• Journal of Embryo Transfer
• /
• v.27 no.4
• /
• pp.245-252
• /
• 2012

The purpose of the present study was to investigate the effect of IFN-${\tau}$ on prostaglandin synthesis, cyclooxygenase-2 (COX-2) gene expression in vitro and concentration of progesterone (P4) in endometrial cells. Epithelial and stromal cells cultured in vitro were isolated from bovine endometrium and stimulated with increasing doses of IFN-${\tau}$ (0, 0.02, 0.2 and 2 ug/ml). Human chorionic gonadotropin (hCG, 1.5 IU/ml) was used as a positive control. Prostaglandin $E_2$ and $F_{2{\alpha}}$ levels in the culture media were analyzed by enzyme immunoassays and total RNA was extracted from the cells for RT-PCR. P4 concentrations of blood samples were assayed by chemiluminescent immuno assays system. In epithelial cells, COX-2 gene expression was increased in the presence of IFN-${\tau}$ (p<0.05), but it was not significantly different in all groups of stromal cells except for 2 ug/ml IFN-${\tau}$ group (p<0.05). Although IFN-${\tau}$ did not affect $PGE_2$ and $PGF_{2{\alpha}}$ production in epithelial cells, it decreased $PGE_2$ and $PGF_{2{\alpha}}$ production significantly in stromal cells (p<0.05). In vivo experiment, blood concentration of P4 was significantly increased after addition of IFN-${\tau}$ (1 ug/ml). The results indicate that PG production was mediated by COX-2 expression in stromal cells but it was not affected in epithelial cells and this suggest that treatment of IFN-${\tau}$ could improve the implantation environment of uterine by maintenance of high P4 concentration.

• The KIPS Transactions:PartB
• /
• v.16B no.2
• /
• pp.131-140
• /
• 2009

This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.

• Korean Journal of Construction Engineering and Management
• /
• v.5 no.2 s.18
• /
• pp.162-171
• /
• 2004

Crack sealing is a maintenance procedure that is commonly used to reduce pavement degradation. If cracks in pavements are not sealed, surface water penetration can reduce the strength of the sub-base layers, which can result in increased deflections of the pavement. Reduced strength of the sub-base also accelerates the deterioration of the surface, due to development of greater cracking and potholes. Crack sealing is performed to reduce water and debris penetration, thereby helping to maintain pavement structural capacity and limiting future degradation. The process of sealing cracks in pavements is however dangerous, costly, and labor-intensive operation. Labor turnover and training are increasing problems related to crack sealing crews, and as traffic volumes increase. Automating crack sealing can reduce labor and road user costs, improve work quality, and decrease worker exposure to roadway hazards. The main objective of this research is to develop an automated system for sealing cracks in pavement. Extension of the algorithms and tools presented in this research is also recommended for future study.

• The KIPS Transactions:PartD
• /
• v.11D no.6
• /
• pp.1221-1230
• /
• 2004

In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.

• Journal of the Society of Disaster Information
• /
• v.14 no.3
• /
• pp.334-342
• /
• 2018

Purpose: The purpose of this study is to examine and improve the issues related to National Safety Inspection currently operation and reform the system for response to various disasters. Method: For the completion, this study established theoretical background using materials related to National Safety Inspection and identified the issues using the open statistical data for National Safety Inspection to suggest the improvement plans. Results: National Safety Inspection has been operating a complete large-scale inspection on risk factors in cooperation with the central government, local governments, and citizens since 2015 to remove various disaster factors neglected in people's daily lives. Operation of National Safety Inspection had positive influence in preventing major disasters. However, inefficient activity is pointed out due to issues related to cooperation with other institutes, limitation for citizen's positional role, and superficial inspection. Conclution: To solve this issue, this study proposed strengthening of communication activity with disaster institutes, strengthening of efficiency through citizen participation by type, and actualization of checklist used in National Safety Inspection.

• Journal of Korean Ophthalmic Optics Society
• /
• v.14 no.3
• /
• pp.43-49
• /
• 2009

Purpose: The purpose of this study was to obtain the fundamental data of dynamic visual acuity and dynamic stereoacuity. Methods: The subjects were 20 athletes (high school baseball player) and 40 nonathletes (20 male, 20 female). We assessed static visual acuity, dynamic visual acuity, static stereoacuity and dynamic stereoacuity using rotating mirror projection system and computer program. Results: Three groups had similar static visual acuity and static stereoacuity. On the other hand, the dynamic visual acuity and dynamic stereoacuity showed statistically significant differency. The mean dynamic visual acuity for athletes was 174.80${\pm}$28.70 deg/sec, 137.10${\pm}$16.54 deg/sec for male nonathletes and 111.59${\pm}$15.40 deg/sec for female nonathletes. The mean dynamic stereoacuity for athlets was 234.55${\pm}$19.64, 249.05${\pm}$8.86 for male nonathletes and 247.10${\pm}$14.89 for female nonathletes. The group of athletes had better dynamic visual acuity and dynamic stereoacuity. Conclusions: If the result of this study apply to sports, it will be very useful to improve sports performance.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.10
• /
• pp.382-395
• /
• 2016

The purpose of this study is to examine how area characteristics influence the health of a population in a particular area by investigating how area deprivation and social capital influence self-rated health. For this study, a multi-level logistic regression was employed to analyze the data collected by Community Health Survey conducted on a target population of 229,186 living at 253 administrative areas of Korea in 2011. First, an analysis was conducted for subjects who have rated their self-health assessment as 'fair', 'poor', and 'very poor' in a 5 -item response survey. Then, a second analysis was conducted for the same subjects by excluding those with a rating of 'fair'. As a result, we found that area deprivation significantly influenced the population's health, according to our second analysis, while it was not significant according to our first analysis. Moreover, social capital was not significant in both analyses. Area deprivation-although the value of it was not so high-seems to explain the differences of individual self-rated health assessment as a contextual effect. In addition, influence of area characteristics is not limited to certain local areas, but to all local areas of Korea. Therefore, it is suggested that efforts to improve area characteristics are necessary to upgrade the individual's health level. A standardized classification system-distinguishing between good and poor self-rated health-is necessary through further comparative studies on self-rated health assessment.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.8
• /
• pp.359-368
• /
• 2017

What is the term "intelligence information society", which is a term that has been continuously discussed recently? This means that the automation beyond the limits of human ability in the whole societies based on intelligent information technology is a universalized social future. In particular, it is a concept that minimizes human intervention and continuously pursues evolution to data (or big data) -based automation. For example, autonomous automation is constantly aiming at unmanned vehicles with artificial intelligence as a key element. However, until now, intelligent information research has focused on the intelligence itself and has made an effort to improve intelligence logic and replace human brain and intelligence. On the other hand, in order to replace the human labor force, we have continued to make efforts to replace workers with robots by analyzing the working principles of workers and developing optimized simple logic. This study proposes important strategies and directions to implement intelligent information education policy and intelligent information technology research strategy by suggesting access strategy, education method and detailed policy road map for intelligent information technology research strategy and educational service. In particular, we propose a phased approach to intelligent information education such as basic intelligence education, intelligent content education, and intelligent application education. In addition, we propose education policy plan for the improvement of intelligent information technology, intelligent education contents, and intelligent education system as an important factor for success and failure of the 4th industrial revolution, which is centered on intelligence and automation.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.6
• /
• pp.35-47
• /
• 2020

Box-office prediction is important to movie stakeholders. It is necessary to accurately predict box-office and select important variables. In this paper, we propose a multivariate time series classification and important variable selection method to improve accuracy of predicting the box-office. As a research method, we collected daily data from KOBIS and NAVER for South Korean movies, selected important variables using Random Forest and predicted multivariate time series using Deep Learning. Based on the Korean screen quota system, Deep Learning was used to compare the accuracy of box-office predictions on the 73^rd day from movie release with the important variables and entire variables, and the results was tested whether they are statistically significant. As a Deep Learning model, Multi-Layer Perceptron, Fully Convolutional Neural Networks, and Residual Network were used. Among the Deep Learning models, the model using important variables and Residual Network had the highest prediction accuracy at 93%.

• 재활복지
• /
• v.20 no.3
• /
• pp.17-43
• /
• 2016

This study is on understanding the reality of disabled seniors and investigation of factors that affect overall life satisfaction, making a proposal to improve their life quality. Situation data for the disabled, gathered by Korea Institute for Health and Social Affairs (KIHASA) in 2014, was used to perform the study, and the target group is 3,181 people with disability, above the age of 65. Descriptive statistics was presented for data analysis and logistic regression analysis was performed to investigate factors that affect life satisfaction. It was concluded from the analysis that gender, age, presence of spouse (demographic factors), house income, possession of house, presence of pensioner, registration to public pension plan, social discrimination (social-economical factors), level of disability, subjective health status, level of help needed for daily living, presence of care-giver, sufficiency of help, ability to go out by oneself, difficulty of using public transportations, and presence of medical checkups (disability and health factors.) make meaningful effects to life satisfaction of disabled seniors. Based on the derived results, this study suggests intensive interests and care-giving service for disabled seniors that live alone, institutional complementations to guarantee income security, including public or private pensions, improvements to social recognition and environments for discrimination of the disabled, organization of health and medical treatment service and health care system, comprehensive service provision to social welfare for both the disabled and seniors, and comprehensive service provision to both health care and social welfare.