• The Korean Journal of Nuclear Medicine
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• 제38권3호
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• pp.233-240
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• 2004

Purpose: We developed a computer-aided classifier using artificial neural network (ANN) to discriminate the cerebral metabolic pattern of medial and lateral temporal lobe epilepsy (TLE). Materials and Methods: We studied brain F-18-FDG PET images of 113 epilepsy patients sugically and pathologically proven as medial TLE (left 41, right 42) or lateral TLE (left 14, right 16). PET images were spatially transformed onto a standard template and normalized to the mean counts of cortical regions. Asymmetry indices for predefined 17 mirrored regions to hemispheric midline and those for medial and lateral temporal lobes were used as input features for ANN. ANN classifier was composed of 3 independent multi-layered perceptrons (1 for left/right lateralization and 2 for medial/lateral discrimination) and trained to interpret metabolic patterns and produce one of 4 diagnoses (L/R medial TLE or L/R lateral TLE). Randomly selected 8 images from each group were used to train the ANN classifier and remaining 51 images were used as test sets. The accuracy of the diagnosis with ANN was estimated by averaging the agreement rates of independent 50 trials and compared to that of nuclear medicine experts. Results: The accuracy in lateralization was 89% by the human experts and 90% by the ANN classifier Overall accuracy in localization of epileptogenic zones by the ANN classifier was 69%, which was comparable to that by the human experts (72%). Conclusion: We conclude that ANN classifier performed as well as human experts and could be potentially useful supporting tool for the differential diagnosis of TLE.

• Management & Information Systems Review
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• 제31권2호
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• pp.41-59
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• 2012

ERP is a new technique of process innovation. It indicates enterprise resource planning whose purpose is an integrated total management of enterprise resources. ERP can be also seen as one of the latest management systems that organically connects by using computers all business processes including marketing, production and delivery and control those processes on a real-time basis. Currently, however, it's not easy for local enterprises to have operators who will be in charge of ERP programs, even if they want to introduce the resource management system. This suggests that it's urgently needed to train such operators through ERP education at school. But in the field of education, actually, the lack of professional ERP instructors and less effective learning programs for industrial applications of ERP are obstacles to bringing up ERP workers who are competent as much as required by enterprises. In ERP, accounting is more important than any others. Accountants are assuming more and more roles in ERP. Thus, there's a rapidly increasing demand for experts in ERP accounting. This study examined previous researches and literature concerning ERP education, identified problems with current ERP education at college and proposed how to solve the problems. This study proposed the ways of improving ERP education at college as follows. First, a prerequisite learning of ERP, that is, educating the principle of accounting should be intensified to make students get a basic theoretical knowledge of ERP enough. Second, lots of different scenarios designed to try ERP programs in business should be created. In association, students should be educated to get a better understanding of incidents or events taken place in those scenarios and apply it to trying ERP for themselves. Third, as mentioned earlier, ERP is a system that integrates all enterprise resources such as marketing, procurement, personnel management, remuneration and production under the framework of accounting. It should be noted that under ERP, business activities are organically connected with accounting modules. More importantly, those modules should be recognized not individually, but as parts comprising a whole flow of accounting. This study has a limitation because it is a literature research that heavily relied on previous studies, publications and reports. This suggests the need to compare the efficiency of ERP education between before and after applying what this study proposed to improve that education. Also, it's needed to determine students' and professors' perceived effectiveness of current ERP education and compare and analyze the difference in that perception between the two groups.

• Korean Security Journal
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• 제14호
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• pp.517-534
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• 2007

Since the beginning of human society, there have always been struggles and competitions for survival and prosperity, terrorism is not a recent phenomenon, however in modern times it has progressed to reflect the advances in civilization and power structures. At the time of the 9.11 terrorist attacks in the U.S. A., a new world order was in the process of being established after the breakdown of the Cold War era. The attacks drove both the Western and the Islamic worlds into heightened fear of terrorism and war, which threatened the quality of life of the whole mankind. Through two war campaigns against the Islamic world, it seems the U.S. has been pushing its own militaristic security road map of the Greater Middle East democratic initiative, justifying it as a means to retaliate and eradicate the terrorist threats towards themselves. However, with its five-year lopsided victories that cost the nation almost four thousand military casualties, and the war expenses that could match the Vietnam war, the U.S. does not yet seem to be totally emancipated from the fears of terrorism. Terrorism, in itself, is a means of resisting forced rules a form of alternative competition by the weak against the strong, and a way of expressing a dismissive response against dictatorial ideas or orders which allow for no normal changes. Intrinsically, the nature of terrorism is a reaction opposing power logics. Confronted with the absolute military power of the U.S., the Islamic strategies of terrorism have begun to rapidly evolve into a new stage. The new strategies take advantage of their civilization and circumstances, they train and inspire their front-line fighters on the Internet, and issue their orders through the clandestine network of the Al Qaeda operatives. These spontaneously generated strategies have been gained speed among the second, and third Islamic generations, many of whom are now spread throughout western societies. This represents a failure of the power-driven, one-sided overseas security initiatives by the U.S., and is creating a culture of fear and distrust in western societies. It is feared that the U.S. war campaigns have made the clash of religions far worse than before, and may ever lead to global ethnic separations and large-scale population movements. Eventually, it may result in the terrorist groups, enlarged and secretly supported by the huge sums of oil money, driving all mankind into a series of irreparable catastrophes.

• Atmosphere
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• 제28권3호
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• pp.305-315
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• 2018

This study investigates the characteristic spatial patterns and dynamic processes associated with the summertime extreme temperature events in South Korea during the last 20 years (1995~2014) using Self-Organizing Map (SOM). The classified SOM patterns commonly have high temperature and anticyclonic circulation anomalies over South Korea. The two major teleconnection patterns are identified: one is from the subtropical western North Pacific (WNP) affecting to the north and the other is from the North Atlantic (NA) affecting downstream region. The meridional teleconnection pattern is related to the forcing of positive sea surface temperature (SST) anomaly over the WNP. The northward propagating Rossby wave generates the East Asia-Pacific (EAP) pattern to form an anticyclonic circulation anomaly over South Korea. On the other hand, NA SST anomalies generate an eastward Rossby wave train across the Eurasian continent, leading to the development of an anticyclonic circulation anomaly over South Korea. The EAP pattern occurs more frequently in July and August, whereas the midlatitude teleconnection pattern associated with NA SST anomalies develops more frequently in early summer (June).

• Korean Journal of Hospice Care
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• 제2권2호
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• pp.28-48
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• 2002

The advances of medical technologies have not only prolonged human life span, but also extended suffering period for the patients with incurable medical diseases. Hospice movement was developed to help these patients keep dignity and lives peaceful at the end of their life. Since many patients prefer to spend the last moment of life at home with their family, hospice home care has become very popular worldwide. The purpose of this study for a promotion and development of hospice home care in Korea, and features basic research on medical profession's knowledge and attitudes to hospice home care. This study which was used for the research questionnaires developed by the researcher that were answered by 100 physicians and 127 nurses in a general hospital. Data were collected from April 22, 2002 to May 10, 2002. The SPSS was used to make a comparative analysis of the frequency, percentile, ANOVA, and x2-test. The results of the study were as follows; 1.The medical profession showed high level of knowledge of the definition and philosophy of hospice. However, the physician group of the examinees showed insufficient knowledge of the fact that hospice care includes bereavement care, while the nurse group's response to the same question showed a significant difference(x2=10.752, p=.001). 2.For whom the hospice home care is provided, 95.6% of the respondents showed very high level of knowledge as answering that the incurable terminal illness patients and their families are the beneficiaries of hospice care. The respondents counted nurses, volunteers, pastors, physicians and social workers, consecutively, as hospice care providers. More nurse were positive toward pastors than physicians in regarding as a hospice care provider by a significant difference(x2=11.634, p=.001). 3.For when to referral hospice home care to the patients, only 34.2% answered that patients with less than 6 months of survival time are advised to receive hospice care, reflecting very low level of knowledge. 23.0% of the physicians and 48.0% of the nurses answered that hospice care should be provided when death is imminent, making a significant difference between the two groups(x2=6.413, p=.000). 4.To promote hospice activities, 87.2% pointed out that it is crucial to make general people, including those engaging in the medical field, more aware of hospice. 79.7% answered that a national hospice management should be developed, marking a significant difference between the physician group and nurse group(x2=10.485, p=.001). 5.Advantages of hospice home care are 87.2% responded that patients can have better rest at home receiving hospice home care. Economical merit was brought forward as one of the advantages also, where there was a significant difference between the physicians group and nurse group(x2=7.009, p=.008). 6.The medical professions' attitude to hospice home care are 92.8% of the physicians answered that they would advise incurable terminally ill patients to be discharged from hospital, with 44.3% of them advising the patients to receive hospice home care after leaving the hospital. From the nurses' point of view, 20.9% of the terminally ill patients are being referred to hospice home care after discharge, which makes a significant difference from the physicians' response(x2=19.121, p=.001). 7. 30.6% of physicians have referred terminally ill patients to hospice home care, 75.9% of whom were satisfied with their decision. Those physicians who have never referred their patients to hospice home care either did not know how to do it(66.7%) or were afraid of losing trust by giving the patients an impression of giving up(27.3%). 94.9% of the physicians responded that they would refer their last stage patients to a doctor who is involving palliative care. 8.Only 36.2% of nurses have suggested to physicians that refer the terminally ill patients discharged from the hospital to hospice home care. Once suggested, 95.8% of the physicians have accepted the suggestion. Nurses were reluctant to suggest hospice home care to the physicians, as 48.8% of the nurses said they did not want to. From the result of this study the following conclusion can be drawn, the medical profession's awareness of general hospice care has been increased greatly compared to the results of the previously performed studies. However, this study result also shows that their knowledge of hospice home care is not good enough yet. There is a need for high recommended that medical education institute and develop regular courses on various types of hospice care. Medical field training courses for physicians and nurses will be very helpful as well. It is also important to train hospice experts such as palliative physicians and develop a national hospice management urgently in order to improve the hospice care in Korea.

• The Korean Journal of Mycology
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• 제38권2호
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• pp.105-111
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• 2010

Lentinus lepideus, known as train wrecker fungus, has been used for nutritional and medicinal purposes. Recently, commercial cultivation technique and a new cultivar of the mushroom were developed. To investigate the genetic diversity and phylogenetic relationship for identifying the mushroom strains and cultivar, one commercial and 13 strains of Lentinus lepideus from different geographical regions of Korea were analyzed by ITS regions of rDNA and RAPD of genomic DNA. Three strains of Lentinus edodes were also used for the analysis. The size of the ITS1 and ITS2 regions of rDNA from the different strains varied from 173 to 179 bp and 203 to 205 bp, respectively. The sequence of ITS1 was more variable than that of ITS2, while the 5.8S sequences were identical with 156 base pairs. A phylogenetic tree based on the ITS region sequences indicated that selected strains could be classified into four clusters, while 3 strains of L. edodes was divided into a new cluster. Ten primers out of 20 arbitrary primers used in the RAPD-PCR efficiently amplified the genomic DNA. The numbers of amplified DNA bands varied with the primers and strains, with polymorphic DNA fragments in the range from 0.2 to 2.6 kb. The results showed that phylogenetic relationship among Korean strains of Lentnus lepideus is high, but genetic diversity is low.

• Journal of Intelligence and Information Systems
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• 제25권1호
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Korean Journal of Heritage: History & Science
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• 제53권4호
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• pp.198-215
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• 2020

Official development assistance refers to assistance provided by governments and other public institutions in donor countries, aimed at promoting economic development and social welfare in developing countries. The purpose of this research is to examine the construction process of the "Myanmar Cultural Heritage Management System" that is underway as part of the ODA project to strengthen cultural and artistic capabilities and analyze the achievements and challenges of the Digital Cultural Heritage ODA. The digital cultural heritage management system is intended to achieve the permanent preservation and sustainable utilization of tangible and intangible cultural heritage materials. Cultural heritage can be stored in digital archives, newly approached using computer analysis technology, and information can be used in multiple dimensions. First, the Digital Cultural Heritage ODA was able to permanently preserve cultural heritage content that urgently needed digitalization by overcoming and documenting the "risk" associated with cultural heritage under threat of being extinguished, damaged, degraded, or distorted in Myanmar. Second, information on Myanmar's cultural heritage can be systematically managed and used in many ways through linkages between materials. Third, cultural maps can be implemented that are based on accurate geographical location information as to where cultural heritage is located or inherited. Various items of cultural heritage were collectively and intensively visualized to maximize utility and convenience for academic, policy, and practical purposes. Fourth, we were able to overcome the one-sided limitations of cultural ODA in relations between donor and recipient countries. Fifth, the capacity building program run by officials in charge of the beneficiary country, which could be the most important form of sustainable development in the cultural ODA, was operated together. Sixth, there is an implication that it is an ODA that can be relatively smooth and non-face-to-face in nature, without requiring the movement of manpower between countries during the current global pandemic. However, the following tasks remain to be solved through active discussion and deliberation in the future. First, the content of the data uploaded to the system should be verified. Second, to preserve digital cultural heritage, it must be protected from various threats. For example, it is necessary to train local experts to prepare for errors caused by computer viruses, stored data, or operating systems. Third, due to the nature of the rapidly changing environment of computer technology, measures should also be discussed to address the problems that tend to follow when new versions and programs are developed after the end of the ODA project, or when developers have not continued to manage their programs. Fourth, since the classification system criteria and decisions regarding whether the data will be disclosed or not are set according to Myanmar's political judgment, it is necessary to let the beneficiary country understand the ultimate purpose of the cultural ODA project.

• Economic and Environmental Geology
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• 제55권5호
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Journal of Intelligence and Information Systems
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• 제28권1호
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• pp.69-88
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• 2022

One of the characteristics of South Korea's economic structure is that it is highly dependent on exports. Thus, many businesses are closely related to the global economy and diplomatic situation. In addition, small and medium-sized enterprises(SMEs) specialized in exporting are struggling due to the spread of COVID-19. Therefore, this study aimed to develop a model to forecast exports for next year to support SMEs' export strategy and decision making. Also, this study proposed a strategy to recommend promising export countries of each item based on the forecasting model. We analyzed important variables used in previous studies such as country-specific, item-specific, and macro-economic variables and collected those variables to train our prediction model. Next, through the exploratory data analysis(EDA) it was found that exports, which is a target variable, have a highly skewed distribution. To deal with this issue and improve predictive performance, we suggest a separated learning method. In a separated learning method, the whole dataset is divided into homogeneous subgroups and a prediction algorithm is applied to each group. Thus, characteristics of each group can be more precisely trained using different input variables and algorithms. In this study, we divided the dataset into five subgroups based on the exports to decrease skewness of the target variable. After the separation, we found that each group has different characteristics in countries and goods. For example, In Group 1, most of the exporting countries are developing countries and the majority of exporting goods are low value products such as glass and prints. On the other hand, major exporting countries of South Korea such as China, USA, and Vietnam are included in Group 4 and Group 5 and most exporting goods in these groups are high value products. Then we used LightGBM(LGBM) and Exponential Moving Average(EMA) for prediction. Considering the characteristics of each group, models were built using LGBM for Group 1 to 4 and EMA for Group 5. To evaluate the performance of the model, we compare different model structures and algorithms. As a result, it was found that the separated learning model had best performance compared to other models. After the model was built, we also provided variable importance of each group using SHAP-value to add explainability of our model. Based on the prediction model, we proposed a second-stage recommendation strategy for potential export countries. In the first phase, BCG matrix was used to find Star and Question Mark markets that are expected to grow rapidly. In the second phase, we calculated scores for each country and recommendations were made according to ranking. Using this recommendation framework, potential export countries were selected and information about those countries for each item was presented. There are several implications of this study. First of all, most of the preceding studies have conducted research on the specific situation or country. However, this study use various variables and develops a machine learning model for a wide range of countries and items. Second, as to our knowledge, it is the first attempt to adopt a separated learning method for exports prediction. By separating the dataset into 5 homogeneous subgroups, we could enhance the predictive performance of the model. Also, more detailed explanation of models by group is provided using SHAP values. Lastly, this study has several practical implications. There are some platforms which serve trade information including KOTRA, but most of them are based on past data. Therefore, it is not easy for companies to predict future trends. By utilizing the model and recommendation strategy in this research, trade related services in each platform can be improved so that companies including SMEs can fully utilize the service when making strategies and decisions for exports.