• Nutrition Research and Practice
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• v.13 no.4
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• pp.333-343
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• 2019

BACKGROUND/OBJECTIVES: To compare five indices of adherence to the Mediterranean Diet (MD) among adults living in the Mediterranean region. SUBJECTS/METHODS: A total of 100 healthy Lebanese adults aged between 18 and 65 years. Face-to-face interviews to collect sociodemographic and medical information, to take anthropometric measurements, and to fill a validated, culturally adapted, food frequency questionnaire (FFQ). The score for each item was calculated following the recommendations for each corresponding index. The five MD indices were Mediterranean Diet Scale (MDScale), Mediterranean Food Pattern (MFP), MD Score (MDS), Short Mediterranean Diet Questionnaire (SMDQ), and the MedDiet score. RESULTS: Significant correlations were detected between items with P-values < 0.001. Minimal agreement was seen between MDScale and MedDiet score and maximal agreement between MDS and MedDiet score. Univariate and multivariate analyses showed that MDS and MedDiet scores had significant correlations with fiber and olive oil intake, main components of the MD. MDScale showed a significant correlation with waist-to-hip ratio and with total energy intake but none of the five indices was correlated to body mass index (BMI). CONCLUSIONS: The indices that showed the highest correlation with variables related to the MD are the MDScale and the MedDiet score; therefore, they can be used to assess our future study populations. Based on the current results, more than half of the study population was non-adherent to the MD and adherence to this diet did not appear to protect against being overweight ($BMI{\geq}30$).

• Horticulture, Environment, and Biotechnology : HEB
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• v.59 no.6
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• pp.875-888
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• 2018

Tulip (Tulipa L.) is one of the most important ornamental geophytes in the world. Analysis of molecular variability of tulips is of great importance in conservation and parental lines selection in breeding programs. Of the 70 genic microsatellites, 15 highly polymorphic and reproducible markers were used to assess the genetic diversity, structure, and relationships among 280 individuals of 36 wild and cultivated tulip accessions from two countries: Iran and the Netherlands. The mean values of gene diversity and polymorphism information content were 0.69 and 0.66, respectively, which indicated the high discriminatory power of markers. The calculated genetic diversity parameters were found to be the highest in wild T. systola Stapf (Derak region). Bayesian model-based STRU CTU RE analysis detected five gene pools for 36 germplasms which corresponded with morphological observations and traditional classifications. Based on analysis of molecular variance, to conserve wild genetic resources in some geographical locations, sampling should be performed from distant locations to achieve high diversity. The unweighted pair group method with arithmetic mean dendrogram and principal component analysis plot indicated that among wild tulips, T. systola and T. micheliana Hoog exhibited the closest relationships with cultivated tulips. Thus, it can be assumed that wild tulips from Iran and perhaps other Middle East countries played a role in the origin of T. gesneriana, which is likely a tulip species hybrid of unclear origin. In conclusion, due to the high genetic variability of wild tulips, they can be used in tulip breeding programs as a source of useful alleles related to resistance against stresses.

• Journal of Microbiology and Biotechnology
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• v.29 no.3
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• pp.429-440
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• 2019

Several studies have attempted to identify factors associated with longevity and maintenance of health in centenarians. In this study, we analyzed and compared the gut microbiota of centenarians in longevity villages with the elderly and adults in the same region and urbanized towns. Fecal samples were collected from centenarians, elderly, and young adults in longevity villages, and the gut microbiota sequences of elderly and young adults in urbanized towns of Korea were obtained from public databases. The relative abundance of Firmicutes was found to be considerably higher in subjects from longevity villages than those from urbanized towns, whereas Bacteroidetes was lower. Age-related rearrangement of gut microbiota was observed in centenarians, such as reduced proportions of Faecalibacterium and Prevotella, and increased proportion of Escherichia, along with higher abundances of Akkermansia, Clostridium, Collinsella, and uncultured Christensenellaceae. Gut microbiota of centenarians in rehabilitation hospitals were also different to those residing at home. These differences could be due to differences in diet patterns and living environments. In addition, phosphatidylinositol signaling system, glycosphingolipid biosynthesis, and various types of N-glycan biosynthesis were predicted to be higher in the gut microbiota of centenarians (corrected p < 0.05). These three metabolic pathways of gut microbiota can be associated with the immune status and healthy gut environment of centenarians. Although further studies are necessary to validate the function of microbiota between groups, this study provides valuable information on centenarians' gut microbiota.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.403-412
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• 2019

The purpose of this study is to analyze temporal and spatial variations of atopic dermatitis and to identify major factors. Data utilized in the study were collected by the Community Health Survey, KOSIS and so and on from 2009 to 2013. This study was analyzed using descriptive statistics and Geographically weighted regression model. As a result, regional diagnosis rate of atopic dermatitis was increased by 5 years, and difference related to geographic location was so large. The regional characteristics that contribute to the diagnosis of atopic dermatitis were as follows: older adults population ratio, ratio of basic living security received people, depression experience rate, high risk drinking rate, number of wastewater discharge business, number of tobacco retail business, number of fast food restaurant business. This study is meaningful in that it provided basic data on health policy direction and provided information on prioritization of health business in each region.

• Database Research
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• v.34 no.3
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• pp.124-136
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• 2018

There have been active research activities to use neural networks to analyze OCT images and make medical decisions. One requirement for these approaches to be promising solutions is that the trained network must be generalized to new devices without a substantial loss of performance. In this paper, we use a deep convolutional neural network to distinguish AMD from normal patients. The network was trained using a data set generated from an OCT device. We observed a significant performance degradation when it was applied to a new data set obtained from a different OCT device. To overcome this performance degradation, we propose an image normalization method which performs segmentation of OCT images to identify the retina area and aligns images so that the retina region lies horizontally in the image. We experimentally evaluated the performance of the proposed method. The experiment confirmed a significant performance improvement of our approach.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.125-135
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• 2020

The uncontrolled urban expansion causes various social, economic problems and natural/environmental problems. Therefore, it is necessary to forecast urban expansion by identifying various factors related to urban expansion. This study aims to forecast it using a decision tree that is widely used in various areas. The study used geographic data such as the area of use, geographical data like elevation and slope, the environmental conservation value assessment map, and population density data for 2006 and 2018. It extracted the new urban expansion areas by comparing the residential, industrial, and commercial zones of the zoning in 2006 and 2018 and derived a decision tree using the 2006 data as independent variables. It is intended to forecast urban expansion in 2030 by applying the data for 2018 to the derived decision tree. The analysis result confirmed that the distance from the green area, the elevation, the grade of the environmental conservation value assessment map, and the distance from the industrial area were important factors in forecasting the urban area expansion. The AUC of 0.95051 showed excellent explanatory power in the ROC analysis performed to verify the accuracy. However, the forecast of the urban area expansion for 2018 using the decision tree was 15,459.98㎢, which was significantly different from the actual urban area of 4,144.93㎢ for 2018. Since many regions use decision tree to forecast urban expansion, they can be useful for identifying which factors affect urban expansion, although they are not suitable for forecasting the expansion of urban region in detail. Identifying such important factors for urban expansion is expected to provide information that can be used in future land, urban, and environmental planning.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.75-81
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• 2020

The purpose of this study was to investigate whether there is a relationship between COVID-19 of feelings, work values, and employment preparation behaviors of nursing student and to prepare plans for the curriculum and activities of nursing students. The subject of the study was a questionnaire for 130 students 4th grade, who are graduating grades in one region. Data analysis was performed with the SPSS Win 19.0 program and correlation was analyzed by Pearson's correlation. As a result of the study, the average score for emotions from COVID-19 was 3.61±0.62. There was significant correlation between feelings and extrinsicl values from COVID-19. There was a significant repayment relationship with intrinsic work values and job preparation behavior. Based on these studies, it is meaningful to provide an effective way to prepare for employment programs and provide educational programs related to COVID-19.

• Journal of The Korea Institute of Healthcare Architecture
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• v.27 no.2
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• pp.39-48
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• 2021

Purpose: The study aims to demonstrate regional diagnosis methods and results combined with geographical information to expand the physical infrastructure related to community care services. To this end, the physical infrastructure for the core elements of community care was analyzed in terms of the fulfilment and access of facilities to derive the underserved elements and regions. Methods: Utilizes GIS network analysis techniques that can derive physical infrastructure service areas. Underserved elements are derived by comparing and analyzing the service area for each core element. Next, the underserved regions for each core element are derived through the overlapping of the set service area and the diagnosis population. Results: Among the physical infrastructure by core elements for community care, the housing support element was considerably weak, and the nursing care facility compared to health care was also analyzed to be weak. In addition, underserved regions by dong in Mapo-gu were deduced and presented for each diagnosed population. Implications: The discovery of underserved elements and underserved regions is meaningful as a diagnostic process that can derive the physical infrastructure that needs to be expanded urgently for the realization of community care and determine the priority projects and targets of the projects.

• Journal of Radiation Protection and Research
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• v.47 no.2
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• pp.67-76
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• 2022

Background: We conducted a cross-sectional study of residents within and outside Fukushima Prefecture to clarify their perceptions of the need for smartphone applications (apps) for explaining exposure doses. The results will lead to more effective methods for identifying target groups for future app development by researchers and municipalities, which will promote residents' understanding of radiological situations. Materials and Methods: In November 2019, 400 people in Fukushima Prefecture and 400 people outside were surveyed via a web-based questionnaire. In addition to basic characteristics, survey items included concerns about radiation levels and intention to use a smartphone app to keep track of exposure. The analysis was conducted by stratifying responses in each region and then cross-tabulating responses to concerns about radiation levels and intention to use an app by demographic variables. The intention to use an app was analyzed by binomial logistic regression analysis. Text-mining analyses were conducted in KH Coder software. Results and Discussion: Outside Fukushima Prefecture, concerns about the medical exposure of women to radiation exceeded 30%. Within the prefecture, the medical exposure of women, purchasing food products, and consumption of own-grown food were the main concerns. Within the prefecture, having children under the age of 18, the experience of measurement, and having experience of evacuation were significantly related to the intention to use an app. Conclusion: Regional and individual differences were evident. Since respondents differ, it is necessary to develop and promote app use in accordance with their needs and with phases of reconstruction. We expect that a suitable app will not only collect data but also connect local service providers and residents, while protecting personal information.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.87-96
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• 2022

This paper is an empirical analysis as a reference model that can predict up to the maximum number of elementary school student care needs in local governments across the country. This study analyzed and predicted the characteristics of the region based on machine learning to predict the demand for elementary care in a new apartment complex. For this purpose, a total of 292 variables were used, including data related to apartment structure, such as number of parking spaces per household, and building-to-land ratio, environmental data around apartments such as distance to elementary schools, and population data of administrative districts. The use of various variables is of great significance, and it is meaningful in complex analysis. It is also an empirical case study that increased the reliability of the model through comparison with the actual value of the basic local government.