• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.303-307
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• 2022

The purpose of the study is to determine the key aspects of the problems of employment of the population and the directions of their state regulation in war conditions. Employment policy involves a system of measures to create conditions for a more complete use of the potential of labor and business activity of the able-bodied population, linking this activity through taking into account the specifics of group interests with the tasks and guidelines for socio-economic development. But in the conditions of war, this problem acquires a new relevance. For the study, a number of theoretical methods of analysis were used. Based on the results of the study, the key aspects of the problems of employment of the population and the directions of their state regulation in war conditions were identified.

• Journal of KIBIM
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• v.9 no.1
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• pp.22-31
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• 2019

In this paper, we construct a prototype model for city data prediction by using time series data of floating population, and use machine learning to analyze urban data of complex structure. A correlation prediction model was constructed using three of the 10 data (total flow population, male flow population, and Monday flow population), and the result was compared with the actual data. The results of the accuracy were evaluated. The results of this study show that the predicted model of the floating population predicts the correlation between the predicted floating population and the current state of commerce. It is expected that it will help efficient and objective design in the planning stages of architecture, landscape, and urban areas such as tree environment design and layout of trails. Also, it is expected that the dynamic population prediction using multivariate time series data and collected location data will be able to perform integrated simulation with time series data of various fields.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.3
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• pp.115-126
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• 2023

Understanding the carrying capacity of a habitat is crucial for effectively managing populations of wild boars (Sus scrofa), which are designated as harmful wild animal species in national parks. Carrying capacity refers to the maximum population size supported by a park's environmental conditions. This study aimed to estimate the appropriate wild boar population size by integrating population characteristics and habitat suitability for wild boars in the Bukhansan National Park using the HexSim program. Population characteristics included age, survival, reproduction, and movement. Habitat suitability, which reflects prospecting and resource acquisition, was determined using the Maximum Entropy model. This study found that the optimal population size for wild boar ranged from 217 to 254 individuals. The population size varied depending on the amount of resources available within the home range, indicating fewer individuals in a larger home range. The estimated wild boar population size was 217 individuals for the minimum amount of resources (50% minimum convex polygon [MCP] home range), 225 individuals for the average amount of resources (95% MCP home range), and 254 individuals for the maximum amount of resources (100% MCP home range). The results of one-way analysis of variance revealed a significant difference in wild boar population size based on the amount of resources within the home range. These findings provide a basis for the development and implementation of effective management strategies for wild boar populations.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.51-62
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• 2022

Purpose: This study analyzes accessibility of outdoor evacuation places for earthquake and the accessibility improvement effects when expanding the evacuation places in accessibility-deficient areas. In order to consider real-world evacuees, the accessibility analysis is based on service population not on resident population. Method: Location-allocation model as a GIS-based spatial optimization mode is used to analyze accessibility and vulnerable areas to evacuation places. Of location-allocation problem types, 'Maximize Coverage' method is chosen to allocate as many potential evacuees as possible to evacuation places. And impedence cutoffs or evacuation distances (times) are applied to three classes: 500m (7.5 minutes), 1,000m (15 minutes), and 1,500m (22.5 minutes). Case study area is Jung-gu areas, Seoul as a high-density downtown area. Result: Results show that accessibility-deficient areas and population to evacuation places are much more in service population than in resident population. Accessibility is significantly improved when increases when expanding the evacuation places in accessibility-deficient areas. Yet, accessibility-deficient areas are still remained since available lands are insufficient in the high-density downtown area. Conclusion: The study suggests that temporary evacuation facilities like outdoor evacuation places for earthquake need to consider real potential evacuees based not only on resident population but also on service population. Also, policy measures to provide emergency shelters need to more utilize spatial optimization tools like location-allocation model.

• Physical Therapy Korea
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• v.23 no.2
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• pp.93-99
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• 2016

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

• Land and Housing Review
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• v.14 no.2
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• pp.73-82
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• 2023

This study empirically analyzes the policy demand for population inflow in Hongcheon-gun, a region that has experienced population decline over the past decade. The results of this study based on the multinominal logit model provide the policy implications as follows. First, due to the differing factors influencing the demand for population inflow policies among the young and the elderly, local governments should clearly define the policy targets for population inflow. Second, in the context of policy demand for population inflow through corporate attraction, we identify statistically significant and positive effects of the length of residence for both young and old people, and the level of formal education for the elderly. These results emphasize the importance of formulating population inflow policies distinctively targeted for the young and the elderly generations, respectively, thereby increasing population inflow in the population reduction area.

• Survey Research
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• v.10 no.3
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• pp.157-172
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• 2009

For a survey research in which the characteristics of the population of interest are investigated from a sample, representativeness of the sampling frame is one of the most important part to be considered. If the sampling frame fails to represent the population properly, statistical procedures based on the even efficient sampling design result in significant nonsampling biases and thus the statistical validities of the results could be damaged. But the construction of the reliable sampling frame that covers the population properly costs money and time and thus the sampling frame based on a census or a large scale survey is often used in practice. For example, the sampling frame based on the population households census is used for many household surveys in Korea. But due to the time difference between the census and a survey of interest, the sampling frame constructed from the census is expected to fail to cover the population of interest. Especially, one could expect a large amount of population and household movement in a large city like Seoul. Thus in our research, we considered the construction of new sampling frame and the procedure of sample selection for 2008 Seoul survey. We analyzed the sampling frame based on 2005 population households census and found that it does not represent the population properly. Thus, we proposed a new sampling frame based on resident registration DB for 2008 Seoul survey. We also proposed the sampling weights and estimator of the population mean based on the sample selected from the newly constructed sampling frame.

• Nutrition Research and Practice
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• v.10 no.6
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• pp.616-622
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• 2016

BACKGROUND/OBJECTIVES: In Argentina, obesity prevalence rose from 14.6% in 2005 to 20.8% in 2013. Although the number of studies on noncommunicable diseases and dietary patterns as a unique dietary exposure measure has increased, information on this topic remains scarce in developing countries. This is the first population-based study investigating the association between diet and obesity using a dietary pattern approach in Argentina. We aimed (a) to identify current dietary patterns of the population of $C{\acute{o}}rdoba$ city, (b) to investigate its association with obesity prevalence, and (c) to identify and describe dietary patterns from the subgroup of people with obesity. SUBJECTS/METHODS: The $C{\acute{o}}rdoba$ Obesity and Diet Study (CODIES) was conducted in $C{\acute{o}}rdoba$ city by using a random sample of n = 4,327 subjects between 2005 and 2012. Empirically derived dietary patterns were identified through principal component factor analysis. A multiple logistic regression analysis was used to investigate the association of dietary patterns with obesity. RESULTS: Four dietary patterns were identified, called "Starchy-Sugar", "Prudent", "Western", and "Sugary drinks". High scores for the "Western" pattern (with strongest factor loading on meats/eggs, processed meats, and alcohol) showed a positive association with obesity (OR: 1.33, 95% CI: 1.06-1.67, for third versus first tertile of factor score). "Meats/Cheeses" and "Snacks/Alcohol" patterns emerged in people with obesity. CONCLUSIONS: The findings suggest that high adherence to the "Western" pattern promoted obesity in this urban population. In addition, people with obesity showed characteristic dietary patterns that differ from those identified in the overall population.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1033-1042
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• 2003

In this study, the economic population prediction by computer simulation has been studied by using statistical model. The forecast of future population based on that of the past is a very difficult problem as uncertain conditions are modeled in it. Even if a thought forecast is possible, world-wide cultures and the local culture emotion the cultures of the world and out country can not be predicted due to rapid change and the estimation of population is ‘nowadays more and more’ difficult to be made good guess. In the estimation of economic population, by using the census population from 1960 to 1990, and using ARIMA model developed by Box and Jenkins, the estimation has been done on the economic population until 2021 according to age as appeared table and appendix. This kind of forecast would have both good point and weak point of ARIMA model theory saying that prediction can be done only by the economic population.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.6
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• pp.2583-2591
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• 2013

A number of cities have been constantly decreasing their residents by the low quality of life and environment. A creative industry is being noticed for not only securing the competitiveness of the city but also increasing the number of population. Thus, the urban structure for inducing creative industry population becomes to major issue to the most of local governments. This study aims to suggest the relationships between urban structure and creative industry population based on different urban sizes. To measure the population of creative industry, this study used the 'National Business Survey' by the National Statistical Office, which classified the statistical data of industrial places on a basis of city, district, and borough. Based on the results of expert questionnaire surveys, it conducted an analysis on the importance of urban structure and drew some critical factors that have an important effect on attracting the population of creative industry. The relationships between creative industry population and urban structure evaluated by multiple regression analysis. This study found out that the cultural factors like cultural space or culture events were drawn as very significant factors that have a positive effect on the population of creative industry population. It is judged that the creation of culture environment, which can enrich the creative industry, is needed to strengthen the competitiveness of the cities.