• 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 Korean Society of Transportation
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• v.30 no.2
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• pp.101-116
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• 2012

Accident prediction models have been utilized to predict accident possibilities in existing or projected freeways and to evaluate programs or policies for improving safety. In this study, a traffic accident prediction model for freeways was developed for the above purposes. When selecting variables for the model, the highest priority was on the ease of both collecting data and applying them into the model. The dependent variable was set as the number of total accidents and the number of accidents including casualties in the unit of IC(or JCT). As a result, two models were developed; the overall accident model and the casualty-related accident model. The error structure adjusted to each model was the negative binomial distribution and the Poisson distribution, respectively. Among the two models, a more appropriate model was selected by statistical estimation. Major nine national freeways were selected and five-year dada of 2003~2007 were utilized. Explanatory variables should take on either a predictable value such as traffic volumes or a fixed value with respect to geometric conditions. As a result of the Maximum Likelihood estimation, significant variables of the overall accident model were found to be the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volume to the number of curved segments between ICs(or JCTs). For the casualty-related accident model, the link length between ICs(or JCTs), the daily volumes(AADT), and the ratio of bus volumes had a significant impact on the accident. The likelihood ratio test was conducted to verify the spatial and temporal transferability for estimated parameters of each model. It was found that the overall accident model could be transferred only to the road with four or more than six lanes. On the other hand, the casualty-related accident model was transferrable to every road and every time period. In conclusion, the model developed in this study was able to be extended to various applications to establish future plans and evaluate policies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.6
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• pp.54-63
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• 2014

Traffic accident frequency and severity level in Korea are known to be very serious. Especially the number of pedestrian fatalities was much worse and 1.6 time higher than the OECD average. According to the National Police Agency, the flash signals are reported to have many safety benefits as well as travel time reduction, which is opposed to the foreign studies. With this background of expanding the flash signal, this research aims to investigate the overall impact of the flash signal operation on safety, investigating and comparing the accident occurrence on the flash signal and the full signal intersections. For doing this accident prediction models for both flash and full signal intersections were estimated using independent variables (geometric features and traffic volume) and 3-year (2011-2013) accident data collected in Seoul. Considering the rare and random nature of accident occurrence and overdispersion (variance > mean) of the data, the negative binomial regression model was applied. As a result, installing wider crosswalk and increasing the number of pedestrian push buttons seemed to increase the safety of the flash signal intersections. In addition, the result showed that the average accident occurrence at the flash signal intersections was higher than at the full signal-operated intersections, 9% higher with everything else the same.

• Journal of Korea Port Economic Association
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• v.36 no.4
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• pp.17-30
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• 2020

In the shipping industry, it is essential to engage in the preemptive prediction of freight rate volatility through market monitoring. Considering that freight rates have already started to fall, the loss of shipping companies will soon be uncontrollable. Therefore, in this study, factors affecting the freight rates of bulk carriers, which have relatively large freight rate volatility as compared to container freight rates, were quantified and analyzed. In doing so, we intended to contribute to future shipping market monitoring. We performed an analysis using a vector error correction model and estimated the influence of six independent variables on the charter rates of bulk carriers by Handy Size, Supramax, Panamax, and Cape Size. The six independent variables included the bulk carrier fleet volume, iron ore traffic volume, ribo interest rate, bunker oil price, and Euro-Dollar exchange rate. The dependent variables were handy size (32,000 DWT) spot charter rates, Supramax 6 T/C average charter rates, Pana Max (75,000 DWT) spot charter, and Cape Size (170,000 DWT) spot charter. The study examined charter rates by size of bulk carriers, which was different from studies on existing specific types of ships or fares in oil tankers and chemical carriers other than bulk carriers. Findings revealed that influencing factors differed for each ship size. The Libo interest rate had a significant effect on all four ship types, and the iron ore traffic volume had a significant effect on three ship types. The Ribo rate showed a negative (-) relationship with Handy Size, Supramax, Panamax, and Cape Size. Iron ore traffic influenced three types of linearity, except for Panamax. The size of shipping companies differed depending on their characteristics. These findings are expected to contribute to the establishment of a management strategy for shipping companies by analyzing the factors influencing changes in the freight rates of charterers, which have a profound effect on the management performance of shipping companies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.78-95
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• 2022

The result of previous studies and epidemiological invstigations for infectious diseases epidemic in livestock have shown that trips made by livestock-related vehicles are the main cause of the spread of these epidemics. In this study, the OD traffic volume of livestock freight vehicle during the week in each zone was calculated using livestock facility visit history data and digital tachograph data. Based on this, a model for predicting the spread of infectious diseases in livestock was developed. This model was trained using zonal records of foot-and-mouth disease in Gyeonggi-do for one week in January and February 2015 and in positive, it was succesful in predicting the outcome in all out of a total 13 actual infected samples for test.

• International Journal of Highway Engineering
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• v.18 no.1
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• pp.33-41
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• 2016

PURPOSES : This study primarily focused on evaluating the performance characteristics of 4.75-mm nominal maximum aggregate size (NMAS) asphalt mixtures for their more effective implementation to a layered flexible pavement system. METHODS : The full-scale pavements in the FDOT's accelerated pavement testing (APT) program, including 4.75-mm mixtures at the top with different thicknesses and asphalt binder types, were considered for the faster and more realistic evaluation of the rutting performance. The results of superpave indirect tensile (IDT) tests and hot-mix asphalt fracture mechanics (HMA-FM) based model predictions were used for cracking performance assessments. RESULTS : The results indicated that the rutting performance of pavement structures with 4.75-mm mixtures may not be as good as to those with the typical 12.5-mm mixtures, and pavement rutting was primarily confined to the top layer of 4.75-mm mixtures. This was likely due to the relatively higher mixture instability and lower shear resistance compared to 12.5-mm mixtures. The energy ratio (ER) and HMA-FM based model performance prediction results showed a potential benefit of 4.75-mm mixtures in enhanced cracking resistance. CONCLUSIONS : In relation to their implementation, the best use of 4.75-mm mixtures seem to be as a surface course for low-traffic-volume applications. These mixtures can also be properly used as a preservation treatment that does not necessarily last as long as 12.5-mm NMAS structural mixes. It is recommended that adequate thicknesses and binder types be considered for the proper application of a 4.75-mm mixture in asphalt pavements to effectively resist both rutting and cracking.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.2
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• pp.68-75
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• 2015

This study established key factors causing deck slab deterioration based on GPR database of 747 highway bridges, and predicted deck slab damage rates with respect to bridge service life. To minimize the influence of bridge service life on deck slab deterioration, the deck slab damage rate database was corrected based on a linear regression model of bridge service life vs. deck slab damage rate. The corrected deck slab damage rates were analyzed to determine correlation considering the number of snowy days, the amount of snowfalls, the number of freeze-thaw days, average winter temperature, altitude, the amount of deicing chemicals and equivalent traffic volume, and then both the number of freeze-thaw days and the amount of deicing chemicals were determined to be key factors causing deck slab deterioration. The complex deterioration considering both key factors was represented deck slab damage rate charts, and the average deck slab life was derived. The results of this study will be used as a guideline for highway bridge maintenance to identify the progress of deck slab deterioration for a given bridge and predict the time required deck slab rehabilitation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.133-141
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• 2017

Traffic volume increases according to highway expansion and industrial development which causes repetitive defect and durability degradation on pavement. The research of quality assurance system used abroad has introduced Korea. Korea Expressway Corporation (KEC) has developed a Quality Performance Index (QPI) that quantitatively assesses the level of quality of the final product, and practical applications. Assessment factor on concrete pavement consisted of pavement thickness, compressive strength, IRI and spacing factor. Assessment factor on concrete pavement is determined by empirical evaluation factor from abroad. In this study, analysis of evaluation factors of concrete pavement by using pavement life prediction simulation and measured data were evaluated with consideration of feasibility of the assessment factor. Pavement life, performance and durability are affected by pavement thickness, compressive strength, IRI and spacing factor in assessment factor on concrete pavement, QPI.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5321-5329
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• 2011

Space Layout has been an issue in the facet of reducing the co2 in that the transportation sector has been to represent almost more than 20% of the total energy consumption for decades. Beside the development of the more efficient transportation systems, an efficient space layout makes it possible to reduce the amount of energy consumption in the transportation sector through allocating the sub-spaces in such an arrangement of minimizing the travel distances. In line with this thinking, this research aims at implementing a simulator which can calculate the vehicle-based travel distance upon a certain space layout. Based on the findings that the vehicle-based travels take place between the two functionally related sub-spaces, this research addresses a method of calculating the vehicle-based travel distance by multiplying the traffic volume of each sub-spaces by the travel distance to the other connected sub-spaces.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.113-124
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• 2009

This paper suggests a new approach for providing information for driver safety at signalized intersections. Particularly dangerous situations at signalized intersections such as red-light violations, accelerating through yellow intervals, red-light running, and stopping abruptly due to the dilemma zone problem are considered in this study. This paper presents the development of a dangerous vehicle determination algorithm by collecting real-time vehicle speeds and times from multiple point detectors when the vehicles are traveling during phase-change. For an evaluation of this algorithm, VISSIM is used to perform a real-time multiple detection situation by changing the input data such as various inflow-volume, design speed change, driver perception, and response time. As a result the correct-classification rate is approximately 98.5% and the prediction rate of the algorithm is approximately 88.5%. This paper shows the sensitivity results by changing the input data. This result showed that the new approach can be used to improve safety for signalized intersections.