• English Language & Literature Teaching
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• v.16 no.3
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• pp.1-18
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• 2010

This study examined the effects of previewing and providing background knowledge on low level EFL readers' comprehension of expository texts and their responses to these treatments. 130 college freshmen were randomly placed into one of three treatment groups and read two expository texts reflecting unfamiliar cultural information. Prior to reading, one group was given previewing instruction, which included vocabulary preteaching and summaries, and a second group was provided with culture-specific background knowledge through watching videos and slides. The third group read each text without any prereading instruction. Immediately after reading a passage, subjects answered a 10-item multiple-choice test. Results showed significant positive effects of the previewing treatment and weak positive effects of the providing background knowledge treatment. Students' responses on the questionnaires revealed that the majority felt that the experimental treatments contributed to comprehension enhancement, made reading more enjoyable, and expedited their reading process. Students in the control group, however, indicated that they needed explicit prereading instruction in order to understand the texts. Pedagogical implications of the findings for EFL reading instruction are provided.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.1
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• pp.23-30
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• 2022

Recently, there are various studies underway on the deep learning-used image matting methods. Even in the field of photogrammetry, a process of extracting information about relics from images photographed is essential to produce a high-quality realistic model. Such a process requires a great deal of time and manpower, so chroma-key has been used for extraction so far. This method is low in accuracy of sub-classification, however, it is difficult to apply the existing method to high-quality realistic models. Thus, this study attempted to remove background information from high-resolution relic images by using prior background information and trained learning data and evaluate both qualitative and quantitative results of the relic images extracted. As a result, this proposed method with FBA(manual trimap) showed quantitatively better results, and even in the qualitative evaluation, it was high in accuracy of classification around relics. Accordingly, this study confirmed the applicability of the proposed method in the indoor relic photography since it showed high accuracy and fast processing speed by acquiring prior background information when classifying high-resolution relic images.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.442-453
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• 2020

Underwater color images suffer from low visibility and color cast effects caused by light attenuation by water and floating particles. This study applied single image enhancement techniques to enhance the quality of underwater images and compared their performance with real underwater images taken in Korean waters. Dark channel prior (DCP), gradient transform, image fusion, and generative adversarial networks (GAN), such as cycleGAN and underwater GAN (UGAN), were considered for single image enhancement. Their performance was evaluated in terms of underwater image quality measure, underwater color image quality evaluation, gray-world assumption, and blur metric. The DCP saturated the underwater images to a specific greenish or bluish color tone and reduced the brightness of the background signal. The gradient transform method with two transmission maps were sensitive to the light source and highlighted the region exposed to light. Although image fusion enabled reasonable color correction, the object details were lost due to the last fusion step. CycleGAN corrected overall color tone relatively well but generated artifacts in the background. UGAN showed good visual quality and obtained the highest scores against all figures of merit (FOMs) by compensating for the colors and visibility compared to the other single enhancement methods.

• International Journal of Contents
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• v.9 no.1
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• pp.6-10
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• 2013

Foreground estimation in object segmentation has been an important issue for last few decades. In this paper we propose a GrabCut based automatic foreground estimation method using block clustering. GrabCut is one of popular algorithms for image segmentation in 2D image. However GrabCut is semi-automatic algorithm. So it requires the user input a rough boundary for foreground and background. Typically, the user draws a rectangle around the object of interest manually. The goal of proposed method is to generate an initial rectangle automatically. In order to create initial rectangle, we use Gabor filter and Saliency map and then we use 4 features (amount of area, variance, amount of class with boundary area, amount of class with saliency map) to categorize foreground and background. From the experimental results, our proposed algorithm can achieve satisfactory accuracy in object segmentation without any prior information by the user.

• English Language & Literature Teaching
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• v.15 no.4
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• pp.1-22
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• 2009

This case study aimed to explore proficient EFL readers' perceptions and experiences about reading tasks and how those perceptions and experiences influence their reading processing behaviors, and to examine how the cultural background of a text affects their reading strategies and comprehension. Three college students who were non-English majors participated in this study. Three data sources were employed: questionnaires, interviews, and think-alouds. The results showed that: (1) the participants emphasized comprehension as the goal of reading and considered themselves good EFL readers; (2) their reading purposes were closely associated with personal pursuits; (3) they preferred to read materials that deal with areas of interest but did not try to take a risk in terms of level of difficulty and/or length; (4) they implemented a multistrategic approach to reading in that the majority of their strategy use was in conjunction with their concern about meaning construction; (5) they were able to develop useful understandings of unknown vocabulary; and (6) their clear awareness of the cultural background presupposed in the text helped them invoke prior knowledge and reduce unknown vocabulary hindrances which contributed to comprehension. Pedagogical implications for EFL reading instruction are provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4976-4994
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• 2018

The diffusion-based salient object detection methods have shown excellent detection results and more efficient computation in recent years. However, the current diffusion-based salient object detection methods still have disadvantage of detecting the object appearing at the image boundaries and different scales. To address the above mentioned issues, this paper proposes a multi-scale diffusion-based salient object detection algorithm with background and objectness seeds. In specific, the image is firstly over-segmented at several scales. Secondly, the background and objectness saliency of each superpixel is then calculated and fused in each scale. Thirdly, manifold ranking method is chosen to propagate the Bayessian fusion of background and objectness saliency to the whole image. Finally, the pixel-level saliency map is constructed by weighted summation of saliency values under different scales. We evaluate our salient object detection algorithm with other 24 state-of-the-art methods on four public benchmark datasets, i.e., ASD, SED1, SED2 and SOD. The results show that the proposed method performs favorably against 24 state-of-the-art salient object detection approaches in term of popular measures of PR curve and F-measure. And the visual comparison results also show that our method highlights the salient objects more effectively.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.5
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• pp.547-556
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• 2007

The release, sampling and analytical methods have been developed and tested for perfluorocarbons (PFCs) atmospheric tracers in order to gain insight into the atmospheric transport and dispersion over the urban conditions of Seoul, Korea. Although PFCs tracer experiments provide unique opportunities to test local and urban scale of transport and dispersion, no previous experiment with PFCs has been conducted in Korea. PMCH and PDCH were chosen as targeted tracers in our study due to their extreme low ambient concentrations and great sensitivities among various PFCs. For PFCs release system, a set of micro-metering pump, electronic balance, vaporizing furnace and high speed blower was constructed for precise and accurate release of tracers. The precision of released rate by this system was estimated to be 1%. Samplings of PFCs were carried out by fabricated portable air samplers with micro pumps and rotameters into glass tubes packed with 150 mg of Carboxen-569. The uncertainty of these sampling system was maintained below 14%. PMCH and PDCH were quantified in GC/ECD with preconditioned injection system to eliminate the interference compounds using traps and subsequent catalytic conversion system prior to column separation. Three intensive field test were undertaken during the springtime of 2002 to 2004 in eastern part of Seoul. Daily background samples were collected to characterize the background levels of PMCH and PDCH prior to their release. The observed background concentrations of PMCH ranged from 3.5 to 10.1 fL/L and varied randomly in location and time in this study. Its mean and standard variation of background concentration ($6.8{\pm}1.9\;fL/L$) are higher than those ($3.2{\sim}5.8\;fL/L$) of other historic tracer studies. Identified uncertainty for background PMCH was $1.7{\sim}2.0\;fL/L$ using this analytical system. Combined relative uncertainty in determining the tracer's concentrations was estimated as 17%. However, its background concentrations and uncertainty in concentration determination were found to be low and stable enough for tracer study.

• Annals of Laboratory Medicine
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• v.38 no.6
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• pp.545-554
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• 2018

Background: The increasing morbidity and mortality rates associated with Acinetobacter baumannii are due to the emergence of drug resistance and the limited treatment options. We compared characteristics of colistin-resistant Acinetobacter baumannii (CR-AB) clinical isolates recovered from patients with and without prior colistin treatment. We assessed whether prior colistin treatment affects the resistance mechanism of CR-AB isolates, mortality rates, and clinical characteristics. Additionally, a proper method for identifying CR-AB was determined. Methods: We collected 36 non-duplicate CR-AB clinical isolates resistant to colistin. Antimicrobial susceptibility testing, Sanger sequencing analysis, molecular typing, lipid A structure analysis, and in vitro synergy testing were performed. Eleven colistin-susceptible AB isolates were used as controls. Results: Despite no differences in clinical characteristics between patients with and without prior colistin treatment, resistance-causing genetic mutations were more frequent in isolates from colistin-treated patients. Distinct mutations were overlooked via the Sanger sequencing method, perhaps because of a masking effect by the colistin-susceptible AB subpopulation of CR-AB isolates lacking genetic mutations. However, modified lipid A analysis revealed colistin resistance peaks, despite the population heterogeneity, and peak levels were significantly different between the groups. Conclusions: Although prior colistin use did not induce clinical or susceptibility differences, we demonstrated that identification of CR-AB by sequencing is insufficient. We propose that population heterogeneity has a masking effect, especially in colistin non-treated patients; therefore, accurate testing methods reflecting physiological alterations of the bacteria, such as phosphoethanolamine-modified lipid A identification by matrix-assisted laser desorption ionization-time of flight, should be employed.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.685-695
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• 2008

This paper presents a method to segment the object of interest from a set of multi-view images with minimal user interaction. Specifically, after the user segments an initial image, we first estimate the transformations between foreground and background of the segmented image and the neighboring image, respectively. From these transformations, we obtain regions in the neighboring image that respectively correspond to the foreground and the background of the segmented image. We are then able to segment the neighboring image based on these regions, and iterate this process to segment the whole image set. Transformation of foregrounds are estimated by feature-based registration with free-form deformation, while transformation of backgrounds are estimated by homography constrained to affine transformation. Here, both are based on correspondence point pairs. Segmentation is done by estimating pixel color distributions and defining a shape prior based on the obtained foreground and background regions and applying them to a Markov random field (MRF) energy minimization framework for image segmentation. Experimental results demonstrate the effectiveness of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.175-178
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• 2010

Slow movement of snail can be a benefit since it means less speed of tracking is required to get accurate movement track, but in the other side it is difficult to extract the object because the snail is almost as static as the background. In this paper, we present a technique to track the snail by using one of its common characteristic, dark color of its shell. The technique needs to be robust to illumination change since the experiment is usually to observe the movement of snail both at bright and dim condition. Snail position coordinate in 3D space is calculated using orthogonal stereo vision which combines the information from two images taken from cameras at the top and in front of the aquarium. Experimental results show this technique does not need prior background image extraction and robust to gradual or sudden illumination change.