• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.4
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• pp.325-334
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• 2008

The standard prestressed concrete I-girder bridge (PSC I-girder bridge) is one of the most prevalent types for small and medium bridges in Korea. When determining the member forces in a section to assess the safety of girder in this type of bridge, the general practice is to use the simplified practical equations or the live load distribution factors proposed in design standards rather than the precise analysis through the finite element method or so. Meanwhile, the live load distribution factors currently used in Korean design practice are just a reflection of overseas research results or design standards without alterations. Therefore, it is necessary to develop an equation of the live load distribution factors fit for the design conditions of Korea, considering the standardized section of standard PSC I-girder bridges and the design strength of concrete. In this study, to develop an equation of the live load distribution factors, a parametric analysis and sensitivity analysis were carried out on the parameters such as width of bridge, span length, girder spacing, width of traffic lane, etc. As a result, the major variables to determine the size of distribution factors were girder spacing, overhang length and span length in case of external girders. For internal adjacent girders, the determinant factors were girder spacing, overhang length, span length and width of bridge. For internal girders, the factors were girder spacing, width of bridge and span length. Then, an equation of live load distribution factors was developed through the multiple linear regression analysis on the results of parametric analysis. When the actual practice engineers design a bridge with the equation of live load distribution factors developed here, they will determine the design of member forces ensuring the appropriate safety rate more easily. Moreover, in the preliminary design, this model is expected to save much time for the repetitive design to improve the structural efficiency of PSC I-girder bridges.

• Tuberculosis and Respiratory Diseases
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• v.50 no.4
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• pp.426-436
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• 2001

Background : Chronic obstructive pulmonary disease(COPD) is one of the major contributors to morbidity and mortality among the adult population. Cigarette smoking(CS) is undoubtedly the single most important factor in the pathogenesis of COPD. However, its mechanism is unclear. The current hypothesis regarding the pathogenesis of COPD postulates that an imbalance between proteases and antiproteases leads to the destructive changes in the lung parenchyma. This study had two aims. First, to evaluate the effect of CS exposure on histologic changes of the lung parenchyme, and second, to evaluate the effect of CS exposure on the expression of the gelatinolytic enzymes in BAL fluid cells in guinea pigs. Methods : Two groups of five guinea pigs were exposed to the whole smoke of 20 commercial cigarettes per day, 5 hours/day, 5 days/week, for 6weeks, and 12 weeks, respectively, using a smoking apparatus. Five age-matched guinea pigs exposed to room air were used as controls. Five or more sections were microscopically extamined(${\times}400$) and the number of cellular infiltration of the alveolar wall was measured in order to evaluate the effect of CS exposure on the histologic changes of lung parenchyme. The statistical significance was analyzed by a linear regression method. To evaluate the expression of the gelatinolytic enzymes in intraalveolar cells, BAL fluid was obtained and the intraalveolar cells were separated by centrifugation (500 g for 10 min at $4^{\circ}C$). Two sets of culture plates were loaded with $1{\times}10^6$ intraalveolar cells. One plate, contained O.1mM EDTA, a inhibitor of matrix metalloproteases(MMPs), and the other plate had no EDTA. Both plates were incubated for 48 hours at $37^{\circ}C$. After incubation, gelatinolytic protease expression in the supernatants was analyzed by gelatin zymography. Results : At the end of CS exposure, the level of blood carboxy Hb had increased significantly(4.1g/dl in control group, 24g/dl immediately after CS exposure, 18g/dl 30 min after CS exposure, 15g/dl 1 hour after CS exposure). Alveolar inflammatory cells were identified in the CS exposed guinea pigs. The number of alveolar cellular cells observed in a microscopic field ($400{\times}$) was $121.4{\pm}7.2$, $158.0{\pm}20.2$, $196.8{\pm}32.8$, in the control, the 6 weeks, and the 12 weeks group, respectively. The increased extent of inflammatory cellular infiltration of the lung parenchema showed a statistically significant linear relationship with the duration of CS exposure(p=0.001, $r^2=0.675$). Several types of gelatinolytic enzymes in the intraalveolar cells of CS exposed guinea pigs were expressed, of which some were inhibited by EDT A. However, the gelatinolytic enzymes were not expressed in the control groups. Conclusion : CS exposure increases inflammatory cellular infiltration of the alveolar wall and the expression of gelatinolytic proteases in guinea pigs. EDTA inhibits some of the gelatinolytic proteases. These findings suggest a possibility that CS exposure may increase MMP expression in the lungs of guinea pigs.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.