• Journal of agriculture & life science
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• v.46 no.5
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• pp.73-82
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• 2012

Allele information from the analysis of the 13 microsatellite (MS) markers, were classified into the $F_0$, $F_1$ and $F_2$ generations, and probabilities of the same individual emergency in each generation was calculated. As a result, the 13 MS markers showed an estimate of $3.84{\times}10^{-23}$ on the premise of the randomly mated group of $F_2$, which implies that the same individuals may emerge by the use of 37 kinds of SNP markers. In this study, the experimental pigs were intercross between only 2 breeds (Korean native pig and Landrace). In addition, the success rate of paternity tests was analyzed on the whole group, by the use of the 13 MS markers and 37 SNP markers. As regards the exclusionary power of the second parent ($PE_{pu}$), MS markers and SNP markers showed 0.97897 and 0.99149, respectively. In relation to the parent exclusion power of both parent (PE), MS markers and SNP markers showed 0.99916 and 0.99949, respectively. In the case of the estimate to identify parental candidates that had the highest probability ($PNE_{pp}$), the two showed 1.00000 all. The Korean pig industry tends to mass produce hogs with limited numbers of alleles in limited parents. Such being the case, there is a need to organize a marker, for which it is imperative to find markers with high efficiency and high economic feasibility of the characteristics of DNA markers, sample size, the accuracy and expenses of genotyping cost, the manageability of data and the compatibility among analysis systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.6
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• pp.719-730
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• 2017

Recently, oceanic research has been carried out investigating global scientific interests and the territorial management of national marine jurisdictional waters, including exclusive economic zones (EEZ) and the open seas. To meet the needs of ocean researchers pursuing these - objectives, acquiring advanced research infrastructure, including research vessels, large facilities, and equipment, is a top priority in ocean science. However, ocean science is a similar to space science, and securing resources and state-of-the-art technology can be expensive. Faced with these challenges, our study focused on establishing a strategy for the efficient operation and management of research vessels, attempting to establish benchmarks from foreign examples that can be adapted to suit the target context. The results of this study provide ways to identify operating systems that could increase the efficiency of joint-use research vessels. The different systems examined in this study included a joint-use committee-based management system (JCMS, Type 1), private enterprise entrusted operating system (PEOS, Type 2), institutional investment operating system (IIOS, Type 3), and commissioned executive operating system (CEOS, Type 4). The efficiencies of JCMS, PEOS, IIOS and CEOS were 9.17, 5.82, 11.2 and -1.72 %, respectively. Given the total costs involved, the most affordable operating system was IIOS. JCMS was the most cost-effective system based on a quantitative cost-benefit analysis, but IIOS also had an acceptable cost-benefit balance. An operational committee would be required and regulations and guidelines shoulde be established to employ, JCMS, while a strategy to yield independent revenue would be needed to utilize an IIOS system.

• Journal of Korean Society of Forest Science
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• v.108 no.3
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• pp.429-439
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• 2019

The objectives of this study were to gauge the extent of the forestry business through establishing the definition of forestry industry from the perspective of economic convergence and to analyze key components that affect each growth phase of a forestry business entity by classifying them. A total of 1,397 "sixth-sector industry" management entities were certified by the Ministry of Agriculture, Food, and Rural Affairs in South Korea from 2012-2017. Of these, 259 (18.5%) were in the forestry sector. In this study, the 259 forestry management entities were further classified into three phases based on sales distribution: entrance, development, and maturity. The entrance phase (<100 million KRW), development phase (>100 million and <1 billion KRW), and maturity phase (>1 billion KRW) constituted 33.2%, 55.4%, and 12.4% of the total 259 entities, respectively. The results showed that most of the management entities were either in the entrance or development phases, and only a small portion was in the maturity phase. To identify the key variables that affect each of the phases, chi-square analysis was used. We designed the "sixth-sector industry" type as an independent variable, whereas selected region, business organization, manager age group, forest product, processing type, and service type were designated as dependent variables. The results of the analysis showed that the processing and service types influenced all three developmental phases. Moreover, as the phase advanced, processing type showed a higher proportion of health-functional ingredients, such as powder or extract from forest products, which enable to develop and produce a variety of products. Service type also changed from simple experience to integrated experience tourism and finally to tourism education. Distribution and sales channel also turned out to be a significant factor during the development phase. This study provides the basic information needed to guide government support in the implementation of a formal forestry business through convergence as well as to increase the efficiency of business management.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.6
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• pp.1-15
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• 2020

The purpose of this study is to propose a direction for designing and managing a smart park for realizing a smart green city and to present measures in the landscape field to foster related industries. The research process is as follows. First, the concept of a smart park was operationally defined through a literature review, and three principles to be considered in the process of creation and management were established. Second, in terms of the three principles, problems and implications for improvement were derived through an analysis of established cases of smart parks in new and pre-existing cities. Third, a pool of designs and management standards for each spatial component of a smart park was prepared through literature and case studies, and then further refined through brainstorming with experts in related fields. Fourth, measures were suggested to the government, local governments, and the landscape field to promote smart park creation and management. The main findings are as follows. First, the concept of a smart park is defined as "a park that contributes to securing the social, economic, and environmental sustainability of cities and local communities by supporting citizens' safe and pleasant use of parks and improving the management and operational efficiency by utilizing the digital, environment, and material technologies." Second, the three principles of smart parks are to improve the intrinsic value of parks, to improve the innovative functions of parks to solve urban problems, and to make the design, construction, and management process smart. Third, improvement implications were derived through the analysis of cases of smart parks creation in new and pre-existing cities. Fourth, the directions for smart park design and management were suggested in five aspects: green area, hydroponic facility area, road and plaza area, landscape facilities area, and park design method. Fifth, as for policy implications for revitalizing the construction and management of smart parks, the development of smart park policy business models by city growth stage, and park type, the promotion of pilot projects, the promotion of smart park projects in connection with the Korean New Deal policy, and smart park policies led by landscape experts were presented.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.468-475
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• 2022

This study was conducted to find out the efficiency of heating initiative temperature and carbon dioxide fertilization in summer squash (Cucurbita moschata D.). The heating start temperature experiment was performed at 9℃, 12℃, and 15℃ using an electric heater and operated when the temperature was lower than the target temperature. The CO₂ fertilization concentration experiment was performed from 7 to 12 with the control, 500 µmol·mol^-1, and 800 µmol·mol^-1 using liquefied carbon dioxide. Investigation items were plant height, stem diameter, number of leaves, leaf area, fresh weight, dry weight, also economic analysis was conducted by surveying only fruits exceeding 100 g. Photosynthesis was measured for the upper leaf position to calculate the saturation point according to the control. The photo saturation point was 587 µmol·m^-2·s^-1, and the CO₂ saturation point was 702 µmol·mol^-1. A_max values by carbon dioxide were 13.4, 17.8, 17.2, 19.6, and 17.5 µmolCO₂·m^-2·s^-1 in the order of 9℃, 12℃, 15℃, 500 µmol·mol^-1, and 800 µmol·mol^-1. In the temperature experiment, 9℃ in growth did not grow normally and no fruiting was performed. 12℃ and 15℃ were higher than 9℃, but there was no significant difference in growth and production. The CO₂ fertilization experiment showed no significant difference between the treatment in growth, but the productivity of 800 µmol·mol^-1 was the best. Comprehensively, the heating initiative temperature of 15℃ was good for crop growth and production, but there is no significant difference from 12℃, so it is good to set the heating start temperature to 12℃ economically, and maintaining of 800 µmol·mol^-1 is effective in increasing production.

• Korea Science and Art Forum
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• v.36
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• pp.391-400
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• 2018

To ensure a user-centered treatment environment, hospital construction needs an approach that is not centered on functional aspects such as efficiency or economic feasibility but on the consideration of needs as reflected in user psychology and behavior. Patients who are physically and psychologically vulnerable experience psychological pressure when they are placed in an unfamiliar environment. Most of existing studies however focus on the evaluation of the physical environment, without paying attention to the psychological or behavioral approach to anxiety and stress that patients may experience in a special environment that a hospital may be to them. This study examines general hospital inpatients to understand the usage of major space available and their satisfaction with privacy. This study provides useful primary information needed for the user-centered design of general hospital for improved patient health and welfare. For the purpose of the study, literature review, site investigation, and survey were conducted. Major functional space and privacy in general hospitals were studied, and the site investigation was performed to identify the plans and their status. Survey was also performed to understand the usage of functional space and satisfaction with such space usage as well as satisfaction with privacy. The findings were as follows: (1) Space usage was rated as average in general. It was found that patients used their rooms and lobby on a daily basis. By age, the usage was highest in the group in their 40s; the usage was relatively lower in the groups in their 30s or younger. (2) Space satisfaction was above average, indicating that patients were fairly satisfied. Satisfaction was highest in the lobby space designed with distinct features. By case, satisfaction was highest in Case B, characterized by its wide horizontal space in the rural settings. (3) Satisfaction with privacy in hospital was average, indicating that the demand for privacy was relatively higher but what patients receive in return was lower than their expectation. It was also found that satisfaction with privacy was a crucial element that affected the overall satisfaction with hospital.

• Korea Science and Art Forum
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• v.25
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• pp.103-118
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• 2016

Due to the rapid development of ICT, corporate business models quickly changed and because of the radical growth of IT technology, sequential or gradual survival has become difficult. Internet-based new businesses such as IT service companies are seeking for new convergence business models that have not existed before to create business models that are more competitive, but the economic efficiency of business models that were successful in the past is wearing off. Yet, as reaching the critical point where the platform value becomes extremely high for platforms via the Internet is happening at a much higher speed than before, platform-ization has become a very important condition for rapid business expansion for all kinds of businesses. This study analyzes the necessity of establishing platform business models in IT service planning and identifies their characteristics through case analyses of platform business models. The results derived features First, there is a need to ensure sufficient buyers and sellers, and second, platform business model should provide customers with distinctive value of the only platforms are generating. third, the common interests between platform-driven company and a partner, participants Should be existing. Fourthly, by expanding base of participants and upgrades, expansion of adjacent areas we must have a continuous scalability and evolution must be sustainable. While it is expected that the identified characteristics will cause tremendous impacts to the establishment of platform business models and to the graphing of service planning, we also look forward to this study serving as the starting point for the establishment of theories of profit models for platform businesses, which were not mentioned in the study, so that planners responsible for platform-based IT service planning will spend less time and draw bigger schemes in building planning drafts.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.35 no.6
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• pp.109-120
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• 2023

The High-Frequency Radar (HFR) is an equipment designed to measure real-time surface ocean currents in broad maritime areas.It emits radio waves at a specific frequency (HF) towards the sea surface and analyzes the backscattered waves to measure surface current vectors (Crombie, 1955; Barrick, 1972).The Seasonde HF Radar from Codar, utilized in this study, determines the speed and location of radial currents by analyzing the Bragg peak intensity of transmitted and received waves from an omnidirectional antenna and employing the Multiple Signal Classification (MUSIC) algorithm. The generated currents are initially considered ideal patterns without taking into account the characteristics of the observed electromagnetic wave propagation environment. To correct this, Antenna Pattern Measurement (APM) is performed, measuring the strength of signals at various positions received by the antenna and calculating the corrected measured vector to radial currents.The APM principle involves modifying the position and phase information of the currents based on the measured signal strength at each location. Typically, experiments are conducted by installing an antenna on a ship (Kim et al., 2022). However, using a ship introduces various environmental constraints, such as weather conditions and maritime situations. To reduce dependence on maritime conditions and enhance economic efficiency, this study explores the possibility of using unmanned aerial vehicles (drones) for APM. The research conducted APM experiments using a high-frequency radar installed at Dangsa Lighthouse in Dangsa-ri, Wando County, Jeollanam-do. The study compared and analyzed the results of APM experiments using ships and drones, utilizing the calculated radial currents and surface current fields obtained from each experiment.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.3
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• pp.105-118
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• 2023

Purpose: This study aimed to gain better understanding of the importance of dental prosthesis order platform services and to identify the essential elements for their enhancement and wider adoption among dental professionals. Materials and Methods: A survey was conducted to assess the perspectives of dentists, dental technicians, dental hygienists, and dental industry professionals toward dental prosthesis ordering and associated platform services (a total of 53 respondents). The questionnaire was devised after an expert review and assessed for reliability using Cronbach's alpha coefficient. Factor analysis revealed that 57 factors across five categories accounted for 88.417% of the total variance. The survey was administered through an online questionnaire platform, and data analysis was conducted using a statistical software, employing one-way analysis of variance and Tukey's honestly significant difference test (α = 0.05). Results: The essential elements identified were accurate information input, effective communication, delivery of distortion-free impressions, convenience in data transmission and storage, development of stable and affordable platform services (P < 0.05). Furthermore, significant differences were observed in the importance of these items based on age, dental profession, and career experience (P < 0.05). Conclusion: The dental prosthesis ordering platform services, the requirements of dental personnel were stability, economic efficiency, and ease of transmitting and storing prosthesis data. The findings can serve as important indicators for the development and improvement of dental prosthesis order platform services.