• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.9 s.102
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• pp.1070-1076
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• 2005

Vibration test using the MAST(multi axial simulation table) provide a more reliable testing environment than any conventional one. The multi axial simulation could be possible with a advanced control algorithm and hardware supports so that most of the operation is automatically conducted by MAST system itself except the input information that is synthesized by the measured response signals. That means the reliability of the vibration test is highly depended on the quality of the input profile. In this paper, the optimal algorithm based on the energy method is introduced to construct a best combination of candidated input PSD data could be constructed. Since the optimal algorithm renders time information, the nitration fatigue test is completely possible for any measured signals one wants. The proposed method is explained with representing acquired road signals from the candidate input PSD obtained from a proving ground.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.4
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• pp.62-70
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• 2007

Recently, the increasing trend for the transshipment traffic of Busan port in Korea is slowing down because of the extensive development plan of domestic ports in china. For solving this problem, Korea is going on the project for preoccupying the transshipment port for attraction of port traffic from the newly potential markets(NPM) based on the Northeast Asia area. As a part of the project, this paper proposes the efficient methodology for selecting the optimal shipping network and strategic transshipment port within NPM using the mathematical models and simulation analysis. For that, we firstly find the alternative transshipment ports within NPM through the status analysis of the current port traffic and shipping network and then, we choose the candidate transshipment-ports in order of minimizing the transport costs through the mathematical approach. With the scenarios based on the selected transshipment-ports, we perform the simulation analysis for choosing the optimal transshipment-ports and the shipping network minimizing the total costs and times concurrently. We expect that the results of this paper will be used efficiently when korea select the strategic transshipment-port in the future.

• Transactions of the Korean Society of Automotive Engineers
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• v.23 no.6
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• pp.591-600
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• 2015

The efficiency of a powertrain system of hybrid vehicle is highly dependent on the design and control of the hybrid powertrain system. In other words, the optimal design of the powertrain systems is coupled with optimal control of the powertrain system. Therefore, the solution of an optimal design problem for hybrid vehicles is computationally and timely very expensive. For example, dynamic programming, which is a recursive optimization method, is usually used to evaluate the best fuel economy of certain hybrid vehicle design, and, thus, the evaluation takes tens of minutes to several hours. This research aims to accelerate the speed of efficiency evaluation of hybrid vehicles. We suggest a mathematical treat and a methodological treat to reduce the computational load. The mathematical treat is that the dynamics of system is discretized with sparse sampling time without loss of energy balance. The methodological treat is that the efficiency of the hybrid vehicle is inferred by characteristic loss evaluation that is computationally inexpensive. With the suggested methodology, evaluating a design candidate of hybrid powertrain system is taken few minutes, which was taken several hours when dynamic programming is used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1648-1672
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• 2020

There are several types of image registration in the sense of stitching separated images that overlap each other. One of these is feature-based registration by a common feature descriptor. In this study, we generate a mosaic of images using feature-based registration for drone aerial images. As a feature descriptor, we apply the scale-invariant feature transform descriptor. In order to investigate the authenticity of the feature points and to have the mapping function, we employ the sample consensus method; we consider the sensed image's inherent characteristic such as the geometric congruence between the feature points of the images to propose a novel hypothesis estimation of the mapping function of the stitching via some optimally chosen initial candidate inliers in the sample consensus method. Based on the experimental results, we show the efficiency of the proposed method compared with benchmark methodologies of random sampling consensus method (RANSAC); the well-ordering property defined in the context and the extensive stitching examples have supported the utility. Moreover, the sample consensus scheme proposed in this study is uncomplicated and robust, and some fatal miss stitching by RANSAC is remarkably reduced in the measure of the pixel difference.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.699-712
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• 2016

Recently, greedy algorithm has received much attention as a cost-effective means to reconstruct the sparse signals from compressed measurements. Much of previous work has focused on the investigation of a single candidate to identify the support (index set of nonzero elements) of the sparse signals. Well-known drawback of the greedy approach is that the chosen candidate is often not the optimal solution due to the myopic decision in each iteration. In this paper, we propose a tree search based sparse signal recovery algorithm referred to as the tree search matching pursuit (TSMP). Two key ingredients of the proposed TSMP algorithm to control the computational complexity are the pre-selection to put a restriction on columns of the sensing matrix to be investigated and the tree pruning to eliminate unpromising paths from the search tree. In numerical simulations of Internet of Things (IoT) environments, it is shown that TSMP outperforms conventional schemes by a large margin.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1369-1379
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• 2018

In this paper, a model predictive torque control (MPTC) without the use of a weighting factor for surface mounted permanent-magnet synchronous machine (SPMSM) drive systems is presented. Firstly, the desired voltage vector is predicted in real time according to the principles of deadbeat torque and flux control. Then the sector of this desired voltage vector is determined. The complete enumeration for testing all of the feasible voltage vectors is avoided by testing only the candidate vectors contained in the sector. This means that only two voltage vectors in the sector need to be tested for selecting the optimal voltage vector in each control period. Thus, the calculation time can be reduced when compared with the conventional enumeration method. On the other hand, a novel cost function that only includes the dq-axis voltage errors between the desired voltage and candidate voltage is designed to eliminate the weighting factor used in the conventional MPTC. Thus, the control complexity caused by the tuning of the weighting factor is effectively decreased when compared with the conventional MPTC. Simulation and experimental investigation have been carried out to verify the proposed method.

• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.252-261
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• 2012

This papers proposes a motion vector coding method which selects the optimal predictive motion vector after excluding some candidate predictive motion vectors in the minimum rate-distortion sense, and prunes the candidate predictive motion vectors by a contradiction testing that operates under a predefined criterion at both encoder and decoder for reducing the signaling information. Experimental results show that the proposed method gains in BDBR by up to 1.8% compared to the H.264/AVC.

• Journal of KIISE
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• v.43 no.11
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• pp.1275-1280
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• 2016

Existing techniques for string similarity search first generate a set of candidate strings and then verify the candidates. The efficiency of string similarity search is highly dependent on candidate generation methods. State of the art techniques select fixed length q-grams from a query string and generate candidates using inverted lists of the selected q-grams. In this paper, we propose a technique to generate candidates using variable length grams of a query string and develop a dynamic programming algorithm that selects an optimal combination of variable length grams from a query string. Experimental results show that the proposed technique improves the performance of string similarity search compared with the existing techniques.

• Advances in Energy Research
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• v.5 no.2
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• pp.147-177
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• 2017

This study aims to evaluate and prioritize ten different sites in Iran's Khorasan provinces for the construction of wind farm. After studying the geography of the sites, nine criteria; including wind power, topography, wind direction, population, distance from power grid, level of air pollution, land cost per square meter, rate of natural disasters, and distance from road network-are selected for the analysis. Prioritization is performed using data envelopment analysis (DEA). The developed DEA model is validated through value engineering based on the results of brainstorming sessions. The results show that the order of priority of ten assessed candidate sites for installing wind turbines is Khaf, Afriz, Ghadamgah, Fadashk, Sarakhs, Bojnoord, Nehbandan, Esfarayen, Davarzan, and Roudab. Additionally, the outcomes extracted from the value engineering method identify the city of Khaf as the best candidate site. Six different wind turbines (7.5 to 5,000 kW) are considered in this location to generate electricity. Regarding an approach to produce and store hydrogen from wind farm installed in the location, the AREVA M5000 wind turbine can produce approximately $337ton-H_2$ over a year. It is an enormous amount that can be used in transportation and other industries.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.328-336
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• 2012

In this paper, we propose a robust fingertip extraction and extended Continuously Adaptive Mean Shift (CAMSHIFT) based robust hand gesture recognition for natural human-like HRI (Human-Robot Interaction). Firstly, for efficient and rapid hand detection, the hand candidate regions are segmented by the combination with robust $YC_bC_r$ skin color model and haar-like features based adaboost. Using the extracted hand candidate regions, we estimate the palm region and fingertip position from distance transformation based voting and geometrical feature of hands. From the hand orientation and palm center position, we find the optimal fingertip position and its orientation. Then using extended CAMSHIFT, we reliably track the 2D hand gesture trajectory with extracted fingertip. Finally, we applied the conditional density propagation (CONDENSATION) to recognize the pre-defined temporal motion trajectories. Experimental results show that the proposed algorithm not only rapidly extracts the hand region with accurately extracted fingertip and its angle but also robustly tracks the hand under different illumination, size and rotation conditions. Using these results, we successfully recognize the multiple hand gestures.