• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.66-75
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• 2010

The authors argues that the current road updating system based on traditional aerial photograph or multi-spectral satellite image appears to be non-user friendly due to lack of the frequent cartographic representation for the new construction sites. Google Earth are currently being emerged as one of important places to extract road features since the RGB satellite image with high multi-temporal resolution can be accessed freely over large areas. This paper is primarily intended to evaluate optimal threshold of RGB pixel values to extract road features from Google Earth. An empirical study for five experimental sites was conducted to confirm how a RGB picture provided Google Earth can be used to extact the road feature. The results indicate that optimal threshold of RGB pixel values to extract road features was identified as 126, 125, 127 for manual operation which corresponds to 25%, 30%, 19%. Also, it was found that display scale difference of Google Earth was not very influential in tracking required RGB pixel value. As a result the 61cm resolution of Quickbird RGB data has shown the potential to realistically identified the major type of road feature by large scale spatial precision while the typical algorithm revealed successfully the area-wide optimal threshold of RGB pixel for road appeared in the study area.

• Journal of radiological science and technology
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• v.38 no.4
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• pp.421-427
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• 2015

In this study, we have observed the change of the Hounsfield (HU) in the alteration of by changing in size of physical area and setting size of region of interest (ROI) at focus on kVp and mAs. Four-channel multi-detector computed tomography was used to get transverse axial scanning images and HU. Three dimensional printer which is type of fused deposition modeling (FDM) was used to produce the Phantom. The structure of the phantom was designed to be a type of cylinder that contains 33 mm, 24 mm, 19 mm, 16 mm, 9 mm size of circle holes that are symmetrically located. It was charged with mixing iodine contrast agent and distilled water in the holes. The images were gained with changing by 90 kVp, 120 kVp, 140 kVp and 50 mAs, 100 mAs, 150 mAs, respectively. The 'image J' was used to get the HU measurement of gained images of ROI. As a result, it was confirmed that kVp affects to HU more than mAs. And it is suggested that the smaller size of physical area, the more decreasing HU even in material of a uniform density and the smaller setting size of ROI, the more increasing HU. Therefore, it is reason that to set maximum ROI within 5 HU is the best way to minimize in the alteration of by changing in size of physical area and setting size of region of interest.

• Journal of Animal Science and Technology
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• v.53 no.5
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• pp.475-480
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• 2011

This study was conducted to investigate the effects of different feeding level of TDN (Total Digestible Nutrients) on the generation of main greenhouse gases such as carbon dioxide and methane in Hanwoo cows. The diet TDN (kg) adjusted to achieve ADG of 0 g/day (Control), 200 g/day (T1), and 400 g/day (T2) of the maintenance level TMR (Total Mixed Ration) delivered twice a day at 08:30 and 17:30. Cow are housed in a respiration chamber and the environmental temperature was maintained at $20^{\circ}C$. The gases were measured for 24 hours using the multi-detector instrument Mamos-300. The analyzed methane emissions of T1 and T2 were 33.5% and 69.6% higher than control, respectively, and the carbon dioxide emissions were 21.1% and 40.6% higher than control. Also, the hourly pattern of carbon dioxide and methane production were showed very similar emission. Gas production showed peak after 1 hour of feeding and this gap was wider in the afternoon than in the morning hours. It is clearly conducted that $CO_2$ and $CH_4$ emissions were different by limited intake levels of feed.

• Journal of Sensor Science and Technology
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• v.7 no.2
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• pp.124-130
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• 1998

High-speed 3D vision systems are essential for autonomous robot or vehicle control applications. In our study, a stereo vision process has been developed. It consists of three steps : extraction of edges in right and left images, matching corresponding edges and calculation of the 3D map. This process is implemented in a VME 150/40 Imaging Technology vision system. It is a modular system composed by a display, an acquisition, a four Mbytes image frame memory, and three computational cards. Programmable accelerator computational modules are running at 40 MHz and are based on TMS320C31 DSP with a $64{\times}32$ bit instruction cache and two $1024{\times}32$ bit internal RAMs. Each is equipped with 512 Kbytes static RAM, 4 Mbytes image memory, 1 Mbytes flash EEPROM and a serial port. Data transfers and communications between modules are provided by three 8 bit global video bus, and three local configurable pipeline 8 bit video bus. The VME bus is dedicated to system management. Tasks between DSPs are distributed as follows: two DSPs are used to edges detection, one for the right image and the other for the left one. The last processor computes the matching process and the 3D calculation. With $512{\times}512$ pixels images, this sensor generates dense 3D maps at a rate of about 1 Hz depending of the scene complexity. Results can surely be improved by using a special suited multiprocessors cards.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.754-761
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• 2008

As the automobile industry and technologies are developed, driver's tend to more concern about service matters than mechanical matters. For this reason, interests about recognition of human knowledge and emotion to make safe and convenient driving environment for driver are increasing more and more. recognition of human knowledge and emotion are emotion engineering technology which has been studied since the late 1980s to provide people with human-friendly services. Emotion engineering technology analyzes people's emotion through their faces, voices and gestures, so if we use this technology for automobile, we can supply drivels with various kinds of service for each driver's situation and help them drive safely. Furthermore, we can prevent accidents which are caused by careless driving or dozing off while driving by recognizing driver's gestures. the purpose of this paper is to develop a system which can recognize states of driver's emotion and attention for safe driving. First of all, we detect a signals of driver's emotion by using bio-motion signals, sleepiness and attention, and then we build several types of databases. by analyzing this databases, we find some special features about drivers' emotion, sleepiness and attention, and fuse the results through Multi-Modal method so that it is possible to develop the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1557-1564
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• 2014

In this paper, we propose a signal detection technique based on the parallel orthogonal matching pursuit (POMP) is proposed for generalized shift space keying (GSSK) systems, which is a modified version of the orthogonal matching pursuit (OMP) that is widely used as a greedy algorithm for sparse signal recovery. The signal recovery problem in the GSSK systems is similar to that in the compressed sensing (CS). In the proposed POMP technique, multiple indexes which have the maximum correlation between the received signal and the channel matrix are selected at the first iteration, while a single index is selected in the OMP algorithm. Finally, the index yielding the minimum residual between the received signal and the M recovered signals is selected as an estimate of the original transmitted signal. POMP with Quantization (POMP-Q) is also proposed, which combines the POMP technique with the signal quantization at each iteration. The proposed POMP technique induces the computational complexity M times, compared with the OMP, but the performance of the signal recovery significantly outperform the conventional OMP algorithm.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.9
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• pp.623-629
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• 2012

The objective was to evaluate the quality of harvested rainwater of the roofing materials used and the presence of lichens/mosses on the roofing surface. This experiment was studied in the field where five pilot structures with different roofing materials (i.e., wooden shingle tiles, wooden shingle tiles (including mosses), concrete tiles, clay tiles [Gi-Wa] and slate tiles) were installed. As a result, the clay tiles [Gi-Wa] was found to be the most suitable for rainwater harvesting applications. It was due to the disinfection from ultraviolet light and high temperature according to characteristic of roofing materials. Comparison with quality of rainwater on that wooden shingle tiles with and without including mosses, which may affect the concentration of and wooden shingle tiles including mosses, mosses may affect concentration of TOC, nitrate, and sulfate. Additionally, the average concentration of asbestos was determined to be measured at $0.002/cm^3$ for the slate tiles. The value satisfied with it met the Ministry of Environment's Multi-use facility standard and Ministry of Labor's Office standard ($0.01/cm^3$).

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.261-274
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• 2011

In recent competitive business environment each enterprise has to be agile and flexible. For these purposes run-time monitoring ofservices provided by an enterprise and early decision making through this becomes core competition of the enterprise. In addition, in order to process various innumerable events which are generated on enterprise systems techniques which make filtering of meaningful data are needed. However, the existing study related with this is nothing but discovering of service faults by monitoring depending upon API of BPEL engine or middleware, or is nothing but processing of simple events based on low-level events. Accordingly, there would be limitations to provide useful business information. In this paper, through situation detection an extended complex event model is presented, which is possible to provide more valuable and useful business information. Concretely, first of all an event processing architecture in an enterprise system is proposed, and event meta-model which is suitable to the proposed architecture is going to be defined. Based on the defined meta-model, It is presented that syntax and semantics of constructs in our event processing language including various and progressive event operators, complex event pattern, key, etc. In addition, an event context mechanism is proposed to analyze more delicate events. Finally, through application studies application possibility of this study would be shown and merits of this event model would be present through comparison with other event model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.2
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• pp.1414-1419
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• 2015

A method for detecting a skin region on the image is generally used to detect the color information. However, If saturation lowered, skin detection is difficult because hue information of the pixels is lost. So in this paper, we propose a method of correcting color of lower saturation of skin region images by the lighting. Color correction process of this method is saturation image acquisition and low-saturation region classification, segmentation, and the saturation of the split in the low saturation region extraction and color values, the color correction sequence. This method extracts the low saturation regions in the image and extract the color and saturation in the region and the surrounding region to produce a color similar to the original color. Therefore, the method of extracting the low saturation region should be correctly preceding. Because more accurate segmentation in the process of obtaining a low saturation regions, we use a multi-threshold method proposed Otsu in Hue values of the HSV color space, and create a binary image. Our experimental results for 170 portrait images show a possibility that the proposed method could be used efficiently preprocessing of skin color detection method, because the detection result of proposed method is 5.8% higher than not used it.