• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.46-54
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• 2003

In this paper, we propose segmentation algorithm for MR brain images using the histogram of T1-weighted, T2-weighted and PD images. Segmentation algorithm is composed of 3 steps. The first step involves the extraction of cerebrum images by ram a cerebrum mask over three input images. In the second step, peak ranges are determined from the histogram of the cerebrum image. In the final step, cerebrum images are segmented using coarse to fine clustering technique. We compare the segmentation result and processing time according to peak ranges. Also compare with the other segmentation methods. The proposed algorithm achieved better segmentation results than the other methods.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.235-245
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• 2018

Recently panoramic image overcomes camera limited viewing angle and offers wide viewing angle by stitching plenty of images. In this paper, we propose pre-processing and post-processing algorithm which makes speed and accuracy improvements when making panoramic images. In pre-processing, we can get camera sensor information and use three-dimensional rotation angle to find RoI(Region of Interest) image. Finding RoI images can reduce time when extracting feature point. In post-processing, we propose weighted minimal error boundary cut blending algorithm to improve accuracy. This paper explains our algorithm and shows experimental results comparing with existing algorithms.

• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.371-382
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• 2004

To improve the precision of relative positioning for GPS single frequency(L1) receiver, we accomplished the GPS data processing using the weighted smoothing techniques. The weighted phase smoothing technique is used to minimize the measurement error of pseudorange and position domain smoothing technique is adopted to make the complement of cycle-slip affection. we also considered some component errors like as ionospheric error, which are related with baseline length, and processed for several baselines (5, 10, 30, 40, and 150 km) to check the coverage area of this algorithm. This paper shows that weighted phase smoothing technique give more stable results after using this technique and the position domain smoothing technique can reduce the errors which are sensitive to the observational environment. Based on the results, we could find out that this algorithm is available for post-time and real-time applications and these techniques can be substitution methods which is able to get the high accuracy and precision without resolving the Integer ambiguity.

• Advances in Energy Research
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• v.7 no.1
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• pp.35-52
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• 2020

The paper proposes a hybrid approach of artificial bee colony (ABC) and grey wolf optimizer (GWO) algorithm for multi-objective and multidimensional engine optimization of a converted plug-in hybrid electric vehicle. The proposed strategy is used to optimize all emissions along with brake specific fuel consumption (FC) for converted parallel operated diesel plug-in hybrid electric vehicle (PHEV). All emissions particulate matter (PM), nitrogen oxide (NOx), carbon monoxide (CO) and hydrocarbon (HC) are considered as optimization parameters with weighted factors. 70 hp engine data of NOx, PM, HC, CO and FC obtained from Oak Ridge National Laboratory is used for the study. The algorithm is initialized with feasible solutions followed by the employee bee phase of artificial bee colony algorithm to provide exploitation. Onlooker and scout bee phase is replaced by GWO algorithm to provide exploration. MATLAB program is used for simulation. Hybrid ABC-GWO algorithm developed is tested extensively for various values of speeds and torque. The optimization performance and its environmental impact are discussed in detail. The optimization results obtained are verified by real data engine maps. It is also compared with modified ABC and GWO algorithm for checking the effectiveness of proposed algorithm. Hybrid ABC-GWO offers combine benefits of ABC and GWO by reducing computational load and complexity with less computation time providing a balance of exploitation and exploration and passes repeatability towards use for real-time optimization.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.621-633
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• 1997

This paper is concerned with the multiobjective vehicle scheduling problem with time and area-dependent travel speeds(MVSPTD), in which two conflicting objectives are explicitly treated and the travel speed between two locations depends on the passing area and time of day. The two objectives are the minimization of total vehicle travel time and the minimization of total weighted tardiness. First, I construct a mixed integer linear programming formulation of the MVSPTD, and present o heuristic algorithm that builds the vehicle schedules based on the savings computed. The results of computational experiments showed that the heuristic performs very well. Finally, I propose an expert system for vehicle scheduling in the MVSPTD. Its whole process is executed under VP-Expert expert system environment.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.296-304
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• 2005

Quantitative analysis compare to dynamic characteristic change of the regional cerebral blood volume(rCBV) after development of cerebral fat embolism in cats using perfusion magnetic resonance(MR) Imaging. Twenty cats were used. Linoleic acid (n=11) were injected into the internal carotid artery using microcatheter through the transfemoral approach. Polyvinyl alcohol (Ivalon) (n=9) was injected as a control group. Perfusion MR images were obtained at 30 minutes and 2 hours after embolization, based on T2 and diffusion-weighted images. The data was time-to-signal intensity curve and ${\Delta}R_2^*$ curve were obtained continuously with the aid of home-maid image process algorithm and IDL(interactive data Banguage, USA) softwares. The ratios of rCBV increased significantly at 2 hours compared with those of 30 minutes (P<0.005). In conclusion, cerebral blood flow decreased in cerebral fat embolism immediately after embolization and recovered remarkably in time course. It is thought that clinically informations to dynamic characteristic change of the cerebral hemodynamics to the early finding in cerebral infarction by diffusion weighted imaging(DWI) and perfusion weighted imaging(PWI).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.4B
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• pp.675-682
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• 2000

In this paper, we propose a new scheduling algorithm called the Adaptive Weighted Round Robin with Delay Tolerance (AWRR/DT). The proposed scheme is based on the per-class queueing mechanism in which a number of connections of similar characteristics are multiplexed into one class-queue. Traffic classes of the proposed method are classified into a single non-real-time traffic class and other real-time traffic classes. The proposed scheme determines the weights of classes according to the input traffic and delay characteristics of each class at the beginning of every cycle. Furthermore, this scheme incorporates a cell discarding method to reduce the QoS degradation that may be incurred by congestion of networks. We have evaluated the proposed scheme through discrete-event simulation. Simulation results indicate that the proposed scheme can reduce the average delay of non-real-time class while maintaining the QoS of real-timeclasses. The proposed algorithm can be effectively applied to high-speed networks such as ATM networks.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.87-97
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• 2004

In this paper, we propose an algorithm for interlaced-to-progressive conversion by the weighted summation of the information collected from spatial do-interlacing method, in which the weighted edge based line average is applied, and the temporal method in which the motion compensation is employed by using hi-directional BMA (block matching algorithm). We employed time-recursive and motion adaptive processing as motion detection is involved. Also, a median filter is used to deal with limitation of the linear summation in which only an intermediate of values being involved is determined. The main goal of the approach is to overcome the shortcomings of each of the do-interlacing techniques without significant increment of the computational complexity, and the proposed method is apt to implement in hardware for real-time processing.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.77-88
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• 2015

In this paper, we consider a two-agent single-machine scheduling problem with exponential job-dependent position-based learning effects. The objective is to minimize the total weighted completion time of one agent with the restriction that the makespan of the other agent cannot exceed an upper bound. First, we propose a branch-and-bound algorithm by developing some dominance /feasibility properties and a lower bound to find an optimal solution. Second, we design an efficient simulated annealing (SA) algorithm to search a near optimal solution by considering six different SAs to generate initial solutions. We show the performance superiority of the suggested SA using a numerical experiment. Specifically, we verify that there is no significant difference in the performance of %errors between different considered SAs using the paired t-test. Furthermore, we testify that random generation method is better than the others for agent A, whereas the initial solution method for agent B did not affect the performance of %errors.

• ETRI Journal
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• v.29 no.3
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• pp.329-335
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• 2007

This paper considers a timeslot assignment problem in an interactive satellite multimedia (ISM) system with digital video broadcast-return channel via satellite (DVB-RCS). The timeslot assignment problem is formulated as a binary integer programming to maximize the overall weighted throughput and is shown to be NP-hard. Thus, three real-time heuristic algorithms including ratio-based, packet-size (PS)-based, and transmission gain (TG)-based are derived, and some computational experiments are made. Considering the results, the ratio-based heuristic algorithm is demonstrated to be the most effective and efficient. We propose adapting the ratio-based heuristic algorithm to the timeslot assignment problem to greatly improve the ISM system utilization.