• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.587-592
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• 2019

The importance of software technologies is becoming more prominent because of the competition to secure a competitive edge in software, which has been intensified since the emergence of smartphones and IoT. Thus, to assure the initiative in the global software industry and to foster superior human resources, there is a growing need for outstanding software development professionals. This paper analyzes the factors that affect the basic perception of software, the need for software development, and the enhancement of software coding ability based on a compulsory software class, which aims to increase the workforce of the converged software industry. The analysis shows that among other technical practices to enhance coding ability, learner-centered technical contents showed the most positive effect regarding the recognition and motive of development and are an essential factor in improving coding skills. The findings indicate that the need for program development and active involvement in the development of the program are the most important factors in improving the practical ability. The analysis presents meaningful results by suggesting a methodology for improving software development capabilities.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.147-155
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• 2019

In the glocal era, the competition becomes more intense in regional development centered around cities rather than countries. This suggests that increasing the city's unique charms through a positive city image can allow the city to gain a competitive edge in the competition for regional development. In this background, this study would contribute to improving the positive image of Pyeongtaek City, presenting the value and development direction of the image it would pursue, aiming to develop a promotional design for the improvement of the city image. As the details of the research, this study recognized the city image as an efficient means of public relations of the city from its concept and necessity. Thus, this study conducted a survey on the analysis of status and image of Pyeongtaek City. This study would contribute to improving the positive image of Pyeongtaek City, presenting the results of the development of a promotional design of its administration and a plan for utilization in the manual, proceeding by stages.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.87-96
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• 2019

Low power issue is one of the most critical problems in the Internet of Things (IoT), which are powered by battery. To solve this problem, various approaches have been presented so far. In this paper, we propose a method to reduce the power consumption by reducing the numbers of accesses into the flash memory consuming a large amount of power for on-chip software execution. Our approach is based on using cooperative logging structure to distribute the sampling overhead in single sensor node to adjacent nodes in case of rare-event applications. The proposed algorithm to identify event occurrence is newly introduced with negative feedback method by observing difference between past data and recent data coming from the sensor. When an event with need of flash access is determined, the proposed approach only allows access to write the sampled data in flash memory. The proposed event detection algorithm (EDA) result in 30% reduction of power consumption compared to the conventional flash write scheme for all cases of event. The sampled data from the sensor is first traced into the random access memory (RAM), and write access to the flash memory is delayed until the page buffer of the on-chip flash memory controller in the micro controller unit (MCU) is full of the numbers of the traced data, thereby reducing the frequency of accessing flash memory. This technique additionally reduces power consumption by 40% compared to flash-write all data. By sharing the sampling information via LoRa channel, the overhead in sampling data is distributed, to reduce the sampling load on each node, so that the 66% reduction of total power consumption is achieved in several IoT edge nodes by removing the sampling operation of duplicated data.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.125-131
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• 2019

A vanishing point is a point on an image to which parallel lines projected from a real space gather. A vanishing point in a road space provides important spatial information. It is possible to improve the position of an extracted lane or generate a depth map image using a vanishing point in the road space. In this paper, we propose a method of detecting vanishing points on images taken from a vehicle's point of view using Deep Neural Network (DNN) and Histogram of Oriented Gradient (HoG). The proposed algorithm is divided into a HoG feature extraction step, in which the edge direction is extracted by dividing an image into blocks, a DNN learning step, and a test step. In the learning stage, learning is performed using 2,300 road images taken from a vehicle's point of views. In the test phase, the efficiency of the proposed algorithm using the Normalized Euclidean Distance (NormDist) method is measured.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.31-37
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• 2018

This paper proposes an effective single-image haze-removal algorithm with low complexity by using a dual dark channel prior (DCP) and an adaptive brightness correction technique. The dark channel of a small patch preserves the edge information of the image, but is sensitive to noise and local brightness variations. On the other hand, the dark channel of a large patch is advantageous in estimation of the exact haze value, but halo effects from block effects deteriorate haze-removal performance. In order to solve this problem, the proposed algorithm builds a dual DCP as a combination of dark channels from patches with different sizes, and this meets low-memory and low-complexity requirements, while the conventional method uses a matting technique, which requires a large amount of memory and heavy computations. Moreover, an adaptive brightness correction technique that is applied to the recovered image preserves the objects in the image more clearly. Experimental results for various hazy images demonstrate that the proposed algorithm removes haze effectively, while requiring much fewer computations and less memory than conventional methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.525-534
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• 2018

Camera calibration is the process of determining the parameters such as the focal length of a camera, the position of a principal point, and lens distortions. For this purpose, images of checkerboard have been mainly used. When targets were automatically recognized in checkerboard image, the existing studies had limitations in that the user should have a good understanding of the input parameters for recognizing the target or that all checkerboard should appear in the image. In this study, a methodology for automatic target recognition was proposed. In this method, even if only a part of the checkerboard image was captured using rectangles including eight blobs, four each at the central portion and the outer portion of the checkerboard, the index of the target can be automatically assigned. In addition, there is no need for input parameters. In this study, three conditions were used to automatically extract the center point of the checkerboard target: the distortion of black and white pattern, the frequency of edge change, and the ratio of black and white pixels. Also, the direction and numbering of the checkerboard targets were made with blobs. Through experiments on two types of checkerboards, it was possible to automatically recognize checkerboard targets within a minute for 36 images.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.95-108
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• 2019

Quality management has become an pervasive philosophy in most sectors of business. Specific movements such as statistical quality control, quality circle, total quality management, and quality management system have become embedded in business organizations. Only the companies with competitive edge can survive in the competition in global market. KSA(Korean Standards Association) established in 1962 has launched all kinds of quality education, quality standard certification service for business, and KNQA(Korean National Quality Award) system. This article considers quality competitiveness excellent company award among KNQA. We performed a statistical analysis of audit data for quality competitiveness excellent company for three years, from 2015 to 2017. By using ANOVA and two sample t-tests, the average scores of 13 evaluation fields were significantly different depending on company size and type. We proposed ways to improve the current hall of fame system. We discovered that the average scores of 13 evaluation fields in the audit data according to years and hall of fame status were not significantly different. We also showed linear relationships among 13 evaluation fields by correlation analysis and obtained an estimated linear regression equation : Business Performance, which is a comprehensive index, as a dependent variable was significantly related to Customer Focus and Product Liability as regressor variables among 13 evaluation fields by regression analysis.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.729-738
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• 2021

Feedback flow control using an artificial neural network was numerically investigated for NACA0015 Airfoil to suppress flow separation on an airfoil. In order to achieve goal of flow control which is aimed to reduce the size of separation on the airfoil, Blowing&Suction actuator was implemented near the separation point. In the system modeling step, the proper orthogonal decomposition was applied to the pressure field. Then, some POD modes that are necessary for flow control are extracted to analyze the unsteady characteristics. NARX neural network based on decomposed modes are trained to represent the flow dynamics and finally operated in the feedback control loop. Predicted control signal was numerically applied on CFD simulation so that control effect was analyzed through comparing the characteristic of aerodynamic force and spatial modes depending on the presence of the control. The feedback control showed effectiveness in pressure drag reduction up to 29%. Numerical results confirm that the effect is due to dramatic pressure recovery around the trailing edge of the airfoil.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.415-423
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• 2019

In this paper, a design method for a high-sensitivity microstrip patch sensor antenna (MPSA) loaded with a bent-slot was studied for the permittivity measurement. The bent-slot similar to a single-ring complementary split ring resonator was added along a radiating edge of the patch in order to enhance the sensitivity to the permittivity. The sensitivity of the proposed MPSA was compared with that of a conventional rectangular MPSA and a thin rectangular-slotted MPSA. Three MPSAs were designed and fabricated on a 0.76-mm-thick RF-35 substrate so that the input reflection coefficient would resonate at 2.5 GHz in the absence of the superstrate under test. When five different Taconic substrates with a relative permittivity ranging from 2.17 to 10.2 were used as the superstrate under test, experiment results show that the sensitivity of the proposed MPSA, which is measured by the shift in the resonant frequency of the input reflection coefficient, is 4.1 to 6.1 times higher than that of the conventional MPSA.

• Journal of Ginseng Research
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• v.45 no.1
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• pp.58-65
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• 2021

Background: Panax ginseng, as one of the most widely used herbal medicines worldwide, has been studied comprehensively in terms of the chemical components and pharmacology. The proteins from ginseng are also of great importance for both nutrition value and the mechanism of secondary metabolites. However, the proteomic studies are less reported in the absence of the genome information. With the completion of ginseng genome sequencing, the proteome profiling has become available for the functional study of ginseng protein components. Methods: We optimized the protein extraction process systematically by using SDS-PAGE and one-dimensional liquid chromatography mass spectrometry. The extracted proteins were then analyzed by two-dimensional chromatography separation and cutting-edge mass spectrometry technique. Results: A total of 2,732 and 3,608 proteins were identified from ginseng root and cauline leaf, respectively, which was the largest data set reported so far. Only around 50% protein overlapped between the cauline leaf and root tissue parts because of the function assignment for plant growing. Further gene ontology and KEGG pathway revealed the distinguish difference between ginseng root and leaf, which accounts for the photosynthesis and metabolic process. With in-deep analysis of functional proteins related to ginsenoside synthesis, we interestingly found the cytochrome P450 and UDP-glycosyltransferase expression extensively in cauline leaf but not in the root, indicating that the post glucoside synthesis of ginsenosides might be carried out when growing and then transported to the root at withering. Conclusion: The systematically proteome analysis of Panax ginseng will provide us comprehensive understanding of ginsenoside synthesis and guidance for artificial cultivation.