• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.257-269
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• 2024

Purpose: The purpose of this study is to explain the pivotal role of the travel forecasting process in urban transportation planning. This study emphasizes the use of travel forecasting models to anticipate future traffic. Method: This study examines the methodology used in urban travel demand modeling within transportation planning, specifically focusing on the Urban Transportation Modeling System (UTMS). UTMS is designed to predict various aspects of urban transportation, including quantities, temporal patterns, origin-destination pairs, modal preferences, and optimal routes in metropolitan areas. By analyzing UTMS and its operational framework, this research aims to enhance an understanding of contemporary urban travel demand modeling practices and their implications for transportation planning and urban mobility management. Result: The result of this study provides a nuanced understanding of travel dynamics, emphasizing the influence of variables such as average income, household size, and vehicle ownership on travel patterns. Furthermore, the attraction model highlights specific areas of significance, elucidating the role of retail locations, non-retail areas, and other locales in shaping the observed dynamics of transportation. Conclusion: The study methodically addressed urban travel dynamics in a four-ward area, employing a comprehensive modeling approach involving trip generation, attraction, distribution, modal split, and assignment. The findings, such as the prevalence of motorbikes as the primary mode of transportation and the impact of adjusted traffic patterns on reduced travel times, offer valuable insights for urban planners and policymakers in optimizing transportation networks. These insights can inform strategic decisions to enhance efficiency and sustainability in urban mobility planning.

• International Journal of Highway Engineering
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• v.11 no.3
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• pp.129-139
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• 2009

The transportation network is a critical infrastructure in the event of natural and human caused disasters such as rainfall, snowfall, and terror and so on. Particularly, the transportation network in an urban area where a large number of population live is subject to be negatively affected from such events. Therefore, efficient traffic operation plans are required to assist rapid evacuation and effective detour of vehicles on the network as soon as possible. Recently, ubiquitous communication and sensor network technology is very useful to improve data collection and connection related emergency information. In this study, we develop a specific algorithm to provide evacuation route and detour information only for vehicles under emergency situations. Our algorithm is based on shortest path search technique and dynamic traffic assignment. We perform the case study to evaluate model performance applying hypothetical scenarios involved terror. Results show that the model successfully describe effective path for each vehicle under emergency situation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2261-2269
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• 2017

The current LTE network system provides service by locally allocating eNodeB to the EPC(Evolved Packet Core). However, it is not suitable for inter-node communication based on the distributed network environment. In this paper, we propose an integrated system by configuring E-UTRAN and EPC as All-In-One type to enable service in each distributed node. M2M UE is mounted on a each node for wireless In-band backhaul link. The integrated node provides inter-node communication over the wireless in-band backhaul link. If a normal UE moves and an access node changes in the system all entities of LTE integrated into one, it is necessary to change the P-GW which is IP anchor. In order to support the inter-node mobility even if P-GW is changed, We defined UPFE(User Packet Forwarding Extension) scheme and implemented the handover procedure of EPC. Also, we analyze the cell range of the integrated LTE system with the addition of the node and compare the handover delay with the current system.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.9
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• pp.13-19
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• 2008

Time synchronization of nodes in sensor network synchronizes sensor nodes to one time clock. This is very essential in sensor networks so that the information collected and reported from the sensor nodes becomes meaningful. If sensor nodes are not synchronized, disaster report with time information can be wrong analyzed and this may lead to big calamity. With the limitation of battery and computing power, time synchronization algorithm imported in sensor nodes has to be as simple as it doesn't need big complexity, nor generates many synchronization messages. To reduce the synchronization error, hop count should be kept small between reference node to initiate synchronization and sensor nodes to be synchronized. Therefore, multiple reference nodes are used instead of single reference node. The use of multiple reference nodes introduce the requirement of synchronization among reference nodes in the network. Several algorithms have been proposed till now, but the synchronization among reference nodes are not well considered. This paper proposes improved time synchronization for sensor networks by synchronizing multiple reference nodes inside the network. Through simulation, we validated the effects of new algorithm.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.899-907
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• 2022

Purpose: Although many studies on seismic fragility analysis of general bridges have been conducted using machine learning methods, studies on curved bridge structures are insignificant. Therefore, the purpose of this study is to analyze the seismic fragility of bridges with I-shaped curved girders based on the machine learning method considering the material property and geometric uncertainties. Method: Material properties and pier height were considered as uncertainty parameters. Parameters were sampled using the Latin hypercube technique and time history analysis was performed considering the seismic uncertainty. Machine learning data was created by applying artificial neural network and response surface analysis method to the original data. Finally, earthquake fragility analysis was performed using original data and learning data. Result: Parameters were sampled using the Latin hypercube technique, and a total of 160 time history analyzes were performed considering the uncertainty of the earthquake. The analysis result and the predicted value obtained through machine learning were compared, and the coefficient of determination was compared to compare the similarity between the two values. The coefficient of determination of the response surface method was 0.737, which was relatively similar to the observed value. The seismic fragility curve also showed that the predicted value through the response surface method was similar to the observed value. Conclusion: In this study, when the observed value through the finite element analysis and the predicted value through the machine learning method were compared, it was found that the response surface method predicted a result similar to the observed value. However, both machine learning methods were found to underestimate the observed values.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.591-601
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• 2017

The purpose of this research was to identify the effects of factors determining life satisfaction (LS) of local residents in chungbuk province. After reviewing the literature, this research selected and developed the 9 categories and specific indicators of LS. This research had obtained data through a face to face investigation using questionnaire, which surveyed 1,619 residents at 11 local governments in chungbuk province. This research analyzed the data using descriptive statistical methods and multiple linear regression method. This research found that 1) the level of overall LS had 4.433 points out of 7, the level of residential environment satisfaction had highest point (4.911), but the level of leisure culture satisfaction had lowest point (4.155), 2) in multiple regression analysis, The effect of income and consumption level on LS was highest. The degree of labor and life-social services was important factor to increase LS. The results of this study were expected to provide many implications for implementing policies to improve LS in the country and local governments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.271-276
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• 2009

An local area weather condition monitoring system to minimize many disasters from the sudden change of weather condition in local and mountain area is proposed. Firstly, the comparison of present state of the related monitoring systems and the possibility of realization with some merits are investigated. Moreover, this paper present direction of local area weather condition monitoring system based on integration of wireless sensor network and CDMA network following some case study. Through the efficient integration of both networks, the measured weather condition data from sensors can be transmitted to the server or mobile to monitor with high reliability. The proposed monitoring system will guide new type of project in wireless sensor network and support alarm service of the sudden change of weather condition to mobile user from central official regulations.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.342-350
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• 2022

In this paper, actual drone noise samples are collected for speech processing in disaster environments to build noise-corrupted speech database, and speech enhancement performance is evaluated by applying spectrum subtraction and mask-based speech enhancement techniques. To improve the performance of VoiceFilter (VF), an existing deep neural network-based speech enhancement model, we apply the Self-Attention operation and use the estimated noise information as input to the Attention model. Compared to existing VF model techniques, the experimental results show 3.77%, 1.66% and 0.32% improvements for Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligence (STOI), respectively. When trained with a 75% mix of speech data with drone sounds collected from the Internet, the relative performance drop rates for SDR, PESQ, and STOI are 3.18%, 2.79% and 0.96%, respectively, compared to using only actual drone noise. This confirms that data similar to real data can be collected and effectively used for model training for speech enhancement in environments where real data is difficult to obtain.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2298-2319
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• 1999

In this paper, we propose a new moving mobile base station (MMBS) scheme for very low power and micro-size RMIMS (radio-interfaced micro information monitoring system) terminals. RMIMS terminals can be used in various application service areas such as pollution monitoring, environment surveillance, traffic monitoring, emergency monitoring (e.g., building, bridge, railroad breakdown), security monitoring (e.g., theft, alarm) and military application. For these applications based on wireless transmission technologies, sensor type RMIMS terminals must satisfy low cost and low power design (e.g., solar power, life limited battery) requirement. In RMIMS terminal design, this low power requirement limits transmission range of uplink or reverse link and means small cell size. Also these applications using RMIMS terminals may have a little bit non real-time traffic characteristic and low scattering density in service area.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.13-26
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• 2009

Wireless Sensor Networks (WSNs) is one of the key technologies that make it possible to provide u-service in a ubiquitous society, however, it has disadvantages such as difficulty of managing sensor nodes and weaknesses of stability or mobility in large-scale WSNs. In order to solve these problems, 6LoWPAN that integrates with WSNs and IP networks has been studied widely. In this paper, we propose a Location Tracking Service Based on Google Map (LTSGM) system using 6LoWPAN. Since LTSGM system provides visual location information of sensor nodes through Google Map, it is possible to makes it easier than ever to manage sensor nodes in large-scale WSNs. Moreover, LTSGM can be used for various services such as applications for disaster or crime because it can trace the location of mobile nodes. Implementation of LTSGM system will be a test platform for 6LoWPAN.