• Journal of Animal Science and Technology
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• v.53 no.1
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• pp.29-34
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• 2011

Using the materials collected from nine farms in a three-way cross system to produce commercial pigs produced from F1 sows (Landrace $\times$ Large White) $\times$ Duroc, the power of individual discrimination and parentage of the 13 microsatellite (MS) marker set that has been suggested for individual/brand identification (traceability) was empirically tested. Initially, genotypes of the parental population ($F_1$ sows and Duroc), and commercial pigs were determined and the genotype frequency and polymorphic index were estimated using the Cervus 2.0 program. The probability of identity among genotypes of random individuals, that random half sibs and that of full sib individuals, based on the genotypes from 91 $F_1$ sows and Duroc were expected to be $4.94{\times}10^{-34}$, $8.16{\times}10^{-23}$ and $2.01{\times}10^{-08}$, respectively, using the API-CALC version 1.0 program. When commercial pigs were included, the estimates increased to $3.74{\times}10^{-35}$, $5.48{\times}10^{-25}$ and $2.96{\times}10^{-11}$, respectively. For the empirical verification of the estimated powers of individual discrimination and parentage, the parentage test was performed for 452 commercial pigs using PAPA version 2.0, and individuals with the same genotype were investigated using the Cervus version 2.0 program. Parents for all commercial pigs were successfully estimated and no identical individual was identified in the pedigree. Although the individual discriminating power was not fully verified because of the lack of individuals corresponding with the theoretical power, the 100% efficiency of parentage test was clearly confirmed. Therefore, we believe that the 13 MS marker set in conjunction with management record/information for the pig production kept in a farm/brand should be useful in the pork traceability in a brand unit.

• International Journal of Highway Engineering
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• v.11 no.4
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• pp.69-78
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• 2009

Korea has achieved significant economic growth with building the Gyeongbu Expressway. As the number of new road construction projects has decreased, it becomes more important to maintain optimal status of the current road networks. One of the best ways to accomplish it is weight enforcement as active control measure of traffic load. This study is to develop High-speed Weigh-in-motion System in order to enhance efficiency of weight enforcement, and to analyze patterns of overloaded trucks on highways through the system. Furthermore, it is to review possibilities of developing overweight control system with application of the HS-WIM system. The HS-WIM system developed by this study consists of two sets of an axle load sensor, a loop sensor and a wandering sensor on each lane. A wandering sensor detects whether a travelling vehicle is off the lane or not with the function of checking the location of tire imprint. The sensor of the WIM system has better function of classifying types of vehicles than other existing systems by detecting wheel distance and tire type such as single or dual tire. As a result, its measurement errors regarding 12 types of vehicle classification are very low, which is an advantage of the sensor. The verification tests of the system under all conditions showed that the mean measurement errors of axle weight and gross axle weight were within 15 percent and 7 percent respectively. According to the WIM rate standard of the COST-323, the WIM system of this study is ranked at B(10). It means the system is appropriate for the purpose of design, maintenance and valuation of road infrastructure. The WIM system in testing a 5-axle cargo truck, the most frequently overloaded vehicle among 12 types of vehicles, is ranked at A(5) which means the system is available to control overloaded vehicles. In this case, the measurement errors of axle load and gross axle load were within 8 percent and 5 percent respectively. Weight analysis of all types of vehicles on highways showed that the most frequently overloaded vehicles were type 5, 6, 7 and 12 among 12 vehicle types. As a result, it is necessary to use more effective overweight enforcement system for vehicles which are seriously overloaded due to their lift axles. Traffic volume data depending upon vehicle types is basic information for road design and construction, maintenance, analysis of traffic flow, road policies as well as research.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.64-73
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• 2001

Generally potassium in the soil can be remained as water soluble, exchangeable, and available types, respectively. Theses types of potassiums are also known to keep their kinetic relationships to each other. The Purpose on this research was to investigate types and relationships of potassium in the soil, and the characteristics of potassium supply in different forest soils. The results could be summarized as follows; 1. The amounts of available potassium in A and B horizon soils by continuous leaching with 0.01N-HCl were as follows : for A Horizon soils, pohang(Gray brown forest soils), Changsung (Brown forest soils), and Youngwol(Dark red forest soils) were ranged from 0.2me/l00g to 0.8me/100g, Taean(Red and Yellow forest soils) was 0.1-0.6me/100g, Kapyung(Brown forest soils) was 0.2-0.4me/100g. For the B layer, Youngwol was 0.1-0.5me/100g, Pohang, Taean, Kapyung were 0.1-0.4me/100g, Changsung was 0.1-0.3me/100g, respectivly. 2. Of ten times-pulse leaching with 0.01N-HCl for A layer soil, more 80% of total available potassium leaching were recovered by the second pulse as leachate for Pohang, Changsung, Youngwol, while similar amounts of potassium in the leachate were obtained with the third pulse leaching for Kapyung, Taean, respectively, On the other hand, the 80 % release of available potassium from the B layer soil was obtained by the second pulse leaching for all areas investigated. 3. For the relationships between soluble potassium and exchangeable potassium, the exchangeable potassium was increased while the soluble potassium was not changed significantly in B layer. And both soluble potassium and exchangeable potassium in A layer were similar. For the relationship between exchangeable potassium and available potassium in both A and B layers, the amounts of available potassium increased by 1.2 to 1.5 times as the exchangeable potassium increased. 4. For distribution of all types of potassium throughout locations investigated, the types of potassium were in the decreasing orders of available, exchangeable, and soluble. 5. The simplified method for an analysis of all types of potassium by sequential leaching with 0.01N-HCl should be developed not only with respect to time-saving and efficiency but also verification of the relationship between available potassium and tree growth.

• Journal of the Korean GEO-environmental Society
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• v.20 no.2
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• pp.41-48
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• 2019

Soil compaction is one of the most important activities in the area of civil works, including road construction, airport construction, port construction and backfilling construction of structures. Soil compaction, particularly in road construction, can be categorized into subgrade compaction and roadbed compaction, and is significant work that when done poorly can serve as a factor causing poor construction due to a lack of compaction. Currently, there are many different types of compaction tests, and the plate bearing test and the unit weight of soil test based on the sand cone method are commonly used to measure the degree of compaction, but many other methods are under development as it is difficult to secure economic efficiency. For the purpose of this research, a portable penetration meter called the Free-Fall Penetration Test (FFPT) was developed and manufactured. In this study, a homogeneous sample was obtained from the construction site and soil was classified through a sieve analysis test in order to perform grain size analysis and a specific gravity test for an indoor test. The principle of FFPT is that the penetration needle installed at the tip of an object put into free fall using gravity is used to measure the depth of penetration into the road surface after subgrade or roadbed compaction has been completed; the degree of compaction is obtained through the unit weight of soil test according to the sand cone method and the relationship between the degree of compaction and the depth of the penetration needle is verified. The maximum allowable grain size of soil is 2.36 mm. For $A_1$ compaction, a trend line was developed using the result of the test performed from a drop height of 10 cm, and coefficient of determination of the trend line was $R^2=0.8677$, while for $D_2$ compaction, coefficient of determination of the trend line was $R^2=0.9815$ when testing at a drop height of 20 cm. Free fall test was carried out with the drop height adjusted from 10 cm to 50 cm at increments of 10 cm. This study intends to compare and analyze the correlation between the degree of compaction obtained from the unit weight of soil test based on the sand cone method and the depth of penetration of the penetration needle obtained from the FFPT meter. As such, it is expected that a portable penetration tester will make it easy to test the degree of compaction at many construction sites, and will lead to a reduction in time, equipment, and manpower which are the disadvantages of the current degree of compaction test, ultimately contributing to accurate and simple measurements of the degree of compaction as well as greater economic feasibility.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.249-267
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• 2021

The use of big data accumulated along with the progress of digitalization is bringing disruptive innovation to the global agricultural industry. Recently, the government is establishing an agricultural big data platform and a support organization. However, in the domestic agricultural industry, the use of big data is insufficient except for some companies in the field of cultivation and growth. In this context, this study identifies factors affecting the intention to use big data in terms of technology, organization and environment, and also confirm the moderating effect of technical field, focusing on agricultural ventures which should be the main entities in creating innovation by using big data. Research data was obtained from 309 agricultural ventures supported by the A+ Center of FACT(Foundation of AgTech Commercialization and Transfer), and was analyzed using IBM SPSS 22.0. As a result, Among technical factors, relative advantage and compatibility were found to have a significant positive (+) effect. Among organizational factors, it was found that management support had a positive (+) effect and cost had a negative (-) effect. Among environmental factors, policy support were found to have a positive (+) effect. As a result of the verification of the moderating effect of technology field, it was found that firms other than cultivation had a moderating effect that alleviated the relationship between all variables other than relative advantage, compatibility, and competitor pressure and the intention to use big data. These results suggest the following implications. First, it is necessary to select a core business that will provide opportunities to generate new profits and improve operational efficiency to agricultural ventures through the use of big data, and to increase collaboration opportunities through policy. Second, it is necessary to provide a big data analysis solution that can overcome the difficulties of analysis due to the characteristics of the agricultural industry. Third, in small organizations such as agricultural ventures, the will of the top management to reorganize the organizational culture should be preceded by a high level of understanding on the use of big data. Fourth, it is important to discover and promote successful cases that can be benchmarked at the level of SMEs and venture companies. Fifth, it will be more effective to divide the priorities of core business and support business by agricultural venture technology sector. Finally, the limitations of this study and follow-up research tasks are presented.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.143-174
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• 2023

With the development of deep learning technologies, Artificial Intelligence powered Optical Character Recognition (AI-OCR) has evolved to read multiple languages from various forms of images accurately. For the financial industry, where a large number of diverse documents are processed through manpower, the potential for using AI-OCR is great. In this study, we present a configuration and a design of an AI-OCR modality for use in the financial industry and discuss the platform construction with application cases. Since the use of financial domain data is prohibited under the Personal Information Protection Act, we developed a deep learning-based data generation approach and used it to train the AI-OCR models. The AI-OCR models are trained for image preprocessing, text recognition, and language processing and are configured as a microservice architected platform to process a broad variety of documents. We have demonstrated the AI-OCR platform by applying it to financial domain tasks of document sorting, document verification, and typing assistance The demonstrations confirm the increasing work efficiency and conveniences.

• 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 Wetlands Research
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• v.26 no.1
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• pp.41-50
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• 2024

Plant Microbial Fuel Cells (P-MFCs) are biomass-based energy technologies that generate electricity from plant and root microbial communities and are suitable for natural fundamental solutions considering sustainable environments. In order to develop P-MFC technology suitable for domestic waterfront space, it is necessary to analyze international research trends first. Therefore, in this study, 700 P-MFC-related research papers were investigated in Web of Science, and the core keywords were derived using VOSviewer, a word analysis program, and the research trends were analyzed. First, P-MFC-related research has been on the rise since 1998, especially since the mid to late 2010s. The number of papers submitted by each country was "China," "U.S." and "India." Since the 2010s, interest in P-MFCs has increased, and the number of publications in the Philippines, Ukraine, and Mexico, which have abundant waterfront space and wetland environments, is increasing. Secondly, from the perspective of research trends in different periods, 1998-2015 mainly carried out microbial fuel cell performance verification research in different environments. The 2016-2020 period focuses on the specific conditions of microbial fuel cell use, the structure of P-MFC and how it develops. From 2021 to 2023, specific research on constraints and efficiency improvement in the development of P-MFC was carried out. The P-MFC-related international research trends identified through this study can be used as useful data for developing technologies suitable for domestic waterfront space in the future. In addition to this study, further research is needed on research trends and levels in subsectors, and in order to develop and revitalize P-MFC technologies in Korea, research on field applicability should be expanded and policies and systems improved.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.