• Journal of Korean Home Economics Education Association
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• v.18 no.3 s.41
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• pp.1-22
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• 2006

The purpose of this study is that I should look for a desirous directions about home economics by studying the requirements and perception of the high school parents who have finished the course of home economics. It was about 600 parents whom I have searched Seoul-Pusan, Ganwon. Ghynggi province, Choongcheong-Gyungsang province, Cheonla and Jeju province of 600, I chose only 560 as apparently suitable research. The questions include 61 requirements about home economics and one which we never fail to keep among the contents, whenever possible and one about the perception of home economics aims 11 about the perception of home economics courses and management. The collections were analyzed frequency, percent, mean. standard deviation t-test by using SAS program. The followings is the summary result of studying of it. 1. All the boys and girls learning together about the Idea of healthy lives and desirous human formulation and knowledge together are higher. 2. Among the teaching purposes of home economics, the item of the scientific principle and knowledge for improvements of home life shows 15.7% below average value. 3. The recognition degree about the quality of home economics is highly related with the real life, and about the system. we recognize lacking in periods and contents of home economics field and about guiding content, accomplishment and application qualities are higher regardless of sex. 4. The important term which we should emphasize in the subject of home economics is family part. 5. Among the needs of home economic requirement in freshman, in the middle unit, their growth and development are higher than anything else, representing 4.11, and by contrast the basic principle and actuality is 3.70, which is lowest among them. 6. In the case of second grade requirement of home economics content for parents in the middle unit young man and consuming life is 4.09 highest. 7. In the case of 3rd grade requirement of economics contents in the middle unit the choice of coming direction and job ethics is highest 4.16, and preparing meals and evaluation is lowest 3.50.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.185-202
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• 2012

.Since the value of information has been realized in the information society, the usage and collection of information has become important. A facial expression that contains thousands of information as an artistic painting can be described in thousands of words. Followed by the idea, there has recently been a number of attempts to provide customers and companies with an intelligent service, which enables the perception of human emotions through one's facial expressions. For example, MIT Media Lab, the leading organization in this research area, has developed the human emotion prediction model, and has applied their studies to the commercial business. In the academic area, a number of the conventional methods such as Multiple Regression Analysis (MRA) or Artificial Neural Networks (ANN) have been applied to predict human emotion in prior studies. However, MRA is generally criticized because of its low prediction accuracy. This is inevitable since MRA can only explain the linear relationship between the dependent variables and the independent variable. To mitigate the limitations of MRA, some studies like Jung and Kim (2012) have used ANN as the alternative, and they reported that ANN generated more accurate prediction than the statistical methods like MRA. However, it has also been criticized due to over fitting and the difficulty of the network design (e.g. setting the number of the layers and the number of the nodes in the hidden layers). Under this background, we propose a novel model using Support Vector Regression (SVR) in order to increase the prediction accuracy. SVR is an extensive version of Support Vector Machine (SVM) designated to solve the regression problems. The model produced by SVR only depends on a subset of the training data, because the cost function for building the model ignores any training data that is close (within a threshold ${\varepsilon}$) to the model prediction. Using SVR, we tried to build a model that can measure the level of arousal and valence from the facial features. To validate the usefulness of the proposed model, we collected the data of facial reactions when providing appropriate visual stimulating contents, and extracted the features from the data. Next, the steps of the preprocessing were taken to choose statistically significant variables. In total, 297 cases were used for the experiment. As the comparative models, we also applied MRA and ANN to the same data set. For SVR, we adopted '${\varepsilon}$-insensitive loss function', and 'grid search' technique to find the optimal values of the parameters like C, d, ${\sigma}^2$, and ${\varepsilon}$. In the case of ANN, we adopted a standard three-layer backpropagation network, which has a single hidden layer. The learning rate and momentum rate of ANN were set to 10%, and we used sigmoid function as the transfer function of hidden and output nodes. We performed the experiments repeatedly by varying the number of nodes in the hidden layer to n/2, n, 3n/2, and 2n, where n is the number of the input variables. The stopping condition for ANN was set to 50,000 learning events. And, we used MAE (Mean Absolute Error) as the measure for performance comparison. From the experiment, we found that SVR achieved the highest prediction accuracy for the hold-out data set compared to MRA and ANN. Regardless of the target variables (the level of arousal, or the level of positive / negative valence), SVR showed the best performance for the hold-out data set. ANN also outperformed MRA, however, it showed the considerably lower prediction accuracy than SVR for both target variables. The findings of our research are expected to be useful to the researchers or practitioners who are willing to build the models for recognizing human emotions.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.12 no.4
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• pp.47-60
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• 2017

As the recent cultural contents area start-ups are creating remarkable outcomes such as investment attraction together with the reinforced institutional supports from the government, this study aimed to reverify the significance of researches related to correlation analysis between service of Business Incubating Center of Small & Medium Business Administration operated with no separation of business type, and corporate performance, in the aspect of Business Incubating Center in cultural contents area, and also to suggest the importance of establishing the business incubating system in the systematic and rational cultural contents area through the differentiated business incubating service by verifying the significant effects of the business validity of items on corporate performance, and then discovering services suitable for business incubating in cultural contents area, targeting Gyeonggi-do cultural contents area Business Incubating Center recently showing the biggest growth. Especially, contrary to the existing researches, in order to verify the characteristics of Gyeonggi-do Cultural Contents Business Incubating Center, the personal support service and marketing support service were included. It also aimed to understand the effects of the business validity of start-up items on corporate performance. Summarizing the results of this study, contrary to the results of the existing researches saying that spatial & additional support service, management support service, technical support service, personal support service, and marketing support service had significant effects on corporate performance, among the support service of Gyeonggi-do cultural contents area Business Incubating Center, the spatial & additional support service, personal support service, and marketing support service had significantly positive(+) effects on corporate performance while the management support service and technical support service had no significant effects on it. Comparing with the results of the researches on the support service of Business Incubating Center(BI) of Small & Medium Business Administration, the effects of the management support service and technical support service of Gyeonggi-do cultural contents area Business Incubating Center on corporate financial/non-financial performance were not huge. Also, in the results of analyzing the business validity of star-up items, the spatial & additional support service, management support service, and technical support service did not have significant effects on the business validity of start-up items while the personal support service and marketing support service had significantly positive(+) effects on it. In case when selecting companies, Gyeonggi-do Business Incubating Center emphasized the business validity of start-up items. However, the support service provided after the selection did not have huge effects on the business validity of start-up items. Lastly, in the results of analyzing the effects of the business validity of start-up items in Gyeonggi-do cultural contents area on corporate performance, among the success factors of business start-up, the business validity of start-up items was an important element having effects on corporate performance(financial/non-financial) in the cultural contents area.

• Clinical and Experimental Reproductive Medicine
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• v.35 no.2
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• pp.119-129
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• 2008

Objective: The purpose of this study was to quantify decidual $CD56^+$ and $CD16^+$ NK cell subtype population and to evaluate the correlation between decidual NK cell expression and peripheral $CD56^+$ NK cell expression in women with a history of recurrent abortion and increased peripheral NK cells. Methods: Twenty-nine women with recurrent abortion and elevated peripheral $CD56^+$ NK cell percentage who had chromosomally normal conceptus were included in this study. Thirty-two women with recurrent abortion who had chromosomally abnormal conceptus were used as controls. Distribution of $CD56^+$ and $CD16^+$ NK cells in decidual tissues including implantation sites was examined by immunohistochemical staining. The degree of immunohistochemical staining was interpreted by score and percentage. Results: There was a significant difference in decidual $CD56^+$ NK cell score ($43.6{\pm}24.5$ vs. $23.9{\pm}16.3$ P =0.001) and $CD56^+$ NK cell percentage ($42.1{\pm}11.7$ vs. $33.9{\pm}15.8$ P =0.027) between increased peripheral NK cell group and control group. However, there was no statistically significant difference in decidual $CD16^+$ NK cell score ($18.7{\pm}9.5$ vs. $13.2{\pm}39.4$ P =0.108) and $CD16^+$ NK cell percentage ($24.7{\pm}5.9$ vs. $23.4{\pm}11.7$ P =0.599). There was no significant correlation between decidual NK cell score and peripheral NK cell percentage in increase peripheral NK cell group (peripheral $CD56^+$ NK cell percentage vs. decidual $CD56^+$ NK cell score, r=-0.016, P =0.932, peripheral $CD16^+$ NK cell percentage vs. decidual $CD16^+$ NK cell score, r=0.008, P =0.968). Conclusion: This study shows that $CD56^+$ decidual NK cells are increased in decidua of women exhibiting a history of recurrent abortion with increased $CD56^+$ peripheral NK cell. There was no significant correlation between decidual and peripheral NK cell increment in increase peripheral NK cell group. This study suggests the possibility that decidual NK cells may play an important role in the immune mechanism of recurrent abortion.

• Journal of agricultural medicine and community health
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• v.26 no.1
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• pp.37-56
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• 2001

This study was conducted to analyze the degree of changes in knowledge and attitude toward smoking and to examine the factors affecting knowledge and attitude for smoking after providing a smoking prevention program based on social influence model for a year to middle school students. Study population consists of 665 subjects of middle school students(aged 14 years) in Gumi city in Kyeongsangbukdo Province. Among them three-hundred sixty-seven students(intervention group) were educated to a smoking prevention program for 1 year from April 1999 to April 2000. School-based four-class program to prevent smoking was developed. The program provides instruction about short and long-term negative physiologic and social consequences of smoking and also discussed the health hazards of smoking, social pressure to smoke, peer norms regarding tobacco use, and refusal skill. A 45-item self-administered structured questionnaire was designed to evaluate the change of knowledge, attitude, smoking rate and the amount of smoking. The instrument was comprised of 11 knowledge items, thirteen attitude item and demographic items. Each scales were created by summing responses to each items within each scales and high scores on the knowledge, attitude, and smoking behavioral intention scales indicated positive responses. Based on the changes before and after the implementation of smoking prevention program between intervention and control group, the change of scores on knowledge were significantly different between the control group and the intervention group(p<0.05) and the change of scores on the attitude toward smoking was significantly different between intervention and control group. The change of smoking rate were not showing a significant difference between two groups but the amount of smoking were significantly reduced in intervention group than control group. In multiple regression analysis on changes of knowledge about smoking, the variables of smoking prevention program education, previous knowledge on smoking and students' school performance were selected the significant variables. In multiple regression to analysis of the factors influencing changes in attitude toward smoking, the variables of smoking prevention program education, previous knowledge on smoking were shown to be significant. The smoking prevention program was effective on change of knowledge and attitude of middle school students. In considering that the policy should be needed to extent of implementation of school-based health education curricula based on social influence model and it would contribute to reduce smoking of students.

• Tuberculosis and Respiratory Diseases
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• v.43 no.2
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• pp.190-200
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• 1996

Background : Mechanical ventilation constitutes the last therapeutic method for acute respiratory failure when oxygen therapy and medical treatment fail to improve the respiratory status of the patient. This invasive ventilation, classically administered by endotracheal intubation or by tracheostomy, is associated with significant mortality and morbidity. Consequently, any less invasive method able to avoid the use of endotracheal ventilation would appear to be useful in high risk patient. Over recent years, the efficacy of nasal mask ventilation has been demonstrated in the treatment of chronic restrictive respiratory failure, particularly in patients with neuromuscular diseases. More recently, this method has been successfully used in the treatment of acute respiratory failure due to parenchymal disease. Method : We assessed the efficacy of Bilevel positive airway pressure(BiPAP) in the treatment of acute exacerbation of chronic obstructive pulmonary disease(COPD). This study prospectively evaluated the clinical effectiveness of a treatment schedule with positive pressure ventilation via nasal mask(Respironics BiPAP device) in 22 patients with acute exacerbations of COPD. Eleven patients with acute exacerbations of COPD were treated with nasal pressure support ventilation delivered via a nasal ventilatory support system plus standard treatment for 3 consecutive days. An additional 11 control patients were treated only with standard treatment. The standard treatment consisted of medical and oxygen therapy. The nasal BiPAP was delivered by a pressure support ventilator in spontaneous timed mode and at an inspiratory positive airway pressure $6-8cmH_2O$ and an expiratory positive airway pressure $3-4cmH_2O$. Patients were evaluated with physical examination(respiratory rate), modified Borg scale and arterial blood gas before and after the acute therapeutic intervention. Results : Pretreatment and after 3 days of treatment, mean $PaO_2$ was 56.3mmHg and 79.1mmHg (p<0.05) in BiPAP group and 56.9mmHg and 70.2mmHg (p<0.05) in conventional treatment (CT) group and $PaCO_2$ was 63.9mmHg and 56.9mmHg (p<0.05) in BiPAP group and 53mmHg and 52.8mmHg in CT group respectively. pH was 7.36 and 7.41 (p<0.05) in BiPAP group and 7.37 and 7.38 in cr group respectively. Pretreatment and after treatment, mean respiratory rate was 28 and 23 beats/min in BiPAP group and 25 and 20 beats/min in CT group respectively. Borg scale was 7.6 and 4.7 in BiPAP group and 6.4 and 3.8 in CT group respectively. There were significant differences between the two groups in changes of mean $PaO_2$, $PaCO_2$ and pH respectively. Conclusion: We conclude that short-term nasal pressure-support ventilation delivered via nasal BiPAP in the treatment of acute exacerbation of COPD, is an efficient mode of assisted ventilation for improving blood gas values and dyspnea sensation and may reduce the need for endotracheal intubation with mechanical ventilation.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.49-65
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• 2014

Word of Mouth (WOM) is a behavior used by consumers to transfer or communicate their product or service experience to other consumers. Due to the popularity of social media such as Facebook, Twitter, blogs, and online communities, electronic WOM (e-WOM) has become important to the success of products or services. As a result, most enterprises pay close attention to e-WOM for their products or services. This is especially important for movies, as these are experiential products. This paper aims to identify the network factors of an online movie community that impact box office revenue using social network analysis. In addition to traditional WOM factors (volume and valence of WOM), network centrality measures of the online community are included as influential factors in box office revenue. Based on previous research results, we develop five hypotheses on the relationships between potential influential factors (WOM volume, WOM valence, degree centrality, betweenness centrality, closeness centrality) and box office revenue. The first hypothesis is that the accumulated volume of WOM in online product communities is positively related to the total revenue of movies. The second hypothesis is that the accumulated valence of WOM in online product communities is positively related to the total revenue of movies. The third hypothesis is that the average of degree centralities of reviewers in online product communities is positively related to the total revenue of movies. The fourth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. The fifth hypothesis is that the average of betweenness centralities of reviewers in online product communities is positively related to the total revenue of movies. To verify our research model, we collect movie review data from the Internet Movie Database (IMDb), which is a representative online movie community, and movie revenue data from the Box-Office-Mojo website. The movies in this analysis include weekly top-10 movies from September 1, 2012, to September 1, 2013, with in total. We collect movie metadata such as screening periods and user ratings; and community data in IMDb including reviewer identification, review content, review times, responder identification, reply content, reply times, and reply relationships. For the same period, the revenue data from Box-Office-Mojo is collected on a weekly basis. Movie community networks are constructed based on reply relationships between reviewers. Using a social network analysis tool, NodeXL, we calculate the averages of three centralities including degree, betweenness, and closeness centrality for each movie. Correlation analysis of focal variables and the dependent variable (final revenue) shows that three centrality measures are highly correlated, prompting us to perform multiple regressions separately with each centrality measure. Consistent with previous research results, our regression analysis results show that the volume and valence of WOM are positively related to the final box office revenue of movies. Moreover, the averages of betweenness centralities from initial community networks impact the final movie revenues. However, both of the averages of degree centralities and closeness centralities do not influence final movie performance. Based on the regression results, three hypotheses, 1, 2, and 4, are accepted, and two hypotheses, 3 and 5, are rejected. This study tries to link the network structure of e-WOM on online product communities with the product's performance. Based on the analysis of a real online movie community, the results show that online community network structures can work as a predictor of movie performance. The results show that the betweenness centralities of the reviewer community are critical for the prediction of movie performance. However, degree centralities and closeness centralities do not influence movie performance. As future research topics, similar analyses are required for other product categories such as electronic goods and online content to generalize the study results.

• Journal of Chest Surgery
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• v.32 no.3
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• pp.224-236
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• 1999

Background: To evaluate the short-term effect of dynamic cardiomyoplasty on circulatory function and detect the related factors that can affect it, experimental cardiomyoplasties were performed under the state of normal cardiac function and heart failure. Material and Method: A total of 10 mongrel dogs weighing 20 to 30kg were divided arbitrarily into two groups. Five dogs of group A underwent cardiomyoplasty with latissimus dorsi(LD) muscle mobilization followed by a 2-week vascular delay and 6-week muscle training. Then, hemodynamic studies were conducted. In group B, doxorubicin was given to 5 dogs in an IV dose of 1 mg/kg once a week for 8 weeks to induce chronic heart failure, and simultaneous muscle training was given for preconditioning during this period. Then, cardiomyoplasties were performed and hemodynamic studies were conducted immediately after these cardiomyoplasties in group B. Result: In group A, under the state of normal cardiac function, only mean right atrial pressure significantly increased with the pacer-on(p<0.05) and the left ventricular hemodynamic parameters did not change significantly. However, with pacer-on in group B, cardiac output(CO), rate of left ventricular pressure development(dp/dt), stroke volume(SV), and left ventricular stroke work(SW) increased by 16.7${\pm}$7.2%, 9.3${\pm}$3.2%, 16.8${\pm}$8.6%, and 23.1${\pm}$9.7%, respectively, whereas left ventricular end-diastole pressure(LVEDP) and mean pulmonary capillary wedge pressure(mPCWP) decreased by 32.1${\pm}$4.6% and 17.7${\pm}$9.1%, respectively(p<0.05). In group A, imipramine was infused at the rate of 7.5mg/kg/hour for 34${\pm}$2.6 minutes to induce acute heart failure, which resulted in the reduction of cardiac output by 17.5${\pm}$2.7%, systolic left ventricular pressure by 15.8${\pm}$2.5% and the elevation of left ventricular end-diastole pressure by 54.3${\pm}$15.2%(p<0.05). With pacer-on under this state of acute heart failu e, CO, dp/dt, SV, and SW increased by 4.5${\pm}$1.8% and 3.1${\pm}$1.1%, 5.7${\pm}$3.6%, and 6.9${\pm}$4.4%, respectively, whereas LVEDP decreased by 11.7${\pm}$4.7%(p<0.05). Comparing CO, dp/dt, SV, SW and LVEDP that changed significantly with pacer-on, both under the state of acute and chronic heart failure, augmentation widths of these left ventricular hemodynamic parameters were significantly larger under the state of chronic heart failure(group B) than acute heart failure(group A)(p<0.05). On gross inspection, variable degrees of adhesion and inflammation were present in all 5 dogs of group A, including 2 dogs that showed no muscle contraction. No adhesion and inflammation were, however, present in all 5 dogs of group B, which showed vivid muscle contractions. Considering these differences in gross findings along with the following premise that the acute heart failure state was not statistically different from the chronic one in terms of left ventricular parameters(p>0.05), the larger augmentation effect seen in group B is presumed to be mainly attributed to the viability and contractility of the LD muscle. Conclusion: These results indicate that the positive circulatory augmentation effect of cardiomyoplasty is apparent only under the state of heart failure and the preservation of muscle contractility is important to maximize this effect.

• Journal of Korean Society of Transportation
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• v.20 no.7
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• pp.155-166
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• 2002

Since 1990s. there has been an increasing number of traffic accidents at intersection. which requires more urgent measures to insure safety on intersection. This study set out to analyze the road conditions, traffic conditions and traffic operation conditions on signalized intersection. to identify the elements that would impose obstructions in safety, and to develop a traffic accident prediction model to evaluate the safety of an intersection using the cop relation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on the intersection in developing a traffic accident prediction model fir a signalized intersection. The data for the study was collected at an intersection located in Wonju city from January to December 2001. It consisted of the number of accidents, the road conditions, the traffic conditions, and the traffic operation conditions at the intersection. The collected data was first statistically analyzed and then the results identified the elements that had close correlations with accidents. They included the area pattern, the use of land, the bus stopping activities, the parking and stopping activities on the road, the total volume, the turning volume, the number of lanes, the width of the road, the intersection area, the cycle, the sight distance, and the turning radius. These elements were used in the second correlation analysis. The significant level was 95% or higher in all of them. There were few correlations between independent variables. The variables that affected the accident rate were the number of lanes, the turning radius, the sight distance and the cycle, which were used to develop a traffic accident prediction model formula considering their distribution. The model formula was compared with a general linear regression model in accuracy. In addition, the statistics of domestic accidents were investigated to analyze the distribution of the accidents and to classify intersections according to the risk level. Finally, the results were applied to the Spearman-rank correlation coefficient to see if the model was appropriate. As a result, the coefficient of determination was highly significant with the value of 0.985 and the ranks among the intersections according to the risk level were appropriate too. The actual number of accidents and the predicted ones were compared in terms of the risk level and they were about the same in the risk level for 80% of the intersections.