• Journal of Digital Convergence
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• v.20 no.4
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• pp.469-482
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• 2022

The purpose of this study is to analyze regional variation factors of hypertension treatment rate in COVID-19 based on the analysis results based on ecological methodology. To this end, data suitable for ecological analysis were collected from the Korea Centers for Disease Control and Prevention's regional health statistics, local government COVID-19 confirmed cases, National Health Insurance Corporation, Health Insurance Review and Assessment Service's welfare statistics, and Korea Transport Institute's traffic access index. Descriptive statistics and correlation analysis were conducted using SPSS Statistics 23 for regional variation and related factors in hypertension treatment rate, and geographical weighted regression analysis was conducted using Arc GIS for regional variation factors. As a result of the study, the overall explanatory power of the calculated geo-weighted regression model was 27.6%, distributed from 23.1% to 33.4% by region. As factors affecting the treatment rate of hypertension, the higher the rate of basic living security medical benefits, diabetes treatment rate, and health institutions per 100,000 population, the higher the rate of hypertension treatment, the lower the number of COVID-19 confirmed patients, the lower the rate of physical activity, and the alcohol consumption. Percentage of alcohol consumption decreased due to COVID-19 pandemic. It was analyzed that the lower the ratio, the higher the treatment rate for hypertension. Based on these results, the analysis of regional variables in the treatment rate of hypertension in COVID-19 can be expected to be effective in managing the treatment rate of hypertension, and furthermore, it is expected to be used to establish community-centered health promotion policies.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.69-76
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• 2013

The incidence of globally infectious and pathogenic diseases such as H1N1 (swine flu) and Avian Influenza (AI) has recently increased. An infectious disease is a pathogen-caused disease, which can be passed from the infected person to the susceptible host. Pathogens of infectious diseases, which are bacillus, spirochaeta, rickettsia, virus, fungus, and parasite, etc., cause various symptoms such as respiratory disease, gastrointestinal disease, liver disease, and acute febrile illness. They can be spread through various means such as food, water, insect, breathing and contact with other persons. Recently, most countries around the world use a mathematical model to predict and prepare for the spread of infectious diseases. In a modern society, however, infectious diseases are spread in a fast and complicated manner because of rapid development of transportation (both ground and underground). Therefore, we do not have enough time to predict the fast spreading and complicated infectious diseases. Therefore, new system, which can prevent the spread of infectious diseases by predicting its pathway, needs to be developed. In this study, to solve this kind of problem, an integrated monitoring system, which can track and predict the pathway of infectious diseases for its realtime monitoring and control, is developed. This system is implemented based on the conventional mathematical model called by 'Susceptible-Infectious-Recovered (SIR) Model.' The proposed model has characteristics that both inter- and intra-city modes of transportation to express interpersonal contact (i.e., migration flow) are considered. They include the means of transportation such as bus, train, car and airplane. Also, modified real data according to the geographical characteristics of Korea are employed to reflect realistic circumstances of possible disease spreading in Korea. We can predict where and when vaccination needs to be performed by parameters control in this model. The simulation includes several assumptions and scenarios. Using the data of Statistics Korea, five major cities, which are assumed to have the most population migration have been chosen; Seoul, Incheon (Incheon International Airport), Gangneung, Pyeongchang and Wonju. It was assumed that the cities were connected in one network, and infectious disease was spread through denoted transportation methods only. In terms of traffic volume, daily traffic volume was obtained from Korean Statistical Information Service (KOSIS). In addition, the population of each city was acquired from Statistics Korea. Moreover, data on H1N1 (swine flu) were provided by Korea Centers for Disease Control and Prevention, and air transport statistics were obtained from Aeronautical Information Portal System. As mentioned above, daily traffic volume, population statistics, H1N1 (swine flu) and air transport statistics data have been adjusted in consideration of the current conditions in Korea and several realistic assumptions and scenarios. Three scenarios (occurrence of H1N1 in Incheon International Airport, not-vaccinated in all cities and vaccinated in Seoul and Pyeongchang respectively) were simulated, and the number of days taken for the number of the infected to reach its peak and proportion of Infectious (I) were compared. According to the simulation, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days when vaccination was not considered. In terms of the proportion of I, Seoul was the highest while Pyeongchang was the lowest. When they were vaccinated in Seoul, the number of days taken for the number of the infected to reach at its peak was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. When they were vaccinated in Pyeongchang, the number of days was the fastest in Seoul with 37 days and the slowest in Pyeongchang with 43 days. In terms of the proportion of I, Gangneung was the highest while Pyeongchang was the lowest. Based on the results above, it has been confirmed that H1N1, upon the first occurrence, is proportionally spread by the traffic volume in each city. Because the infection pathway is different by the traffic volume in each city, therefore, it is possible to come up with a preventive measurement against infectious disease by tracking and predicting its pathway through the analysis of traffic volume.

• Journal of the Korean Mathematical Society
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• v.35 no.3
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• pp.539-557
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• 1998

This paper is concerned with the performance evaluation of loss networks. We shall review the Erlang Fixed Point (EFP) method for estimating the blocking probabilities, which is based on an assumption that links are blocked independently. For networks with linear structure, the behaviour of adjacent links can be highly correlated. We shall give particular attention to recently-developed fixed-point methods which specifically account for the dependencies between neighbouring links. For the network considered here, namely a ring network with two types of traffic, these methods produce relative errors typically $10^{-5}$ of that found using the basic EFP approximation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.5
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• pp.475-491
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• 2009

This paper is primarily concerned with multi-path routing in Mobile Ad hoc Networks (MANETs). We propose a novel associativity-based on-demand source routing protocol for MANETs that attempts to establish relatively stable path(s) between the source and the destination. We introduce a new notion for gauging the temporal and spatial stability of nodes, and hence the paths interconnecting them. The proposed protocol is compared with other unipath (DSDV and AODV) and multi-path (AOMDV) routing protocols. We investigate the performance in terms of throughput, normalized routing overhead, packet delivery ratio etc. All on-demand protocols show good performance in mobile environments with less traffic overhead compared to proactive approaches, but they are prone to longer end-to-end delays due to route discovery and maintenance.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.61-66
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• 2005

Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine loaming, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more cornputationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.911-916
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• 2005

Noise map is a presentation of existing data or predicted noise situation in terms of noise indicator. However, it has shortcoming for assessing the number of people exposed, or the number of dwellings affected to any relevant limit values of noise level in certain areas. In this study, so called over-ride value noise mapping is proposed to make up for the shortcoming by using over-ride function of object-oriented programming and it is to show the guard of the area where it is satisfied the standard of option, or it is not satisfactory. Over-ride value noisemap data is combined with topography layer, population and house statistics, and GIS space statistical analysis. The over-ride value noise mapping can also he applied to make the road traffic noisemap, the railroad noisemap, the aircraft noisemap, and the industrial site noisemap This can express noise damage information more exactly.

• Journal of the Korean Society of Safety
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• v.29 no.6
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• pp.151-157
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• 2014

This study deals with the rear-end collision at roundabouts. The purpose of this study is to develop the accident models of rear-end collision in Korea. In pursuing the above, this study gives particular attention to developing the appropriate models using Poisson, negative binomial model, ZAM, multiple linear and nonlinear regression models, and statistical analysis tools. The main results are as follows. First, the Vuong statistics and overdispersion parameters indicate that ZIP is the most appropriate model among count data models. Second, RMSE, MPB, MAD and correlation coefficient tests show that the multiple nonlinear model is the most suitable to the rear-end collision data. Finally, such the independent variables as traffic volume, ratio of heavy vehicle, number of circulatory roadway lane, number of crosswalk and stop line are adopted in the optimal model.

• Journal of Navigation and Port Research
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• v.35 no.4
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• pp.289-297
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• 2011

This paper details the maritime accidents that occurred in the Philippines from 1972 to 2010. Firstly, it describes the general maritime situation in the country. It was followed by the traffic and safety infrastructure and the prevailing weather in the archipelago. The third section deals with the accidents' statistics and their geographical locations which is further sub-divided into three regions. It is grouped according to 10-year period. This paper describes the actual maritime situations, the pertinent national regulations, the inter-agencies policies and their safety regimes. It illustrates the shipping environment in the country including the maritime aids and infrastructure and the on human element factors.

• Communications for Statistical Applications and Methods
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• v.21 no.5
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• pp.387-393
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• 2014

Recurrent gap times are analyzed with diverse methods under several assumptions such as a marginal model or a frailty model. Several resampling techniques have been recently suggested to estimate the covariate effect; however, these approaches can be applied with a time-fixed covariate. According to simulation results, these methods result in biased estimates for a time-varying covariate which is often observed in a longitudinal study. In this paper, we extend a resampling method by incorporating new weights and sampling scheme. Simulation studies are performed to compare the suggested method with previous resampling methods. The proposed method is applied to estimate the effect of an educational program on traffic conviction data where a program participation occurs in the middle of the study.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.13 no.4
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• pp.1-10
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• 2005

According to the aviational definition, the fog is an obscuration phenomenon when prevailing visibility becomes less than 1,000m. Fog defined above causes so many aviation traffic problems like detour, flight delay and cancel. Therefore this study investigated quantitatively the fog effects on flight operation using flight delay and cancel statistic data during last four years from 1st Jul. 2001 to 30th Jun. 2005 at the Incheon Int'l Airport. The results of this study show that the hazardous meteorological condition is a important cause of flight delay and cancel, especially fog phenomenon. And it is expected that the results of this study give us the necessary and importance of fog prediction at the Incheon Int'l Airport.