• Title/Summary/Keyword: Human Interaction

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Prognostic Value of the Expression of p53 and bcl-2 in Non-Small Cell Lung Cancer (비소세포폐암에서 p53과 bcl-2의 발현이 예후에 미치는 영향)

  • Yang, Seok-Chul;Yoon, Ho-Joo;Shin, Dong-Ho;Park, Sung-Soo;Lee, Jung-Hee;Keum, Joo-Seob;Kong, Gu;Lee, Jung-Dal
    • Tuberculosis and Respiratory Diseases
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    • v.45 no.5
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    • pp.962-974
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    • 1998
  • Background: Alteration of p53 tumor suppressor genes is most frequently identified in human neoplasms, including lung carcinoma. It is well known that bcl-2 oncoprotein protects cells from apoptosis. Recent studies have demonstrated that bcl-2 expression is associated with favorable prognosis for patients with non-small cell lung carcinoma. However, the precise biologic role of bcl-2 in the development of these tumors is still obscure. p53 and bcl-2 have important regulatory influence in the apoptotic pathway and thus their relationship is of interest in tumorigenesis, especially lung cancer. Purpose: The author investigated to know the prognostic significance of the expression of p53 and bcl-2 in radically resected non-small cell lung cancer. Method: 84 cases of formalin-fixed paraffin-embedded blocks from resected primary non-small cell lung cancer from 1980 to 1994 at Hanyang University Hospital were available for both clinical follow-up and immunohistochemical staining using monoclonal antibodies for p53 and bcl-2. Results : The histologic classification of the tumor was based on WHO criteria., and the specimens included 45 squamous cell carcinomas(53.6%), 28 adeonocarcinomas(33.3%) and 11 large cell carcinomas(13.1 %). p53 immunoreactivity was noted in 47 cases of 84 cases(56.0%). bcl-2 immunoreactivity was noted in 15 cases of 84 cases(17.9%). The mean survival duration was $64.23{\pm}10.73$ months in bcl-2 positive group and $35.28{\pm}4$. 39 months in bcl-2 negative group. The bcl-2 expression was significantly correlated with survival in radically resected non-small cell lung cancer patients(p=0.03). The mean survival duration was $34.71{\pm}6.12$ months in p53 positive group and $45.35{\pm}6.30$ months in p53 negative group(p=0.21). The p53 expression was not predictive for survival. There was no correlation between combination of the different status of p53 and bcl-2 expression in our study. Conclusions : The interaction and the regulation of new biologic markers, such as those involved in the apoptotic pathway, are complex. bcl-2 overexpression is a good prognostic factor in non-small cell lung cancer and p53 expression is not significantly associated with the prognostic factor in non-small cell lung cancer.

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The Audience Behavior-based Emotion Prediction Model for Personalized Service (고객 맞춤형 서비스를 위한 관객 행동 기반 감정예측모형)

  • Ryoo, Eun Chung;Ahn, Hyunchul;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.73-85
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    • 2013
  • Nowadays, in today's information society, the importance of the knowledge service using the information to creative value is getting higher day by day. In addition, depending on the development of IT technology, it is ease to collect and use information. Also, many companies actively use customer information to marketing in a variety of industries. Into the 21st century, companies have been actively using the culture arts to manage corporate image and marketing closely linked to their commercial interests. But, it is difficult that companies attract or maintain consumer's interest through their technology. For that reason, it is trend to perform cultural activities for tool of differentiation over many firms. Many firms used the customer's experience to new marketing strategy in order to effectively respond to competitive market. Accordingly, it is emerging rapidly that the necessity of personalized service to provide a new experience for people based on the personal profile information that contains the characteristics of the individual. Like this, personalized service using customer's individual profile information such as language, symbols, behavior, and emotions is very important today. Through this, we will be able to judge interaction between people and content and to maximize customer's experience and satisfaction. There are various relative works provide customer-centered service. Specially, emotion recognition research is emerging recently. Existing researches experienced emotion recognition using mostly bio-signal. Most of researches are voice and face studies that have great emotional changes. However, there are several difficulties to predict people's emotion caused by limitation of equipment and service environments. So, in this paper, we develop emotion prediction model based on vision-based interface to overcome existing limitations. Emotion recognition research based on people's gesture and posture has been processed by several researchers. This paper developed a model that recognizes people's emotional states through body gesture and posture using difference image method. And we found optimization validation model for four kinds of emotions' prediction. A proposed model purposed to automatically determine and predict 4 human emotions (Sadness, Surprise, Joy, and Disgust). To build up the model, event booth was installed in the KOCCA's lobby and we provided some proper stimulative movie to collect their body gesture and posture as the change of emotions. And then, we extracted body movements using difference image method. And we revised people data to build proposed model through neural network. The proposed model for emotion prediction used 3 type time-frame sets (20 frames, 30 frames, and 40 frames). And then, we adopted the model which has best performance compared with other models.' Before build three kinds of models, the entire 97 data set were divided into three data sets of learning, test, and validation set. The proposed model for emotion prediction was constructed using artificial neural network. In this paper, we used the back-propagation algorithm as a learning method, and set learning rate to 10%, momentum rate to 10%. The sigmoid function was used as the transform function. And we designed a three-layer perceptron neural network with one hidden layer and four output nodes. Based on the test data set, the learning for this research model was stopped when it reaches 50000 after reaching the minimum error in order to explore the point of learning. We finally processed each model's accuracy and found best model to predict each emotions. The result showed prediction accuracy 100% from sadness, and 96% from joy prediction in 20 frames set model. And 88% from surprise, and 98% from disgust in 30 frames set model. The findings of our research are expected to be useful to provide effective algorithm for personalized service in various industries such as advertisement, exhibition, performance, etc.

The Effects of Proinflammatory Cytokines and TGF-beta, on The Fibroblast Proliferation (Proinflammatory Cytokines과 TGF-beta가 섬유모세포의 증식에 미치는 영향)

  • Kim, Chul;Park, Choon-Sik;Kim, Mi-Ho;Chang, Hun-Soo;Chung, Il-Yup;Ki, Shin-Young;Uh, Soo-Taek;Moon, Seung-Hyuk;Kim, Yong-Hoon;Lee, Hi-Bal
    • Tuberculosis and Respiratory Diseases
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    • v.45 no.4
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    • pp.861-869
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    • 1998
  • Backgrounds: The injury of a tissue results in the infalmmation, and the imflammed tissue is replaced by the normal parenchymal cells during the process of repair. But, constitutional or repetitive damage of a tissue causes the deposition of collagen resulting in the loss of its function. These lesions are found in the lung of patients with idiopathic pulmonary fibrosis, complicated fibrosis after diffuse alveolar damage (DAD) and inorganic dust-induced lung fibrosis. The tissue from lungs of patients undergoing episodes of active and/or end-stage pulmonary fibrosis shows the accumulation of inflammatory cells, such as mononuclear cells, neutrophils, mast cells and eosinophils, and fibroblast hyperplasia. In this regard, it appears that the inflammation triggers fibroblast activation and proliferation with enhanced matrix synthesis, stimulated by inflammatory mediators such as interleukin-1 (IL-1) and/or tumor necrosis factor (TNF). It has been well known that TGF-$\beta$ enhance the proliferation of fibroblasts and the production of collagen and fibronectin, and inhibit the degradation of collagen. In this regard, It is likely that TGF-$\beta$ undergoes important roles in the pathogenesis of pulmonary fibrosis. Nevertheless, this single cytokine is not the sole regulator of the pulmonary fibrotic response. It is likely that the balance of many cytokines including TGF-$\beta$, IL-1, IL-6 and TNF-$\alpha$ regulates the pathogenesis of pulmonary fibrosis. In this study, we investigate the interaction of TGF-$\beta$, IL-1$\beta$, IL-6 and TNF-$\alpha$ and their effect on the proliferation of fibroblasts. Methods: We used a human fibroblast cell line, MRC-5 (ATCC). The culture of MRC-5 was confirmed by immunofluorecent staining. First, we determined the concentration of serum in cuture medium, in which the proliferation of MRC-5 is supressed but the survival of MRC-5 is retained. Second, we measured optical density after staining the cytokine-stimulated cells with 0.5% naphthol blue black in order to detect the effect of cytokines on the proliferation of MRC-5. Result: In the medium containing 0.5% fetal calf serum, the proliferation of MRC-5 increased by 50%, and it was maintained for 6 days. IL-1$\beta$, TNF-$\alpha$ and IL-6 induced the proliferation of MRC-5 by 45%, 160% and 120%, respectively. IL-1$\beta$ and TNF-$\alpha$ enhanced TGF-$\beta$-induced proliferation of MRC-5 by 64% and 159%, but IL-6 did not affect the TGF-$\beta$-induced proliferation. And lNF-$\alpha$-induced proliferation of MRC-5 was reduced by IL-1$\beta$ in 50%. TGF-$\beta$, TNF-$\alpha$ and both induced the proliferation of MRC-5 to 89%, 135% and 222%, respectively. Conclusions: TNF-$\alpha$, TGF-$\beta$ and IL-1$\beta$, in the order of the effectiveness, showed the induction of MRC-5 proliferation of MRC-5. TNF-$\alpha$ and IL-1$\beta$ enhance the TGF-$\beta$-induced proliferation of MRC-5, but IL-6 did not have any effect TNF-$\alpha$-induced proliferation of MRC-5 is diminished by IL-1, and TNF-$\alpha$ and TGF-$\beta$ showed a additive effect.

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A Study on Startups' Dependence on Business Incubation Centers (창업보육서비스에 따른 입주기업의 창업보육센터 의존도에 관한 연구)

  • Park, JaeSung;Lee, Chul;Kim, JaeJon
    • Korean small business review
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    • v.31 no.2
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    • pp.103-120
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    • 2009
  • As business incubation centers (BICs) have been operating for more than 10 years in Korea, many early stage startups tend to use the services provided by the incubating centers. BICs in Korea have accumulated the knowledge and experience in the past ten years and their services have been considerably improved. The business incubating service has three facets : (1) business infrastructure service, (2) direct service, and (3) indirect service. The mission of BICs is to provide the early stage entrepreneurs with the incubating service in a limited period time to help them grow strong enough to survive the fierce competition after graduating from the incubation. However, the incubating services sometimes fail to foster the independence of new startup companies, and raise the dependence of many companies on BICs. Thus, the dependence on BICs is a very important factor to understand the survival of the incubated startup companies after graduation from BICs. The purpose of this study is to identify the main factors that influence the firm's dependence on BICs and to characterize the relationships among the identified factors. The business incubating service is a core construct of this study. It includes various activities and resources, such as offering the physical facilities, legal service, and connecting them with outside organizations. These services are extensive and take various forms. They are provided by BICs directly or indirectly. Past studies have identified various incubating services and classify them in different ways. Based on the past studies, we classify the business incubating service into three categories as mentioned above : (1) business infrastructure support, (2) direct support, and (3) networking support. The business infrastructure support is to provide the essential resources to start the business, such as physical facilities. The direct support is to offer the business resources available in the BICs, such as human, technical, and administrational resources. Finally, the indirect service was to support the resource in the outside of business incubation center. Dependence is generally defined as the degree to which a client firm needs the resources provided by the service provider in order to achieve its goals. Dependence is generated when a firm recognizes the benefits of interacting with its counterpart. Hence, the more positive outcomes a firm derives from its relationship with the partner, the more dependent on the partner the firm must inevitably become. In business incubating, as a resident firm is incubated in longer period, we can predict that her dependence on BICs would be stronger. In order to foster the independence of the incubated firms, BICs have to be able to manipulate the provision of their services to control the firms' dependence on BICs. Based on the above discussion, the research model for relationships between dependence and its affecting factors was developed. We surveyed the companies residing in BICs to test our research model. The instrument of our study was modified, in part, on the basis of previous relevant studies. For the purposes of testing reliability and validity, preliminary testing was conducted with firms that were residing in BICs and incubated by the BICs in the region of Gwangju and Jeonnam. The questionnaire was modified in accordance with the pre-test feedback. We mailed to all of the firms that had been incubated by the BICs with the help of business incubating managers of each BIC. The survey was conducted over a three week period. Gifts (of approximately ₩10,000 value) were offered to all actively participating respondents. The incubating period was reported by the business incubating managers, and it was transformed using natural logarithms. A total of 180 firms participated in the survey. However, we excluded 4 cases due to a lack of consistency using reversed items in the answers of the companies, and 176 cases were used for the analysis. We acknowledge that 176 samples may not be sufficient to conduct regression analyses with 5 research variables in our study. Each variable was measured through multiple items. We conducted an exploratory factor analysis to assess their unidimensionality. In an effort to test the construct validity of the instruments, a principal component factor analysis was conducted with Varimax rotation. The items correspond well to each singular factor, demonstrating a high degree of convergent validity. As the factor loadings for a variable (or factor) are higher than the factor loadings for the other variables, the instrument's discriminant validity is shown to be clear. Each factor was extracted as expected, which explained 70.97, 66.321, and 52.97 percent, respectively, of the total variance each with eigen values greater than 1.000. The internal consistency reliability of the variables was evaluated by computing Cronbach's alphas. The Cronbach's alpha values of the variables, which ranged from 0.717 to 0.950, were all securely over 0.700, which is satisfactory. The reliability and validity of the research variables are all, therefore, considered acceptable. The effects of dependence were assessed using a regression analysis. The Pearson correlations were calculated for the variables, measured by interval or ratio scales. Potential multicollinearity among the antecedents was evaluated prior to the multiple regression analysis, as some of the variables were significantly correlated with others (e.g., direct service and indirect service). Although several variables show the evidence of significant correlations, their tolerance values range between 0.334 and 0.613, thereby demonstrating that multicollinearity is not a likely threat to the parameter estimates. Checking some basic assumptions for the regression analyses, we decided to conduct multiple regression analyses and moderated regression analyses to test the given hypotheses. The results of the regression analyses indicate that the regression model is significant at p < 0.001 (F = 44.260), and that the predictors of the research model explain 42.6 percent of the total variance. Hypotheses 1, 2, and 3 address the relationships between the dependence of the incubated firms and the business incubating services. Business infrastructure service, direct service, and indirect service are all significantly related with dependence (β = 0.300, p < 0.001; β = 0.230, p < 0.001; β = 0.226, p < 0.001), thus supporting Hypotheses 1, 2, and 3. When the incubating period is the moderator and dependence is the dependent variable, the addition of the interaction terms with the antecedents to the regression equation yielded a significant increase in R2 (F change = 2.789, p < 0.05). In particular, direct service and indirect service exert different effects on dependence. Hence, the results support Hypotheses 5 and 6. This study provides several strategies and specific calls to action for BICs, based on our empirical findings. Business infrastructure service has more effect on the firm's dependence than the other two services. The introduction of an additional high charge rate for a graduated but allowed to stay in the BIC is a basic and legitimate condition for the BIC to control the firm's dependence. We detected the differential effects of direct and indirect services on the firm's dependence. The firms with long incubating period are more sensitive to indirect service positively, and more sensitive to direct service negatively, when assessing their levels of dependence. This implies that BICs must develop a strategy on the basis of a firm's incubating period. Last but not least, it would be valuable to discover other important variables that influence the firm's dependence in the future studies. Moreover, future studies to explain the independence of startup companies in BICs would also be valuable.