• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5B
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• pp.348-356
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• 2012

The application traffic analysis is getting more and more challenging due to the huge amount of traffic from high-speed network link and variety of applications running on wired and wireless Internet devices. Multi-level combination of various analysis methods is desired to achieve high completeness and accuracy of analysis results for a real-time analysis system, while requires much of processing burden on the contrary. This paper proposes a novel architecture for a real-time traffic analysis system which improves the processing performance on multi-core CPU environment. The main contribution of the proposed architecture is an efficient parallel processing mechanism with multiple threads of various analysis methods. The feasibility of the proposed architecture was proved by implementing and deploying it on our campus network.

• Journal of Korean Society of Transportation
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• v.34 no.4
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• pp.354-372
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• 2016

This study identified factors affecting the crash severity at freeway work zones. A nice feature of this study was to take into account the characteristics of work zone traffic management in analyzing traffic safety concerns. In addition to crash records, vehicle detection systems (VDS) data and work zone historical data were used for establishing a dataset to be used for statistical analyses based on an ordered probit model. A total of six safety improvement strategies for freeway work zones, including traffic merging method, guidance information provision, speed management, warning information systems, traffic safety facility, and monitoring of effectiveness for countermeasures, were also proposed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.7
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Smart Structures and Systems
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• v.15 no.3
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• pp.683-698
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• 2015

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

• Smart Structures and Systems
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• v.17 no.6
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• pp.917-933
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• 2016

In a prestressed concrete bridge, the magnitude of the prestress force (PF) decreases with time. This unexpected loss can cause failure of a bridge which makes prestress force identification (PFI) critical to evaluate bridge safety. However, it has been difficult to identify the PF non-destructively. Although some research has shown the feasibility of vibration based methods in PFI, the requirement of having a determinate exciting force in these methods hinders applications onto in-service bridges. Ideally, it will be efficient if the normal traffic could be treated as an excitation, but the load caused by vehicles is difficult to measure. Hence it prompts the need to investigate whether PF and moving load could be identified together. This paper presents a synergic identification method to determine PF and moving load applied on a simply supported prestressed concrete beam via the dynamic responses caused by this unknown moving load. This method consists of three parts: (i) the PF is transformed into an external pseudo-load localized in each beam element via virtual distortion method (VDM); (ii) then these pseudo-loads are identified simultaneously with the moving load via Duhamel Integral; (iii) the time consuming problem during the inversion of Duhamel Integral is overcome by the load-shape function (LSF). The method is examined against different cases of PFs, vehicle speeds and noise levels by means of simulations. Results show that this method attains a good degree of accuracy and efficiency, as well as robustness to noise.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.54 no.7
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• pp.309-316
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• 2005

In this paper we analyzed a dangerous failure and a safety requirement based on HIA (Hazard Identification and Analysis) of an interface model between CTC (Centralized Traffic Control) system and El (Interlocking) system, and assigned SU (Safety Integrity Level) by way of an risk estimation of the interface, which employed PHA (Preliminary Hazard Analysis) for the interface of the track control system, being managed as separated system between the centralized traffic control system and the interlocking system, An estimation which satisfies a safety reference of the international standard has been achieved through a quantification of the system failure rate and the dangerous failure rate of the interface model.

• International Journal of Aeronautical and Space Sciences
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• v.13 no.3
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• pp.377-385
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• 2012

The Automatic Dependent Surveillance Broadcast (ADS-B) system is a key component of CNS/ATM recommended by the International Civil Aviation Organization (ICAO) as the next generation air traffic control system. ADS-B broadcasts identification, positional data, and operation information of an aircraft to other aircraft, ground vehicles and ground stations in the nearby region. This paper explores the ADS-B based trajectory prediction and the conflict detection algorithm. The multiple-model based trajectory prediction algorithm leads accurate predicted conflict probability at a future forecast time. We propose an efficient and accurate algorithm to calculate conflict probability based on approximation of the conflict zone by a set of blocks. The performance of proposed algorithms is demonstrated by a numerical simulation of two aircraft encounter scenarios.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10A
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• pp.930-937
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• 2005

In this paper, a processing time and traffic capacity analysis algorithm for RFID system using LBT-serial searching scheme is proposed. Service time, carrier sensing time, additional delay time required for contiguous frequency channel occupancy, and additional delay time required for the contiguous using the same frequency channel are considered and the processing delay and frequency channel capacity are analyzed for the steady state operation of the system. The simulation results showing maximum capacity of the system and explaining the accuracy of the algorithm are provided.

• Journal of the Korean Institute of Navigation
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• v.25 no.1
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• pp.11-22
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• 2001

Nowadays, it is planning to establish a coastal VTS in Korean southern coastal waters in order to enhance the safety of vessel traffic and to protect the marine environment. But, it surely needs over ten billions Won to establish, operate and maintain the above mentioned coastal VTS. Therefore, this paper proposes the VTS cost-benefit analysis model to confirm the reasonability and decide the priority of the project. This model has three distinct processes. Fist, it is the identification in qualitative terms of the effects of a given proposal. Second, it quantify the specified effects in physical terms. Third, it is the evaluation of the total effects of project. The proposed model in this Paper will contribute to the confirmation and the priority of the project in future.

• Journal of Navigation and Port Research
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• v.31 no.4
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• pp.295-307
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• 2007

The statistics of Korean Maritime Safety Tribunal and Japan Marine Accidents Inquiry Agency shows that the major muses of collision at sea are Improper lookout and Non-compliance with marine traffic rules. Those two muses are occupying more than 70% of collision, and it's clear that those muses are undoubtedly closely related to simple human error. In this paper we tried to find out the root muses of this kind of human error of OOWs(officers on watch) through risk identification method and studied how to tackle them via risk control theory. In conclusion, the measures studied in this paper could be applied to help OOWs avoid their own human error as well as be used in shipping company for their fleets' safety management.