• Journal of electromagnetic engineering and science
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• v.18 no.2
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• pp.78-87
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• 2018

This paper describes specular reflectance measurements of dielectric plates in three waveguide frequency bands: D-band (110-170 GHz), G-band (140-220 GHz), and J-band (220-325 GHz). The transmit (Tx) part of the proposed specular reflectance measurement system is stationary, while the receive (Rx) part and the material under test (MUT) holder are concentric-rotating with a 2:1 speed ratio for specular reflectance measurements. In specular reflectance measurements, the first step measures the specular reflection coefficients of an MUT and a metal plate on the MUT holder located at the center of the Tx and Rx parts, and the second step calculates the specular reflectance defined by the specular reflection power (i.e., intensity) of the MUT normalized to that of the metal plate. Multiple reflection effects between the Tx and Rx antennas and the MUT on the measured specular reflectance are minimized by averaging out the multiple specular reflectances measured with changing the separation distance between the two antennas by ${\lambda}/8$ intervals. Measurement results of the perpendicular-polarized specular reflectance of commonly used dielectric plates are verified by comparing those with the analytic results and show that the results measured over the overlapped frequency range of the D-/G-bands and at the boundary frequency of the G-/J-bands agree well with the results for the other band, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1549-1557
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• 1999

In this paper, we propose a face recognition algorithm based on the differential image method-DCT This algorithm uses neural networks which is flexible for noise. Using the same condition (same luminous intensity and same distance from the fixed CCD camera to human face), we have captured two images. One doesn't contain human face. The other contains human face. Differential image method is used to separate the second image into face region and background region. After that, we have extracted square area from the face region, which is based on the edge distribution. This square region is used as the characteristics region of human face. It contains the eye bows, the eyes, the nose, and the mouth. After executing DCT for this square region, we have extracted the feature vectors. The feature vectors were normalized and used as the input vectors of the neural network. Simulation results show 100% recognition rate when face images were learned and 92.25% recognition rate when face images weren't learned for 30 persons.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.71-81
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• 1995

The purpose of this research were to find ways to detect ecotone between the Mt. Pukhansan National Park and adjacent urban residential areas, to measure the width and size of ecotone around the park, and to investigate temporal change of ecotone around the Park. Normalized Difference Vegetation Index(NDVI) derived from TM data (May of 1985, 1987, and 1993) and the analytical capabilities of GIS were used to investigate the impacts of human activities inside of and outside of the boundary of the park. Major findings of the study can be summarized as follows: First, ecotone around the boundary of the national park could be identified from NDVI-distance curves derived by a series of buffering operations with a GIS. Second, average width of ecotone around the park was nealy doubled during 1985-1993 period. Third, NDVI vaules of the park were about 14 percent higher than those of surrounding areas. Finally, it seems that the expansion of the ecotone of the park is related to heavy trampling of visitors and various types of environmental pollution of the adjacent urban areas.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.537-552
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• 2019

Purpose: The development of information technology makes it easy to utilize high-dimensional categorical data. In this regard, the purpose of this study is to propose a novel method to select the proper categorical variables in high-dimensional categorical data. Methods: The proposed feature selection method consists of three steps: (1) The first step defines the goodness-to-pick measure. In this paper, a categorical variable is relevant if it has relationships among other variables. According to the above definition of relevant variables, the goodness-to-pick measure calculates the normalized conditional entropy with other variables. (2) The second step finds the relevant feature subset from the original variables set. This step decides whether a variable is relevant or not. (3) The third step eliminates redundancy variables from the relevant feature subset. Results: Our experimental results showed that the proposed feature selection method generally yielded better classification performance than without feature selection in high-dimensional categorical data, especially as the number of irrelevant categorical variables increase. Besides, as the number of irrelevant categorical variables that have imbalanced categorical values is increasing, the difference in accuracy between the proposed method and the existing methods being compared increases. Conclusion: According to experimental results, we confirmed that the proposed method makes it possible to consistently produce high classification accuracy rates in high-dimensional categorical data. Therefore, the proposed method is promising to be used effectively in high-dimensional situation.

• Journal of the Korean Solar Energy Society
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• v.36 no.1
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• pp.11-18
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• 2016

The local wind systems in the Pohang region were categorized into wind sectors. Still, thorough knowledge of wind resource assessment, wind environment analysis, and atmospheric environmental impact assessment was required since the region has outstanding wind resources, it is located on the path of typhoon, and it has large-scale atmospheric pollution sources. To overcome the resolution limitation of meteorological dataset and problems of categorization criteria of the preceding studies, the high-resolution wind resource map of the Korea Institute of Energy Research was used as time-series meteorological data; the 2-step method of determining the clustering coefficient through hierarchical clustering analysis and subsequently categorizing the wind sectors through non-hierarchical K-means clustering analysis was adopted. The similarity of normalized time-series wind vector was proposed as the Euclidean distance. The meteor-statistical characteristics of the mean vector wind distribution and meteorological variables of each wind sector were compared. The comparison confirmed significant differences among wind sectors according to the terrain elevation, mean wind speed, Weibull shape parameter, etc.

• Physical Therapy Rehabilitation Science
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• v.10 no.4
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• pp.503-511
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• 2021

Objective: This study compared pain, muscle power (MP), muscle thickness (MT), and normalized position of the scapula (POS) between general physical therapy and general physical therapy with strengthening exercises of the lower trapezius in patients with rounded shoulder and chronic neck pain. Design: Randomized controlled trial. Methods: The participants were 30 patients of W hospital in Gangnamgu, Seoul, with rounded shoulders who were diagnosed with chronic neck pain. Rounded shoulder was defined as a distance between the surface and acromion of >1 inch in the supine position. The participants were assigned to an experimental group (n=15) and a control group (n=15). The experimental group completed four types of strengthening exercises program for 15 minutes, twice weekly, for a total of 5 weeks. Soft tissue mobilization (STM), cervical extension flexion rotation (CEFR), and physical modality were also performed in both groups. Results: The degree of pain was assessed using the numerical rating scale (NRS), MP was measured a handheld dynamometer, MT was measured by ultrasound, and POS was measured using a tapeline. Significant between-group differences were observed in VAS, MP, MP, and POS. Significant changes were observed in the experimental group for VAS, MP, MT, and POS. Conclusions: Based on the results of this study, it was indicated that lower trapezius strengthening exercises performed together with general physical therapy was significantly improved in pain, MP, MT, and POS in patients with rounded shoulder and chronic neck pain compared to when general physical therapy was performed alone.

• Physical Therapy Rehabilitation Science
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• v.8 no.3
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• pp.125-133
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• 2019

Objective: To compare the postural control between non-specific chronic low back pain (NSCLBP) subgroups and healthy people during dynamic balance performance using a modified Star Excursion Balance Test (mSEBT). Design: Cross-sectional study. Methods: Eighteen NSCLBP subjects (9 active extension pattern [AEP], 9 flexion pattern [FP]), and 10 healthy controls were enrolled in this study. All subjects performed mSEBT on their dominant leg on a force plate. Normalized reach distance and balance parameters, including the center of pressure (COP) displacement and velocity, were recorded. Results: There were significant differences in mean reach distances in both posterolateral and posteromedial (PM) reach directions between AEP and healthy subjects (p<0.001) and between FP and healthy subjects (p<0.001). However, there were no significant differences among the three groups in the anterior reach direction. Also, the results showed no significant differences in mean COP variables (velocity and displacement) between pooled NSCLBP and healthy subjects. However, the subjects were reclassified into AEP, FP and healthy groups and the results showed a significant difference in mean COP velocity in the PM direction between AEP and FP subjects (p=0.048), and between AEP and healthy subjects (p=0.024). Conclusions: The findings in this study highlight the heterogeneity of the individuals with NSCLBP and the importance of identifying the homogenous subgroups. Individuals with AEP and FP experience deficits in dynamic postural control compared to healthy controls. In addition, the findings of this study support the concept of the Multidimensional Classification System.

• Geomechanics and Engineering
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• v.18 no.1
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• pp.11-20
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• 2019

The purpose of this study was to propose a new approach for quantifying in situ rock mass damage, which would include a degree-of-damage and the degraded strength of a rock mass, along with its prediction based on real-time Acoustic Emission (AE) observations. The basic approach for quantifying in-situ rock mass damage is to derive the normalized value of measured AE energy with the maximum AE energy, called the degree-of-damage in this study. With regard to estimation of the AE energy, an AE crack source location algorithm of the Wigner-Ville Distribution combined with Biot's wave dispersion model, was applied for more reliable AE crack source localization in a rock mass. In situ AE wave attenuation was also taken into account for AE energy correction in accordance with the propagation distance of an AE wave. To infer the maximum AE energy, fractal theory was used for scale-independent AE energy estimation. In addition, the Weibull model was also applied to determine statistically the AE crack size under a jointed rock mass. Subsequently, the proposed methodology was calibrated using an in situ test carried out in the Underground Research Tunnel at the Korea Atomic Energy Research Institute. This was done under a condition of controlled incremental cyclic loading, which had been performed as part of a preceding study. It was found that the inferred degree-of-damage agreed quite well with the results from the in situ test. The methodology proposed in this study can be regarded as a reasonable approach for quantifying rock mass damage.

• Structural Monitoring and Maintenance
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• v.9 no.1
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• pp.43-57
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• 2022

One of the instances which demand structural engineer's greatest attention and upgradation is the changing live load requirement in bridge design code. The challenge increases in developing countries as the pace of infrastructural growth is being catered by the respective country codes with bigger and heavier vehicles to be considered in the design. This paper presents the case study of India where Indian Roads Congress (IRC) codes in its revised version from 2014 to 2017 introduced massive Special vehicle (SV) around 40 m long and weighing 3850 kN to be considered in the design of road bridges. The code does not specify the minimum distance between successive special vehicles unlike other loading classes and hence the consequences of it form the motivation for this study. The effect of SV in comparison with Class 70R, Class AA, Class A, and Class B loading is studied based on the maximum bending moment with moving load applied in Autodesk Robot Structural Analysis. The spans considered in the analysis varied from 10 m to 1991 m corresponding to the span of Akashi Kaikyo Bridge (longest bridge span in the world). A total of 182 analyses for 7 types of vehicles (class B, class A, class 70R tracked, class 70R wheeled, class AA tracked, AA wheeled, and Special vehicle) on 26 different span lengths is carried out. The span corresponding to other vehicles which would equal the bending moment of a single SV is presented along with a comparison relative to Standard Uniformly Distributed Load. Further, the results are presented by introducing a new parameter named Intensity Factor which is proven to relate the effect of axle spacing of vehicle on the normalized bending moment developed.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.164-164
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• 2023

This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.