• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.6
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• pp.546-554
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• 2015

Ultra-wideband(UWB) radar is widely used in many penetration radar applications, such as ground-penetrating radar and foliage-penetrating radar, because it has many advantages in detecting concealed objects. One type of UWB radar system is random noise radar, which many be robust to jamming environment. However conventional random noise radar requires high-speed analog-to-digital convertor(ADC) for matched filtering. In this thesis, a pseudo-random noise radar system that maintains anti-jamming characteristics but does not require high-speed ADC is researched. and The UWB system is implemented in a low frequency system, and its performance has been demonstrated by experiment, which proves the concept of the proposed pseudo-random noise radar system.

• Journal of Auto-vehicle Safety Association
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• v.9 no.2
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• pp.6-12
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• 2017

An autonomous driving system based on a precise digital map is developed. The system is implemented to the Hyundai's Tucsan fuel cell car, which has a camera, smart cruise control (SCC) and Blind spot detection (BSD) radars, 4-Layer LiDARs, and a standard GPS module. The precise digital map has various information such as lanes, speed bumps, crosswalks and land marks, etc. They can be distinguished as lane-level. The system fuses sensed data around the vehicle for localization and estimates the vehicle's location in the precise map. Objects around the vehicle are detected by the sensor fusion system. Collision threat assessment is performed by detecting dangerous vehicles on the precise map. When an obstacle is on the driving path, the system estimates time to collision and slow down the speed. The vehicle has driven autonomously in the Hyundai-Kia Namyang Research Center.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.405-416
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• 2019

Due to the development of information and communication technology, the production and processing speed of data is getting faster. To classify objects using machine learning, which is a field of artificial intelligence, data required for training can be easily collected due to the development of internet and geospatial information technology. In the field of geospatial information, machine learning is also being applied to classify or recognize objects using images and point clouds. In this study, the problem of manually constructing training data using existing digital map version 1.0 was improved, and the technique of classifying roads, buildings and vegetation using image and point clouds were proposed. Through experiments, it was possible to classify roads, buildings, and vegetation that could clearly distinguish colors when using true ortho-image with only RGB (Red, Green, Blue) bands. However, if the colors of the objects to be classified are similar, it was possible to identify the limitations of poor classification of the objects. To improve the limitations, random forest and support vector machine techniques were applied after band fusion of true ortho-image and normalized digital surface model, and roads, buildings, and vegetation were classified with more than 85% accuracy.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.1-10
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• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• Wind and Structures
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• v.19 no.2
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• pp.145-167
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• 2014

Wind-vehicle-bridge (WVB) interaction can be regarded as a coupled vibration system. Aerodynamic forces and moment on vehicles and bridge decks play an important role in the vibration analysis of the coupled WVB system. High-speed vehicle motion has certain effects on the aerodynamic characteristics of a vehicle-bridge system under crosswinds, but it is not taken into account in most previous studies. In this study, a new testing system with a moving vehicle model was developed to directly measure the aerodynamic forces and moment on the vehicle and bridge deck when the vehicle model moved on the bridge deck under crosswinds in a large wind tunnel. The testing system, with a total length of 18.0 m, consisted of three main parts: vehicle-bridge model system, motion system and signal measuring system. The wind speed, vehicle speed, test objects and relative position of the vehicle to the bridge deck could be easily altered for different test cases. The aerodynamic forces and moment on the moving vehicle and bridge deck were measured utilizing the new testing system. The effects of the vehicle speed, wind yaw angle, rail track position and vehicle type on the aerodynamic characteristics of the vehicle and bridge deck were investigated. In addition, a data processing method was proposed according to the characteristics of the dynamic testing signals to determine the variations of aerodynamic forces and moment on the moving vehicle and bridge deck. Three-car and single-car models were employed as the moving rail vehicle model and road vehicle model, respectively. The results indicate that the drag and lift coefficients of the vehicle tend to increase with the increase of the vehicle speed and the decrease of the resultant wind yaw angle and that the vehicle speed has more significant effect on the aerodynamic coefficients of the single-car model than on those of the three-car model. This study also reveals that the aerodynamic coefficients of the vehicle and bridge deck are strongly influenced by the rail track positions, while the aerodynamic coefficients of the bridge deck are insensitive to the vehicle speed or resultant wind yaw angle.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.523-530
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• 2014

Machine material and structural strain are critical factors for appraising mechanical properties and safety. Particularly in three and four-point bending tests, which appraise the deflection and flexural strain of an object due to external force, measurements are made by the crosshead movement or deflection meter of a universal testing machine. The Digital Image Correlation (DIC) method is one of the non-contact measurement methods. It uses the image analyzing method that compares the reference image with the deformed image for measuring the displacement and strain of the objects caused by external force. Accordingly, the advantage of this method is that the object's surface roughness, shape, and temperature have little influence. However, its disadvantage is that it requires extensive time to compare the reference image with the deformed image for measuring the displacement and strain. In this study, an algorithm is developed for DIC that can improve the speed of image analysis for measuring the deflection and strain of an object caused by a three-point bending load. To implement this algorithm for improving the speed of image analysis, LabVIEW 2010 was used. Furthermore, to evaluate the accuracy of the developed fast correlation algorithm, the deflection of an aluminum specimen under a three-point bending load was measured by using the universal test machine and DIC measurement system.

• Physical Therapy Korea
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• v.30 no.3
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• pp.202-210
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• 2023

Background: The elderly population is increasing rapidly worldwide. Muscle mass, usual walking speed (UWS), knee extension strength (KES), hand grip strength (HGS), peak expiratory flow (PEF), and depression is used for sarcopenia diagnosis. All four of these factors (KES, HGS, PEF, and depression) correlated with UWS and also to muscle mass. But, many studies have suggested that no correlation exists between muscle mass and UWS. Objects: This study aimed: 1) to investigate whether muscle mass reduction affected UWS, as mediated by KES, HGS, PEF and depression, and 2) to explored whether significant changes in these mediators varied by the body segment in which muscle mass evaluated in elderly female aged 65-80 years. Methods: A total of 100 female aged 65-80 years were surveyed. Muscle mass was measured by body segment (upper and lower segment), and KES, HGS, PEF, depression, and UWS were also assessed. Median analyses were progressed in IBM SPSS software (ver. 23.0, IBM Co.) using a downloaded INDIRECT macro. Results: The direct effect of the KES and PEF were significant, and the indirect effect of KES and PEF were not significant. Thus, KES and PEF served as full mediators of the effect of muscle mass on UWS. Regardless of bodily region, KES and PEF combined with muscle mass were significant mediators of UWS, with similar indirect effect sizes. Conclusion: KES and PEF are the only mediators regardless of body part. Therefore, mediating the KES and PEF may prevent sarcopenia progression in elderly female. Also, sarcopenia can be readily assessed by evaluating either the upper or lower body; it is not necessary to measure total muscle mass.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3C
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• pp.255-261
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• 2008

Conventional look-up table(LT) has gained a lot of speed increase in generation of digital holograms for 3D objects, but it has required an enormous memory size of the LT. In this paper, a novel approach to dramatically reduce the size of the conventional LT, still keeping its advantage of fast computational speed is proposed, which is called here a N-LT(novel look-up table) method. In the proposed method, only the fringe patterns of the center points on each image plane are pre-calculated, called elemental fringe patterns and stored in the look-up table. Then, the fringe patterns for other object points on each image plane can be obtained by simply shifting this pre-calculated elemental fringe pattern according to the displaced values from the center to those points and adding them together. Some experimental results revealed that the computational speed and the required memory size of the proposed approach are found to be 48.7 times faster than that of the ray-tracing method and 217 times smaller than that of the conventional LT method, respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.66-77
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• 2014

UTIS(Urban Traffic Information System) directly collects link travel time in urban area by using probe vehicles. Therefore it can estimate more accurate link travel speed compared to other traffic detection systems. However, UTIS includes some missing data caused by the lack of probe vehicles and RSEs on road network, system failures, and other factors. In this study, we suggest a new model, based on k-NN algorithm, for imputing missing data to provide more accurate travel time information. New imputation model is an adaptive k-NN which can flexibly adjust the number of nearest neighbors(NN) depending on the distribution of candidate objects. The evaluation result indicates that the new model successfully imputed missing speed data and significantly reduced the imputation error as compared with other models(ARIMA and etc). We have a plan to use the new imputation model improving traffic information service by applying UTIS Central Traffic Information Center.