• Proceedings of the KSR Conference
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• 2005.11a
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• pp.1109-1114
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• 2005

The rolling contact fatigue of wheels for high speed trains is a matter of increasing importance. The wheel damages from fatigue crack makes noise up and safety down. RCF-casued accidents cause traffic congestion and economical costs as well as personal injuries. In this study, we examine the rolling contact fatigue of wheels for power car running at 300km/h. Using the results of multi-body dynamic analysis and the proposed procedure of Ekberg, we calculate the fatigue index of surface-initiated fatigue, subsurface-initiated fatigue and fatigue initiated at deep material defects. As a result. the fatigue index shows us whether fatigue will appear and in which form. In addition, we present Shakedown map on surface-initiated fatigue.

• IEMEK Journal of Embedded Systems and Applications
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• v.5 no.1
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• pp.7-17
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• 2010

ITS(Intelligent Transport System) as things are used for Broadcast service using TDMB/TPEG/NAVI rather than personal seamless service. It is attaching weight to Traffic information gathering, Charging, Settlement service. This research is applied to improve DCCP(Datagram Congestion Control Protocol) which has function as protecting data and preserving message boundary. The improving method is like that we solve data trust in UDP because Connection and Transmission overhead in UDP is less than in TCP. We fix the data loss which is generated from unordered delivery section of IP base wireless service by using DCCP protocol. We guarantee of connection with OBE(On-Board Equipment) and reliance about transmission of data by complement to mapping table and multi-hoping. Finally, We evaluate the performance about transmission of IP based data. We constructed a test-bed near research center for this test.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.127-134
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• 2003

Ad Hoc Networks, autonomous distributed network using routing scheme, does not operate properly owing to multi flow service when network load increases at specific network node. In this paper, we suggest traffic management routing protocol in Ad Hoc Network to reduce network traffic congestion and distribute network load in data transmission. Through test results of proposed algorithm under NS(Network Simulator)simulator environments . we acquired reduced network load and increased data transmission rate.

• Journal of Korean Society of Transportation
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• v.13 no.1
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• pp.35-62
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• 1995

Traffic has a very important function but has caused such social problems as traffic congestion parking and traffic accidents in metropolitan areas. It is difficult to examine the causes of traffic accidents related to human life, which occur by human, vehicle and environmental factors. But human factor is the only measure requlating these factors together an analyzing factors influencing establishment of counterplan of traffic accidents. Consequently , this study employs the principal component analysis and stepwise multiple regression analysis to estimate the characteristics and influential factors of traffic accidents and defines the typical patterns of happening lots of traffic accidents. Accordingly, this study establishes an acknowledgement model of the causes and preference model of the counterplan of traffic accidents using Multi-Dimension Preference(MDPREF) method.

• Journal of Internet of Things and Convergence
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• v.1 no.1
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• pp.1-4
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• 2015

This paper aims to present the mathematical model to find the mean web object transfer latency in the slow-start phase of TCP congestion control mechanism, which is one of the main control techniques of Internet. Mean latency is an important service quality measure of end-user in the network. The application area of the proposed latency model is the narrowband environment including multi-hop wireless network and Internet of Things(IoT), where packet loss occurs in the slow-start phase only due to small window. The model finds the latency considering initial window size and the packet loss rate. Our model shows that for a given packet loss rate, round trip time and initial window size mainly affect the mean web object transfer latency. The proposed model can be applied to estimate the mean response time that end user requires in the IoT service applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12B
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• pp.1081-1090
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• 2003

NGI(Next Generation Internet) is characterized by QoS(Quality of Service) and high speed transmission. Recently, DiffServ and MPLS become most influential NGI architecture. To guarantee end-to-end QoS, it is essential for NGI to interwork MPLS with DiffServ. Here, MPLS WG(Working Group) in IETF(Internet Engineering Task Force) proposed the method of E-LSP(EXP inferred-PSC LSPs) and L-LSP(Label-Only-Inferred PSC LSPs), but both of them have serious problems to satisfy perfect interworking. In this paper, we proposed an extended E-LSP architecture that supports Perfect DiffServ class and experimental function in MPLS such as ECN(Explicit Congestion Notification) capability. We verify that the proposed E-LSP architecture improves QoS in NGI by using ns2 simulator.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.65-72
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• 2002

In this paper, we implement a high-speed swatch tilth the function for label integration to enhance the expansion of networks using the label space of routers efficiently on MPLS over ATM networks. We propose an appropriate hardware structure to support the VC-merge function and differentiated services simultaneously. In this paper, we use the adaptive congestion control method such as EPD algorithm in carte that there is a possibility of network congestion in output buffers of each core LSR. In addition, we justify the validity of the proposed VC-merge method through simulation and comparison to conventional Non VC-merge methods. The proposed VC-merge capable switch is modeled in VHDL. synthesized, and fabricated using the SAMSUNG 0.5um SOG process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.178-202
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• 2012

In this paper, we first survey cross-layer architectures for Wireless Sensor Networks (WSNs) and Wireless Multimedia Sensor Networks (WMSNs). Afterwards, we propose a novel cross-layer architecture for QoS provisioning in clustered and multi-hop based WMSNs. The proposed architecture provides support for multiple network-based applications on a single sensor node. For supporting multiple applications on a single node, an area in memory is reserved where each application can store its network protocols settings. Furthermore, the proposed cross-layer architecture supports heterogeneous flows by classifying WMSN traffic into six traffic classes. The architecture incorporates a service differentiation module for QoS provisioning in WMSNs. The service differentiation module defines the forwarding behavior corresponding to each traffic class. The forwarding behavior is primarily determined by the priority of the traffic class, moreover the service differentiation module allocates bandwidth to each traffic class with goals to maximize network utilization and avoid starvation of low priority flows. The proposal incorporates the congestion detection and control algorithm. Upon detection of congestion, the congested node makes an estimate of the data rate that should be used by the node itself and its one-hop away upstream nodes. While estimating the data rate, the congested node considers the characteristics of different traffic classes along with their total bandwidth usage. The architecture uses a shared database to enable cross-layer interactions. Application's network protocol settings and the interaction with the shared database is done through a cross-layer optimization middleware.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.2
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• pp.53-65
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• 2016

Static wireless multi-hop networks, such as wireless mesh networks and wireless sensor networks have proliferated in recent years because of they are easy to deploy and have low installation cost. Two key measures are used to evaluate the performance of a multicast tree algorithm or protocol : end-to-end delay and the number of transmissions. End-to-end delay is the most important measure in terms of QoS because it affects the total throughput in wireless networks. Delay is similar to the hop count or path length from the source to each destination and is directly related to packet success ratio. In wireless networks, each node uses the air medium to transmit data, and thus, bandwidth consumption is related to the number of transmission nodes. A network has many transmitting nodes, which will cause many collisions and queues because of congestion. In this paper, we optimize two metrics through a guaranteed delay scheme. We provide an integer linear programming formulation to minimize the number of transmissions with a guaranteed hop count and preprocessing to solve the aforementioned problem. We extend this scheme not only with the guaranteed minimum hop count, but also with one or more guaranteed delay bounds to compromise two key metrics. We also provide an explanation of the proposed heuristic algorithm and show its performance and results.

• Journal of IKEEE
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• v.23 no.4
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• pp.1381-1386
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• 2019

As traffic congestion in cities becomes more serious, intelligent traffic control is actively being researched. Reinforcement learning is the most actively used algorithm for traffic signal control, and recently Deep reinforcement learning has attracted attention of researchers. Extended versions of deep reinforcement learning have been emerged as deep reinforcement learning algorithm showed high performance in various fields. However, most of the existing traffic signal control were studied in a single intersection environment, and there is a limitation that the method at a single intersection does not consider the traffic conditions of the entire city. In this paper, we propose a cooperative traffic control at multi-intersection environment. The traffic signal control algorithm is based on a combination of extended versions of deep reinforcement learning and we considers traffic conditions of adjacent intersections. In the experiment, we compare the proposed algorithm with the existing deep reinforcement learning algorithm, and further demonstrate the high performance of our model with and without cooperative method.