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A Study for strategic cooperaton of enterprise security and business (기업보안과 비즈니스의 전략적 협력에 관한 연구)

  • Ryu, Hyung-Chang
    • Korean Security Journal
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    • no.28
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    • pp.103-130
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    • 2011
  • This study is the research of enterprise security for raising the profitability and stability of Korean companies in global business environment and strategic cooperation of business. As the scientific technology gets complicated as day goes by and new competitors appear regardless the border in the modern business environment, the situation happens frequently which the huge company hands over their market to the new one armed with the innovative thinking overnight. To survive such new environment, the answer is the change of paradigm regarding business management method at the new point of view. With the low level of security risk management of Korean companies which stick to old habit, the security management which helps the companies secure profits is not affordable. The global village where the population of 7 billions live in 21st century is facing up to the rapid ecological adaptation. The rapid change of climatic environment creates the hundreds of thousands of sufferers in a moment, and we have been watching the millions of livestock are buried alive due to new contagious disease everyday. Such change encourages the humans in global village to change the basic way of living. The business ecosystem which is the basic root for economic life cannot be an exception. To survive the business environment of 21st century, the security risk management at management level is required and the reporting line of companies should be established newly for raising business competing power through security risk management. The companies should bear in mind that they can be disappeared into our old memories overnight if they are not sensitive to the changing environment. Out of new risks for the modern companies, the field especially Korean companies are dealing easily is the security risk. Not like past, the security risk which's size is much more massive and its propagation velocity is very fast is the one of important business risks which the management should take care. Out of security risks which influence on the modern companies significantly, the brand of companies, protection of their reputation, continuity of production and operation and keeping customer's trust are prior to the others. This study offered the suggestion regarding enterprise security and the strategic cooperation of business to deal with such security risk effectively.

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A study on the characteristics of Goryeo dynasty cargo tag mokkans In comparison with mokkans of the Song and Yuan dynasty (고려시대 화물표 목간의 특징에 대한 고찰 - 중국 송·원대(宋·元代) 목간과의 비교를 중심으로 -)

  • LEE, Yeonjae
    • Korean Journal of Heritage: History & Science
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    • v.54 no.4
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    • pp.60-77
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    • 2021
  • From 2007 to 2011, four Goryeo Dynasty vessels, namely the Taean treasure ship, Taean Mado Shipwreck No.1, No.2, No.3 were discovered in Taean area, Chungcheongnam-do province. From the shipwrecks, 175 pieces of mokkan (wooden tablet) were excavated. These mokkans are the only case of Goryeo Dynasty and represent the unique usage of mokkan as cargo tags, after the paper replaced the wooden tablets as writing materials. The Taean mokkans provide details, such as the year, recipient, port of origin, types of the cargo, quantity and unit, the name of the responsible person for shipment. Thus, they enable us to speculate about the characteristics of the cargo. Furthermore, through studying the writing style, form, material and manufacturing method, researchers can extract which form and characteristics were favored at that time. The Taean mokkans have no preset style for writing. Therefore, they can be written selectively and freely. And since the mokkan were attached to cargos, mokkans with furrows on upper side were favored, and efficiency and simplification of the manufacturing process were priorities in making mokkans. The Taean mokkans can be compared to those from the Shinan ship and the Quanzhou ship because those are of the same era and use. On the writing styles and information, Chinese mokkans are focused on the cargo owners, while The Taean mokkan includes more detailed information, such as the recipients. In forms, Chinese mokkans have maximum thickness of 1.0 centimeter and have pointed edges in lower parts, while mokkans from Taean do not have fixed thickness or edges. Furthermore, Chinese mokkans and Korean mokkans have different styles from manufacturing methods and material selections. These differences between Chinese and Goryeo mokkan are related to the differences between littoral-transport Goryeo ships and ocean-transport Chinese ships, such as shipping distances, types of cargo, shipping systems, packing methods, and transport operators. At the moment, because there are only small amount of data and materials of Chinese mokkan, comparative studies regarding Goryeo and Chinese mokkan can only be fragmentary. However, this article can be a base from which to expand the scope of Goryeo mokkan studies.

Structural Behavior Evaluation of NRC Beam-Column Connections (NRC 보-기둥 접합부의 구조적 거동 평가)

  • Jeon, Ji-Hwan;Lee, Sang-Yun;Kim, Seung-Hun
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.26 no.1
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    • pp.73-80
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    • 2022
  • In this study, details of NRC beam-column connections were developed in which beam and columns pre-assembled in factories using steel angles were bolted on site. The developed joint details are NRC-J type and NRC-JD type. NRC-J type is a method of tensile joining with TS bolts to the side and lower surfaces of the side plate of the NRC column and the end plate of the NRC beam. NRC-JD type has a rigid joint with high-strength bolts between the NRC beam and the side of the NRC column for shear, and with lap splices of reinforcing bar penetrating the joint and the beam main reinforcement for bending. For the seismic performance evaluation of the joint, three specimens were tested: an NRC-J specimen and NRC-JD specimen with NRC beam-column joint details, and an RC-J specimen with RC beam-column joint detail. As a result of the repeated lateral load test, the final failure mode of all specimens was the bending fracture of the beam at the beam-column interface. Compared to the RC-J specimen, the maximum strength of the specimen by the positive force was 10.1% and 29.6% higher in the NRC-J specimen and the NRC-JD specimen, respectively. Both NRC joint details were evaluated to secure ductility of 0.03 rad or more, the minimum total inter-story displacement angle required for the composite intermediate moment frame according to the KDS standard (KDS 41 31 00). At the slope by relative storey displacemet of 5.7%, the NRC-J specimen and the NRC-JD specimen had about 34.8% and 61.1% greater cumulative energy dissipation capacity than the RC specimen. The experimental strength of the NRC beam-column connection was evaluated to be 30% to 53% greater than the theoretical strength according to the KDS standard formula, and the standard formula evaluated the joint performance as a safety side.

Estimation of grid-type precipitation quantile using satellite based re-analysis precipitation data in Korean peninsula (위성 기반 재분석 강수 자료를 이용한 한반도 격자형 확률강수량 산정)

  • Lee, Jinwook;Jun, Changhyun;Kim, Hyeon-joon;Byun, Jongyun;Baik, Jongjin
    • Journal of Korea Water Resources Association
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    • v.55 no.6
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    • pp.447-459
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    • 2022
  • This study estimated the grid-type precipitation quantile for the Korean Peninsula using PERSIANN-CCS-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System-Climate Data Record), a satellite based re-analysis precipitation data. The period considered is a total of 38 years from 1983 to 2020. The spatial resolution of the data is 0.04° and the temporal resolution is 3 hours. For the probability distribution, the Gumbel distribution which is generally used for frequency analysis was used, and the probability weighted moment method was applied to estimate parameters. The duration ranged from 3 hours to 144 hours, and the return period from 2 years to 500 years was considered. The results were compared and reviewed with the estimated precipitation quantile using precipitation data from the Automated Synoptic Observing System (ASOS) weather station. As a result, the parameter estimates of the Gumbel distribution from the PERSIANN-CCS-CDR showed a similar pattern to the results of the ASOS as the duration increased, and the estimates of precipitation quantiles showed a rather large difference when the duration was short. However, when the duration was 18 h or longer, the difference decreased to less than about 20%. In addition, the difference between results of the South and North Korea was examined, it was confirmed that the location parameters among parameters of the Gumbel distribution was markedly different. As the duration increased, the precipitation quantile in North Korea was relatively smaller than those in South Korea, and it was 84% of that of South Korea for a duration of 3 h, and 70-75% of that of South Korea for a duration of 144 h.

A Comparative Analysis of Social Commerce and Open Market Using User Reviews in Korean Mobile Commerce (사용자 리뷰를 통한 소셜커머스와 오픈마켓의 이용경험 비교분석)

  • Chae, Seung Hoon;Lim, Jay Ick;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.53-77
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    • 2015
  • Mobile commerce provides a convenient shopping experience in which users can buy products without the constraints of time and space. Mobile commerce has already set off a mega trend in Korea. The market size is estimated at approximately 15 trillion won (KRW) for 2015, thus far. In the Korean market, social commerce and open market are key components. Social commerce has an overwhelming open market in terms of the number of users in the Korean mobile commerce market. From the point of view of the industry, quick market entry, and content curation are considered to be the major success factors, reflecting the rapid growth of social commerce in the market. However, academics' empirical research and analysis to prove the success rate of social commerce is still insufficient. Henceforward, it is to be expected that social commerce and the open market in the Korean mobile commerce will compete intensively. So it is important to conduct an empirical analysis to prove the differences in user experience between social commerce and open market. This paper is an exploratory study that shows a comparative analysis of social commerce and the open market regarding user experience, which is based on the mobile users' reviews. Firstly, this study includes a collection of approximately 10,000 user reviews of social commerce and open market listed Google play. A collection of mobile user reviews were classified into topics, such as perceived usefulness and perceived ease of use through LDA topic modeling. Then, a sentimental analysis and co-occurrence analysis on the topics of perceived usefulness and perceived ease of use was conducted. The study's results demonstrated that social commerce users have a more positive experience in terms of service usefulness and convenience versus open market in the mobile commerce market. Social commerce has provided positive user experiences to mobile users in terms of service areas, like 'delivery,' 'coupon,' and 'discount,' while open market has been faced with user complaints in terms of technical problems and inconveniences like 'login error,' 'view details,' and 'stoppage.' This result has shown that social commerce has a good performance in terms of user service experience, since the aggressive marketing campaign conducted and there have been investments in building logistics infrastructure. However, the open market still has mobile optimization problems, since the open market in mobile commerce still has not resolved user complaints and inconveniences from technical problems. This study presents an exploratory research method used to analyze user experience by utilizing an empirical approach to user reviews. In contrast to previous studies, which conducted surveys to analyze user experience, this study was conducted by using empirical analysis that incorporates user reviews for reflecting users' vivid and actual experiences. Specifically, by using an LDA topic model and TAM this study presents its methodology, which shows an analysis of user reviews that are effective due to the method of dividing user reviews into service areas and technical areas from a new perspective. The methodology of this study has not only proven the differences in user experience between social commerce and open market, but also has provided a deep understanding of user experience in Korean mobile commerce. In addition, the results of this study have important implications on social commerce and open market by proving that user insights can be utilized in establishing competitive and groundbreaking strategies in the market. The limitations and research direction for follow-up studies are as follows. In a follow-up study, it will be required to design a more elaborate technique of the text analysis. This study could not clearly refine the user reviews, even though the ones online have inherent typos and mistakes. This study has proven that the user reviews are an invaluable source to analyze user experience. The methodology of this study can be expected to further expand comparative research of services using user reviews. Even at this moment, users around the world are posting their reviews about service experiences after using the mobile game, commerce, and messenger applications.

Corporate Default Prediction Model Using Deep Learning Time Series Algorithm, RNN and LSTM (딥러닝 시계열 알고리즘 적용한 기업부도예측모형 유용성 검증)

  • Cha, Sungjae;Kang, Jungseok
    • Journal of Intelligence and Information Systems
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    • v.24 no.4
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    • pp.1-32
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    • 2018
  • In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

Radioimmunoassay Reagent Survey and Evaluation (검사별 radioimmunoassay시약 조사 및 비교실험)

  • Kim, Ji-Na;An, Jae-seok;Jeon, Young-woo;Yoon, Sang-hyuk;Kim, Yoon-cheol
    • The Korean Journal of Nuclear Medicine Technology
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    • v.25 no.1
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    • pp.34-40
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    • 2021
  • Purpose If a new test is introduced or reagents are changed in the laboratory of a medical institution, the characteristics of the test should be analyzed according to the procedure and the assessment of reagents should be made. However, several necessary conditions must be met to perform all required comparative evaluations, first enough samples should be prepared for each test, and secondly, various reagents applicable to the comparative evaluations must be supplied. Even if enough comparative evaluations have been done, there is a limit to the fact that the data variation for the new reagent represents the overall patient data variation, The fact puts a burden on the laboratory to the change the reagent. Due to these various difficulties, reagent changes in the laboratory are limited. In order to introduce a competitive bid, the institute conducted a full investigation of Radioimmunoassay(RIA) reagents for each test and established the range of reagents available in the laboratory through comparative evaluations. We wanted to share this process. Materials and Methods There are 20 items of tests conducted in our laboratory except for consignment tests. For each test, RIA reagents that can be used were fully investigated with the reference to external quality control report. and the manuals for each reagent were obtained. Each reagent was checked for the manual to check the test method, Incubation time, sample volume needed for the test. After that, the primary selection was made according to whether it was available in this laboratory. The primary selected reagents were supplied with 2kits based on 100tests, and the data correlation test, sensitivity measurement, recovery rate measurement, and dilution test were conducted. The secondary selection was performed according to the results of the comparative evaluation. The reagents that passed the primary and secondary selections were submitted to the competitive bidding list. In the case of reagent is designated as a singular, we submitted a explanatory statement with the data obtained during the primary and secondary selection processes. Results Excluded from the primary selection was the case where TAT was expected to be delayed at the moment, and it was impossible to apply to our equipment due to the large volume of reagents used during the test. In the primary selection, there were five items which only one reagent was available.(squamous cell carcinoma Ag(SCC Ag), β-human chorionic gonadotropin(β-HCG), vitamin B12, folate, free testosterone), two reagents were available(CA19-9, CA125, CA72-4, ferritin, thyroglobulin antibody(TG Ab), microsomal antibody(Mic Ab), thyroid stimulating hormone-receptor-antibody(TSH-R-Ab), calcitonin), three reagents were available (triiodothyronine(T3), Tree T3, Free T4, TSH, intact parathyroid hormone(intact PTH)) and four reagents were available are carcinoembryonic antigen(CEA), TG. In the secondary selection, there were eight items which only one reagent was available.(ferritin, TG, CA19-9, SCC, β-HCG, vitaminB12, folate, free testosterone), two reagents were available(TG Ab, Mic Ab, TSH-R-Ab, CA125, CA72-4, intact PTH, calcitonin), three reagents were available(T3, Tree T3, Free T4, TSH, CEA). Reasons excluded from the secondary selection were the lack of reagent supply for comparative evaluations, the problems with data reproducibility, and the inability to accept data variations. The most problematic part of comparative evaluations was sample collection. It didn't matter if the number of samples requested was large and the capacity needed for the test was small. It was difficult to collect various concentration samples in the case of a small number of tests(100 cases per month or less), and it was difficult to conduct a recovery rate test in the case of a relatively large volume of samples required for a single test(more than 100 uL). In addition, the lack of dilution solution or standard zero material for sensitivity measurement or dilution tests was one of the problems. Conclusion Comparative evaluation for changing test reagents require appropriate preparation time to collect diverse and sufficient samples. In addition, setting the total sample volume and reagent volume range required for comparative evaluations, depending on the sample volume and reagent volume required for one test, will reduce the burden of sample collection and planning for each comparative evaluation.