• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.63-70
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• 2019

Electric transmission towers are facilities to transport electrical power from a plant to an electrical substation. The towers are connected using wires considering the wire tension and the clearance from the ground or nearby objects. The wires are installed on a rights-of-way that is a strip of land used by electrical utilities to maintain the transmission line facilities. Trees and plants around transmission lines must be managed to keep the operation of these lines safe and reliable. This study proposed the use of a low-cost drone photogrammetry for the transmission line rights-of-way mapping. Aerial photogrammetry is carried out to generate a dense point cloud around the transmission lines from which a DSM (Digital Surface Model) and DTM (Digital Terrain Model) are created. The lines and nearby objects are separated using nDSM (normalized Digital Surface Model) and the noises are suppressed in the multiple image space for the geospatial analysis. The experimental result with drone images over two spans of transmission lines on a mountain area showed that the proposed method successfully generate the rights-of-way map with hazard nearby objects.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.237-245
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• 2022

The prominence of IoTs (Internet of Things) and exponential advancement of computer networks has resulted in massive essential applications. Recognizing various cyber-attacks or anomalies in networks and establishing effective intrusion recognition systems are becoming increasingly vital to current security. MLTs (Machine Learning Techniques) can be developed for such data-driven intelligent recognition systems. Researchers have employed a TFDNNs (Tensor Flow Deep Neural Networks) and DCNNs (Deep Convolution Neural Networks) to recognize pirated software and malwares efficiently. However, tuning the amount of neurons in multiple layers with activation functions leads to learning error rates, degrading classifier's reliability. HTFDNNs ( Hybrid tensor flow DNNs) and MRNs (Modified Residual Networks) or Resnet CNNs were presented to recognize software piracy and malwares. This study proposes HTFDNNs to identify stolen software starting with plagiarized source codes. This work uses Tokens and weights for filtering noises while focusing on token's for identifying source code thefts. DLTs (Deep learning techniques) are then used to detect plagiarized sources. Data from Google Code Jam is used for finding software piracy. MRNs visualize colour images for identifying harms in networks using IoTs. Malware samples of Maling dataset is used for tests in this work.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.4
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• pp.49-57
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• 2012

This paper presents a fast multiple-image-based deblurring method that decreases the computation loads in the image deblurring, enhancing the sharpness of the textures or edges of the restored images. First, two blurred images with some blurring artifacts and one noisy image including severe noises are consecutively captured under a relatively long and short exposures, respectively. To improve the processing speeds, the captured multiple images are downsampled at the ratio of two, and then a way of estimating the point spread function(PSF) based on the image or edge patches extracted from the whole images, is introduced. The method enables to effectively reduce the computation time taken in the PSF prediction. Next, the texture-enhanced image deblurring method of supplementing the ability of the texture representation degraded by the downsampling of the input images, is developed and then applied. Finally, to get the same image size as the original input images, an upsampling method of utilizing the sharp edges of the captured noisy image is applied. By using the proposed method, the processing times taken in the image deblurring, which is the main obstacle of its application to the digital cameras, can be shortened, while recovering the fine details of the textures or edge components.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.11-20
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• 1997

The passive noise control techniques used until now cancel the noise in terms of the characteristics of materials, which increase the mass and the dimension and have a limit that is effective only to attenuate the high frequency components of the noise. But the active noise control techniques developed in recent years have merits that they decrease the mass and the dimension and are effective to attenuating the low frequency noises. In this paper, the real-time active noise control system attenuating the engine booming noise in a car using the digital signal processing(DSP) techniques in terms of the principle of active noise control. The multiple-error filtered-x LMS(Least-Mean Square) algorithm is used as the adaptive algorithm for active noise control and is implemented using the DSP processor Motorola DSP56001 as a controller. According to the result that the experiments are performed for the engine as the RPM changes in a car, the noise attenuating performances are achieved in an overall car interior and is verified to be 20 dB higher for pure-tone and globally, 15 dB.

• Smart Structures and Systems
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• v.20 no.4
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• pp.427-440
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• 2017

One of the suitable structural damage detection methods using vibrational characteristics are damage-index-based methods. In this study, a damage index for identifying damages in plate structures using frequency response function (FRF) data has been provided. One of the significant challenges of identifying the damages in plate structures is high number of degrees of freedom resulting in decreased damage identifying accuracy. On the other hand, FRF data are of high volume and this dramatically decreases the computing speed and increases the memory necessary to store the data, which makes the use of this method difficult. In this study, FRF data are compressed using two-dimensional principal component analysis (2D-PCA), and then converted into damage index vectors. The damage indices, each of which represents a specific condition of intact or damaged structures are stored in a database. After computing damage index of structure with unknown damage and using algorithm of lookup tables, the structural damage including the severity and location of the damage will be identified. In this study, damage detection accuracy using the proposed damage index in square-shaped structural plates with dimensions of 3, 7 and 10 meters and with boundary conditions of four simply supported edges (4S), three clamped edges (3C), and four clamped edges (4C) under various single and multiple-element damage scenarios have been studied. Furthermore, in order to model uncertainties of measurement, insensitivity of this method to noises in the data measured by applying values of 5, 10, 15 and 20 percent of normal Gaussian noise to FRF values is discussed.

• Journal of Korean Society for Geospatial Information Science
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• v.3 no.1 s.5
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• pp.55-66
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• 1995

Most studies using satellite images have been performed to determine three dimensional positioning by stereoscopic analysis for stereo-pair or to extract digital elevation model by stereo matching using image correlation techniques. Because the small errors on the ground control points have a great impact on the results, however, it is hard to get reliable products when we analyze satellite orbital parameters or acquire digital elevation model by using only stereo-pair. Also, if there are noises, shadows, or clouds on the one of stereo pair, it is difficult to produce DEM(digital elevation model) on the area under analysis or to have good accuracy. In these case, it can be solved by systematic analysis of the multiple stereo images. This paper suggests the improvements on the accuracy of the digital elevation model by the developments of stereoscopic analysis techniques for the triplet of SPOT satellite images on the same area.

• Survey Research
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• v.11 no.2
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• pp.29-44
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• 2010

The aim of this study was to determine principal non-acoustical factors for noise annoyance in the vicinity of Kimpo Airport in Seoul, Korea. Noise annoyance was estimated using self-reported annoyance scale. We have conducted a social survey aiming to identify the main sound sources, evaluate the annoyance and analyse the main effects of noise on people. Acoustical and non-acoustical variables are expected to greatly affect annoyance responses. This study divided acoustical variables into aircraft, road traffic and neighboring noises, and non-acoustical variables into demographic, situational and attitudinal variables. The study performed multiple regression analysis to determine the influences each variable has on annoyance responses. Acoustical variables affect noise annoyance to aircraft and neighboring noise except road traffic noise. For road traffic and neighboring noise annoyance was affected by non-acoustical variable, insulation by housing type. For aircraft noise, main noise source of this area, annoyance was affected by acoustical variable and some non-acoustical variables, mainly exposure time.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.4
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• pp.97-105
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• 2016

Radiography image detector produces digital images by collecting the charges from the incident x-ray photons and converting it to the voltage signals and then the digital signals. The fixed-pattern noise from the nonuinform amplifier gains in the employed multiple readout circuits. In order to correct the nonuniform gains, a gain-correction technique which is based on the gain map is conventionally used. Since the photon noise remains in the designed gain map, the noise contaminates the gain-corrected images. In this paper, experimental observations are conducted for filtering the remained noise in the gain map, and a filter optimization algorithm is proposed to efficiently remove the noise. For acquired x-ray images from detectors, the filtered gain maps are evaluated and it is shown that optimization algorithm can improve the filtering performance even for relatively strong fixed-pattern noises, which cannot be removed by a simple filter.

• Journal of the Korean Society of Radiology
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• v.2 no.1
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• pp.23-29
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• 2008

The present study proposed a method that dissolves ultrasonographic images into multiple resolutions using wavelet conversion and a boundary detection filter and improves the quality of ultrasonographic images through boundary detection filtering. In order to reduce noises and strengthen edges, the proposed method adjusted selectivity coefficient by area step by step from a low resolution image obtained from wavelet converted images to a high resolution image and performed edge filtering in consideration of direction. Through this method, we generated a selective low pass filtering effect in areas except edges by decreasing the wavelet coefficient for pixels in spot areas, improved continuity by smoothing edges in the tangential direction, and enhanced contrast by thinning in the normal direction. Through an experiment, we compared the filtering method using a non linear anisotropic expansion model and the filtering method using wavelet contraction structure in single resolution.

• 한국지형공간정보학회:학술대회논문집
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• 1995.10a
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• pp.99-119
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• 1995

Most studies using satellite images have been performed to determine three dimensional positioning by stereoscopic analysis for stereo-pair or to extract digital elevation model by stereo matching using image correlation techniques. Because the small errors on the ground control points have a great impact on the results, honorer, it is hard to get reliable products when we analyze satellite orbital parameters or acquire digital elevation model by using only stereo-pair. Also, if there are noises, shadows, or clouds on the one of stereo pair, it is difficult to produce DEM(digital elevation model) on the area under analysis or to have good accuracy. In these case, it can be solved by systematic analysis of the multiple stereo images. This paper suggests the improvements on the accuracy of the digital elevation model by the developments of stereoscopic analysis techniques for the triplet of SPOT satellite images on the same area.