• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.624-627
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• 2014

In vehicular network, the basic goal is to provide vehicle safety service and commercial service such as ITS(Intelligent Transportation System) or video, etc on the road. And most research concentrated on transportation of safety message in congestion situation. It is important to allocate channel for safety message in congestion situation, but providing suitable service is also important problem in vehicular network. For this reason, IEEE 1609.4 allocate 4 multiple service channels (SCHs) for non-safety data transfer. But, in congestion situation with many vehicles, the contention for channel acquisition between services becomes more severe. So services are provided improperly because of lack of service channel. This paper suggests dynamic channel allocation algorithm. The proposed algorithm is that RSU(RaodSide Unit) maintain and manage the information about service and status of channels. On based of the SJF(Shortest Job First) scheduling using those information, RSU selects the most appropriate channel among the 4 SCHs allocated by IEEE 1609.4 in network congestion situation.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.9
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• pp.758-767
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• 2000

The properties of linear time-varying(LTV) systems vary because of the time-varying property of plant parameters. The generalized controller design method for linear time-varying systems does not exit because the analytic soultion of dynamic equation has not been found yet. Hence, to design a controller for LTV systems, the robust control methods for uncertain LTI systems which are the approximation of LTV systems have been generally ised omstead. However, these methods are not sufficient to reflect the fast dynamics of the original time-varying systems such as missiles and supersonic aircraft. In general, both the performance and the robustness of the control system which is designed with these are not satisfactory. In addition, since a better model will give the more robustness to the controlled system, a gain scheduling technique based on LTI controller design methods has been uesd to solve time problem. Therefore, we propose a new gain scheduled QFT method for LTV systems based on neural networks in this paper. The gain scheduled QFT involves gain dcheduling procedured which are the first trial for QFT and are well suited consideration of the properties of the existing QFT method. The proposed method is illustrated by a numerical example.

• The Transactions of the Korea Information Processing Society
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• v.7 no.1
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• pp.12-19
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• 2000

In the development of a production process scheduling system a collaboration method must be defined for the cooperation among submodules within the system. The blackboard architecture is exploited for solving the collaboration problem, which is one of the problem solving architecture that belongs to the distributed artificial intelligence. The dynamic states of the problem solving processes are presented in the hierarchically constructed shared working memory called as a blackboard. The communication for the collaboration is done through the blackboard. The problem solving steps are contained in the global controller, one of a component that consists the blackboard architecture, as knowledge. The global controller activates proper submodules based on the knowledge. By applying the blackboard architecture the collaboration problem among submodules in the grating production process scheduling system (GPSS) has been solved as well as the system became adaptable to the future modifications and expansions.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.2
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• pp.95-103
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• 2007

Dynamic voltage scaling (DVS) is a well-known and effective power management technique. While there has been research on slack distribution, voltage allocation and other aspects of DVS, its effects on non-voltage-scalable devices has hardly been considered. A DC-DC converter plays an important role in voltage generation and regulation in most embedded systems, and is an essential component in DVS-enabled systems that scale supply voltage dynamically. We introduce a power consumption model of DC-DC converters and analyze the energy consumption of the system including the DC-DC converter. We propose an energy-optimal off-line DVS scheduling algorithm for systems with DC-DC converters, and show experimentally that our algorithm outperforms existing DVS algorithms in terms of energy consumption.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.2
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• pp.75-86
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• 2002

The selection of the optimal checkpointing interval has been a very critical issue to implement a checkpointing recovery scheme for the fault tolerant distributed system. This paper presents a new scheme that allows a process to select the proper checkpointing interval dynamically. A process in the system evaluates the cost of checkpointing and possible rollback for each checkpointing interval and selects the proper time interval for the next checkpointing Unlike the other scheme, the overhead incurred by both of the checkpointing and rollback activities are considered for the cost evaluation and current communication pattern is reflected in the selection of the checkpointing interval. Moreover, the proposed scheme requires no extra message communication for the checkpointing interval selection and can easily be incorporated into the existing checkpointing coordination schemes.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.1
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• pp.1-8
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• 2016

We proposed a load unbalancing scheduling method for energy-efficient multi-core embedded systems considering DVFS (Dynamic Voltage/Frequency Scaling) power consumption and task characteristics. It is a new kind of scheduler which combines load balancing and load unbalancing technique. The purpose of the method is to effectively utilize energy without much effect in performance. In this paper, we conduct experiments on energy consumption and performance using the previous load balancing and unbalancing techniques and our proposed technique. The proposed technique reduced energy consumption more than 13.7% when compared to other algorithms. As a result, the proposed technique shows low energy consumption without much decline in the performance and is adequate for energy-efficient multi-core embedded systems.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.12
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• pp.594-602
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• 1986

This paper proposes an effective algorithm for short-term generation scheduling for the purpose of economic and secure operation of thermal power systems. Especially, in the procedure of solution by Dynamic Programming, Linear Programming is introduced to promote the possibility of optimal solution and the security of power systems, and evaluation of security function is improved by the application of seven step approximation of normal distribution. Several necessary considerations, that is, time dependent start-up and constant down cost of generating units, demand and spinning reserve constraints, minimum up and sown time constraints, the number of possible start-up of a generating unit in a d and the number of generating units which can be started up at the same time at the same bus, are also incoporated to elevate the usability and flexibility of the algorithm. Finally, the effectiveness of the proposed algorithm has been demonstrated by applying to the 6-gen. 21-bus model power system.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.1
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• pp.17-26
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• 2000

This paper presents an integrated order scheduling method with the improved DRP concept for multi-echelon distribution system that has the constraint of limited production capacity of producers. The proposed method reflects the dynamic characteristics of inventory level changes in the regional and central distribution center. The simulation is done with two models : the traditional DRP method and the proposed method presented in this paper. From the results, the latter is more efficient than the former in cost, customer's service level as well as balanced production load on each producer.

• The KSFM Journal of Fluid Machinery
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• v.18 no.1
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• pp.59-64
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• 2015

The pitch control system in wind turbines becomes more and more important as the wind turbines are larger in multi-MW size. PI controller has been applied in most pitch controllers and it has been known that gain-scheduling is essential for pitch control of wind turbines. A demo model of 2 MW wind turbine which represents the whole dynamics of wind turbine including dynamic behaviors of blade, tower and rotational shaft is given in the commercial Bladed S/W for real wind turbines. In this paper, some results on step responses of the pitch PI controller and effectiveness of gain-scheduled pitch PI controller are presented through the Bladed S/W for the 2 MW wind turbine.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.1940-1949
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• 2015

This paper presents an Enhanced Particle Swarm Optimization (EPSO) to solve short-term hydrothermal scheduling (STHS) problem with non-convex fuel cost function and a variety of operational constraints related to hydro and thermal units. The operators of the conventional PSO are dynamically controlled using exponential functions for better exploration and exploitation of the search space. The overall methodology efficiently regulates the velocity of particles during their flight and results in substantial improvement in the conventional PSO. The effectiveness of the proposed method has been tested for STHS of two standard test generating systems while considering several operational constraints like system power balance constraints, power generation limit constraints, reservoir storage volume limit constraints, water discharge rate limit constraints, water dynamic balance constraints, initial and end reservoir storage volume limit constraints, valve-point loading effect, etc. The application results show that the proposed EPSO method is capable to solve the hard combinatorial constraint optimization problems very efficiently.