• Journal of IKEEE
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• v.22 no.3
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• pp.747-753
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• 2018

Currently, many companies have succeeded in logistics delivery experiments utilizing drone and report it. When a drone is used commercially, long-term flight is an important performance that a drone should have. However, unlike vehicles operated on the ground, drone is a vehicle that continues to consume energy when maintaining the current altitude or moving to the destination. Therefore, the drones can fly for a long time as the capacity of the battery is large, but the batteries with large capacity are restricted by heavy weight and it acts as a limiting factor in a commercial use. To address this issue, we attempt to compare how far we can fly than forward flight based on the flight pattern with the same energy consumption condition. In this paper, the comparison of energy consumption was performed in three flight pattern, forward flight without altitude change and forward flight with altitude change, by computer simulation and it shows the increasing of flight distances when the quadrotor fly with altitude change from high altitude to low altitude.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.307-313
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• 2008

In this paper, we propose a novel defects inspection algorithm for TFT-LCD panels. We first compensate the distorted image caused by the camera distortion and the uneven illumination environment using the least squares method and the bezier surface. We find a starting point of each pattern for restricting each pattern. A clean image is compared to each pattern to find defects using modified PCSR-G algorithm. The simulation example shows that our algorithm not only inspects the defects well, but also is robust to the 1-pixel error.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.832-837
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• 2015

The group method of data handling (GMDH) algorithm has proven to be a powerful and effective way to extract rules or polynomials from an electric load pattern. However, because it is nonstationary, the load pattern needs to be decomposed using a discrete wavelet transform. In addition, if a load pattern has a complicated curve pattern, GMDH should use a higher polynomial, which requires complex computing and consumes a lot of time. This paper suggests a method for short-term electric load forecasting that uses a wavelet transform and a GMDH algorithm. Case studies with the proposed algorithm were carried out for one-day-ahead forecasting of hourly electric loads using data during the years 2008-2011. To prove the effectiveness of our proposed approach, the results were evaluated and compared with those obtained by Holt-Winters method and artificial neural network. Our suggested method resulted in better performance than either comparison group.

• Journal of the Korean Home Economics Association
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• v.37 no.9
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• pp.57-71
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• 1999

This study was intended to find the body pattern of the middle-aged women and to make new experimental basic pattern for upper-half of the body for them. To analyze the body pattern of middle-aged women, the methodologies of measurement of the individual part of the body, group aged-analysis, Rohrer Index, Vervaeck Index, factor analysis, discriminant analysis, cluster analysis and girth index were used. The comparison of the twentieth to the thirtieth, the fortieth and the fiftieth showed bigger change in the thirtieth and the biggest change in the fortieth in girth. The fiftieth showed thick body pattern by increasing the depth but decreasing the girth. Body types were divided into three groups, thin, standard and fatty troupes by Rohrer index. With Rohrer Index, there was no difference for back length in three groups, but girth showed shorter in thin and standard groups but longer in fatty group.

• Journal of the korean academy of Pediatric Dentistry
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• v.23 no.4
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• pp.946-953
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• 1996

The occlusal patterns and profiles of the primary dentition were studied by oral examination from 3 to 6 year-old children (200 boys, 200 girls) in Kwangju city. The results were as follows; 1. In sagittal primary canine relationship, Class 1 pattern (74.75 %) was prevalent. 2. In sagittal primary molar relationship, Class 1 pattern (56 %) was prevalent. 3. In profile view, straight profile (77%) was prevalent. 4. In comparison of relationship between primary canine relationship, primary molar relationship and profile, Class 1 pattern-Class 1 pattern-Straight profile (43.14 %) was prevalent.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.383-386
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• 2002

In this paper, we investigated the pattern recognition performance of the numeric patterns (from 0 to 9) using DNA coding method. The pattern recognition performance of the DNA coding method is compared to the that of the GA(Genetic Algorithm). GA searches effectively an optimal solution via the artificial evolution of individual group of binary string using binary coding, while DNA coding method uses four-type bases denoted by A(Adenine), C(Cytosine), G(Guanine) and T(Thymine), The pattern recognition performance of GA and DNA coding method is evaluated by using the same genetic operators(crossover and mutation) and the crossover probability and mutation probability are set the same value to the both methods. The DNA coding method has better characteristics over genetic algorithms (GA). The reasons for this outstanding performance is multiple possible solution presentation in one string and variable solution string length.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1422-1423
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• 2007

This study deals with various neural network algorithms for the on-site partial discharge pattern recognition. For the purpose, the pattern recognition has been carried out on partial discharge data for the typical artificial defect using 9 different neural network models. In order to enhance on-site applicability, artificial defects were installed in the insulation joint box of extra-high voltage xLPE cables and partial discharges were measured by use of the metal foil sensor and a HFCT as a sensor. As the result, it is found out that the accuracy of pattern recognition could be enhanced through the application of the Sigmoid function, the Momentum algorithm and the Genetic algorism on the artificial neural networks. Although Multilayer Perceptron (MLP) algorism showed the best result among 9 neural network algorisms, it is thought that more researches on others would be needed in consideration of on-site application.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.3
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• pp.139-146
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• 2004

In this study, to achieve the optimal conditions for mechanical hyper-fine pattern fabrication process, deformation behavior of the materials during indentation scratch test was studied with numerical method by ABAQUS S/W. Brittle materials (Si, Pyrex glass 7740) were used as specimens, and forming conditions to reduce the elastic recovery and pile-up were proposed. The indenter was modeled as a rigid surface. Minimum mesh sizes of specimens are 1-l0nm. Variables of the nanoindentation scratch test analysis are scratching speed, scratching load, tip radius and tip geometry. The nano-indentation scratch tests were performed by using the Berkovich pyramidal diamond indenter. Comparison between the experimental data and numerical result demonstrated that the FEM approach can be a good model of the nanoindentation scratch test. The result of the investigation will be applied to the fabrication of the hyper-fine pattern.

• Journal of Biomedical Engineering Research
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• v.14 no.2
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• pp.185-193
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• 1993

In this paper, the peak detection algorithm was developed for the purpose of screening of the target compounds. Algorithm is divided into searching the characteristic ion and peak detection. The heuristic knowledge about analytical chemistry was applied for the searching the characteristic ion. Peak detection was accomplished in comparison with the peak identification strings and pattern strings around the retention time. Pattern strings are composed with the number which generated by pattern identification function. The variables of pattern identification function are the codes which represent the difference of two adjacent abundances Some of the free steroids were selected to demonstrate the proposed algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.3
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• pp.4-19
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• 1991

In this paper, we propose a fuzzy neural network pattern classifier utilizing fuzzy information. This system works without any a priori information about the number of clusters or cluster centers. It classifies each input according to the distance between the weights and the normalized input using Bezdek's [1] fuzzy membership value equation. This model returns the correct membership value for each input vector and find several cluster centers. Some experimental studies of comparison with other algorithms will be presented for sample data sets.