• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.59 no.1
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• pp.1-15
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• 2014

The cultivation situation of Korean wheat of 175 farmers in nationwide for two years, 2010/2011 and 2011/2012, was analyzed to obtain basic data for extension cultivated area and enhancing the self-sufficiency ratio of Korean wheat. Compared to the mean temperature and precipitation in the normal year, the mean temperature was lower before the heading stage and higher amount of precipitation after the heading stage in 2010/2011 and higher the mean temperature and lower amount of precipitation after the heading stage in 2011/2012. Average cultivation career and area were 7.7years and 2.4~3.3ha, Keumkang cv. was mainly cultivated for two years and Jokyung and Baekjoong cvs. were increased cultivation areas in southern part of Korea, Gyeongsangnam-do, Jeolllanambuk-do and Kwangju metropolitan city, including in 2011/2012. Most farmers (144) sown wheat seeds from late October to the beginning November with broadcasting method and the other famers were sown using the drill method. Average amount for basal fertilizer was 29.7 kg/10a with complex fertilizer mixed for wheat and barley cultivation, which was higher amount compared to recommended rate of fertilizer amount by rural development administration. Top dressing using nitrogen fertilizer was applied from in the late February to the beginning March. Heading date was the beginning May in 2011 and the late April in 2012, which the mean temperature from regeneration stage to tillering stage in 2011 was higher than that of 2012. Most farmers harvested wheat in mid-June and Pre-harvest sprouting and Fusarium head blight were occurred in 2011 due to the high amount precipitation during grain filling period.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.3
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• pp.135-142
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• 2016

The aim of this study was to confirm the improvement of efficiency for temperature estimation at 0600 and 1500 LST by using a simple method for estimating temperature lapse rate modulated by the amount of clouds in comparison with the case adopting the existing single temperature lapse rate ($-6.5^{\circ}C/km$ or $-9^{\circ}C/km$). A catchment of the 'Hadong Watermark2,' which includes Hadong, Gurye, and Gwangyang was selected as the area for evaluating the practicality of the temperature lapse rate estimation method. The weather data of 0600 and 1500 LST at 12 weather observation sites within the catchment were collected during the entire year of 2015. Also, the 'sky condition' of digital forecast products of KMA in 2015 ($5{\times}5km$ lattice resolution) were overlapped with the catchment of the 'Hadong Watermark2,' to calculate the spatial average value within the catchment, which were used to simulate the 0600 and 1500 LST temperature lapse rate of the catchment. The estimation errors of the temperatures at 0600 LST were ME $-0.39^{\circ}C$ and RMSE $1.45^{\circ}C$ in 2015, when applying the existing temperature lapse rate. Using the estimated temperature lapse rate, they were improved to ME $-0.19^{\circ}C$ and RMSE $1.32^{\circ}C$. At 1500 LST, the effect of the improvements found from the comparison between the existing temperature lapse rate and the estimated temperature lapse rate were minute, because the estimated lapse rate of clear days is not very different from the existing lapse rate. However, the estimation errors of the temperatures at 1500 LST during cloudy days were improved from ME $-0.69^{\circ}C$, RMSE $1.54^{\circ}C$ to ME $-0.51^{\circ}C$, RMSE $1.19^{\circ}C$.

• Proceedings of the Korean Reliability Society Conference
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• 2001.06a
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• pp.277-278
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• 2001

The successful operation of a product In service depends upon the effective provision of logistic support in order to achieve and maintain the required levels of performance and customer satisfaction. Logistic support encompasses the activities and facilities required to maintain a product (hardware and software) in service. Logistic support covers maintenance, manpower and personnel, training, spares, technical documentation and packaging handling, storage and transportation and support facilities.The cost of logistic support is often a major contributor to the Life Cycle Cost (LCC) of a product and increasingly customers are making purchase decisions based on lifecycle cost rather than initial purchase price alone. Logistic support considerations can therefore have a major impact on product sales by ensuring that the product can be easily maintained at a reasonable cost and that all the necessary facilities have been provided to fully support the product in the field so that it meets the required availability. Quantification of support costs allows the manufacturer to estimate the support cost elements and evaluate possible warranty costs. This reduces risk and allows support costs to be set at competitive rates.Integrated Logistic Support (ILS) is a management method by which all the logistic support services required by a customer can be brought together in a structured way and In harmony with a product. In essence the application of ILS:- causes logistic support considerations to be integrated into product design;- develops logistic support arrangements that are consistently related to the design and to each other;- provides the necessary logistic support at the beginning and during customer use at optimum cost.The method by which ILS achieves much of the above is through the application of Logistic Support Analysis (LSA). This is a series of support analysis tasks that are performed throughout the design process in order to ensure that the product can be supported efficiently In accordance with the requirements of the customer.The successful application of ILS will result in a number of customer and supplier benefits. These should include some or all of the following:- greater product uptime;- fewer product modifications due to supportability deficiencies and hence less supplier rework;- better adherence to production schedules in process plants through reduced maintenance, better support;- lower supplier product costs;- Bower customer support costs;- better visibility of support costs;- reduced product LCC;- a better and more saleable product;- Improved safety;- increased overall customer satisfaction;- increased product purchases;- potential for purchase or upgrade of the product sooner through customer savings on support of current product.ILS should be an integral part of the total management process with an on-going improvement activity using monitoring of achieved performance to tailor existing support and influence future design activities. For many years, ILS was predominantly applied to military procurement, primarily using standards generated by the US Government Department of Defense (DoD). The military standards refer to specialized government infrastructures and are too complex for commercial application. The methods and benefits of ILS, however, have potential for much wider application in commercial and civilian use. The concept of ILS is simple and depends on a structured procedure that assures that logistic aspects are fully considered throughout the design and development phases of a product, in close cooperation with the designers. The ability to effectively support the product is given equal weight to performance and is fully considered in relation to its cost.The application of ILS provides improvements in availability, maintenance support and longterm 3ogistic cost savings. Logistic costs are significant through the life of a system and can often amount to many times the initial purchase cost of the system.This study provides guidance on the minimum activities necessary to Implement effective ILS for a wide range of commercial suppliers. The guide supplements IEC60106-4, Guide on maintainability of equipment Part 4: Section Eight maintenance and maintenance support planning, which emphasizes the maintenance aspects of the support requirements and refers to other existing standards where appropriate. The use of Reliability and Maintainability studies is also mentioned in this study, as R&M is an important interface area to ILS.

• Korean Journal of Occupational Health Nursing
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• v.6 no.2
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• pp.110-127
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• 1997

The aim of this study is to present the basic datum for the promotion of effectiveness and improvement of nursery tasks, by grasping the situation of operating room nurses tasks and the degree of their fatigue. For these researches, 70 nurses out of the operating rooms of 3 university-affiliated hospitals-two in Seoul and one in Pusan, were chosen at random by a non-probability sampling method. These researches were done from April 14 to April 26 in 1997 by questionairing method. The questionaire was composed of 30 items, which asks the examinees of their physical, mental, and neurosensory symptoms, with 10 items respectively. The reliability of the research instrument was turned out very high with Cronbach's ${\alpha}=.9376$. The datum were electronically processed using Statistics Program for Social Sciences(SPSS). The analysis of datum in this study has a general character, in which the demosociological character and the special ex-officio character was calculated by frequency and percentage. The situation of tasks in operating rooms was calculated by frequency and percentage. The fatigue of operating room nurses was calculated by average and standard deviation. To compare the fatigue with regard to the character of operating room nurse's tasks, t-test and F-test(ANOVA) were used after the character of variations, and the variations at the level of P<.05 which might have some meaning was verified after the fact with Duncan's Multiple Range(DMR). The results of this research are as follows : 1) The nurses working in operating rooms show their fatigue in three fields-in Group I physical symptoms 3.28, in Group III neurosensory symptoms 2.85, and in Group II mental symptoms 2.73, which shows I Dominant type (general type). 2) They complain, in Group I they are "feeling the heavy legs," 3.28 and in Group II they "occasionally forget soon what to do," 3.09. and in Group III, they "feel lumbago," 3.47, which is the highest rate of the three. The highest rate results from the character of their tasks, in which they have to move rapidly the heavy appliances and do their jobs standing many hours, especially wearing heavy radiation protector. 3) As to transportation, subway using group feel the greatest fatigue, 3.18(F=4.315, P=.008). 4) As to department, nurses in the orthopedic's surgery part feel the greatest fatigue, 3.26(F=2.040, P=.050). 5) As to the change of physical symptoms, the group answering that they found physical abnormality after working in operating rooms show the greatest fatigue, 3.12(t=-3.13, P=.003). 6) At to the general circumstances, the group answering that they receive insufficient consideration on their physical abnormality in their department, show the greatest fatigue, 3.10(F=3.200, P=0.47). 7) As to the relation with superior officers, the group answering that their superior officer has an impetuous temperament, show great fatigue, 3.11(F=4.855, P=.011). 8) As to the time of feeling fatigue, the fatigue reaches the highest point 1~2 hours after operations, 3.04(F=2.703, P=.046). 9) When they feel fatigue after scrub nurse duties, they feel the greatest fatigue 2 hours after the duties, 3.09( F=2.841, P=.038). 10) As to the operation instruments, when they use complex instruments borrowing from the outside in addition to the basic instruments, their fatigue becomes the greatest, 3.09(F=7.831, P=.000). 11) As to the kind of operation, when they participate in orthopedic's surgery operations, they feel the greatest fatigue, 3.18(F=4.362, P=.000). With the above results, it is proved that the degree of operating room nurses' fatigue is considerably high. So it may be concluded that the measure for lessening the fatigue should be find immediately, not on the level of personal matters but on the level of hospital nursing administration.

• Journal of Chest Surgery
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• v.38 no.8 s.253
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• pp.551-556
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• 2005

Background: Complete arterial off-pump coronary artery bypass grafting (OPCAB) by sequential anastomoses with one or two arterial grafts provides favorable outcomes. However, problems of insufficient graft length, hypopefusion, kinking of graft, and unfavorable course of graft may be encountered. To solve these problems, we have used different technique with multiple arterial Y composite graft to allow end-to-side rather than sequential anastomoses and evaluated the results of this method. Material and Method: Between February 2003 and October 2004, If patients underwent total arterial OPCAB using multiple arterial V composite grafts with left internal mammary artery (LIMA), radial artery (RA), and right internal mammary artery (RIMA). We divided RA into multiple segments by number of distal target site after measuring of individual proper length and constructed arterial composite graft. One of segments was sutured end-to-side to LIMA and other segment was sutured end-to-side to the previously constructed radial graft. Postoperative graft patency was evaluated in 6f patients by multi-slice computed tomegraphy. Result: An average of $2.5\pm0.6$ arteries and $3.7pm0.7$ distal anastomoses per patient were done. There was no perioperative myocardial infarction, clinical hypoperfusion syndromes, and operative mortality. Postoperative mean CK-MB level was $17.4pm29.7\;IU/L.$Overall graft patency was $99.1\%\;(214/216)(LIMA:\;100\%,\;RA:\;98.4\%,\;RIMA:\;100\%).$ Conclusion: This technique allows total arterial OPCAB without technical problems and provides excellent early clinical results and graft patency. We believe that this technique is more convenient in the obtuse marginal area compared to sequential technique, and helpful in patients who require complex arterial grafting.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.749-758
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• 2004

In this paper, we propose a new method utilizing only raw corpus without additional human effort for disambiguation of target word selection in English-Korean machine translation. We use two data-driven techniques; one is the Latent Semantic Analysis(LSA) and the other the Probabilistic Latent Semantic Analysis(PLSA). These two techniques can represent complex semantic structures in given contexts like text passages. We construct linguistic semantic knowledge by using the two techniques and use the knowledge for target word selection in English-Korean machine translation. For target word selection, we utilize a grammatical relationship stored in a dictionary. We use k- nearest neighbor learning algorithm for the resolution of data sparseness Problem in target word selection and estimate the distance between instances based on these models. In experiments, we use TREC data of AP news for construction of latent semantic space and Wail Street Journal corpus for evaluation of target word selection. Through the Latent Semantic Analysis methods, the accuracy of target word selection has improved over 10% and PLSA has showed better accuracy than LSA method. finally we have showed the relatedness between the accuracy and two important factors ; one is dimensionality of latent space and k value of k-NT learning by using correlation calculation.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Journal of Food Hygiene and Safety
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• v.32 no.3
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• pp.187-192
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• 2017

The consumption of herbal medicines has been increasing with growing interest in health. However, due to recent climate change and the complex distribution process of herbal medicines with high import dependence the likelihood of contamination with mycotoxin has been increased. Mycotoxins are emerging as key indicators for ensuring safety of herbal medicines. A total of 498 herbal medicine samples were screened for mycotoxin contamination in this study. Aflatoxin in the herbal medicine samples was extracted by using immunoaffinity column, then the extracted aflatoxin was quantified via high performance liquid chromatography coupled with fluorescence detection (HPLC-FLD) method. The extraction method was verified by linearity, recovery, LOD and LOQ. Aflatoxins were detected in 39/498 samples in an average of $7.670{\mu}g/kg$ ($0.610-77.452{\mu}g/kg$ range). Although safety standards for Corydalis Tuber is not currently available in korea, five of the 39 samples had high concentration of aflatoxins (average of $14.9{\pm}4.1{\mu}g/kg$). In conclusion, it is urgent to establish safety criteria of aflatoxin in Corydalis Tuber. The results of the current study suggest that continuous monitoring is necessary for proactive management of herbal medicine safety.

• Cartoon and Animation Studies
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• s.47
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• pp.31-52
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• 2017

NCS education was created to realize a society in which skills and abilities are respected, such as transcending specifications, establishing recruitment systems, and developing and disseminating national incompetence standards. At the university level, special lectures and job training are being strengthened to raise industrial experts. Especially, in the field of animation, new technologies are rapidly emerging and demanding convergent talents with various fields. In order to meet these social demands, there is a limit to the existing one-class teaching method. In order to solve this problem, it is necessary to participate in a variety of specialized teachers. In other words, rather than solving problems of students' job training and job creation, It is aimed to solve jointly, Team teaching was suggested as a method for this. The expected effects that can be obtained through this are as follows. First, the field of animation is becoming more diverse and complex. The ability to use NCS job-related skills pools can be matched with professors from other departments to enable a wider range of professional instruction. Second, it is possible to use partial professorships in other departments by actively utilizing professors in the university. This leads to the strengthening of the capacity of teachers in universities. Third, it is possible to build a broader and more integrated educational system through cooperative teaching of professors in other departments. Finally, the advantages of special lectures and mentor support of college professors' pools are broader than those of field specialists. A variety of guidance for students can be made with responsible professors. In other words, time and space constraints can be avoided because the mentor is easily met and guided by the university.