• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.1
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• pp.17-23
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• 2013

In a subway vehicle, a lateral damper is used for compensating the lateral stiffness deterioration due to the air-spring as a secondary suspension. This lateral damper can reduce the lateral vibration of the carbody. When the damping force of the lateral damper is lowered, the running stability and ride quality of the subway vehicles worsens and the lateral motion of the carbody is increased. In this study, the lateral displacement variation of the carbody according to the damping force of the lateral damper was analyzed by multi-body dynamics to solve the abnormal impact problem during vehicle operation. Furthermore, the noise and vibration due to abnormal impact were considered. An adequate damping coefficient of the lateral damper for the subway vehicle treated in this paper was suggested for preventing abnormal impact.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.511-520
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• 2000

Ultrasonic pulse echo method comes to be difficult to apply to the multi-layered structure with very thin layer, because the echoes from the top and the bottom of the layer are superimposed. We can easily meet this problem when the silicon chip layer in the semiconductor is inspected by a SAM equipment using fairly low frequency lower than 20MHz by which severe attenuation in the epoxy mold compound of packaging material can be overcome. Conventionally, deconvolution technique has been used for the decomposition of superimposed UT signals, however it has disabilities when the waveform of the transmitted signal is distorted according to the propagation. In this paper, the wavelet transform based deconvolution(WTBD) technique is proposed as a new signal processing method that can decompose the superimposed echo signals with superior performances compared to the conventional deconvolution technique. WTBD method uses the wavelet transform in the pre-stage of deconvolution to extract out the common waveform from the transmitted and received signal with distortion. Performances of the proposed method we shown by through computer simulations using model signal with noise and we demonstrated by through experiments for the fabricated semiconductor sample with partial delamination at the top of silicon chip layer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2233-2252
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• 2018

For the problem of cross-layer joint resource allocation (JRA) in the Long-Term Evolution (LTE)-Advanced standard using carrier aggregation (CA) technology, it is difficult to obtain the optimal resource allocation scheme. This paper proposes a joint resource allocation algorithm based on the weights of user's average quality of experience (JRA-WQOE). In contrast to prevalent algorithms, the proposed method can satisfy the carrier aggregation abilities of different users and consider user fairness. An optimization model is established by considering the user quality of experience (QoE) with the aim of maximizing the total user rate. In this model, user QoE is quantified by the mean opinion score (MOS) model, where the average MOS value of users is defined as the weight factor of the optimization model. The JRA-WQOE algorithm consists of the iteration of two algorithms, a component carrier (CC) and resource block (RB) allocation algorithm called DABC-CCRBA and a subgradient power allocation algorithm called SPA. The former is used to dynamically allocate CC and RB for users with different carrier aggregation capacities, and the latter, which is based on the Lagrangian dual method, is used to optimize the power allocation process. Simulation results showed that the proposed JRA-WQOE algorithm has low computational complexity and fast convergence. Compared with existing algorithms, it affords obvious advantages such as improving the average throughput and fairness to users. With varying numbers of users and signal-to-noise ratios (SNRs), the proposed algorithm achieved higher average QoE values than prevalent algorithms.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.37-46
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• 2002

Accurate classification of water area is an preliminary step to accurately analyze the flooded area and damages caused by flood. This step is especially useful for monitoring the region where annually repeating flood is a problem. The accurate estimation of flooded area can ultimately be utilized as a primary source of information for the policy decision. Although SAR (Synthetic Aperture Radar) imagery with its own energy source is sensitive to the water area, its shadow effect similar to the reflectance signature of the water area should be carefully checked before accurate classification. Especially when we want to identify small flood area with mountainous environment, the step for removing shadow effect turns out to be essential in order to accurately classify the water area from the SAR imagery. In this paper, the flood area was classified and monitored using multi-temporal RADARSAT SAR images of Ok-Chun and Bo-Eun located in Chung-Book Province taken in 12th (during the flood) and 19th (after the flood) of August, 1998. We applied several steps of geometric and radiometric calculations to the SAR imagery. First we reduced the speckle noise of two SAR images and then calculated the radar backscattering coefficient $(\sigma^0)$. After that we performed the ortho-rectification via satellite orbit modeling developed in this study using the ephemeris information of the satellite images and ground control points. We also corrected radiometric distortion caused by the terrain relief. Finally, the water area was identified from two images and the flood area is calculated accordingly. The identified flood area is analyzed by overlapping with the existing land use map.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.775-784
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• 2019

Image stitching is a technique for solving the problem of narrow field of view of a camera by composing multiple images. Recently, as the use of content such as Panorama, Super Resolution, and 360 VR increases, the need for faster and more accurate image stitching technology is increasing. So far, many algorithms have been proposed to satisfy the required performance, but the objective evaluation method for measuring the accuracy has not been standardized. In this paper, we present the problems of PSNR and SSIM(Structural similarity index method) measurement methods and propose a Local Differential Pixel Mean method. The LDPM evaluation method that includes geometric similarity and brightness measurement information is proved through a test, and the advantages of the evaluation method are revealed through comparison with SSIM.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.87-87
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• 2019

The consumption of herbal medicine and related products (herbal products) have increased in South Korea. At the same time the quality, safety, and efficacy of herbal products is being raised. Currently, the herbal products are standardized and controlled according to the requirements of the Korean Pharmacopoeia, the National Institute of Health and the Ministry of Public Health and Social Affairs. The validation of herbal products and their medicinal component is important, since many of these herbal products are composed of two or more medicinal plants. However, there are no tools to support the validation process. Interest in deep learning has exploded over the past decade, for herbal medicine using algorithms to achieve herb recognition, symptom related target prediction, and drug repositioning have been reported. In this study, individual images of four herbs (Panax ginseng C.A. Meyer, Atractylodes macrocephala Koidz, Poria cocos Wolf, Glycyrrhiza uralensis Fischer), actually sold in the market, were achieved. Certain image preprocessing steps such as noise reduction and resize were formatted. After the features are optimized, we applied GoogLeNet_Inception v4 model for herb image recognition. Experimental results show that our method achieved test accuracy of 95%. However, there are two limitations in the current study. Firstly, due to the relatively small data collection (100 images), the training loss is much lower than validation loss which possess overfitting problem. Secondly, herbal products are mostly in a mixture, the applied method cannot be reliable to detect a single herb from a mixture. Thus, further large data collection and improved object detection is needed for better classification.

• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.33-38
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• 2018

This paper introduces the simulation concepts and technical approach of wire-guided torpedo performance analysis simulator, as a consequence, provide a framework for understanding overall attack procedures and effectiveness of tactics to torpedo operator. It described the mathematical models of simulation components and weapon engagement principle, especially it derived the closed-form solution of time consumption and leading angle problem of torpedo attack situation based on geographical assumption. In addition, it adopted the proportional navigation guidance at final stage of torpedo attack and also consider the tradeoff relation between target ship speed(propeller noise level) and detection probability, so that it improves the fidelity of physical realism. Simulator is developed with high degree of freedom in the perspective of tactical situation, and it helps user to understand the overall situation and tactical effectiveness.

• Health Policy and Management
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• v.31 no.3
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• pp.255-260
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• 2021

Background: Korea National Health Checkup Programs are aimed at the prevention and early detection of cardiovascular disease in adults. To establish a countermeasure for this tendency, The current Korea National Health Checkup Programs have been providing Health Risk Appraisal (HRA) since 2009, thereby focusing on individual lifestyle correction. However, from 2018, the dyslipidemia screening exam cycle has been changed from 2 to 4 years. Methods: In this study, we try to investigate whether policy decisions are valid based on domestic reports that have influenced policy decisions. First, considering the epidemiology of the domestic cardiovascular disease, dyslipidemia, and metabolic syndrome, the change of the 4-year cycle is appropriate or not. Second, whether the research method that applies came to make policy decisions appropriate or not. Third, our study also investigates whether the direction of policy decision was suitable for the second comprehensive national examination plan. Results: The data that are used in the previous study were that of 10 years ago and there also was a problem in selecting the data, especially the use of one of the research methods to calculate the signal to noise ratio that was aimed at improving health had some problems. This is a research method that does not match with the aim itself. Conclusion: Changing the screening cycle for dyslipidemia does not match the recent trend of general screening to effectively prevent cardiovascular disease in improving individual lifestyles in the national health checkup plan. Studying the relationship with metabolic syndrome, which can be an intermediate stage of cardiovascular disease, could be a policy direction that is more suitable for the national health examination comprehensive plan.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1353-1364
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• 2018

This study proposed a method to detect Cochlodinium polykrikoides red tide pixels in satellite images using a logistic regression model of machine learning technique under Imbalanced data. The spectral profiles extracted from red tide, clear water, and turbid water were used as training dataset. 70% of the entire data set was extracted and used for as model training, and the classification accuracy of the model was evaluated using the remaining 30%. At this time, the white noise was added to the spectral profile of the red tide, which has a relatively small number of data compared to the clear water and the turbid water, and over-sampling was performed to solve the unbalanced data problem. As a result of the accuracy evaluation, the proposed algorithm showed about 94% classification accuracy.

• Journal of the Korea Society for Simulation
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• v.28 no.2
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• pp.81-88
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• 2019

Since the AESA radar scans and tracks a distant targets or ground, it requires a test field which meets far-field condition before flight test. In order to test beam foaming, targeting, and availability from cluttering and jamming, it is general to build a outdoor roof-lab test site at tens of meters high. However, the site is affected by surrounding terrain, weather, and noise wave and is also requires time, space, and a lot of costs. In order to solve this problem, theoretical near-field beam foaming method has proposed. However, it requires modification of associated hardware in order to construct near-field test configuration. In this paper, we propose near-field beam foaming method which use single LUT in order to calibrate the variation of TRM(transmit-receive module) which consists AESA radar without modification of associated hardware and software. It requires less costs than far-field test and multiple LUT based near-field test, nevertheless it can derives similar experimental results.