• Proceedings of the Zoological Society Korea Conference
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• 1994.10a
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• pp.247.2-247
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• 1994

No Abstract, See Full Text

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.183.2-183
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• 1999

No Abstract, See Full Text

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.278.1-278
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• 1999

No Abstract, See Full Text

• Journal of information and communication convergence engineering
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• v.15 no.4
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• pp.217-226
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• 2017

Korea has the tenth largest film industry in the world; however, detailed analyses using the factors contributing to successful film commercialization have not been approached. Using big data, this paper analyzed both internal and external factors (including genre, release date, rating, and number of screenings) that contributed to the commercial success of Korea's top 10 ranking films in 2011-2015. The authors developed a WebCrawler to collect text data about each movie, implemented a Hadoop system for data storage, and classified the data using Map Reduce method. The results showed that the characteristic of "release date," followed closely by "rating" and "genre" were the most influential factors of success in the Korean film industry. The analysis in this study is considered groundwork for the development of software that can predict box-office performance.

• Archives of design research
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• v.17 no.1
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• pp.127-134
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• 2004

The purpose of this study was to compare data input interfaces used in e-business applications on the web and find optimal input design characteristics. Basic data entry tools such as a pull down menu, list, text input box, and radio button were examined by inputting data into a simulated hotel room reservation web site. Experimental results indicated that the text input box was most efficient for experts or experienced operators when there are more than four menu-items and pull down menu was considered most satisfactory, simplest, and easier to use for novices or unexperienced users. A simple list was determined to be the best for the input of binary data considering user's satisfaction, simplicity, and flexibility but radio button was evaluated best for the ease to use. Design guide lines of this study can be applied to build a usable interactive web sites and increase economic efficiency.

• Health Policy and Management
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• v.10 no.1
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• pp.31-56
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• 2000

A purpose of this study is to study on Rene Descartes's mind-body theory in medical aspect. Though Rene Descartes was not so much a doctor as a philosopher, he had health and medical science at heart. When he came into the world in 1596, he was in poor health. Therefore, he suffered from his bad health. Descartes's ideas absolutely colored Western thought for three hundred years, especially, his mind-body theory, mechanistic life-view, and reductionism had important effect on medical study and science of public health. As a rule, we know that his mind-body theory was applicable to mind-body dualism, and his mind-body dualism was connected with biomedical model of medicine. But by this study, his mind-body theory was not only mind-body dualism but also mind-body monoism. And he asserted mind-body interaction too. In other words, he advocated mind-body dualism in scientific aspect, but he knew mind-body monoism from his experence. He confessed this fact to Princess Elizabeth of Bohemia, he wrote mind-body interaction in $\boxDr$Discours de la methode$\boxUl$, $\boxDr$Meditationes de prima philosophia$\boxUl$, and $\boxDr$Traite des passions de 1'ame$\boxUl$ etc. However, only mind-body dualism of his mind-body theories was written in our medical text book, morever mental realm was excluded from the persuit of learning Descartes advocated a mechanistic world-view and mechanistic life-view, he regarded human body as a machine part. And a paticent corresponds to a troubled machine, a doctor deserves a repairman. But this point of view made holistic understanding of man impossible. Descartes divide the whole into basic building blocks, we named the approach Reductionism. Reductionism led to ontological concept in medical science, bacteriology established 'specific cause-specific disease-specific therapy'. We examined medical influence of Descartes's thought, we need to draw out a philosophic basis of medical science and science of public health by a close study of his records.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1419-1429
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• 2014

In this paper, we consider the development of encryption of DES (data encryption standard) based on Microsoft Excel Macro, which was adopted as the FIPS (federal information processing standard) 46 of USA in 1977. Concrete explanation of DES is given. Algorithms for DES encryption are adapted to Excel Macro. By repeating the 16 round which is consisted of diffusion (which hide the relation between plain text and cipher text) and the confusion (which hide the relation between cipher key and cipher text) with Excel Macro, we can easily get the desired DES cipher text.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.87-96
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• 2021

The demand for e-learning through video lectures is rapidly increasing due to its diverse advantages over the traditional learning methods. This led to massive volumes of web-based lecture videos. Indexing and retrieval of a lecture video or a lecture video topic has thus proved to be an exceptionally challenging problem. Many techniques listed by literature were either visual or audio based, but not both. Since the effects of both the visual and audio components are equally important for the content-based indexing and retrieval, the current work is focused on both these components. A framework for automatic topic-based indexing and search depending on the innate content of the lecture videos is presented. The text from the slides is extracted using the proposed Merged Bounding Box (MBB) text detector. The audio component text extraction is done using Google Speech Recognition (GSR) technology. This hybrid approach generates the indexing keywords from the merged transcripts of both the video and audio component extractors. The search within the indexed documents is optimized based on the Naïve Bayes (NB) Classification and K-Means Clustering models. This optimized search retrieves results by searching only the relevant document cluster in the predefined categories and not the whole lecture video corpus. The work is carried out on the dataset generated by assigning categories to the lecture video transcripts gathered from e-learning portals. The performance of search is assessed based on the accuracy and time taken. Further the improved accuracy of the proposed indexing technique is compared with the accepted chain indexing technique.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.77-84
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• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.510-512
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• 2003

본 논문에서는 문서의 자동 분류를 위한 용어 빈도 가중치 계산 방법으로 Box-Cox변환기법을 응용한 정규화 용어빈도 가중치를 정의하고, 이를 문서 분류에 적응하였다. 여기서 Box-Cox 변환기법이란 자료를 정규분포화 할 때 적용하는 통계적인 변환방법으로서, 본 논문에서는 이를 응용하여 새로운 용어빈도가중치 계산법을 제안한다. 문서에서 등장한 용어 빈도는 너무 많거나 적게 등장할 경우, 중요도가 떨어지게 되는데, 이는 용어의 중요도가 빈도에 따른 정규분포로 모델링 될 수 있다는 것을 의미한다. 또한 정규화 가중치 계산방법은 기존의 용어빈도 가중치 공식과 비교할 때, 용어마다 계산방법이 달라져, 로그나 루트와 같은 고정된 가중치 방법보다는 좀더 일반적인 방법이라 할 수 있다. 신문기사 8000건을 대상으로 4개의 그룹으로 나누어 실험 한 결과, 정규화 용어빈도가중치 계산방법이 모두 우위의 분류 정확도롤 가져, 본 논문에서 제안한 방법이 타당함을 알 수 있다.