• Journal of KIISE:Computing Practices and Letters
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• v.9 no.2
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• pp.166-181
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• 2003

With the rapid growth of Internet, many devices such as Web TVs, PDAs and Web phones, begin to be directly connected to the Internet. These devices need real-time operating systems (RTOS) to support complex real-time applications running on them. Development of such real-time applications called embedded internet applications, is difficult due to the lack of adequate tools, especially debuggers. In this paper we present a new tracepoint debugging tool for the Qplus-T RTOS embedded system, which facilitates the instrumentations of the real-time software applications with timing trace-points. Compared with traditional breakpoint debugger, this trace-point debugger provides the ability to dynamically collect and record application data for on-line examination and for further off-line analysis. And, the trace-points can also provide the means for assigning new values to the running application's variables, without neither halting its execution nor interfering with its natural execution flow. Our trace-point debugger provides a highly efficient method for adding numerous monitoring trace-points within a real time target application such as Qplus-T internet applications, utilizing these trace-points to monitor and to analyze the application's behavior while it is running. And also, our trace debugger is different from previous one in that we can specify and detect the timing violations using its RTL (Real-Time Logic) trace experiments.

• Journal of Biosystems Engineering
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• v.28 no.6
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• pp.517-524
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• 2003

There have been worldwide research and development efforts to automate various processes of bio-production and those efforts will be expanded with priority given to tasks which require high intensive labor or produce high value-added product and tasks under hostile environment. In the field of bio-production capabilities of the versatility and robustness of automated system have been major bottlenecks along with economical efficiency. This paper introduces a new concept of automation based on tole-operation, which can provide solutions to overcome inherent difficulties in automating bio-production processes. Operator(farmer), computer, and automatic machinery share their roles utilizing their maximum merits to accomplish given tasks successfully. Among processes of greenhouse watermelon cultivation tasks such as pruning, watering, pesticide application, and harvest with loading were chosen based on the required labor intensiveness and functional similarities to realize the proposed concept. The developed system was composed of 5 major hardware modules such as wireless remote monitoring and task control module, wireless remote image acquisition and data transmission module, gantry system equipped with 4 d.o.f. Cartesian type robotic manipulator, exchangeable modular type end-effectors, and guided watermelon loading and storage module. The system was operated through the graphic user interface using touch screen monitor and wireless data communication among operator, computer, and machine. The proposed system showed practical and feasible way of automation in the field of volatile bio-production process.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.81-90
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• 1999

This paper describes an EEG(electroencephalogram) software for two-channel cerebral function monitoring system to detect the cerebral ischemia. In the software, two-channel bipolar analog EEG signals are digitized and from the signals various EEG parameters are extracted and displayed on a monitor in real-time. Digitized EEG signal is transformed by FFT(Fast Fourier transform) and represented as CSA(compressed spectral array) and DSA(density spectral array). Additional 5 parameters, such as alpha ratio, percent delta, spectral edge frequency, total power, and difference in total power, are estimated using the FFT spectra. All of these are effectively merged in a monitor and displayed in real-time. Through animal experiments and clinical trials on men, the software is modified and enhanced. Since the software provides raw EEG, CSA, DSA, simultaneously with additional 5 parameters in a monitor, it is possible to observe patients multilaterally. For easy comparison of patient's status, reference patterns of CSA, DSA can be captured and displayed on top of the monitor. And user can mark events of surgical operation and patient's conditions on the software, this allow him jump to the points of events directly, when reviewing the recorded EEG file afterwards. Other functions, such as forward/backward jump, gain control, file management are equipped and these are operated by simple mouse click. Clinical tests in a university hospital show that the software responds accurately according to the conditions of patients and medical doctors can use the software easily.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1013-1025
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• 2020

Unmanned Aerial Vehicle (UAV) platform is being widely used in disaster monitoring and smart city, having the advantage of being able to quickly acquire images in small areas at a low cost. Ground Control Points (GCPs) for positioning UAV images are essential to acquire cm-level accuracy when producing UAV-based orthoimages and Digital Surface Model (DSM). However, the on-site acquisition of GCPs takes considerable manpower and time. This research aims to provide an efficient and accurate way to replace the on-site GNSS surveying with three different sources of geospatial data. The three geospatial data used in this study is as follows; 1) 25 cm aerial orthoimages, and Digital Elevation Model (DEM) based on 1:1000 digital topographic map, 2) point cloud data acquired by Mobile Mapping System (MMS), and 3) hybrid point cloud data created by merging MMS data with UAV data. For each dataset a three-dimensional positional accuracy analysis of UAV-based orthoimage and DSM was performed by comparing differences in three-dimensional coordinates of independent check point obtained with those of the RTK-GNSS survey. The result shows the third case, in which MMS data and UAV data combined, to be the most accurate, showing an RMSE accuracy of 8.9 cm in horizontal and 24.5 cm in vertical, respectively. In addition, it has been shown that the distribution of geospatial GCPs has more sensitive on the vertical accuracy than on horizontal accuracy.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.1
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• pp.97-108
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• 2018

The purpose of this study is to propose the construction of a visibility analysis model, which is the basis of the analysis for landscape management on the heritage sites such as historic villages and scenic sites. Results of the visibility analysis using DEM and the visibility analysis of DSM based on 3D mapping data are compared as follows: Precision level of the extracted data was confirmed to be less than 6.5cm, based on RTK survey results produced by constructing orthoimage data and DSM from the digital data of 2cm-class GSD(Ground Sample Distance) obtained by using a small UAV(Unmanned Aerial Vehicle). As a result of comparing the visibility analysis data of Digital Surface Model (DSM) using a small UAV with Digital Elevation Model(DEM) applying the height of the building to the Digital Topographic Map, it was confirmed that more realistic visibility analysis can be accomplished by applying DSM, as the structures such as fences, trees, and houses are reflected in the topographic data. The visibility analysis model using the 3D mapping technique can efficiently obtain the constantly changing topographic information when needed, by immediately constructing the data by utilizing a small UAV. It seems to be possible to propose a reasonable analysis result for preservation management such as landscape evaluation of cultural property.

• Journal of Nutrition and Health
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• v.48 no.5
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• pp.419-428
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• 2015

Purpose: The current study was conducted in order to develop the Korean Healthy Eating Index (KHEI) for assessing adherence to national dietary guidelines and comprehensive diet quality of healthy Korean adults using the 5th Korea National Health and Nutrition Examination Survey (KNHANES) data. Methods: The candidate components of KHEI were selected based on literature reviews, dietary guidelines for Korean adults, 2010 Dietary Reference Intakes for Koreans (2010 KDRI), and objectives of HP 2020. The associations between candidate components and risk of obesity, abdominal obesity, and metabolic syndrome were assessed using the 5th KNHANES data. The expert review process was also performed. Results: Diets that meet the food group recommendations per each energy level receive maximum scores for the 9 adequacy components of the index. Scores for amounts between zero and the standard are prorated linearly. For the three moderation components among the total of five, population probability densities were examined when setting the standards for minimum and maximum scores. Maximum scores for the total of 14 components are 100 points and each component has maximum scores of 5 (fruit intakes excluding juice, fruit intake including juice, vegetable intakes excluding Kimchi and pickles, vegetable intake including Kimchi or pickles, ratio of white meat to read meat, whole grains intake, refined grains intake, and percentages of energy intake from carbohydrate) or 10 points (protein foods intake, milk and dairy food intake, having breakfast, sodium intake, percentages of energy intake from empty calorie foods, and percentages of energy intake from fat). The KHEI is a measure of diet quality as specified by the key diet recommendations of the dietary guidelines and 2010 KDRIs. Conclusion: The KHEI will be used as a tool for monitoring diet quality of the Korean population and subpopulations, evaluation of nutrition interventions and research.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.4
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• pp.263-271
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• 2009

This study evaluated the flocs forming characteristics in the mixing zone to increase the coagulation effect in the drinking water plant. As a measuring tool of formed flocs, on-line particle dispersion analyzer (iPDA) was used in Y drinking water plant. To evaluate the forming flocs, many parameters such as poly amine, coagulant dosing amount, raw water turbidity, and pH was applied in this study. During the periods of field test, poly aluminium chloride (PACl) as a coagulant was used. With the increase of the raw water turbidities, poly amine was also added as one of aids for increasing in coagulation efficiency. The turbidity and pH of raw water was ranged from 7 to 9 and from 25 to 140 NTU, respectively. The increasing of raw water turbidity brought the bigger floc sizes accordingly. From a regression analysis, $R^2$ value was 0.8040 as a function of T, raw water turbidity. Floc size index (FSI) was obtained from a correlation equation as follows; FSI = 0.9388logT - 0.3214 Also, polyamine gave the bigger flocs the moment it is added to the coagulated water in the rapid mixing zone. One of parameters influencing the floc sizes was the addition of powdered active carbon(PAC) in the mixing zone. In case of higher turbidity of raw water, $R^2$ value was 0.9050 in the parameters of [PACl] and [PAC]; FSI = $0.0407[T]^{0.324}[PACI]^{0.769}[PAC]^{0.178}$ On-line floc monitor was beneficial to evaluate the flocs sizes depending on the many parameters consisting raw water properties, bring the profitable basic data to control the mixing zone more effectively.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.989-1006
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• 2020

Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.

• Korean Journal of Heritage: History & Science
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• v.54 no.1
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• pp.206-219
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• 2021

The warming of the climate is increasing the damage caused by termites to wooden buildings, cultural properties and houses. A group removal system can be installed around the building to detect and remove termite damage; however, if the site is not visited regularly, every one to two months, you cannot observe whether termites have spread within, and it is difficult to take prompt effective action. In addition, since the system is installed and operated in an exposed state for a long period of time, it may be ineffective or damaged, resulting in a loss of function. Furthermore if the system is installed near a cultural site, it may affect the aesthetic environment of the site. In this study, we created a detection system that uses wood, cellulose, magnets, and magnetic sensors to determine whether termites have entered the area. The data was then transferred to a low power LoRa Network which displayed the results without the necessity of visiting the site. The wood was made in the shape of a pile, and holes were made from the top to the bottom to make it easier for termites to enter and produce a cellulose sample. The cellulose sample was made in a cylindrical shape with a magnet wrapped in cellulose and inserted into the top of a hole in the wood. Then, the upper part of the wood pile was covered with a stopper to prevent foreign matter from entering. It also served to block external factors such as light and rainfall, and to create an environment where termites could add cellulose samples. When the cellulose was added by the termites, a space was created around the magnet, causing the magnet to either fall or tilt. The magnetic sensor inside the stopper was fixed on the top of the cellulose sample and measured the change in the distance between the magnet and the sensor according to the movement of the magnet. In outdoor experiments, 11 cellulose samples were inserted into the wood detection system and the termite inflow was confirmed through the movement of the magnet without visiting the site within 5 to 17 days. When making further improvements to the function and operation of the system it in the future, it is possible to confirm that termites have invaded without visiting the site. Then it is also possible to reduce damage and fruiting due to product exposure, and which would improve the condition and appearance of cultural properties.

• Journal of Korea Water Resources Association
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• v.55 no.1
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• pp.1-10
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• 2022

Irrigation water supplied to the paddy field is consumed in the amount of evapotranspiration, underground infiltration, and natural and artificial drainage from the paddy field. Irrigation return flow is defined as the excess of irrigation water that is not consumed by evapotranspiration and crop, and which returns to an aquifer by infiltration or drainage. The research on estimating the return flow play an important part in water circulation management of agricultural watershed. However, the return flow rate calculations are needs because the result of calculating return flow is different depending on irrigation channel water loss, analysis methods, and local characteristics. In this study, the irrigation return flow rate of agricultural watershed was estimated using the monitoring and SWMM (Storm Water Management Model) modeling from 2017 to 2020 for the Heungeop reservoir located in Wonju, Gangwon-do. SWMM modeling was performed by weather data and observation data, water of supply and drainage were estimated as the result of SWMM model analysis. The applicability of the SWMM model was verified using RMSE and R-square values. The result of analysis from 2017 to 2020, the average annual quick return flow rate was 53.1%. Based on these results, the analysis of water circulation characteristics can perform, it can be provided as basic data for integrated water management.