Currently, cross-section design can not reflect highway function and traffic volume, various construction. This research paper provides analysis of traffic accident type, improvement of traffic operation and safety, assessment for new cross-section standards of two-lane highway. Research show higher accident rate on 6$\sim$8.9m road than 9$\sim$12.9m road width in two-lane highway. Typical improvement is widening on lane and shoulder width. Simulation show large increase on 6$\sim$7m road delay-time in 1,200vph. In contrast 10$\sim$11.5m road shows slight change on delay-time. This research paper provides various cross-section construction by traffic volume in minor arterial and distributor two-lane highway. The new cross-section design provides adopting highway volume, various construction and flexibility.
KIM, Kyoung Tae;LEE, Inmook;KWAK, Ho-Chan;MIN, Jae Hong
Journal of Korean Society of Transportation
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v.34
no.3
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pp.222-233
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2016
Recently, mobile phone data was applied in travel demand modeling as a new source of dynamic population movement. This study is also aimed to estimate "occupancy population" during a given period of time within a given spatial region using mobile phone data. An occupancy population was defined as the number of people residing or moving within a given time and space. In case of Seoul Metropolitan area, we divided the area into a number of administrative districts as zones for analysis and estimated the occupancy population of each zone by mobile phone data collected by SK telecom Co., a wireless telecommunication provider in Korea. For the expansion of mobile phone data, a new concept of "communication probability" was introduced and applied in the estimation of occupancy population of each zone by the hour. We compared the estimated number with the daytime population and the daytime population index referred by the Statistics Korea. The results showed that a positive correlation existed between the estimated number and the statistical number by nationwide survey. It was concluded that mobile phone data could be more cost-effective sources than a conventional survey method to estimate the pattern of population movement by the hour or by the day.
In situ investigations and laboratory tests using elastic wave have become popular in geotechnical and geoenvironmental engineering. Propagation velocity of elastic wave is the key index to evaluate the ground characteristics. To evaluate this, various methods were used in both time domain and frequency domain. In time domain, the travel time can be found from the two points that have the same phase such as peaks or first rises. Cross-correlation can also be used in time domain by evaluating the time shift amount that makes the product of signals of input and received waveforms maximum. In frequency domain, wave propagation velocity can be evaluated by computing the phase differences between the source and received waves. In this study, wave propagation velocity evaluated by the methods listed above were compared. Bender element tests were conducted on the specimens cut from the undisturbed hand-cut block samples obtained from Block 37 excavation site in Chicago, IL, US. The evaluation methods in time domain provides relatively wide range of wave propagation velocities due to the noise in signals and the sampling frequency of data logger. Frequency domain approach provides relatively accurate wave propagation velocities and is irrelevant to the sampling frequency of data logger.
The Journal of The Korea Institute of Intelligent Transport Systems
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v.19
no.2
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pp.74-88
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2020
A Cooperative Intelligent Transportation System (CITS) provides useful information on upcoming hazards in order to prevent vehicle collisions. In addition, the availability of individual vehicle travel information obtained from the CITS infrastructure allows us to identify the level of road safety in real time and based on analysis of the indicators representing the crash potential. This study proposes a methodology to derive road safety content, and presents evaluation results for its applicability in practice, based on simulation experiments. Both jerk and Stopping Distance Index (SDI) were adopted as safety indicators and were further applied to derive road section safety information. Microscopic simulation results with VISSIM show that 5% and 20% samples of jerk and SDI are sufficient to represent road safety characteristics for all vehicles. It is expected that the outcome of this study will be fundamental to developing a novel and valuable system to monitor the level of road safety in real time.
KSII Transactions on Internet and Information Systems (TIIS)
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v.13
no.4
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pp.2060-2077
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2019
Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.
LOS(Level of Service), the qualitative measure describing operational condition of highway, must be evaluated as quantative index in terms of user service. So, This study is focused on developing the user cost function that user cost is measured in the variation of V/C, MOE(Measure of Effectiveness) of LOS in basic Section of highway. The user cost is calculated as the sum of accident cost, operation cost, travel time cost. The data is collected in the four basic section of Singal-Ansan and Jung bu Highway. As the result of user cost function analysis, the user cost is the lowest When V/C is 0.54. Considering the V/C ratio(0.7) of Basic Section in rural highway suggested in KHCM, We find out that the LOS suggested KHCM increase the user cost of highway.
Journal of the Economic Geographical Society of Korea
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v.22
no.4
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pp.513-525
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2019
In Seoul, the subway system has been in use since 1974 and is the most frequently used travel mode accounting for approximately 40% of passenger journeys in 2015. As such the subway system is widely adopted by people and therefore, can have great impacts on their everyday life. However, it is easily noted that transit resources are not distributed spatially uniform, in other words, not all parts of the city gain the same benefits from their networks. This study aims to examine the inequity of spatial distribution of subway networks based on accessibility. Accessibility of subway networks are calculated based on the time-distance between stations and then equity is measured using the Gini index. Resulted map of subway accessibility shows that the benefits are not evenly distributed in Seoul with a pattern of highly accessible core - less accessible periphery areas. Also the subway accessibility network has fairer distribution against the employees' distribution rather than the distribution of general population or possibly transit dependent groups.
The Bimodal Tram being developed in Korea is a new transit system that provides both benefits of rail and bus systems in terms of accessibility and fixed time schedule. The Bimodal Tram is expected to take an important role of transit system in Korea under the national strategy of transportation system such as 'Low Carbon and Green Growth' for the next generation. This study does define the key indices considered for a decision of introducing the Bimodal Tram system and develop a finalized index, BSI(Bimodal Score for Introduction), showing the level of Bimodal Tram system introduced at a city level. The transport/transit system varies depending on cities with respect to demographic characteristics, travel patterns, financial capabilities, etc. This study will help any cities where transport agencies are trying to introduce the Bimodal Tram as a new transit system.
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.4D
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pp.361-368
/
2010
It is general that mostly congested sections of national backbone networks have been improved based on the national network expansion plan. However, in case of intermodal terminals which are origins of logistics, it is still so congested that travel time between origin and destination is long. Therefore, intermodal transportation systems plan of major intermodal terminals for the intermodal connector networks between intermodal terminal and national backbone network or intermodal terminal was established. With the limitation of priority methodology applying to intermodal connector facility under existing methodology, this study suggests an improved priority methodology. This study includes characteristics of terminal on the hierarchical structure and assessment list, but it does not concentrate on the specific terminal type through survey. To avoid a certain concentration, budget constraint for each terminal type was considered ahead of priority. Finally priority methodology was developed with two-step assessment under consideration that specific terminal is not involved in intermodal connector facility project. As a result of calculating weights by survey, effects such as d/c and accessibility fluctuations index through project implementation gain high weight, and degree of region underdevelopment gets next. Although the methodology in this study could not yields the priority by assessment list, it will be useful for setting the direction on policy related to intermodal connector facility projects.
Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.
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