celebrities as AD models while the number of celebrities who command a high degree of public and media attention are limited. Inevitably, several firms have been adopting the same celebrities as their AD models for different products. If the same AD model is adopted for TV commercials for different products, consumers exposed to those TV commercials are likely to fail to be aware of the target brand due to interference of TV commercials, for other products, employing the same AD model. This is an ad noise caused by employing ad models who have been exposed to consumers in other advertisements, which is the first type of ad noises studied in this research. Another type of AD noises is related to the decision of AD model replacement for the same product advertising. Firms sometimes launch another TV commercial for the same products. Some firms employ the same AD model for the new TV commercial for the same product and other firms employ new AD models for the new TV commercials for the same product. The typical problem with the replacement of AD models is the possibility of interfering with consumers in understanding messages of the TV commercial due to the dissimilarity of the old and new AD models. We studied the effects of these two types of ad noises, which are the typical factors influencing on the effect of communication: (1) ad noises caused by employing ad models who have been exposed to consumers in other advertisements and (2) ad noises caused by changing ad models with different images for same products. First, we measure the negative influence of AD noises on brand awareness and attitudes, in order to provide the importance of studying AD noises. Furthermore, our study unveiled the mediating conditions(variables) which can increase or decrease the effects of ad noises on brand awareness and attitudes. We study the effects of three mediating variables for ad noises caused by employing ad models who have been exposed to consumers in other advertisements: (1) the fit between product image and AD model image, (2) similarity between AD model images in multiple TV commercials employing the same AD model, and (3) similarity between products of which TV commercial employed the same AD model. We analyze the effects of another three mediating variables for ad noises caused by changing ad models with different images for same products: (1) the fit of old and new AD models for the same product, (2) similarity between AD model images in old and new TV commercials for the same product, and (3) concept similarity between old and new TV commercials for the same product. We summarized the empirical results from a field survey as follows. The employment of ad models who have been used in advertisements for other products has negative effects on both brand awareness and attitudes. our empirical study shows that it is possible to reduce the negative effects of ad models used for other products by choosing ad models whose images are relevant to the images of target products for the advertisement, by requiring ad models of images which are different from those of ad models in other advertisements, or by choosing ad models who have been shown in advertisements for other products which are not similar to the target product. The change of ad models for the same product advertisement can positively influence on brand awareness but positively on brand attitudes. Furthermore, the effects of ad model change can be weakened or strengthened depending on the relevancy of new ad models, the similarity of previous and current ad models, and the consistency of the previous and current ad messages.