• Journal of Navigation and Port Research
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• v.40 no.2
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• pp.67-72
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• 2016

Vietnam's sea-port industry has experienced a significant development in recent years. Especially in Northern Vietnam, both the demand and supply of handling services for containerized cargoes have increased at a considerable rates. Accompany with such movement, the competition among container terminals in the area becomes fiercer. In this paper, Hierarchical Cluster Analysis is employed to classify all 11 container terminals in Northern Vietnam by collecting data concerning terminal competitiveness. After the classification, each group will be discussed in order to reveal more details about their competitive characteristics. The paper consists of five sections. Section 1 is the general introduction. Section 2 provides a general literature review about competitiveness and factors to evaluate competitiveness. Section 3 explains variables and methodology applied to do the analysis. Section 4 presents the results with linkage to the current condition. Section 5 summarizes the analysis results. It is shown that container terminals in Northern Vietnam should not only pay attention to their service qualities but also have to find out an appropriate mechanism to avoid unhealthy competition. The paper is expected to contribute a background for further researches in container terminals' competition in the region as well as hints for operators in planning and making decisions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.323-326
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• 2007

When traveling on real road network, it generally takes less travel time in a near straight path than a zig-zaged path with same source and destination. In order to making a left(right/u) turn, the delay should be required to decrease the speed. The traffic signal waiting time of left(right/u) turn is probably longer than straight driving. In this paper, we revise the previous hierarchical path finding algorithm to reduce the number of turns. The algorithm proposed in this paper complied with a hierarchical $A^*$ algorithm, but has a distinct strategy for edge weight. We define an edge that makes a turn as a turn-edge and give the turn-edge lower weight to maintain the straightness of the whole path.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.120-122
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• 2006

The paper concerns the hybrid optimization of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation. The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the hybrid optimization process, two general optimization mechanisms are explored. Thestructural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods.

• Spatial Information Research
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• v.14 no.4 s.39
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• pp.403-419
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• 2006

The well-blown address matching technology developed by the U.S. Census Bureau was applicable only for street addresses. However, many other addressing systems on the basis of a hierarchy of areas (hierarchical areal addressing system), such as Korean or Japanese addressing system, cannot be suitable for the existing address matching method. This paper, therefore, develops an areal address matching method, especially for Korean addressing system, in order to geocode 2D and 3D locational data of human activities. Thus, this study explains a new approach to dealing with 3D positioning method composed of two geocoding methods, which are a '2D Korean Address Matching' technique and a '3D Address Matching' technique.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.344-351
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• 2007

In this paper, we propose an approach to design multi-fuzzy controllers for the superheat and the low pressure that have an influence on energy efficiency and stabilization of air conditioning system with multi-evaporators. Air conditioning system with multi-evaporators is composed of compressor, condenser, several evaporators and several expansion valves. It is quite difficult to control the air conditioning system because the change of the refrigerant condition give an impact on the overall air conditioning system. In order to solve the drawback, we design multi-fuzzy controllers which control simultaneously both three expansion valve and one compressor for the superheat and the low pressure of air conditioning system. The proposed multi fuzzy controllers are given as a kinds of controller types such as a simplified fuzzy inference type. Here the scaling factors of each fuzzy controller are efficiently adjusted by Hierarchical Fair Competition-based Genetic Algorithms. The values of performance index of the simulation results of the A company type compare with simulation results of simplified inference type.

• Journal of Ocean Engineering and Technology
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• v.13 no.3B
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• pp.106-115
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• 1999

Modeling a discrete event system such as a sequential control system is difficult compared with a continuous system. Petri nets have been introduced as an analyzing and design tool for the discrete systems. One of the problems in its applications is that the model can not be analyzed easily in the case of large scale or complicated systems because of increase of the number of components of the system. To overcome this problem, some methods for dividing or reducing Petri nets have been suggested. In this paper, an approach for a hierarchical expression of Petri nets based on Sequential Function Chart(SFC) is proposed. A measuring tank system will be described as a typical kind of discrete systems. The system is modeled by sub Petri nets based on SFC in order to analyze and visualize efficiently about the dynamic behaviors of the system. Some numerical simulations using state equations are performed to prove the validity of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.1-8
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• 2003

Scheduling technology is one of the most important elements required to support the Quality of service (QoS) in the Internet and a lot of scheduling algorithms have been developed. However, most of these algorithms ire not flexible to distribute the excess bandwidth. In order to provide flexibility for distributing the excess bandwidth, we proposed excess bandwidth fair queueing (EBFQ) algorithm with relatively low complexity. In this paper, we propose the new extension to this EBFQ algorithm for the hierarchical fair queueing system. This extension can be naturally applied to the existing hierarchical algorithm and simultaneously provide the same level of fairness. Through the simulation and analysis, we verify it.

• Journal of Communications and Networks
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• v.12 no.2
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• pp.122-129
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• 2010

Energy conservation is one of the most important issues for evaluating the performance of wireless sensor network (WSN) applications. Generally speaking, hierarchical clustering protocols such as LEACH, LEACH-C, EEEAC, and BCDCP are more efficient in energy conservation than flat routing protocols. However, these typical protocols still have drawbacks of unequal and high energy depletion in cluster heads (CHs) due to the different transmission distance from each CH to the base station (BS). In order to minimize the energy consumption and increase the network lifetime, we propose a new hierarchical routing protocol, distance aware intelligent clustering protocol (DAIC), with the key concept of dividing the network into tiers and selecting the high energy CHs at the nearest distance from the BS. We have observed that a considerable amount of energy can be conserved by selecting CHs at the nearest distance from the BS. Also, the number of CHs is computed dynamically to avoid the selection of unnecessarily large number of CHs in the network. Our simulation results showed that the proposed DAIC outperforms LEACH and LEACH-C by 63.28% and 36.27% in energy conservation respectively. The distance aware CH selection method adopted in the proposed DAIC protocol can also be adapted to other hierarchical clustering protocols for the higher energy efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3B
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• pp.143-152
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• 2007

In order to provide new value-added services such as a policy-based routing and the quality of services in next generation network, the Internet routers need to classify packets into flows for different treatments, and it is called a packet classification. Since the packet classification should be performed in wire-speed for every packet incoming in several hundred giga-bits per second, the packet classification becomes a bottleneck in the Internet routers. Therefore, high speed packet classification algorithms are required. In this paper, we propose an efficient packet classification architecture based on a hierarchical binary search fee. The proposed architecture hierarchically connects the binary search tree which does not have empty nodes, and hence the proposed architecture reduces the memory requirement and improves the search performance.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.204-206
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• 2007

In this study, we introduce the optimization method of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation, The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods. Particularly, in parameter identification, we use the UNDX operator which uses multiple parents and generate offsprings around the geographic center off mass of these parents.