• Tunnel and Underground Space
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• v.27 no.1
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• pp.58-68
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• 2017

According to the development of optical technology, the capacity of LIDAR equipments has been greatly improved to get rock mass characteristics precisely and accurately enough and it has been lightened and popularized so that it can be easily used in the field. In this study, we examined the applicability of roughness measurement for joints in a rock slope using LIDAR technique. A triangular irregular network was constructed using LIDAR and a patch, which is a plane structure of discontinuity on rock mass measured from LIDAR scanning, was extracted to estimate the roughness of the rock slope. Four different kinds of roughness parameters were analyzed to find out their correlation with JRC for various point intervals. Among them, $R_s$ parameter was used to measure the roughness of a patch. Regression analysis between four roughness parameters and JRC with respect to point interval was performed. All the roughness parameters decreased with the increase of point interval. In addition, the parameter value showed greater decrease for rougher surfaces. A method of roughness measurement using $R_s$ parameter on rock slope discontinuities was suggested which showed slight overestimation of the real roughness value.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.5
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• pp.585-597
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• 2009

This research aims to develop a registration method to remove the geometric inconsistency between aerial images and LIDAR data acquired from an airborne multi-sensor system. The proposed method mainly includes registration primitives extraction, correspondence establishment, and EOP(Exterior Orientation Parameters) adjustment. As the registration primitives, we extracts planar patches and intersection edges from the LIDAR data and object points and linking edges from the aerial images. The extracted primitives are then categorized into horizontal and vertical ones; and their correspondences are established. These correspondent pairs are incorporated as stochastic constraints into the bundle block adjustment, which finally precisely adjusts the exterior orientation parameters of the images. According to the experimental results from the application of the proposed method to real data, we found that the attitude parameters of EOPs were meaningfully adjusted and the geometric inconsistency of the primitives used for the adjustment is reduced from 2 m to 2 cm before and after the registration. Hence, the results of this research can contribute to data fusion for the high quality 3D spatial information.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.541-547
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• 2019

Recent developments in hacking technology are continuing to increase the number of new security vulnerabilities. Approximately 80,000 new vulnerabilities have been registered in the Common Vulnerability Enumeration (CVE) database, which is a representative vulnerability database, from 2010 to 2015, and the trend is gradually increasing in recent years. While security vulnerabilities are growing at a rapid pace, responses to security vulnerabilities are slow to respond because they rely on manual analysis. To solve this problem, there is a need for a technology that can automatically detect and patch security vulnerabilities and respond to security vulnerabilities in advance. In this paper, we propose the technology to extract the features of the vulnerability-discovery target binary through complexity analysis, and select a vulnerability-discovery strategy suitable for the feature and automatically explore the vulnerability. The proposed technology was compared to the AFL, ANGR, and Driller tools, with about 6% improvement in code coverage, about 2.4 times increase in crash count, and about 11% improvement in crash incidence.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.665-669
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• 2018

In this paper, we design an antenna for LTE / Wi-Fi communication that operates in 2.65 GHz and 5 GHz band for small-sized broadband communication antenna that can be used in the sea. Microstrip patch antennas were chosen to improve the bandwidth. The slot width, length, and transmission line width were calculated using the theoretical formula for each step. In addition, we designed a microstrip antenna using CST Microwave Studio 2014 program that can design 3D. Simulation results show that the reflection lossis -12.712 dB at 2.65 GHz and -16.583 dB at 5 GHz. The gain was 1.738 dBi at 2.65 GHz and 3.284 dBi at 5 GHz. In this paper, we propose a dual-band antenna for LTE / Wi-Fi, which can be used in maritime environments, which is worse than terrestrial communication, because of differences in communication speed and communication stability compared with those used on land.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.35-40
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• 2022

This paper proposes an antenna that is located outside the PCB substrate of an electronic product to enable wireless communication in the ISM band. The PCB designed the T-shaped OPEN-STUB power supply line to be miniaturized so that it does not interfere with parts or interfere with design. The characteristics of the antenna were confirmed in the 2.4GHz and 5.8GHz bands using a T-shaped stub feeder and a spiral structure. The size of the antenna is 5mm in width × 6.5mm in length, and the thickness of the PCB is 1.2T. As a result of measurement of the manufactured antenna, it was possible to obtain a return loss of -10dB or more at 2.4GHz and 5.8GHz. In the E-plane, the gain was -4.45 dBi, and in the H-plane, the gain was -1.05 dBi. Therefore, the proposed small antenna for wireless communication showed excellent performance.

• Journal of Software Assessment and Valuation
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• v.16 no.2
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• pp.9-23
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• 2020

Microsoft's Windows system is widely used as an operating system for the desktops and enterprise servers of companies or organizations, and is a major target of cyber attacks. Microsoft provides various protection technologies and strives for defending the attacks through periodic security patches, however the threats such as DLL injection and process injection still exist. In this paper, we analyze 12 types of injection techniques in Microsoft Windows, and perform injection attack experiments on four application programs. Through the results of the experiments, we identify the risk of injection techniques, and verify the effectiveness of the mitigation technology for defending injection attacks provided by Microsoft. As a result of the experiments, we have found that the current applications are vulnerable to several injection techniques. Finally, we have presented the mitigation techniques for these injection attacks and analyzed their effectiveness.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.558-572
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• 2020

The purpose of this study was to classify the types of degraded areas of Mt. Jirisan section in Baekdudaegan and survey the actual condition of each damage type to use it as basic data for the direction of the restoration of damaged areas according to damage type based on the vegetation information of reference ecosystem. The analysis of the Mt. Jirisan section's actual degraded conditions showed that the total number of patches of degraded areas was 57, and the number of patches and size of degraded areas was higher at the low average altitude and gentle slope. Grasslands (deserted lands) and cultivated areas accounted for a high portion of the damage types, indicating that agricultural land use was a major damage factor. The survey on the conditions of 14 degraded areas showed that the types of damage were classified into the grassland, cultivated area, restoration area, logged-off land, and bare ground. The analysis of the degree of disturbance (the ratio of annual and biennial herb, urbanized index, and disturbance index) by each type showed that the simple single-layer vegetation structure mostly composed of the herbaceous and the degree of disturbance were high in the grassland and cultivated land. The double-layer vegetation structure appeared in the restoration area where the pine seedlings were planted, and the inflow of naturalized plants was especially high compared to other degraded areas due to disturbances caused by the restoration project and the nearby hiking trails. Although the inflow of naturalized plants was low because of high altitude in bare ground, the proportion of annual and biennial herb was high, indicating that all surveyed degraded areas were in early succession stages. The stand ordination by type of damage showed the restoration area on the I-axis, cultivated area, grassland, logged-off land, and bare ground in that order, indicating the arrangement by the damage type. Moreover, the stand ordination of the degraded areas and reference ecosystem based on floristic variation showed a clear difference in species composition. This study diagnosed the status of each damage type based on the reference ecosystem information according to the ecological restoration procedure and confirmed the difference in species composition between the diagnosis result and the reference ecosystem. These findings can be useful basic data for establishing the restoration goal and direction in the future.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.131-143
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• 2014

We propose a no-reference perceptual fog density and visibility prediction model in a single foggy scene based on natural scene statistics (NSS) and perceptual "fog aware" statistical features. Unlike previous studies, the proposed model predicts fog density without multiple foggy images, without salient objects in a scene including lane markings or traffic signs, without supplementary geographical information using an onboard camera, and without training on human-rated judgments. The proposed fog density and visibility predictor makes use of only measurable deviations from statistical regularities observed in natural foggy and fog-free images. Perceptual "fog aware" statistical features are derived from a corpus of natural foggy and fog-free images by using a spatial NSS model and observed fog characteristics including low contrast, faint color, and shifted luminance. The proposed model not only predicts perceptual fog density for the entire image but also provides local fog density for each patch size. To evaluate the performance of the proposed model against human judgments regarding fog visibility, we executed a human subjective study using a variety of 100 foggy images. Results show that the predicted fog density of the model correlates well with human judgments. The proposed model is a new fog density assessment work based on human visual perceptions. We hope that the proposed model will provide fertile ground for future research not only to enhance the visibility of foggy scenes but also to accurately evaluate the performance of defog algorithms.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.583-598
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• 2022

As human-based tunnel inspections are affected by the subjective judgment of the inspector, making continuous history management difficult. There is a lot of deep learning-based automatic crack detection research recently. However, the large public crack datasets used in most studies differ significantly from those in tunnels. Also, additional work is required to build sophisticated crack labels in current tunnel evaluation. Therefore, we present a method to improve crack detection performance by inputting existing datasets into a deep learning model. We evaluate and compare the performance of deep learning models trained by combining existing tunnel datasets, high-quality tunnel datasets, and public crack datasets. As a result, DeepLabv3+ with Cross-Entropy loss function performed best when trained on both public datasets, patchwise classification, and oversampled tunnel datasets. In the future, we expect to contribute to establishing a plan to efficiently utilize the tunnel image acquisition system's data for deep learning model learning.

• Knowledge Management Research
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• v.25 no.1
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• pp.173-192
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• 2024

This study aims to understand the changes in the beauty industry due to the pandemic from the consumer's perspective based on consumers' opinions about their skin online before and after the pandemic. Furthermore, this study tries to derive strategies for companies and governments to support sustainable growth and innovation in the beauty industry. To this end, posts on social media from 2017 to 2022 that contained the keyword 'skin concerns' are collected, and after data preprocessing, 96,908 posts are used for the structural topic model. To examine whether consumers' interest areas related to skin change according to the pandemic situation, the analysis period is divided into 7 periods, and the variables that distinguish each stage are used as meta-variables for the structural topic model. As a result, it is found that consumers' interests can be divided into 22 topics, which can be categorized into four main categories: beauty manufacturing, beauty services, skin concerns, and other. The results of this study are expected to be utilized in construction of product development and marketing strategies of related companies and the establishment of economic support policies by the government in response to changes in demand in the beauty industry due to the pandemic.