• Journal of Korean Society on Water Environment
• /
• v.21 no.1
• /
• pp.66-72
• /
• 2005

Effect of the pH, molar ratio of Cu(II)/EDTA, concentration of Cu(II)-EDTA and ionic strength on the photocatalytic oxidation(PCO) of Cu(II)-EDTA in solar light was studied in this work. Experimental results in this work were compared with previous results obtained with UV-lamp. In the kinetics, Cu(II)-EDTA decomposition was favorable below neutral pH. The removal of Cu(II) and DOC was favorable as $TiO_2$ dosage increased. The initial rate for the decomplexation of Cu(II)-EDTA linearly increased as the concentration of Cu(II)-EDTA increased. The removal of Cu(II) and DOC was not much affected by variation of ionic strength with $NaClO_4$ as a background ion while much reduction was observed in the presence of background ions having higher formal charges. The removal trend of Cu(II) and DOC with variation of ionic strength and concentration of Cu(II)-EDTA in solar light was similar with that in UV light. Variation of the molar ratio of Cu(II)/EDTA showed a negligible effect on the removal of both Cu(II) and DOC. However, removal of both Cu(II) and DOC was two-times greater than that previous results obtained with UV light.

• Smart Media Journal
• /
• v.4 no.2
• /
• pp.26-33
• /
• 2015

In this paper, we propose an efficient automatic pedestrian removal system from a frame in a video sequence. It firstly finds pedestrians from the frame using a Histogram of Oriented Gradient(HOG) / Linear-Support Vector Machine(L-SVM) classifier, searches for proper background patches, and then the patches are used to replace the deleted pedestrians. Background patches are retrieved from the reference video sequence and a modified feather blender algorithm is applied to make boundaries of replaced blocks look naturally. The proposed system, is designed to automatically detect object and generate natural-looking patches, while most existing systems provide search operation in manual. In the experiment, the average PSNR of the replaced blocks is 19.246

• Journal of Korea Multimedia Society
• /
• v.22 no.1
• /
• pp.1-9
• /
• 2019

Single image rain removal is a typical inverse problem which decomposes the image into a background scene and a rain streak. Recent works have witnessed a substantial progress on the task due to the development of convolutional neural network (CNN). However, existing CNN-based approaches train the network with synthetically generated training examples. These data tend to make the network bias to the synthetic scenes. In this paper, we present an unsupervised framework for removing rain streaks from real-world rainy images. We focus on the natural phenomena that static rainy scenes capture a common background but different rain streak. From this observation, we train siamese network with the real rain image pairs, which outputs identical backgrounds from the pairs. To train our network, a real rainy dataset is constructed via web-crawling. We show that our unsupervised framework outperforms the recent CNN-based approaches, which are trained by supervised manner. Experimental results demonstrate that the effectiveness of our framework on both synthetic and real-world datasets, showing improved performance over previous approaches.

• Nuclear Engineering and Technology
• /
• v.38 no.1
• /
• pp.99-108
• /
• 2006

SNU-RCCS is a water pool type RCCS (Reactor Cavity Cooling System) developed for VHTR (Very High Temperature Reactor) application by SNU (Seoul National University). Since radiation heat transfer is the major process of passive heat removal in a RCCS, it is important to determine the precise emissivity of the reactor vessel. Review studies have used a constant emissivity in the passive heat removal analysis, even though the emissivity depends on many factors such as temperature, surface roughness, oxidation level, wavelength, direction, atmosphere conditions, etc. Therefore, information on the emissivity of a given material in a real RCCS is essential in order to properly analyze the radiation heat transfer in a VHTR. The objectives of this study are to develop a method for compensation of the factors affecting the emissivity measurement using an infrared thermometer and to estimate the true emissivity from the measured emissivity via the developed method, especially in the SNU-RCCS environment. From this viewpoint, we investigated factors such as the attenuation effect of the window, filling gas, and the effect of background radiation on the emissivity measurements. The emissivity of the vessel surface of the SNU-RCCS facility was then measured using a sight tube. The background radiation was subsequently removed from the measured emissivity by solving a simultaneous equation. Finally, the calculated emissivity was compared with the measured emissivity in a separate emissivity measurement device, yielding good agreement with the emissivity increase with vessel temperature in a range of 0.82 to 0.88.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.5
• /
• pp.2291-2297
• /
• 2012

X-ray fluorescence sprectrum signal include the continuum. XRF analysis the components of material by the amplitude of peaks. XRF remove the noise and background. To remove the noise, we apply the smoothing filter. And background removal methods applied such as SNIP, Morphology, Threshold methods. In this paper, we applied Threshold using DWT. Interval threshold method divide the some blocks in particular levels. We propose the method that is divided the particular level.

• Journal of the Institute of Convergence Signal Processing
• /
• v.14 no.4
• /
• pp.231-234
• /
• 2013

This paper introduces a mixture of background subtraction technique and K-Means clustering algorithm for removing shadows from video sequences. Lighting conditions cause an issue with segmentation. The proposed method can successfully eradicate artifacts associated with lighting changes such as highlight and reflection, and cast shadows of moving object from segmentation. In this paper, K-Means clustering algorithm is applied to the foreground, which is initially fragmented by background subtraction technique. The estimated shadow region is then superimposed on the background to eliminate the effects that cause redundancy in object detection. Simulation results depict that the proposed approach is capable of removing shadows and reflections from moving objects with an accuracy of more than 95% in every cases considered.

• Korean Journal of Environmental Agriculture
• /
• v.39 no.2
• /
• pp.89-94
• /
• 2020

BACKGROUND: Persistent organic contaminants such as dichlorodiphenyltrichloroethane (DDT) are often found in agricultural soils decades after it was banned in Korea. This study uses hemoglobin and hemoglobin-containing blood meal to reduce the residual DDT in soil. METHODS AND RESULTS: Hemoglobin or blood meal with or without hydrogen peroxide (H₂O₂) was mixed with the DDT-spiked soil prepared for this study, and samples were taken over 14 d-degradation period to measure the residual DDT concentrations. With only hemoglobin, DDT was completely removed after 14 d, while with both hemoglobin and H₂O₂, 73%, on average, removal was observed. Similarly, the blood meal removed 73% of DDT, but with H₂O₂, the DDT removal was only 39%. The lower DDT removal in the presence of H₂O₂ can be attributed to the adverse effects of reactive species. Hemoglobin was more effective than blood meal for DDT removal in a given time; however, with additional blood meal injection, complete DDT removal was achieved. CONCLUSION: Overall, this study shows that the blood meal that is used as a fertilizer can potentially be used to remove residual contaminants such as DDT in agricultural soil.

• Medical Lasers
• /
• v.10 no.2
• /
• pp.106-110
• /
• 2021

Background and Objectives As the popularity of tattooing has increased, the number of people regretting their tattoos, and therefore seeking tattoo removal services has also increased. This study aimed to highlight the reasons for tattoo regrets. We explore herein, the reasons for seeking tattoo removal at a specialized laser center in South America. Materials and Methods This is a retrospective study of over 757 surveys, including patients who sought tattoo removal services between August 2017 and February 2020. The surveys were conducted using questionnaires which were sent to the patients through email and WhatsApp messages. Results Sixty percent of the patients seeking tattoo erasing services were women (α=0.001), an average of 30 years, with a high educational level (46.6% of them were university or tertiary). Most of the tattoos (89%) had a professional origin, 60% were done with black color and 65% were in exposed areas. More than half of the patients (51%) gave dissatisfaction as the main reason for erasing their tattoos. More than half of patients (51.2%) regretted their tattoos between the same day of being tattooed and five years later. Conclusion In the present study, in South America, tattoo regrets were mostly common among educated (university or tertiary level) women in their 30s. The most preferred color for a tattoo was black. Exposed areas, especially the arms, were preferred more than the covered areas. Most of the participants regretted their tattoos within five years of being tattooed.

• Journal of the Korea Computer Graphics Society
• /
• v.25 no.5
• /
• pp.1-9
• /
• 2019

In this paper, we propose a video enhancement method using generative adversarial networks to remove raindrops and restore the background information on the removed region in the coastal wave video imagery distorted by raindrops during rainfall. Two experimental models are implemented: Pix2Pix network widely used for image-to-image translation and Attentive GAN, which is currently performing well for raindrop removal on a single images. The models are trained with a public dataset of paired natural images with and without raindrops and the trained models are evaluated their performance of raindrop removal and background information recovery of rainwater distortion of coastal wave video imagery. In order to improve the performance, we have acquired paired video dataset with and without raindrops at the real coast and conducted transfer learning to the pre-trained models with those new dataset. The performance of fine-tuned models is improved by comparing the results from pre-trained models. The performance is evaluated using the peak signal-to-noise ratio and structural similarity index and the fine-tuned Pix2Pix network by transfer learning shows the best performance to reconstruct distorted coastal wave video imagery by raindrops.

• Journal of Information Technology Application
• /
• v.3 no.2
• /
• pp.133-147
• /
• 2001

This paper proposed a new algorithm for binarization and removal of noises in color images with characters and pictures. Binarization was performed by threshold which had computed with color-relationship relative to the number of pixel in background and character candidates and pre-threshold for dividing of background and character candidates in input images. The pre-threshold has been computed by the histogram of R, G, B In respect of the images, while background and character candidates of input images are divided by the above pre-threshold. As it is possible that threshold can be dynamically decided by the quantity of the noises, and the character images are maintained and the noises are removed to the maximum. And, in this study, we made the noise pattern table as a result of analysis in noise pattern included in the various color images aiming at removal of the noises from the Images. Noises included in the images can figure out Distribution by way of the noise pattern table and pattern matching itself. And then this Distribution classified difficulty of noises included in the images into the three categories. As removal of noises in the images is processed through different procedure according to the its classified difficulties, time required for process was reduced and efficiency of noise removal was improved. As a result of recognition experiments in respect of extracted characters in color images by way of the proposed algorithm, we conformed that the proposed algorithm is useful in a sense that it obtained the recognition rate in general documents without colors and pictures to the same level.