• Journal of Animal Science and Technology
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• v.52 no.5
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• pp.357-366
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• 2010

The emergence of next-generation sequencing technologies has lead to application of new computational and statistical methodologies that allow incorporating genetic information from entire genomes of many individuals composing the population. For example, using single-nucleotide polymorphisms (SNP) obtained from whole genome amplification platforms such as the Ilummina BovineSNP50 chip, many researchers are actively engaged in the genetic evaluation of cattle livestock using whole genome relationship analyses. In this study, we estimated the genomic relationship matrix (GRM) and compared it with one computed using a pedigree relationship matrix (PRM) using a population of Hanwoo. This project is a preliminary study that will eventually include future work on genomic selection and prediction. Data used in this study were obtained from 187 blood samples consisting of the progeny of 20 young bulls collected after parentage testing from the Hanwoo improvement center, National Agriculture Cooperative Federation as well as 103 blood samples from the progeny of 12 proven bulls collected from farms around the Kyong-buk area in South Korea. The data set was divided into two cases for analysis. In the first case missing genotypes were included. In the second case missing genotypes were excluded. The effect of missing genotypes on the accuracy of genomic relationship estimation was investigated. Estimation of relationships using genomic information was also carried out chromosome by chromosome for whole genomic SNP markers based on the regression method using allele frequencies across loci. The average correlation coefficient and standard deviation between relationships using pedigree information and chromosomal genomic information using data which was verified using a parentage test andeliminated missing genotypes was $0.81{\pm}0.04$ and their correlation coefficient when using whole genomic information was 0.98, which was higher. Variation in relationships between non-inbred half sibs was $0.22{\pm}0.17$ on chromosomal and $0.22{\pm}0.04$ on whole genomic SNP markers. The variations were larger and unusual values were observed when non-parentage test data were included. So, relationship matrix by genomic information can be useful for genetic evaluation of animal breeding.

• Asia pacific journal of information systems
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• v.22 no.2
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• pp.21-38
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• 2012

Until recently, successful implementation of ERP systems has been a popular topic among ERP researchers, who have attempted to identify its various contributing factors. None of these efforts, however, explicitly recognize the need to identify disparities that can exist between organizational information requirements and ERP systems. Since ERP systems are in fact "packages" -that is, software programs developed by independent software vendors for sale to organizations that use them-they are designed to meet the general needs of numerous organizations, rather than the unique needs of a particular organization, as is the case with custom-developed software. By adopting standard packages, organizations can substantially reduce many of the potential implementation risks commonly associated with custom-developed software. However, it is also true that the nature of the package itself could be a risk factor as the features and functions of the ERP systems may not completely comply with a particular organization's informational requirements. In this study, based on the organizational memory mismatch perspective that was derived from organizational memory theory and cognitive dissonance theory, we define the nature of disparities, which we call "mismatches," and propose that the mismatch between organizational information requirements and ERP systems is one of the primary determinants in the successful implementation of ERP systems. Furthermore, we suggest that customization efforts as a coping strategy for mismatches can play a significant role in increasing the possibilities of success. In order to examine the contention we propose in this study, we employed a survey-based field study of ERP project team members, resulting in a total of 77 responses. The results of this study show that, as anticipated from the organizational memory mismatch perspective, the mismatch between organizational information requirements and ERP systems makes a significantly negative impact on the implementation success of ERP systems. This finding confirms our hypothesis that the more mismatch there is, the more difficult successful ERP implementation is, and thus requires more attention to be drawn to mismatch as a major failure source in ERP implementation. This study also found that as a coping strategy on mismatch, the effects of customization are significant. In other words, utilizing the appropriate customization method could lead to the implementation success of ERP systems. This is somewhat interesting because it runs counter to the argument of some literature and ERP vendors that minimized customization (or even the lack thereof) is required for successful ERP implementation. In many ERP projects, there is a tendency among ERP developers to adopt default ERP functions without any customization, adhering to the slogan of "the introduction of best practices." However, this study asserts that we cannot expect successful implementation if we don't attempt to customize ERP systems when mismatches exist. For a more detailed analysis, we identified three types of mismatches-Non-ERP, Non-Procedure, and Hybrid. Among these, only Non-ERP mismatches (a situation in which ERP systems cannot support the existing information needs that are currently fulfilled) were found to have a direct influence on the implementation of ERP systems. Neither Non-Procedure nor Hybrid mismatches were found to have significant impact in the ERP context. These findings provide meaningful insights since they could serve as the basis for discussing how the ERP implementation process should be defined and what activities should be included in the implementation process. They show that ERP developers may not want to include organizational (or business processes) changes in the implementation process, suggesting that doing so could lead to failed implementation. And in fact, this suggestion eventually turned out to be true when we found that the application of process customization led to higher possibilities of failure. From these discussions, we are convinced that Non-ERP is the only type of mismatch we need to focus on during the implementation process, implying that organizational changes must be made before, rather than during, the implementation process. Finally, this study found that among the various customization approaches, bolt-on development methods in particular seemed to have significantly positive effects. Interestingly again, this finding is not in the same line of thought as that of the vendors in the ERP industry. The vendors' recommendations are to apply as many best practices as possible, thereby resulting in the minimization of customization and utilization of bolt-on development methods. They particularly advise against changing the source code and rather recommend employing, when necessary, the method of programming additional software code using the computer language of the vendor. As previously stated, however, our study found active customization, especially bolt-on development methods, to have positive effects on ERP, and found source code changes in particular to have the most significant effects. Moreover, our study found programming additional software to be ineffective, suggesting there is much difference between ERP developers and vendors in viewpoints and strategies toward ERP customization. In summary, mismatches are inherent in the ERP implementation context and play an important role in determining its success. Considering the significance of mismatches, this study proposes a new model for successful ERP implementation, developed from the organizational memory mismatch perspective, and provides many insights by empirically confirming the model's usefulness.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.109-127
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• 2014

This study is devised out of the recognition that the existing standardization-related research has not sufficiently examined the overall social environment where a standard is actually made and diffused and the roles of the actors and the changes in them in the complex social system where multiple stakeholders exist. Against this backdrop, this study purports to reconstruct the dynamic process of developing and standardizing an innovative technology through a socio-technical approach involved by multiple stakeholders with different interests in the context of a socio-technical institutional environment. The specific goals to achieve the purpose include first, inspecting the characteristics of the interactions between the human actors and between the human and non-human actors in the socio-technical network surrounding a standardization process. Second, the study aimed to observe the activities of the focal actor who led the standardization process and its changing role. To that end, it analyzed the dynamic features of the process of standardizing a HD 3DTV broadcasting technology that took place in South Korea based on the actor network theory. As for the analysis method, the researchers personally took part in the actor network involving the new technology to analyze the dynamic characteristics of the network, applying the qualitative research method of survey and in-depth interviews and exploring the overall dynamics of environment, behavior and technology observed over the course of the entire standardization process.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.285-301
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• 2023

Due to the increasing demand and importance of non-face-to-face education, open online learning platforms are getting interests both domestically and internationally. These platforms exhibit different characteristics from online courses by universities and other educational institutions. In particular, students engaged in these platforms can receive more learner autonomy, and the development of tools to assist learning is required. From the past, researchers have attempted to utilize process mining to understand realistic study behaviors and derive learning patterns. However, it has a deficiency to employ it to the open online learning platforms. Moreover, existing research has primarily focused on the process model perspective, including process model discovery, but lacks a method for the process pattern and instance perspectives. In this study, we propose a method to identify learning patterns within an open online learning platform using process mining techniques. To achieve this, we suggest three different viewpoints, e.g., model-level, variant-level, and instance-level, to comprehend the learning patterns, and various techniques are employed, such as process discovery, conformance checking, autoencoder-based clustering, and predictive approaches. To validate this method, we collected a learning log of machine learning-related courses on a domestic open education platform. The results unveiled a spaghetti-like process model that can be differentiated into a standard learning pattern and three abnormal patterns. Furthermore, as a result of deriving a pattern classification model, our model achieved a high accuracy of 0.86 when predicting the pattern of instances based on the initial 30% of the entire flow. This study contributes to systematically analyze learners' patterns using process mining.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• The Korean Journal of Nuclear Medicine
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• v.36 no.6
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• pp.317-324
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• 2002

Purpose: The use of statistical parametric mapping (SPM) program has increased for the analysis of brain PET and SPECT images. Montreal Neurological Institute (MNI) coordinate is used in SPM program as a standard anatomical framework. While the most researchers look up Talairach atlas to report the localization of the activations detected in SPM program, there is significant disparity between MNI templates and Talairach atlas. That disparity between Talairach and MNI coordinates makes the interpretation of SPM result time consuming, subjective and inaccurate. The purpose of this study was to develop a program to provide objective anatomical information of each x-y-z position in ICBM coordinate. Materials and Methods: Program was designed to provide the anatomical information for the given x-y-z position in MNI coordinate based on the Statistical Probabilistic Anatomical Map (SPAM) images of ICBM. When x-y-z position was given to the program, names of the anatomical structures with non-zero probability and the probabilities that the given position belongs to the structures were tabulated. The program was coded using IDL and JAVA language for 4he easy transplantation to any operating system or platform. Utility of this program was shown by comparing the results of this program to those of SPM program. Preliminary validation study was peformed by applying this program to the analysis of PET brain activation study of human memory in which the anatomical information on the activated areas are previously known. Results: Real time retrieval of probabilistic information with 1 mm spatial resolution was archived using the programs. Validation study showed the relevance of this program: probability that the activated area for memory belonged to hippocampal formation was more than 80%. Conclusion: These programs will be useful for the result interpretation of the image analysis peformed on MNI coordinate, as done in SPM program.

• Korean Journal of Labor Studies
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• v.24 no.2
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• pp.95-136
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• 2018

As the number of precariats grows, their poor labor rights and working conditions are becoming issues of major concern all over the world but how to represent their interests is still controversial. Basically, the union is the institutional mechanism for representing the labor rights. However, it is difficult for workplaceand enterprise-based unions to fully represent the labor rights of precarious workers. Recently, so-called community unions have emerged in the United States, the United Kingdom, and Japan as independent organizations representing the rights of non-standard workers. Community unions refer to labor unions which organize precarious workers across firms at the regional level. They are known to be suitable for covering the unemployed, job seekers, indirect employment workers, short-term contract workers, and small-firm workers. In South Korea, since the financial crisis in 1997, a dramatic increase in the number of precariats leads to emergence of new types of trade unions such as the Youth Community Union, the Arbeit Workers' Union, the Artist Social Union and the Korea Musician's Union. They have engaged in various activities to guarantee the labor rights of precariats. Recently, researchers have also tried to identify defining characteristics of these new forms of unionism. To expand research on trade unionism in South Korea, this study compares two different types of community unions: the Youth Community Union and the Arbeit Workers' Union. We believe that this attempt can contribute to the research on the alternative labor movement. For this purpose, this study starts with theoretical discussions on community unions, and compares the Youth Community Union with the Arbeit Workers' Union based on the five characteristics of community unionism: membership and organization structure, the recognition struggle, the type or scope of interest, solidarity with other civic organizations, and the repertoire of resistance strategies. Based on this comparative analysis, this study seeks to foresee the possibility of how community unionism will develop in South Korean in the future.

• Korean Journal of Weed Science
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• v.13 no.4
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• pp.210-233
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• 1993

The herbicide has become indispensable as much as nitrogen fertilizer in Korean agriculture from 1970 onwards. It is estimated that in 1991 more than 40 herbicides were registered for rice crop and treated to an area 1.41 times the rice acreage ; more than 30 herbicides were registered for field crops and treated to 89% of the crop area ; the treatment acreage of 3 non-selective foliar-applied herbicides reached 2,555 thousand hectares. During the last 25 years herbicides have benefited the Korean farmers substantially in labor, cost and time of farming. Any herbicide which causes crop injury in ordinary uses is not allowed to register in most country. Herbicides, however, can cause crop injury more or less when they are misused, abused or used under adverse environments. The herbicide use more than 100% of crop acreage means an increased probability of which herbicides are used wrong or under adverse situation. This is true as evidenced by that about 25% of farmers have experienced the herbicide caused crop injury more than once during last 10 years on authors' nationwide surveys in 1992 and 1993 ; one-half of the injury incidences were with crop yield loss greater than 10%. Crop injury caused by herbicide had not occurred to a serious extent in the 1960s when the herbicides fewer than 5 were used by farmers to the field less than 12% of total acreage. Farmers ascribed about 53% of the herbicidal injury incidences at their fields to their misuses such as overdose, careless or improper application, off-time application or wrong choice of the herbicide, etc. While 47% of the incidences were mainly due to adverse natural conditions. Such misuses can be reduced to a minimum through enhanced education/extension services for right uses and, although undesirable, increased farmers' experiences of phytotoxicity. The most difficult primary problem arises from lack of countermeasures for farmers to cope with various adverse environmental conditions. At present almost all the herbicides have"Do not use!" instructions on label to avoid crop injury under adverse environments. These "Do not use!" situations Include sandy, highly percolating, or infertile soils, cool water gushing paddy, poorly draining paddy, terraced paddy, too wet or dry soils, days of abnormally cool or high air temperature, etc. Meanwhile, the cultivated lands are under poor conditions : the average organic matter content ranges 2.5 to 2.8% in paddy soil and 2.0 to 2.6% in upland soil ; the canon exchange capacity ranges 8 to 12 m.e. ; approximately 43% of paddy and 56% of upland are of sandy to sandy gravel soil ; only 42% of paddy and 16% of upland fields are on flat land. The present situation would mean that about 40 to 50% of soil applied herbicides are used on the field where the label instructs "Do not use!". Yet no positive effort has been made for 25 years long by government or companies to develop countermeasures. It is a really sophisticated social problem. In the 1960s and 1970s a subside program to incoporate hillside red clayish soil into sandy paddy as well as campaign for increased application of compost to the field had been operating. Yet majority of the sandy soils remains sandy and the program and campaign had been stopped. With regard to this sandy soil problem the authors have developed a method of "split application of a herbicide onto sandy soil field". A model case study has been carried out with success and is introduced with key procedure in this paper. Climate is variable in its nature. Among the climatic components sudden fall or rise in temperature is hardly avoidable for a crop plant. Our spring air temperature fluctuates so much ; for example, the daily mean air temperature of Inchon city varied from 6.31 to $16.81^{\circ}C$ on April 20, early seeding time of crops, within${\times}$2Sd range of 30 year records. Seeding early in season means an increased liability to phytotoxicity, and this will be more evident in direct water-seeding of rice. About 20% of farmers depend on the cold underground-water pumped for rice irrigation. If the well is deep over 70m, the fresh water may be about $10^{\circ}C$ cold. The water should be warmed to about $20^{\circ}C$ before irrigation. This is not so practiced well by farmers. In addition to the forementioned adverse conditions there exist many other aspects to be amended. Among them the worst for liquid spray type herbicides is almost total lacking in proper knowledge of nozzle types and concern with even spray by the administrative, rural extension officers, company and farmers. Even not available in the market are the nozzles and sprayers appropriate for herbicides spray. Most people perceive all the pesticide sprayers same and concern much with the speed and easiness of spray, not with correct spray. There exist many points to be improved to minimize herbicidal phytotoxicity in Korea and many ways to achieve the goal. First of all it is suggested that 1) the present evaluation of a new herbicide at standard and double doses in registration trials is to be an evaluation for standard, double and triple doses to exploit the response slope in making decision for approval and recommendation of different dose for different situation on label, 2) the government is to recognize the facts and nature of the present problem to correct the present misperceptions and to develop an appropriate national program for improvement of soil conditions, spray equipment, extention manpower and services, 3) the researchers are to enhance researches on the countermeasures and 4) the herbicide makers/dealers are to correct their misperceptions and policy for sales, to develop database on the detailed use conditions of consumer one by one and to serve the consumers with direct counsel based on the database.