• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.107-116
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• 2015

In compliance with digital device growth, the proliferation of high-tech computers, the availability of high quality and inexpensive video cameras, the demands for automated video analysis is increasing, especially in field of intelligent monitor system, video compression and robot vision. That is why object tracking of computer vision comes into the spotlight. Tracking is the process of locating a moving object over time using a camera. The consideration of object's scale, rotation and shape deformation is the most important thing in robust object tracking. In this paper, we propose a robust object tracking scheme using Random Forest. Specifically, an object detection scheme based on region covariance and ZNCC(zeros mean normalized cross correlation) is adopted for estimating accurate object location. Next, the detected region will be divided into five regions for random forest-based learning. The five regions are verified by random forest. The verified regions are put into the model pool. Finally, the input model is updated for the object location correction when the region does not contain the object. The experiments shows that the proposed method produces better accurate performance with respect to object location than the existing methods.

• Physical Therapy Korea
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• v.12 no.3
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• pp.22-30
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• 2005

This study was designed to identify the effect of various decline boards and postures of lower extremities on surface electromyographic (EMG) activity of knee muscles during isometric single-leg decline squat exercises. The subjects were twenty young male adults who had not experienced any knee injury and their Q-angles were within a normal range. They were asked to perform single-leg decline squat exercises in five various conditions. The EMG activities of the gluteus maximus (GM), vastus lateralis (VL), vastus medialis (VMO), tibialis anterior (TA), and gastrocnemius (GCM) muscles were recorded in five various single-leg decline squat exercises by surface electrodes and normalized by maximal voluntary isometric contraction (MVIC) values. The normalized EMG activity levels were compared using one-way ANOVA with repeated measures. The results of this study were as follows: 1) Exercises 2 and 4 produced significantly greater EMG activity of VMO than did exercise 1 ($p_{adj}$<.05/10), 2) The VMO/VL ratio of EMG activity of exercise 4 was the highest, producing a significantly greater ratio than exercise 1 ($p_{adj}$<.05/10). These results show that single-leg lateral oblique decline squat exercise is the best exercise for selective strengthening of VMO, and the posture of the contralateral leg does also affect strengthening of VMO, but we'll need to research patellofemoral joint compression for clinical application of single-leg lateral oblique decline squat exercises.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.4
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• pp.1-9
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• 2015

The development of drought index that provides detailed-spatial-resolution drought information is essential for improving drought planning and preparedness. The objective of this study was to develop the concept of using satellite-based hybrid drought index called the Vegetation Drought Response Index in South Korea (VegDRI-SKorea) that could improve spatial resolution for monitoring local and regional drought. The VegDRI-SKorea was developed using the Classification And Regression Trees (CART) algorithm based on remote sensing data such as Normalized Difference Vegetation Index (NDVI) from MODIS satellite images, climate drought indices such as Self Calibrating Palmer Drought Severity Index (SC-PDSI) and Standardized Precipitation Index (SPI), and the biophysical data such as land cover, eco region, and soil available water capacity. A case study has been done for the 2012 drought to evaluate the VegDRI-SKorea model for South Korea. The VegDRI-SKorea represented the drought areas from the end of May and to the severe drought at the end of June. Results show that the integration of satellite imageries and various associated data allows us to get improved both spatially and temporally drought information using a data mining technique and get better understanding of drought condition. In addition, VegDRI-SKorea is expected to contribute to monitor the current drought condition for evaluating local and regional drought risk assessment and assisting drought-related decision making.

• Korean Journal of Remote Sensing
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• v.32 no.4
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• pp.353-364
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• 2016

Yangon city is experienced a rapid urban expansion over the last two decades due to accelerate with the socioeconomic development. This research work studied an investigation into the application of the integration of the Remote Sensing (RS) and Geographic Information System (GIS) for observing Land Use and Land Cover (LULC) patterns and evaluate its impact on Land Surface Temperature (LST) of the downtown, suburban 1 and suburban 2 of Yangon city. The main purpose of this paper was to examine and analyze the variation of the spatial distribution property of the LULC of urban spatial information related with the LST and Normalized Difference Vegetation Index (NDVI) using RS and GIS. This paper was observed on image processing of LULC classification, LST and NDVI were extracted from Landsat 8 Operational Land Imager (OLI) image data. Then, LULC pattern was linked with the variation of LST data of the Yangon area for the further connection of the correlation between surface temperature and urban structure. As a result, NDVI values were used to examine the relation between thermal behavior and condition of land cover categories. The spatial distribution of LST has been found mixed pattern and higher LST was located with the scatter pattern, which was related to certain LULC types within downtown, suburban 1 and 2. The result of this paper, LST and NDVI analysis exhibited a strong negative correlation without water bodies for all three portions of Yangon area. The strongest coefficient correlation was found downtown area (-0.8707) and followed suburban 1 (-0.7526) and suburban 2(-0.6923).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.10
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• pp.907-913
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• 2015

This work presents a method to predict the near magnetic field distribution on the digital switching circuit mounted on PCB using co-simulation of circuit and electromagnetic fields. The proposed method first obtains the normalized near field distribution by exciting the signal and power ports of the switching circuit using sinusoidal sources. Then the real near magnetic field distribution is determined by weighting the normalized field distribution using the current spectrum of the switching circuit. To confirm the proposed method, a switching IC with a ring oscillator and a output buffer is fabricated and measured in the form of chip-on-board. The surface magnetic field distribution is measured using a magnetic probe above the PCB and compared with the simulation results. Experimental results show the correspondence between simulation and measurement results within 10 dB up to fifth harmonics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4549-4567
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• 2016

To cope with the complex electromagnetic environment of wireless communication systems, anti-jamming decision methods are necessary to keep the reliability of communication. Basing on the rule-reduced genetic algorithm (RRGA), an anti-jamming decision method is proposed in this paper to adapt to the fast channel variations. Firstly, the reduced decision rules are obtained according to the rough set (RS) theory. Secondly, the randomly generated initial population of the genetic algorithm (GA) is screened and the individuals are preserved in accordance with the reduced decision rules. Finally, the initial population after screening is utilized in the genetic algorithm to optimize the communication parameters. In order to remove the dependency on the weights, this paper deploys an anti-jamming decision objective function, which aims at maximizing the normalized transmission rate under the constraints of minimizing the normalized transmitting power with the pre-defined bit error rate (BER). Simulations are carried out to verify the performance of both the traditional genetic algorithm and the adaptive genetic algorithm. Simulation results show that the convergence rates of the two algorithms increase significantly thanks to the initial population determined by the reduced-rules, without losing the accuracy of the decision-making. Meanwhile, the weight-independent objective function makes the algorithm more practical than the traditional methods.

• Korean Journal of Remote Sensing
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• v.33 no.6_3
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• pp.1233-1242
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• 2017

In this study, we tried to analyze deforestation due to forest fire by using KOMPSAT satellite imagery. For deforestation analysis, unsupervised change detection algorithm is applied to multitemporal images. Through ITPCA (ITerative Principal Component Analysis) of NDVI (Normalized Difference Vegetation Index) generated from multitemporal satellite images before and after forest fire, changed areas due to deforestation are extracted. In addition, a post-processing method using SRTM (Shuttle Radar Topographic Mission) data is involved in order to minimize the error of change detection. As a result of the experiment using KOMPSAT-2 and 3 images, it was confirmed that changed areas due to deforestation can be efficiently extracted.

• Journal of Environmental Science International
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• v.19 no.8
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• pp.983-999
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• 2010

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.4 no.2
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• pp.36-44
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• 2001

The main purpose of this study was to classify forest vegetation effectively using Landsat Thematic Mapper data(June, 1994) in mountainous region. The research area was the Mt. Wolak Experimental Forest of Chungbuk National University, near Chungju and Jecheon city, Chungcheongbuk-do. To classify forest vegetation effectively, Normalized Difference Vegetation Index(NDVI) was used to reduce topographic effects. This NDVI was modified and transformed to the value of 0 to 255, and then the modified values were combined with other Landsat Thematic Mapper bands. To classify forest and land cover types, unsupervised classification method was used. The results of this study are summarized as follows. 1. Combinations of band "3, 5, NDVI" in Landsat Thematic Mapper data showed a good separation with high accuracy. The expected classification accuracy was 95.1% in Landsat Thematic Mapper data. 2. The Land Cover types were classified into six groups : coniferous forest, deciduous forest, mixed forest, paddy and grass, non-forest, and other undetectable areas. As these classified results were compared with the reconnaissance survey and aerial black and white infrared photographs, the overall classification accuracy was 76.5% in Landsat Thematic Mapper data. 3. The portion of non-forest in Mt. Wolak area was 1.9%. The percentages of coniferous, deciduous and mixed forests were 30.9%, 35.7% and 26.4%, respectively. 4. As these classified results were compared with other reference data, the percentages of coniferous, deciduous and mixed forests increased, but the portion of non-forest was exceedingly diminished. These differences are thought to be from the different research method and the different season of received Landsat Thematic Mapper data.

• The Korean Journal of Physiology and Pharmacology
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• v.3 no.6
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• pp.605-613
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• 1999

The purpose of the present study was to evaluate cardiovascular regulation during passive standing (PS) after ethanol ingestion by spectral analysis of heart rate variability (HRV) in flushed and nonflushed subjects. Of 24 young male subjects, 8 belonged to flushed group (F) and 16 to nonflushed group (NF). Two sessions of 10-min PS were performed before and after ethanol (0.5 g/kg) ingestion. Powers of R-R interval variability in very low frequency $(VLF,\;0{\sim}0.05\;Hz),$ low frequency $(LF,\;0.05{\sim}0.15\;Hz)$ and high frequency $(HF,\;0.15{\sim}0.50\;Hz)$ bands, normalized powers (LFn and HFn) and LF/HF ratio were obtained. After ethanol ingestion, F showed higher heart rate than NF. PS increased LFn $(+22.9{\pm}3.6\;in\;NF,\;+12.8{\pm}4.7$ in F, in normalized units) and LF/HF $(+3.10{\pm}0.57\;in\;NF,\;+3.00{\pm}1.08\;in\;F)$ and decreased HFn powers. Ethanol ingestion increased LFn and LF/HF and decreased HFn. PS after ethanol resulted in higher LFn and LF/HF and lower HFn than the prior PS. F showed a greater and more sustained HRV change than NF after ethanol. In conclusion, PS or ethanol ingestion increased LFn and LF/HF and decreased HFn. Flushed subjects showed an accentuated HRV response to ethanol.