• Journal of KIISE:Information Networking
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• v.30 no.2
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• pp.260-269
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• 2003

The traditional distributed object middleware platform is not suitable for the transmission of stream data, because RPC(Remote Procedure Call)-based message transmission have a great overhead. Therefore, the OMG(Object Management Group) proposes the AV(Audio and Video) stream reference model for streaming on the distributed object middleware platform. But, this reference model has not a detail of implementation. Particularly it also has not congestion control scheme for improvement of network efficiency on the real network environment. It is a very important and difficult technical issue to provide the stream transmission platform with advanced congestion control scheme. In this paper, we propose an architecture of a distributed stream transport platform and deal with the design and implementation concept of our proposed platform. Also, we present a mechanism to improve streaming utilization by SRTP(Smart RTP). SRTP is our proposed TCP-Friendly scheme.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.67-80
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• 2020

High-speed weigh in motion (HS-WIM) is a real-time unmanned system for measuring the weight of a freight-carrying vehicle while it is in motion without controlling vehicle traffic flow or deceleration. In Korea, HS-WIM systems are installed on the national highways and general national ways for pre-selection by law enforcement. In this study, to improve the measurement accuracy of HS-WIM, we devise improvements to the existing integral and peak weight conversion algorithms, and we provide a new fusion algorithm that can be applied to the mat-type HS-WIM. As a result of analyzing vehicle driving tests at a real site, we confirmed the highest level of weight-measuring accuracy.

• Journal of Radiation Protection and Research
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• v.47 no.3
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• pp.111-133
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• 2022

The exciting advancement related to the "modeling of digital human" in terms of a computational phantom for radiation dose calculations has to do with the latest hype related to deep learning. The advent of deep learning or artificial intelligence (AI) technology involving convolutional neural networks has brought an unprecedented level of innovation to the field of organ segmentation. In addition, graphics processing units (GPUs) are utilized as boosters for both real-time Monte Carlo simulations and AI-based image segmentation applications. These advancements provide the feasibility of creating three-dimensional (3D) geometric details of the human anatomy from tomographic imaging and performing Monte Carlo radiation transport simulations using increasingly fast and inexpensive computers. This review first introduces the history of three types of computational human phantoms: stylized medical internal radiation dosimetry (MIRD) phantoms, voxelized tomographic phantoms, and boundary representation (BREP) deformable phantoms. Then, the development of a person-specific phantom is demonstrated by introducing AI-based organ autosegmentation technology. Next, a new development in GPU-based Monte Carlo radiation dose calculations is introduced. Examples of applying computational phantoms and a new Monte Carlo code named ARCHER (Accelerated Radiation-transport Computations in Heterogeneous EnviRonments) to problems in radiation protection, imaging, and radiotherapy are presented from research projects performed by students at the Rensselaer Polytechnic Institute (RPI) and University of Science and Technology of China (USTC). Finally, this review discusses challenges and future research opportunities. We found that, owing to the latest computer hardware and AI technology, computational human body models are moving closer to real human anatomy structures for accurate radiation dose calculations.

• Convergence Security Journal
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• v.12 no.1
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• pp.35-42
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• 2012

Increase of data traffic and the advent of new real-time services require to change from the traditional TDM-based (Time Division Multiplexing) networks to the optical networks that soft and dynamic configuration. Voice and lease line services are main service area of the traditional TDM-based networks. This optical network became main infrastructure that offer many channel that can convey data, video, and voice. To provide high resilience against failures, Packet-optical networks must have an ability to maintain an acceptable level of service during network failures. Fast and resource optimized lightpath restoration strategies are urgent requirements for the near future Packet-optical networks with a Generalized Multi-Protocol Label Switching(GMPLS) control plane. The goal of this paper is to provide packet-optical network with a hierarchical multi-layer recovery in order to fast and coordinated restoration in packet-optical network/GMPLS, focusing on new implementation information. The proposed schemes do not need an extension of optical network signaling (routing) protocols for support.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.3
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• pp.87-97
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• 2018

The traffic accident reports that are generated by the Traffic Broadcasting Networks(TBN) are unstructured data. It, however, has the value as some sort of real-time traffic information generated by the viewpoint of the drives and/or pedestrians that were on the roads, the time and spots, not the offender or the victim who caused the traffic accidents. However, the traffic accident reports, which are big data, were not applied to traffic accident analysis and traffic related research commonly. This study adopting text-mining technique was able to provide a clue for utilizing it for the impacts of traffic accidents. Seven years of traffic reports were grasped by this analysis. By analyzing the reports, it was possible to identify the road names, accident spot names, time, and to identify factors that have the greatest influence on other drivers due to traffic accidents. Authors plan to combine unstructured accident data with traffic reports for further study.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.125-133
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• 2016

Data processing capacity and speed are rapidly increasing due to the development of hardware and software in recent time. As a result, data usage is geometrically increasing and the amount of data which computers have to process has already exceeded five-thousand transaction per second. That is, the importance of Big Data is due to its 'real-time' and this makes it possible to analyze all the data in order to obtain accurate data at right time under any circumstances. Moreover, there are many researches about this as construction of smart factory with the application of Big Data is expected to have reduction in development, production, and quality management cost. In this paper, system using In-Memory Data Grid for high speed processing is implemented in semiconductor process which numerous data occur and improved performance is proven with experiments. Implemented system is expected to be possible to apply on not only the semiconductor but also any fields using Big Data and further researches will be made for possible application on other fields.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.1
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• pp.13-27
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• 2012

According to the development of Intelligent Transportation System technology, VMS(Variable Message Signs) are operating on highway. But, VMS display information which don't reflect traffic condition and driver's human factor. So driver can't read VMS message during limited time, it makes to reduce VMS's reliability. This paper presents a model for VMS message reading time and distance considering traffic condition and human factor. We built driving simulator by Winroad package which is able to copy real driving condition. Subjects were comprised of 20 people who reflect domestic driver's condition such as sex. We did regression analysis with experiment results and draw the model. The model could be possible to develop message- set considering traffic condition and human factor.

• Journal of KIISE:Information Networking
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• v.33 no.2
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• pp.156-164
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• 2006

The SCTP (Stream Control Transmission Protocol) implementation with the DAR (Dynamic Address Reconfiguration) extension is called the mSCTP (Mobile SCTP) that is proposed recently for mobility support in transport layer. The mSCTP does not satisfy short handover latency for real-time applications and it has no specific handover decision mechanisms. In this paper, we propose fast handover schemes for mobile nodes that are moving into different subnet using pre-acquisition RA (Router Advertisement) and L3 trigger for improving handover performance. Furthermore, we introduce three specific methods which are RA cache, FMIPv6 (Fast Handovers for Mobile IPv6) and dual interface and how proposed scheme can be interoperated with handover process respectively. Finally, we show two experimental results which are the mSCTP and the mSCTP using FMIPv6 on Linux platforms. Experimental results show that handover performance is improved with reducing the time of receiving RA which takes most of total handover latency.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.33-40
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• 2002

This paper presents the evaluation result of the Namsan 1st tunnel traffic information system, which is providing the real time queue length status and incidence information inside of the Namsan 1st tunnel, 1600meters long in the Seoul metropolitan CBD. This information system plays an important role because of notifying drivers to pay a toll for the tunnel path, the congestion information in advance. According to the analysis, an evident improvement on the tunnel path and its bypass without any conspicious adverse impact. Furthermore, survey analysis found that motorists placed a high value on the provided information. During peak time, the system turned out to help motorists to relax their hasty minds. As well, several performance indices showed the reduction of congestion and travel time variation on both of the tunnel path and its bypass, in spite of no traffic information on the bypass.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.22-31
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• 2008

RT/IMPOST is an effective algorithm that can realize real-time internal metering policy (IMP) using queue information from loop detector and signal control strategies. In this paper, an investigation was made to adopt the IMP methodology within COSMOS environments in terms of communication environment and control time point. Through the analysis of the communication environment of COSMOS and communication and control steps in RT/IMPOST, a set of applicable alternative were developed and evaluated. Then, one of the alternatives was selected, and performance of the alternative was compared with RT/IMPOST system using a simulation technique. Results showed that two techniques produced the similar performance. Therefore, the method suggested in this paper was evaluated as a practically viable alternative.