• 기호학연구
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• no.56
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• pp.45-70
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• 2018

Criticism of the postmodern philosophy of the system of representation, which has continued since the Renaissance, is based on a critique of the dichotomy that separates the subjects and objects and the environment from the human being. Interactivity, highlighted in a series of works emerging as postmodern trends in the 1960s, was transmitted to an interactive aspect of digital art in the late 1990s. The key feature of digital art is the possibility of infinite variations reflecting unpredictable changes based on public participation on the spot. In this process, the importance of computer programs is highlighted. Instead of using the existing program as it is, more and more artists are creating and programming their own algorithms or creating unique algorithms through collaborations with programmers. We live in an era of paradigm shift in which programming itself must be considered as a creative act. Simulation technology and VR technology draw attention as a technique to represent the meaning of reality. Simulation technology helps artists create experimental works. In fact, Baudrillard's concept of Simulation defines the other reality that has nothing to do with our reality, rather than a reality that is extremely representative of our reality. His book Simulacra and Simulation refers to the existence of a reality entirely different from the traditional concept of reality. His argument does not concern the problems of right and wrong. There is no metaphysical meaning. Applying the concept of simulation to algorithmic art, the artist models the complex attributes of reality in the digital system. And it aims to build and integrate internal laws that structure and activate the world (specific or individual), that is to say, simulate the world. If the images of the traditional order correspond to the reproduction of the real world, the synthesized images of algorithmic art and simulated space-time are the forms of art that facilitate the experience. The moment of seeing and listening to the work of Ian Cheng presented in this article is a moment of personal experience and the perception is made at that time. It is not a complete and closed process, but a continuous and changing process. It is this active and situational awareness that is required to the audience for the comprehension of post-representation's forms.

• Journal of Chest Surgery
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• v.30 no.5
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• pp.471-478
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• 1997

Introduction: The use of rabbits as a cardiopulmonary bypass(CPB) animal model is extremely dif%cult mainly due to technical problems. On the other hand, deep hypothermic circulatory arrest(CA) is used to facilitate surgical repair in a variety of cardiac diseases. Although steroids are generally known to be effective in the treatment of cerebral edema, the protective effects of steroids on the brain during CA are not conclusively established. Objectives of this study are twofold: the establishment of CPB technique in rabbits and the evaluation of preventive effect of steroid on the development of brain edema during CA. Material '||'&'||' Methods: Fifteen New Zealan white rabbits(average body weight 3.5kg) were divided into three experimental groups; control CA group(n=5), CA with Trendelenberg position group(n=5), and CA with Trendelenberg position + steroid(methylprednisolone 30 mglkg) administration group(n=5). After anesthetic induction and tracheostomy, a median sternotomy was performed. An aortic cannula(3.3mm) and a venous ncannula(14 Fr) were inserted, respectively in the ascending aorta and the right atrium. The CPB circuit consisted of a roller pump and a bubble oxygenator. Priming volume of the circuit was approximately 450m1 with 120" 150ml of blood. CPB was initiated at a flow rate of 80~85ml/kg/min, Ten min after the start of CPB, CA was established with duration of 40min at $20^{\circ}C$ of rectal temperature. After CA, CPB was restarted with 20min period of rewarming. Ten min after weaning, the animal was sacrif;cod. One-to-2g portions of the following tissues were rapidly d:ssected and water contents were examined and compared among gr ups: brain, cervical spinal cord, kidney, duodenum, lung, heart, liver, spleen, pancreas. stomach. Statistical significances were analyzed by Kruskal-Wallis nonparametric test. Results: CPB with CA was successfully performed in all cases. Flow rate of 60-100 mlfkgfmin was able to be maintained throughout CPB. During CPB, no significant metabolic acidosis was detected and aortic pressure ranged between 35-55 mmHg. After weaning from CPB, all hearts resumed normal beating spontaneously. There were no statistically significant differences in the water contents of tissues including brain among the three experimental groups. Conclusion: These results indicate (1) CPB can be reliably administered in rabbits if proper technique is used, (2) the effect of steroid on the protection of brain edema related to Trendelenburg position during CA is not established within the scope of this experiment.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.