• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4684-4705
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• 2019

Collaborative filtering recommender systems are vulnerable to shilling attacks in which malicious users may inject biased profiles to promote or demote a particular item being recommended. To tackle this problem, many robust collaborative recommendation methods have been presented. Unfortunately, the robustness of most methods is improved at the expense of prediction accuracy. In this paper, we construct a robust Bayesian probabilistic matrix factorization model for collaborative filtering recommender systems by incorporating the detection of user anomaly rating behaviors. We first detect the anomaly rating behaviors of users by the modified K-means algorithm and target item identification method to generate an indicator matrix of attack users. Then we incorporate the indicator matrix of attack users to construct a robust Bayesian probabilistic matrix factorization model and based on which a robust collaborative recommendation algorithm is devised. The experimental results on the MovieLens and Netflix datasets show that our model can significantly improve the robustness and recommendation accuracy compared with three baseline methods.

• Journal of the Korean Society of Safety
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• v.35 no.3
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• pp.105-115
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• 2020

This study compares the difference of fit factors (FF) and visual acuity according to masks and eyeglasses preferences for 54 participants. We the precautions and behaviors of discomfort when wearing masks of eyewear wearers. Contact lens discomfort and priority action of complaints was investigated Glasses fitting factors is Optical Center Height(OH), Vertex Distance(VD) and Pantoscopic Angle(PA). We measured those factors and expressed by the ratio of standard point and change point. Quantitative fit factor was measured by Portacount Pro+ 8038. Also, we selected to 6 exercises among 8 exercises OSHA QNFT (Quantitative Fit testing) protocol to measure the fit factors. The pass/ fail criterion of FF was set at 100. Visual acuity(VA) test chart is developed by Chunsuk Han was used, Descriptive statistics was performed. Descriptive statistics(SAS ver 9.2), it is used geometric means, Wilcoxon analysis(P=0.05) When wearing the mask preferentially, fit factor(FF) was high according to the step of glasses fitting parameter. on the other hand, when the glasses first choice, the visual acuity(VA) was high. there was no significant difference. In the case of fit factor (FF), mask first choice/ glasses first choice is OH (p=0.671/ p=0.332), VD (p=0.602/ p=0.571) and PA (p=0.549/ p=0.607). Visual acuity (VA), mask first choice/ glasses first choice is OH (p=0.753/ p=0.386), VD (p=0.815/ p=0.557) and PA (p=0.856/ p=0.562). The workers of workplace and office chose glasses but occupational health workers and students chose mask. In case of discomforts, it was suggested to remove the mask and tolerate discomforts. The main discomforts and usual action of lens were dryness, hyperemia, foreign body sensation, ophthalmodynia, decreased vision and glasses wearing. Therefore, it is necessary to develop a mask wearing method education program considering glasses fitting and develop a hybrid model that minimizes inconvenience when wearing glasses and a mask at the same time.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.04a
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• pp.7-13
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• 2003

Microlens arrays were fabricated using a novel fabrication technology based on the exposure of a PMMA (Polymethylmethacrylate) sheet to deep X-rays and subsequent thermal treatment. X-ray irradiation causes the decrease of molecular weight of PMMA, which in turn decreases the glass transition temperature and consequently causes a net volume increase during the thermal cycle resulting in a swollen microlens. A new physical modeling and analyses for micro lens formation were presented according to experimental procedure. A simple analysis based on the new model is found to be capable of predicting the shapes of micro lens which depend on the thermal treatment. For the replication of micro lens arrays having various diameters with different foci on the same surface, the hot embossing and the microinjection molding processes has been successfully utilized with a mold insert that is fabricated by Ni-electroplating based on a PMMA microstructure of micro lenses. Fabricated microlenses showed good surface roughness with the order of 1nm.

• Radiation Oncology Journal
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• v.35 no.3
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• pp.249-256
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• 2017

Purpose: We retrospectively reviewed the results of radiotherapy for localized ocular adnexal MALT lymphoma (OAML) to investigate the risk factors of cataract. Methods: Sixty-seven patients with stage IE OAML treated with radiotherapy at Seoul St. Mary's Hospital from 2001 to 2016 were included. Median treatment dose was 30 Gy. Lens protection was done in 52 (76%) patients. Radiation therapy (RT) extent was as follows: superficial (82.1%), tumor mass (4.5%), and entire orbital socket (13.4%). The risk factors for symptomatic cataract were analyzed using the Cox proportional hazard model. Results: Median follow-up time was 50.9 months (range, 1.9 to 149.4 months). All patients were alive at the time of analysis. There were 7 recurrences and there was no local recurrence. Median time to recurrence was 40.4 months. There were 14 cases of symptomatic cataract. Dose >30 Gy had hazard ratio of 3.47 for cataract (p = 0.026). Omitting lens protection showed hazard ratio of 4.10 (p = 0.008). Conclusions: RT achieves excellent local control of ocular MALT lymphoma. Consideration of RT-related factors such as lens protection and radiation dose at the stage of RT planning may reduce the risk of RT-induced cataract after radiotherapy.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.1
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• pp.23-29
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• 2016

In this paper, a real-time condition diagnosis system for the lens injection molding process is developed through the use of LabVIEW. The built-in-sensor (BIS) mold, which has pressure and temperature sensors in their cavities, is used to capture real-time signals. The measured pressure and temperature signals are processed to obtain features such as maximum cavity pressure, holding pressure and maximum temperature by the feature extraction algorithm. Using those features, an injection molding condition diagnosis model is established based on a response surface methodology (RSM). In the real-time system using LabVIEW, the front panels of the data loading and setting, feature extraction and condition diagnosis are realized. The developed system is applied in a real industrial site, and a series of injection molding experiments are conducted. Experimental results show that the average real-time condition diagnosis rate is 96%, and applicability and validity of the developed real-time system are verified.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.3
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• pp.1-8
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• 2017

Recently, the development of the head mounted display (HMD) device has attracted a great deal of attention to the actual contents. Especially, Augmented Reality (AR), which is a mixture of actual information and virtual world information, is focused on. AR HMD is able to interact by arranging virtual objects in real space through spatial recognition using depth camera. In order to naturally mix virtual space with real space, it is necessary to develop a technology for realizing spatial mapping information with high accuracy. The purpose of this paper is to evaluate the optimal configuration of augmented reality application program by realizing accurate spatial mapping information when mapping a real space and an object placement environment using HoloLens. To do this, we changed the spatial mapping information in real space to three levels, which are the number of meshes used in cubic meters to scan step by step. After that, it was compared with the 3D model obtained by changing the actual space and mesh number. Experimental result shows that the higher the number of meshes used in cubic meters, the higher the accuracy between real space and spatial mapping. This paper is expected to be applied to augmented reality application programs that require scanning of highly mapped spatial mapping information.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.389-392
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• 2015

We identify a strong lensing galaxy in the cluster IRC 0218 that is spectroscopically confirmed to be at z = 1.62, making it the highest-redshift strong lens galaxy known. The lens is one of the two brightest cluster galaxies and lenses a background source galaxy into an arc and a counterimage. With Hubble Space Telescope (HST) grism and Keck/LRIS spectroscopy, we measure the source redshift to be $z_S=2.26$. Using HST imaging, we model the lens mass distribution with an elliptical power-law profile and account for the effects of the cluster halo and nearby galaxies. The Einstein radius is $^{\theta}E=0.38^{+0.02{\prime}{\prime}}_{-0.01}$ ($3.2^{+0.2}_{-0.1}kpc$) and the total enclosed mass is $M_{tot}(<^{\theta}_E)=1.8^{+0.2}_{-0.1}{\times}10^{11}M_{\odot}$. We estimate that the cluster environment contributes ~ 10% of this total mass. Assuming a Chabrier IMF, the dark matter fraction within $^{\theta}E$ is $f^{Chab}_{DM}=0.3^{+0.1}_{-0.3}$, while a Salpeter IMF is marginally inconsistent with the enclosed mass ($f^{Salp}_{DM}=-0.3^{+0.2}_{-0.5}$).

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.119-119
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• 2019

최근 기후변화와 이상기후의 영향으로 국지성 호우 및 가뭄, 홍수, 태풍 등 재해 발생 규모가 커지고 그 빈도 또한 많아지고 있다. 이러한 자연재해 및 이상현상에 대한 피해를 예방하고 빠르게 대처하기 위해서는 정확한 강우량 추정 및 강우의 시간적 예측이 필요하다. 이러한 강우의 불확실성을 해결하기 위해서 기상청 등에서는 단일 수치예보가 가지는 결정론적인 예측의 한계를 보완한 초기조건, 물리과정, 경계조건 등이 다른 여러 개의 모델을 수행하여, 확률적으로 미래를 예측하는 앙상블 예측 시스템을 예보기술에 응용하고 있으며 기존 수치모델의 정보와 예보 불확실성에 대한 정보를 동시에 제공하고 있다. 그러나 다양한 자연조건에 대한 불완전한 물리적 이해와 연산 능력 등의 한계로 높은 불확실성이 내포되어 있으므로 불확실성을 최소화하기 위한 편의보정이 수행될 필요가 있다. 강우분석의 적용 이전에 해당 자료의 타당성과 신뢰도의 분석이 필요하다. 본 연구에서는 LENS(Local ENsemble prediction System) 예측값과 시강우 관측값을 단기예측모델에 맞추어 3시간 누적하여 비교하였다. 비교 기간은 호우가 집중되는 2016년 10월로 선정하였으며 대상지역은 울산중구로 선정하였다. LENS를 대상 지역의 관측소 지점값과 행정구역 면적값을 따로 추출한 후, 불확실성을 최소화하기 위해 활용되고 있는 CF 기법과 QM 기법을 이용하여 LENS 모델을 재가공하고 이에 따른 편의보정 기법에 따른 LENS 모델을 과거의 실제강우 관측값과의 비교분석을 이용해 적용성을 검토 및 평가하였다.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.19-25
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• 2023

In this paper, we propose a method for improving raw images captured in a low light condition based on deep learning considering the image signal processing. In the case of a smart phone camera, compared to a DSLR camera, the size of a lens or sensor is limited, so the noise increases and the reduces the quality of images in low light conditions. Existing deep learning-based low-light image processing methods create unnatural images in some cases since they do not consider the lens shading effect and white balance, which are major factors in the image signal processing. In this paper, pixel distances from the image center and channel average values are used to consider the lens shading effect and white balance with a deep learning model. Experiments with low-light images taken with a smart phone demonstrate that the proposed method achieves a higher peak signal to noise ratio and structural similarity index measure than the existing method by creating high-quality low-light images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.135-139
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• 1996

In this a paper, a new method to measure the wear of the single crystal diamond(SCD) tool using image processing is presented. To increase resoultion, high magnifying lens is used and to enlarge the measurement field of view, a image region matching method is applied. The shape of SCD tool is modeled by mathematical analysis. Cutting edge chipping and wear are calculated by the model. This method is proved to be efficient in detecting a few micron of wear and cutting edge loss by chipping along the whole cutting edge.