• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1250-1252
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• 2009

Cellular 망에서의 무선통신은 일반적으로 하나의 송수신안테나를 사용하거나 둘 이상의 송수신 안테나를 사용한다. MRRC(Maximum Ratio Receiver Combining)기법의 경우 여러 안테나를 사용하여 신호룰 수신하는 시스템이며, 이 경우 각 안테나의 채널에 따른 이득과 손실을 고려한 수신기가 제안되었다. Cellular model에서의 SINR 값에 따른 추정을 통해 최적 결합 기법을 적용한 MRRC 수신기를 사용하는 경우, 이에 따른 Cellular modeling을 이용하여 시스템 레벨에서의 MRRC 기법과 Optimum-MRRC 기법을 도입으로 인한 성능의 개선을 알 수 있다.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4620-4624
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• 2022

Several cadmium zinc telluride (CZT) crystals were fabricated into radiation detectors using methods that included slicing, dicing, lapping, polishing, and chemical etching. A wet passivation with sodium hypochlorite (NaOCl) was then carried out on the Br-etched detectors. The Te-rich layer on the CZT surface was successfully compensated to the Te oxide layer, which was analyzed with X-ray photoelectron spectroscopy data of both a Br-etched crystal and a passivated CZT crystals. We confirmed that passivation with NaOCl improved the transport property by analyzing the mobility-lifetime product and surface recombination velocity. The electrical and spectroscopic properties of large volume detectors were compared before and after passivation, and then the detectors were observed for a month. Both bar and quasi-hemispherical detectors show an enhancement in performance after passivation. Thus, we could identify the effect of NaOCl passivation on large volume CZT detectors.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.407-414
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• 2014

The aim of the present study was to carry out quantitative analysis of spatial resolution for the influence of the focus size and digital image post-processing on the Computed Radiography (CR). The modulation transfer functions of an edge measuring method (MTF) was used for the evaluation of the spatial resolution. The focus size of X-ray tube was used the small focus (0.6 mm) and the large focus (1.2 mm). We evaluated the 50% and 10% of MTF for the enhancement of edge and contrast by using multi-scale image contrast amplification (MUSICA) in digital image post-processing. As a results, the edge enhancement than the contrast enhancement were significantly higher the spatial resolution of MTF 50% in all focus. Also the spatial resolution of the obtained images in a large focus were improved by digital image processing. In conclusion, the results of this study should serve as a basic data for obtain the high resolution clinical images, such as skeletal and chest images on the CR.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.347-356
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• 2016

The purpose of this study was to develop and examine the effectiveness (knowledge, attitude, skills of Evidence-Based Practice, and problem solving skills) of nursing information literacy competency enhancement program for nursing students. It is a pre-post design study carried out with a single group of 72 sophomores in a nursing college. Nursing information literacy competency enhancement program of 6 times (8 hours) was provided to nursing students. Our results have demonstrated that knowledge, attitude, skills of evidence-based practice, and problem solving skills were significantly higher in nursing students. In conclusion, the nursing information literacy competency enhancement program was effective in promoting knowledge, attitude, skills of evidence-based practice and problem solving skills. Based on our results, the nursing information literacy competency enhancement program can provide a basis for enhancing evidence-based nursing practice competencies and problem solving skills of nursing students.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.385-390
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• 2019

This study aimed to identify the model fit of various versions of Performance Enhancement Attitude Scale (PEAS) developed for measuring quantitatively the attitude toward doping and to provide the information on Korean version of PEAS. One hundred and eighty elite athletic players participated in this study and they filled out 17 items PEAS under the supervision. And 17 items, 11 items, 9 items, 8 items and 6 items PEAS were analyzed by using confirmatory factor analysis. The result of this study showed that an 8 items PEAS was fit for Korean elite athletic players, and a 6 items PEAS was for adolescents, but insignificant. Therefore, further studies of the relationship between psychosocial factors and attitudes toward doping by using 8-items PEAS would provide precise and useful information for developing anti-doping strategy.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.32-40
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• 2022

Underwater optical images face various limitations that degrade the image quality compared with optical images taken in our atmosphere. Attenuation according to the wavelength of light and reflection by very small floating objects cause low contrast, blurry clarity, and color degradation in underwater images. We constructed an image data of the Korean sea and enhanced it by learning the characteristics of underwater images using the deep learning techniques of CycleGAN (cycle-consistent adversarial network), UGAN (underwater GAN), FUnIE-GAN (fast underwater image enhancement GAN). In addition, the underwater optical image was enhanced using the image processing technique of Image Fusion. For a quantitative performance comparison, UIQM (underwater image quality measure), which evaluates the performance of the enhancement in terms of colorfulness, sharpness, and contrast, and UCIQE (underwater color image quality evaluation), which evaluates the performance in terms of chroma, luminance, and saturation were calculated. For 100 underwater images taken in Korean seas, the average UIQMs of CycleGAN, UGAN, and FUnIE-GAN were 3.91, 3.42, and 2.66, respectively, and the average UCIQEs were measured to be 29.9, 26.77, and 22.88, respectively. The average UIQM and UCIQE of Image Fusion were 3.63 and 23.59, respectively. CycleGAN and UGAN qualitatively and quantitatively improved the image quality in various underwater environments, and FUnIE-GAN had performance differences depending on the underwater environment. Image Fusion showed good performance in terms of color correction and sharpness enhancement. It is expected that this method can be used for monitoring underwater works and the autonomous operation of unmanned vehicles by improving the visibility of underwater situations more accurately.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.70-75
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• 2022

With the spread of various digital devices, devices have become commonplace in modern society. Moreover, due to the increase in device usage and online learning while staying indoors during the COVID-19 pandemic, symptoms such as an increase in myopia in children due to eye fatigue, an increase in young presbyopia, and dry eye syndrome are increasing, and now people are paying attention to eye health. This is different from before. There are various prescriptions for eye health, but in this paper, we would like to propose a training method for enhancing visual function using VR contents. The analog methods of the existing teaching aids for visual function reinforcement training were planned and produced as digital contents, and VR-based training contents were selected from among the various methods carried out with teaching aids at the visual function training center, which can be made into contents. was developed with In the training process for each content, it was proposed to apply eye tracking to the VR device in order to give the user feedback on their participation in the training so that the management and concentration of the training process could be analyzed.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.446-450
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• 2020

딥러닝 기반의 영상 분석 방법들은 많은 양의 학습 데이터가 필요하며, 학습 데이터 구축에는 많은 시간과 노력이 소요된다. 특히 객체 검출 분야의 경우 영상 내 객체의 위치, 크기, 범주 등의 정보가 모두 필요하여 학습 데이터 구축에 더 많은 어려움이 있으며, 이를 해결하기 위해 최근 이미지 합성기반 데이터 증강에 관한 연구가 활발히 진행되고 있다. 이미지 합성기반 데이터 증강 방법은 배경 영상에 객체를 합성할 때 객체와 배경 영상이 접한 영역에서 아티팩트(Artifact)가 발생하며, 이는 객체 검출 모델이 아티팩트를 객체의 특징으로 모델링하여 검출 성능이 저하되는 원인이 된다. 이러한 문제를 해결하기 위하여 본 논문에서는 양방향 필터 기반의 이미지 합성 방법을 제안하고, 단일 단계 검출의 대표적인 방법인 RetinaNet을 이용하여 이미지 합성기반 데이터 증강 방법의 성능을 분석하였다. 공개 데이터셋에 대한 실험 결과 본 논문에서 사용한 단일 검출 방법 및 데이터 증강 기법을 사용하면 더 적은 양의 증강 데이터로 기존 방법과 동일한 성능을 보여주는 것을 확인하였다.

• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.1-8
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• 2017

In industry AGV's(automated guided vehicles) that can detect and follow guidelines drawn on the factory floor using magnetic or optical sensors are widely used. However, such AGV's without preview capability cannot effectively avoid collision with obstacles that may occasionally pass through the guideline. Furthermore, without preview information, they consume much energy at the right angle corners as they have to make sudden directional change. Also, the risk of dropping payloads increases in such situations. In this study, infrared preview sensors were adopted to a mobile robot for detecting not only the current position but also the forward position of the guideline and the preview control technique was applied to optimally control the mobile robot's motion using the information from the infrared preview sensors. Then the effectiveness of this approach was investigated through a series of experiments. The experimental result shows that the proposed approach is effective for safety enhancement as well as for better efficiency.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.60-65
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• 2014

This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.