• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.861-866
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• 2023

Individuals with visual impairments face difficulties in accessing accurate information about medical services and medications, making it challenging for them to ensure proper medication intake. While there are healthcare laws addressing this issue, there is a lack of standardized solutions, and not all over-the-counter medications are covered. Therefore, we have undertaken the design of a mobile application that utilizes image recognition technology, barcode scanning, and QR code recognition to provide guidance on how to take over-the-counter medications, filling the existing gaps in the knowledge of visually impaired individuals. Currently available applications for individuals with visual impairments allow them to access information about medications. However, they still require the user to remember which specific medication they are taking, posing a significant challenge. In this research, we are optimizing the camera capture environment, user interface (UI), and user experience (UX) screens for image recognition, ensuring greater accessibility and convenience for visually impaired individuals. By implementing the findings from our research into the application, we aim to assist visually impaired individuals in acquiring the correct methods for taking over-the-counter medications.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.1
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• pp.317-327
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• 2013

Air pollution and artificial heat of urban areas have caused the urban heat island in which asphalt pavements absorb solar heat during the daytime and release the heat at night. Hence, in order to improve the environment of urban areas, it is necessary to examine cooling pavements that can reduce heat on road pavements in urban areas. The application of temperature insulation paints on road pavements require to reduce black brightness for visibility, to increase the reflection rate of infrared light and minimize the reflection rate of visible light. In the study, one part of Acrylic-emulsion was used as a main binder, and the changes in black brightness and the changes of addition ratio (0%, 15%, 30%) of hollow ceramics, as well as kinds of paints (carbon black pigment, mixed mineral pigment) were selected as the main experimental factors. The performance of temperature reduction of cooling pavements was analyzed through the reflection rate of spectrum, the reflection rate of solar heat, and the lamp test. Abrasion resistance, UV accelerated weather resistance, and sliding resistance were tested in real situations. In addition, the performance of heat reduction of testing pavements covered with high-reflection paints was analyzed by using an infrared camera. As the test results, when using mixed mineral paints and hollow ceramic of 30%, the reflection rate of spectrum was 43% in the area of near-infrared ray and 17% in the area of visible light at black brightness of $L^*$=42.89 and the reflection rate of solar heat was 27.5%. Total color difference was ${\Delta}E$=0.27 in the test of UV Accelerated Weather Resistance, indicating almost no changes in color. BPN was more than 53 when scattering #2 and #4 silica sand of more than $0.12kg/m^2$. In Taber's abrasion resistance test, abrasion loss was up to 86.4mg at 500 rotations. The performance of heat reduction was evaluated using an infrared camera at the test section applying high-reflection paints to asphalt pavements, in which the results showed that the temperature was reduced by $12.7^{\circ}C$ on CI-30-40 cooling pavements ($L^*$=38.76) and by $14.2^{\circ}C$ on CI-30-60 cooling pavements ($L^*$=57.12).

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.4
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• pp.377-385
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• 2020

Recently, wheat consumption has been increasing in Korea, requiring increased production. Nitrogen fertilization is a critical determinant in crop yield; therefore, it is necessary to optimize the nitrogen fertilization regime with current trends that emphasize the minimum impact of nitrogen fertilizer on the environment. In this study, both nondestructive spectral analysis using a hyperspectral camera and growth analysis were performed to determine the optimal N top-dressing rates after heading. The nitrogen application regimes consisted of three conditions according to the secondary top-dressing rate: N_4:3:0 (0 kg 10 a^-1), N_4:3:3 (2.73 kg 10 a^-1), and N_4:3:6 (5.46 kg 10 a^-1). Subsequently, growth and physiological investigations were performed at the jointing, heading, and ripening stages of wheat, and spectral investigations were conducted. On April 29, as the nitrogen fertilization rate was increased to N_4:3:3 and N_4:3:6, plant height and grain yield increased by 4% and 8%, and 8% and 52%, respectively, compared to those under N_4:3:0. Leaf area index and SPAD value also increased by 13% and 24%, and 32% and 43%, respectively. The R (red), G (green), and B (blue) of leaf color were lowered by 15, 11, and 4 in N_4:3:3 and 44, 34, and 18 in N_4:3:6, respectively, as compared to the control. Grain yield was the highest at high top-dressing (N_4:3:6), however, there was no difference between no top-dressing (N_4:3:0) and intermediat top-dressing (N_4:3:3). The reflectance analyzed using a hyperspectral camera showed a difference in the near-infrared (NIR) region on March 19, and on April 29, there was a difference both in the visible light region greater than 550 nm and the NIR region. Vegetation indices differed according to fertilization regime, except for the greenness index (GI). The results of this study showed that not only growth and physiological analysis but also spectral indices can be used to optimize the nitrogen top-dressing rate.

• Korean Journal of Materials Research
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• v.11 no.7
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• pp.556-561
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• 2001

We prepared a new a SOS(silicon-on-silicide) wafer pair which is consisted of Si(100)/1000$\AA$-NiSi Si (100) layers. SOS can be employed in MEMS(micro- electronic-mechanical system) application due to low resistance of the NiSi layer. A thermally evaporated $1000\AA$-thick Ni/Si wafer and a clean Si wafer were pre-mated in the class 100 clean room, then annealed at $300~900^{\circ}C$ for 15hrs to induce silicidation reaction. SOS wafer pairs were investigated by a IR camera to measure bonded area and probed by a SEM(scanning electron microscope) and TEM(transmission electron microscope) to observe cross-sectional view of Si/NiSi. IR camera observation showed that the annealed SOS wafer pairs have over 52% bonded area in all temperature region except silicidation phase transition temperature. By probing cross-sectional view with SEM of magnification of 30,000, we found that $1000\AA$-thick uniform NiSi layer was formed at the center area of bonded wafers without void defects. However we observed debonded area at the edge area of wafers. Through TEM observation, we found that $10-20\AA$ thick amourphous layer formed between Si surface and NiSix near the counter part of SOS. This layer may be an oxide layer and lead to degradation of bonding. At the edge area of wafers, that amorphous layer was formed even to thickness of $1500\AA$ during annealing. Therefore, to increase bonding area of Si NiSi ∥ Si wafer pairs, we may lessen the amorphous layers.

• The Korean Journal of Nuclear Medicine
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• v.35 no.2
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• pp.89-99
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• 2001

Purpose: In this study, we developed a new software tool for the analysis of renal scintigraphy which can be modified more easily by a user who needs to study new clinical applications, and the appropriateness of the results from our program was studied. Materials and Methods: The analysis tool was programmed with IDL5.2 and designed for use on a personal computer running Windows. For testing the developed tool and studying the appropriateness of the calculated glomerular filtration rate (GFR), $^{99m}Tc$-DTPA was administered to 10 adults in normal condition. In order to study the appropriateness of the calculated mean transit time (MTT), $^{99m}Tc-DTPA\;and\;^{99m}Tc-MAG3$ were administered to 11 adults in normal condition and 22 kidneys were analyzed. All the images were acquired with ORBITOR. the Siemens gamma camera. Results: With the developed tool, we could show dynamic renal images and time activity curve (TAC) in each ROI and calculate clinical parameters of renal function. The results calculated by the developed tool were not different statistically from the results obtained by the Siemens application program (Tmax: p=0.68, Relative Renal Function: p:1.0, GFR: p=0.25) and the developed program proved reasonable. The MTT calculation tool proved to be reasonable by the evaluation of the influence of hydration status on MTT. Conclusion: We have obtained reasonable clinical parameters for the evaluation of renal function with the software tool developed in this study. The developed tool could prove more practical than conventional, commercial programs.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.609-625
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• 2022

Validation of satellite data products is critical for subsequent analysis that is based on the data. Particularly, performance of ocean color products in turbid and shallow near-land ocean areas has been questioned for long time for its difficulty that stems from the complex optical environment with varying distribution of water constituents. Furthermore, validation with ship-based or station-based measurements has also exhibited clear limitation in its spatial scale that is not compatible with that of satellite data. This study firstly performed validation of major GOCI-II products such as remote sensing reflectance, chlorophyll-a concentration, suspended particulate matter, and colored dissolved organic matter, using the in-situ measurements collected from ship-based field campaign. Secondly, this study also presents preliminary analysis on the use of drone images for product validation. Multispectral images were acquired from a MicaSense RedEdge camera onboard a UAV to compensate for the significant scale difference between the ship-based measurements and the satellite data. Variation of water radiance in terms of camera altitude was analyzed for future application of drone images for validation. Validation conducted with a limited number of samples showed that GOCI-II remote sensing reflectance at 555 nm is overestimated more than 30%, and chlorophyll-a and colored dissolved organic matter products exhibited little correlation with in-situ measurements. Suspended particulate matter showed moderate correlation with in-situ measurements (R²~0.6), with approximately 20% uncertainty.

• Journal of IKEEE
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• v.13 no.4
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• pp.116-124
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• 2009

Recently the CPU performance of modem chipsets or multimedia processors of mobile phone is as high as notebook PC. That is why mobile phone has been emerged as a leading ICON on the convergence of consumer electronics. The various applications of mobile phone such as DMB, digital camera, video telephony and internet full browsing are servicing to consumers. To meet all the demands the image quality has been increasingly important. Mobile phone is a portable device which is widely using in both the indoor and outside environments, so it is needed to be overcome to deteriorate image quality depending on environmental light source. Furthermore touch window is popular on the mobile display panel and it makes contrast loss because of low transmittance of ITO film. This paper presents the image enhancement algorithm to be embedded on image enhancement SoC. In contrast enhancement, we propose Clipped histogram stretching method to make it adaptive with the input images, while S-shape curve and gain/offset method for the static application And CIELCh color space is used to sunlight readability enhancement by controlling the lightness and chroma components which is depended on the sensing value of light sensor. Finally the performance of proposed algorithm is evaluated by using histogram, RGB pixel distribution, entropy and dynamic range of resultant images. We expect that the proposed algorithm is suitable for image enhancement of embedded SoC system which is applicable for the small-sized mobile display.

• Journal of Korean Elementary Science Education
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• v.37 no.2
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• pp.206-218
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• 2018

The purpose of this study is to analyze the teaching behaviors and visual attention according to teacher's career in Elementary Science Inquire-based Class. Participants were four elementary school teachers in Seoul. They were all in grade 5 and taught science. According to the experience of elementary science education, two novice teachers and two expert teachers were identified. Participants taught Respiration in the 'Structure and Function of our Body' in the elementary science fifth grade. The mobile eye tracker used in this study is SMI's ETG 2w, which is a binocular tracking system. In addition, a video camera was installed behind the classroom to record the entire class. We recorded all the contents of the recorded video and analyzed the results. In this study, the actual practice time, participant's visual attention, and decentralized attention ability were analyzed by class phase. The results of the study are as follows. First, there was a difference between planned class time and actual practice time. The novice teachers were having difficulty in reconstructing the contents of education, and the expert teachers were reconstructing the curriculum and interacting with the students with high understanding and application of the curriculum. There were many differences between the novice teachers and the expert teachers in the tour guidance to confirm student activities. Second, if we look at the visual attention on the area related to teaching and learning by class phase, the novice teacher concentrates all the steps in a specific area, expert teachers showed an equal visual attention to meaningful areas of teaching and learning activities. Third, there was a statistically significant difference in activities 1-1, 1-2, 2-1, and 2-2 when the participants' decentralized attention ability. Expert teachers frequently checked students' understanding and interests. There was a lot of interaction with students. It is also shown through the decentralized attention ability that the novice teachers concentrate on a specific area, and the expert teachers have a high degree of decentralized attention ability and visual attention evenly.