• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.9
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• pp.1-6
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• 2007

In this study, tests of brain waves were carried out to investigate the physiological characteristics of drivers during a change of headlight brightness. The participants were 20 males in their 20s. Twenty-three different conditions combining the waveform of light, voltage, and alteration time were used. The measurement of brain waves was performed by an internationally standardized 10-20 method using LXE3232-RF. The results were as follows. 1. From the results of the brain wave map analysis, it was suggested that waveform A increases mental stress and waveform B affects mental and visual stress. The longer the stimulation time, the more stress level was detected. 2. The voltage alteration time of the B waveform should be kept to less than 1500msec, while the voltage should not fall below 11.5[V].

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.671-674
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• 2007

USN (Ubuquitous Sensor Network) identifies that networks are able to gather information from various kinds of sensors with RF. In the USN, it is important that sensor nodes deliver stable data by overcoming limited transmission distance and by setting optimum routes. In this paper, we propose a method to overcome the limited distance of sensor nodes using Wireless Mesh Networks. With this method, environmental monitoring system for u-farm support stable data transmission by applying MAP of Wireless Mesh Networks.

• The Transactions of the Korea Information Processing Society
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• v.1 no.4
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• pp.452-460
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• 1994

Maps are one of the most complicated types of drawings. Drawing recognition technology is not yet sophisticated enough for automated map reading To automatically extract a road map directly from more complicated topographical maps, a very complicated algorithm is needed, since the image generally involves such complicated patterns as symbols, characters, residential sections, rivers, railroads, etc. This paper describes a new feature extraction method based on the human optical neural field. We apply this method to extract complete set of road segments from topographical maps. The proposed method successfully extract road segments from various areas.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.125-130
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• 2006

In this study, tests of brain waves were carried out to investigate the driver's physiological characteristics by the change of the headlight. The participants were 20 men in their 20s and twenty-three different conditions in combinations of waveform of light, voltage, and alteration time were used. The measurement of the brain waves was performed by internationally standardized 10-20 method using LXE3232-RF. The results were analyzed by Power Spectrum Analysis using alpha-, and beta-wave and by the analysis of different brain domains using Brain wave Map. The results were as follows. 1. From the results of the Brain wave Map analysis, it was suggested that A waveform increases mental stress and B waveform affects mental and visual stress. The longer the stimulation time, the more stress level was detected. 2 The voltage alteration time of B waveform should be kept less than 1500msec, and the voltage should not fall below 11.5V.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.771-783
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• 2023

This study aims to compare the performance of each machine learning model for preparing a grid-based disaster risk map related to flooding in Jung-gu, Ulsan, for Typhoon Chaba which occurred in 2016. Dynamic data such as rainfall and river height, and static data such as building, population, and land cover data were used to conduct a risk analysis of flooding disasters. The data were constructed as 10 m-sized grid data based on the national point number, and a sample dataset was constructed using the risk value calculated for each grid as a dependent variable and the value of five influencing factors as an independent variable. The total number of sample datasets is 15,910, and the training, verification, and test datasets are randomly extracted at a 6:2:2 ratio to build a machine-learning model. Machine learning used random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN) techniques, and prediction accuracy by the model was found to be excellent in the order of SVM (91.05%), RF (83.08%), and KNN (76.52%). As a result of deriving the priority of influencing factors through the RF model, it was confirmed that rainfall and river water levels greatly influenced the risk.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.494-502
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• 2007

Ubiquitous location based services (u-LBS) will be interested to an important services. They can easily recognize object position at anytime, anywhere. At present, many researchers are making a study of the position recognition and tracking. This paper consists of postion recognition and user identification system. The position recognition is based on location under services (LBS) using a signal strength map, a database is previously made use of empirical measured received signal strength indicator (RSSI). The user identification system automatically controls instruments which is located in home. Moreover users are able to measures body signal freely. We implemented the multi-hop routing method using the Star-Mesh networks. Also, we use the sensor devices which are satisfied with the IEEE 802.15.4 specification. The used devices are the Nano-24 modules in Octacomm Co. Ltd. A RSSI is very important factor in position recognition analysis. It makes use of the way that decides position recognition and user identification in narrow indoor space. In experiments, we can analyze properties of the RSSI, draw the parameter about position recognition. The experimental result is that RSSI value is attenuated according to increasing distances. It also derives property of the radio frequency (RF) signal. Moreover, we express the monitoring program using the Microsoft C#. Finally, the proposed methods are expected to protect a sudden death and an accident in home.

• Investigative Magnetic Resonance Imaging
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• v.10 no.2
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• pp.108-116
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• 2006

Purpose : High-resolution spiral-scan imaging is performed at 3 Tesla MRI system. Since the gradient waveforms for the spiral-scan imaging have lower slopes than those for the Echo Planar Imaging (EPI), they can be implemented with the gradient systems having lower slew rates. The spiral-scan imaging also involves less eddy currents due to the smooth gradient waveforms. The spiral-scan imaging method does not suffer from high specific absorption rate (SAR), which is one of the main obstacles in high field imaging for rf echo-based fast imaging methods such as fast spin echo techniques. Thus, the spiral-scan imaging has a great potential for the high-speed imaging in high magnetic fields. In this paper, we presented various high-resolution images obtained by the spiral-scan methods at 3T MRI system for various applications. Materials and Methods : High-resolution spiral-scan imaging technique is implemented at 3T whole body MRI system. An efficient and fast higher-order shimming technique is developed to reduce the inhomogeneity, and the single-shot and interleaved spiral-scan imaging methods are developed. Spin-echo and gradient-echo based spiral-scan imaging methods are implemented, and image contrast and signal-tonoise ratio are controlled by the echo time, repetition time, and the rf flip angles. Results : Spiral-scan images having various resolutions are obtained at 3T MRI system. Since the absolute magnitude of the inhomogeneity is increasing in higher magnetic fields, higher order shimming to reduce the inhomogeneity becomes more important. A fast shimming technique in which axial, sagittal, and coronal sectional inhomogeneity maps are obtained in one scan is developed, and the shimming method based on the analysis of spherical harmonics of the inhomogeneity map is applied. For phantom and invivo head imaging, image matrix size of about $100{\times}100$ is obtained by a single-shot spiral-scan imaging, and a matrix size of $256{\times}256$ is obtained by the interleaved spiral-scan imaging with the number of interleaves of from 6 to 12. Conclusion : High field imaging becomes increasingly important due to the improved signal-to-noise ratio, larger spectral separation, and the higher BOLD-based contrast. The increasing SAR is, however, a limiting factor in high field imaging. Since the spiral-scan imaging has a very low SAR, and lower hardware requirements for the implementation of the technique compared to EPI, it is suitable for a rapid imaging in high fields. In this paper, the spiral-scan imaging with various resolutions from $100{\times}100$ to $256{\times}256$ by controlling the number of interleaves are developed for the high-speed imaging in high magnetic fields.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.34-45
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• 2021

Weather is one of the important factors in the agricultural industry as it affects the price, production, and quality of crops. Upland crops are directly exposed to the natural environment because they are mainly grown in mountainous areas. Therefore, it is necessary to provide accurate weather for upland crops. This study examined the effectiveness of 12 forest soil factors to interpolate the weather in mountainous areas. The daily temperature and precipitation were collected by the Korea Meteorological Administration between January 2009 and December 2018. The Generalized Additive Model (GAM), Kriging, and Random Forest (RF) were considered to interpolate. For evaluating the interpolation performance, automatic weather stations were used as training data and automated synoptic observing systems were used as test data for cross-validation. Unfortunately, the forest soil factors were not significant to interpolate the weather in the mountainous areas. GAM with only geography aspects showed that it can interpolate well in terms of root mean squared error and mean absolute error. The significance of the factors was tested at the 5% significance level in GAM, and the climate zone code (CLZN_CD) and soil water code B (SIBFLR_LAR) were identified as relatively important factors. It has shown that CLZN_CD could help to interpolate the daily average and minimum daily temperature for upland crops.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1119-1130
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• 2021

Urban flooding caused by localized heavy rainfall with unstable climate is constantly occurring, but a system that can predict spatial flood information with weather forecast has not been prepared yet. The worst flood situation in urban area can be occurred with difficulties of structural measures such as river levees, discharge capacity of urban sewage, storage basin of storm water, and pump facilities. However, identifying in advance the spatial flood information can have a decisive effect on minimizing flood damage. Therefore, this study presents a methodology that can predict the urban flood map in real-time by using rainfall data of the Korea Meteorological Administration (KMA), the results of two-dimensional flood analysis and random forest (RF) regression model. The Ujeong district in Ulsan metropolitan city, which the flood is frequently occurred, was selected for the study area. The RF regression model predicted the flood map corresponding to the 50 mm, 80 mm, and 110 mm rainfall events with 6-hours duration. And, the predicted results showed 63%, 80%, and 67% goodness of fit compared to the results of two-dimensional flood analysis model. It is judged that the suggested results of this study can be utilized as basic data for evacuation and response to urban flooding that occurs suddenly.

• Plant Breeding and Biotechnology
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• v.7 no.3
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• pp.272-286
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• 2019

Developing elite hybrid rice varieties is one important objective of rice breeding programs. Several genes related to male sterilities, restores, and pollinators have been identified through map-based gene cloning within natural variations of rice. These identified genes are good targets for introducing genetic traits in molecular breeding. This study was conducted to breed elite hybrid lines with major genes related to hybrid traits and disease/insect resistance in 240 genetic resources and F₁ hybrid combinations of rice. Molecular markers were reset for three major hybrid genes (S5, Rf3, Rf4) and thirteen disease/insect resistant genes (rice bacterial blight resistance genes Xa3, Xa4, xa5, Xa7, xa13, Xa21; blast resistance genes Pita, Pib, Pi5, Pii; brown planthopper resistant genes Bph18(t) and tungro virus resistance gene tsv1). Genotypes were then analyzed using molecular marker-assisted selection (MAS). Biological assay was then performed at the Red River Delta region in Vietnam using eleven F₁ hybrid combinations and two control vatieties. Results showed that nine F₁ hybrid combinations were highly resistant to rice bacterial blight and blast. Finally, eight F₁ hybrid rice varieties with resistance to disease/insect were selected from eleven F₁ hybrid combinations. Their characteristics such as agricultural traits and yields were then investigated. These F₁ hybrid rice varieties developed with major genes related to hybrid traits and disease/insect resistant genes could be useful for hybrid breeding programs to achieve high yield with biotic and abiotic resistance.