• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.999-1009
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• 2019

The importance of high-resolution sea ice maps of the Arctic Ocean is increasing due to the possibility of pioneering North Pole Routes and the necessity of precise climate prediction models. In this study,sea ice classification algorithms for two deep learning models were examined using Sentinel-1 A/B SAR data to generate high-resolution sea ice classification maps. Based on current ice charts, three classes (Open Water, First Year Ice, Multi Year Ice) of training data sets were generated by Arctic sea ice and remote sensing experts. Ten sea ice classification algorithms were generated by combing two deep learning models (i.e. Simple CNN and Resnet50) and five cases of input bands including incident angles and thermal noise corrected HV bands. For the ten algorithms, analyses were performed by comparing classification results with ground truth points. A confusion matrix and Cohen's kappa coefficient were produced for the case that showed best result. Furthermore, the classification result with the Maximum Likelihood Classifier that has been traditionally employed to classify sea ice. In conclusion, the Convolutional Neural Network case, which has two convolution layers and two max pooling layers, with HV and incident angle input bands shows classification accuracy of 96.66%, and Cohen's kappa coefficient of 0.9499. All deep learning cases shows better classification accuracy than the classification result of the Maximum Likelihood Classifier.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.33-43
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• 2003

In South Korea, about 74% of total area is mountainous terrain It is therefore inevitable to make tunnel or cutting slope for road construction. According to a related survey, approximately 2,400 sites of cutting slopes were found from 24 different routes of roadway which is overall 900 km long, implying 2.7 slopes per 1km of roadway on average. Even though safety matter such as the slope failure prevention would be the most important consideration for the construction of cutting slopeslandscape of sloped face is nowadays becoming another important factor due to the growing demand for the driver-friendly road environment Various construction methods which attain this goal should therefore be considered in the design stage of the roadway. The objective of this study is to identify important factors in landscape of sloped-cut roadway using factor analysis. For this, 10 main treatment methods of sloped-cut fact were analyzed. This study employed the LISREL(structural analysis of common variance) model in order to capture the qualitative characteristics of the slope-cut road and examine the relationship between the suey error and the variable(s). As a result, more reasonable landscape evaluation model for the road design and construction was proposed.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.95-105
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• 2003

Because the basic assumptions of deterministic user equilibrium assignment that all network users have perfect information of network condition and determine their routes without errors are known to be unrealistic, several stochastic assignment models have been proposed to relax this assumption. However. it is not easy to solve such stochastic assignment models due to the probability distribution they assume. Also. in order to avoid all path enumeration they restrict the number of feasible path set, thereby they can not preciously explain the travel behavior when the travel cost is varied in a network loading step. Another problem of the stochastic assignment models is stemmed from that they use heuristic approach in attaining optimal moving size, due to the difficulty for evaluation of their objective function. This paper presents a logit-based stochastic assignment model and its solution algorithm to cope with the problems above. We also provide a stochastic user equilibrium condition of the model. The model is based on path where all feasible paths are enumerated in advance. This kind of method needs a more computing demand for running the model compared to the link-based one. However, there are same advantages. It could describe the travel behavior more exactly, and too much computing time does not require than we expect, because we calculate the path set only one time in initial step Two numerical examples are also given in order to assess the model and to compare it with other methods.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.77-90
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• 2003

This paper explores the way and the extent to which drivers' route choice was influenced by uncertain information. In particular, this paper investigates the effect of qualitative information on route choice when drivers face a choice with different degrees of uncertain information. The SP survey was conducted and route choice legit models were estimated. We also applied Prospect Theory to the analysis of drivers' decision making under uncertain information. The main findings are firstly, drivers tend to prefer a route with information than(to) one without information. This indicated that providing charge information encouraged drivers to choose the routes for which information is provided in preference to those for which it is not provided. Secondly, drivers also prefer a route with a certain and precise information over one with uncertain and imprecise information. Thirdly, when the information is given as a range, the size of the range of the information influenced route choice slightly and as the range of the charge increases, the route becomes slightly less unattractive. Fourthly, when the information is given as a range, drivers' route choices are influenced more by the median value of the ranges than by the size of the overall ranges of the information. Application of Prospect Theory to the results explains the way drivers may be interpreting the choice situation and how they make a route choice in response to uncertain information. The results of this paper implicate that drivers' decision making under uncertainty seem to be very complicated and flexible, depending on the way drivers interpret the choice situation. Therefore, it is recommended to apply wider related theories to the analysis of the drivers' behaviour.

• Journal of Korean Society of Transportation
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• v.21 no.2
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• pp.71-82
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• 2003

The shortest path problems(SPP) are critical issues in the military logistics such as the simulation of the War-Game. However, the existing SPP has two major drawbacks, one is its accuracy of solution and the other is for only one solution with focused on just link cost in the military transportation planning models. In addition, very few previous studies have been examined for the multi-shortest path problems without considering link capacity reflecting the military characteristics. In order to overcome these drawbacks, it is necessary to apply the multi-shortest paths algorithm reflecting un-expected military incidents. This study examines the multi-shortest paths in the real networks using Shier algorithm. The network contains both military link capacity and time-based cost. Also, the modes are defined as a platoon(group) rather than unit which is used in most of previous studies in the military logistics. To verify the algorithm applied in this study. the comparative analysis was performed with various sizes and routes of network which compares with Dijkstra algorithm. The major findings of this study are as follows ; 1) Regarding the unique characteristics of the military transportation plan, Shier algorithm, which is applied to this study, is more realistic than Dijkstra algorithm. Also, the time based concept is more applicable than the distance based model in the military logistics. 2) Based on the results from the various simulations of this study the capacity-constraint sections appeared in each scenarios. As a consequence, the alternatives are necessary such as measures for vulnerable area, improvement of vehicle(mode), and reflection of separated-marching column in the military manuals. Finally. the limits and future research directions are discussed : 1) It is very hard to compare the results found in this study. which is used in the real network and the previous studies which is used in arbitrary network. 2) In order to reflect the real military situations such as heavy tanks and heavy equipment vehicles. the other constraints such as the safety load of bridges and/or the height of tunnels should be considered for the future studies.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.41-49
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• 2003

Marine traffic management could be defined as the implementation of managerial technical measures to improve vessel traffic safety. The managerial elements of vessel traffic management for ports and harbours or narrow channels include the total amount of traffic control, the vessel traffic separation scheme, speed restriction, traffic control by signals, the navigation information service and so forth. This research aims to quantify how much the traffic separation schemes(TSS) contribute to the alleviation effect of ship handling difficulty and to propose a design standard when the individual management measure is applied in an actual waterway. Traffic separation schemes have now been established in most of the major routes and congested waters of the world, and the number of collisions and groundings have often been dramatically reduced. In this part, the relationship between the alleviation of ship handling difficulty and the reduction of encounter figures among ships is quantitatively clarified by applying the ES model. As results of simulation analysis, it is recognized that a traffic separation system is most effective in the case of narrow width and heavy traffic volume. The centre buoy installation reduces about 1/4 of the alleviation of ship handling difficulty, TSS establishment 1/3, and design change to one-way traffic from two-way traffic reduces 1/2.

• Journal of Korean Society of Transportation
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• v.29 no.1
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• pp.71-79
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• 2011

Traditionally, a dynamic network model is considered as a tool for solving real-time traffic problems. One of useful and practical ways of using such models is to use it to produce and disseminate forecast travel time information so that the travelers can switch their routes from congested to less-congested or uncongested, which can enhance the performance of the network. This approach seems to be promising when the traffic congestion is severe, especially when sudden incidents happen. A consideration that should be given in implementing this method is that travel time information may affect the future traffic condition itself, creating undesirable side effects such as the over-reaction problem. Furthermore incorrect forecast travel time can make the information unreliable. In this paper, a network-wide travel time prediction model under incidents is developed. The model assumes that all drivers have access to detailed traffic information through personalized in-vehicle devices such as car navigation systems. Drivers are assumed to make their own travel choice based on the travel time information provided. A route-based stochastic variational inequality is formulated, which is used as a basic model for the travel time prediction. A diversion function is introduced to account for the motorists' willingness to divert. An inverse function of the diversion curve is derived to develop a variational inequality formulation for the travel time prediction model. Computational results illustrate the characteristics of the proposed model.

• Journal of Korean Society of Transportation
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• v.31 no.3
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• pp.86-95
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• 2013

In this study, a model of compensation and amendment of forecasted travel demand was developed to calculate the range of values depends on the changes in the risk factors, selecting factors that might affect traffic demand changes among risk factors. Selected factors are as follows: influenced area population, the number of registrated vehicle per person, ratio of service industry workers, and city intervals. Then this model is applied to six routes of expressway and the calculated value were compensated with error rate being reflected on each quartile value with respect to influenced area population (200,000 people standards). Result from appling developed model to Cheongwon-Sangju expressway suggests that the model could compensate the error rate by more than 50%, which in turn validate the effectiveness of the model developed. Some limitations and future research agenda have also been identified.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.469-480
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• 2017

On April 1, 2004, KTX (Korea Train eXpress), the first HSR (High-Speed Rail) in Korea, was introduced to Gyeongbu Line. The introduction of the KTX service led to a change in the number of passengers for Gyeongbu Line. Previous studies have analyzed the pre and post-event changes of the intervening events by either simple statistics or intervention ARIMA analysis. However, the intervention ARIMA model has a limitation that several assumptions such as the occurrence time and the type of intervention events are necessary. To this end, this study analyzed the effects of intervention event on the number of passengers using the Gyeongbu line based on a time series outlier detection technique which can overcome limitations in the previous studies. The time series outlier detection technique can analyze the time, effect type and size of an intervention event without the assumption of the time and effect type of the intervention event. The data were collected from the Korea Transport Database (KTDB) for twelve years from 2003 to 2014 (144 months). The analysis results showed that the size of the influence type in the same intervention events was different across the major city routes, and the intervention event which could not be found by previous study methods was also found.

• Toxicological Research
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• v.31 no.2
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• pp.157-163
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• 2015

Nanotechnology has advanced at an extremely rapid pace over the past several years in numerous fields of research. However, the uptake of nanoparticles (NPs) into the body after administration through various routes may pose a risk to human health. In this study, we investigated the potential ocular toxicity of 20-nm, negatively- charged zinc oxide (ZnO) NPs in rats using micro-computed tomography (micro-CT) and histopathological assessment. Animals were divided into four groups as control group, ZnO NPs treatment group (500 mg/kg/day), control recovery group, and ZnO NPs treatment and recovery group. Ocular samples were prepared from animals treated for 90 days (10 males and 10 females, respectively) and from recovery animals (5 males and 5 females, respectively) sacrificed at 14 days after final treatment and were compared to age-matched control animals. Micro-CT analyses represented the deposition and distribution of foreign materials in the eyes of rats treated with ZnO NPs, whereas control animals showed no such findings. X-ray fluorescence spectrometry and energy dispersive spectrometry showed the intraocular foreign materials as zinc in treated rats, whereas control animals showed no zinc signal. Histopathological examination revealed the retinopathy in the eyes of rats treated with ZnO NPs. Neuronal nuclei expression was decreased in neurons of the ganglion cell layer of animals treated with ZnO NPs compared to the control group. Taken together, treatment with 20-nm, negatively-charged ZnO NPs increased retinopathy, associated with local distribution of them in ocular lesions.