• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.37-47
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• 2011

In the recent years, malicious codes called malware are having shown significant increase due to the code obfuscation to evade detection mechanisms. When the code obfuscation technique is applied to malwares, they can change their instruction sequence and also even their signature. These malwares which have same functionality and different appearance are able to evade signature-based AV products. Thus, AV venders paid large amount of cost to analyze and classify malware for generating the new signature. In this paper, we propose a novel approach for detecting metamorphic malwares. The proposed mechanism first converts malware's API call sequences to call graph through dynamic analysis. After that, the callgraph is converted to semantic signature using 128 abstract nodes. Finally, we extract all subgraphs and analyze how similar two malware's behaviors are through subgraph similarity. To validate proposed mechanism, we use 273 real-world malwares include obfuscated malware and analyze 10,100 comparison results. In the evaluation, all metamorphic malwares are classified correctly, and similar module behaviors among different malwares are also discovered.

• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.49-60
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• 2021

Environmental impact assessment (EIA) practitioners play a very pivotal role in establishing EIA policies, and when implementing EIA environmental conflicts can be prevented and resolved by sharing information with stakeholders and coordinating opinions. For this reason, grasping the perceptions of stakeholders including practitioners about the overall system, such as EIA policies and implementation, can be helpful in setting improvement directions and policy directions for EIA. However, there is an insufficient information on the perception and understanding of stakeholders about the EIA system and operation currently in effect in Korea. Therefore, this study diagnoses operational and procedural problems for the EIA system, which is a decision-making tool and a precautionary technique that can minimize adverse effects through the environmental information analysis method, and improvement points and systems of the EIA system in the future. We tried to find a complement of an online survey of 37 questions,responses from 95 responses from stakeholders of EIA were summarized. Stakeholders were aware of the problems of the operation of the current system and the preparation of the evaluation form, and this was reflected. Period and cost of preparation of EIS (49%), the introduction of a new method (26%) and the items of collecting opinions and conflict management (41%), which showed high negative response rates (dissatisfied and very dissatisfied), are considered to be areas that we need to supplement further in the future. As society develops rapidly, the system needs to be supplemented accordingly, and policy improvement efforts are needed for items with high negative responses as a result of the survey.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.41-46
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• 2021

As data acquisition using unmanned aerial vehicles is widely used, as one of the ways to increase the accuracy of photogrammetry using unmanned aerial vehicles, a method of inputting both vertical and oblique images in bundle adjustment of aerial triangulation has been proposed. In this study, in order to find a suitable method for increasing the accuracy of photogrammetry, the accuracy of the case of adjusting the oblique images taken at different shooting angles and the case of adjusting the oblique images with different shooting angles at the same time with the vertical images were compared. As a result of the study, it was found that the error of the checkpoint decreases as the angle of the input oblique images increases. In particular, when the vertical images and oblique images are used together, the height error decreases significantly as the angle of the oblique images increases. The current 『Aerial Photogrammetry Work Regulation』 requires RMSE (Root Mean Square Error), which is the same as GSD (Ground Spatial Distance) of a vertical image. When using an oblique images with a shooting angle of 50°, a result close to this standard is obtained. If the vertical images and the 50° oblique images were adjusted at the same time, the work regulations could be satisfied. Using the results of this study, it is expected that photogrammetry using low-cost cameras mounted on unmanned aerial vehicles will become more active.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.751-760
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• 2021

Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.541-548
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• 2021

Recently, multispectral cameras are being actively utilized in various application fields such as agriculture, forest management, coastal environment monitoring, and so on, particularly onboard UAV's. Resultant multispectral images are typically georeferenced primarily based on the onboard GPS (Global Positioning System) and IMU (Inertial Measurement Unit)or accurate positional information of the pixels, or could be integrated with ground control points that are directly measured on the ground. However, due to the high cost of establishing GCP's prior to the georeferencing or for inaccessible areas, it is often required to derive the positions without such reference information. This study aims to provide a means to improve the georeferencing performance of a multispectral camera images without involving such ground reference points, but instead with the simultaneously onboard high resolution RGB camera. The exterior orientation parameters of the drone camera are first estimated through the bundle adjustment, and compared with the reference values derived with the GCP's. The results showed that the incorporation of the images from a high resolution RGB camera greatly improved both the exterior orientation estimation and the georeferencing of the multispectral camera. Additionally, an evaluation performed on the direction estimation from a ground point to the sensor showed that inclusion of RGB images can reduce the angle errors more by one order.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.57-64
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• 2022

A plant factory is a facility that creates an artificial environment in a controlled space and produces plants systematically through automated facilities. However, automation in the cultivation process is insufficient compared to the internal environment control technology in plant factories. This causes the problem of an increase in operating costs due to the input of a large number of workers. Therefore, this study aims to evaluate economic feasibility by comparing before and after introducing automation in the cultivation process of plant factories. The target plant factory to be analyzed was selected, and the break-even point analysis method was used by comparing the cost required compared to the operating period. As a result, the break-even point was analyzed to be 3.4 years when automation was introduced into six processes for plant cultivation. Therefore, it can be judged that the introduction of automation is excellent in terms of economic feasibility when the target plant factory has been operated for more than 3.4 years. This study is expected to be used as basic data to analyze the economic feasibility of introducing automation in domestic and foreign plant factories.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.55-62
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• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.11-16
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• 2022

The compaction process using vibrating rollers in road construction is essential to increase soil stiffness in earthworks. Currently, there is no clear standard for the operation method of the compaction roller during compaction. Although simple quality inspection techniques have been developed, plate load test (PLT) and field density test (FDT) are the most frequently used test methods to evaluate the degree of compaction during road construction as the most frequently used quality inspection methods. However, both inspection methods are inefficient because they cannot perform quality inspection in all sections due to time and cost reasons. In this study, we analyzed how the operating conditions of vibrating rollers affect the compaction quality. An intelligent quality management system, which is a currently developed and commercialized technology, was used to obtain quality inspection results in all sections. As a result of the test, it was analyzed that the speed and vibration direction of the compaction roller had an effect on the compaction degree, and it was found that the compaction direction had no effect on the compaction degree.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1643-1652
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• 2022

Deposited Marine Debris(DMD) can negatively affect marine ecosystems, fishery resources, and maritime safety and is mainly detected by sonar sensors, lifting frames, and divers. Considering the limitation of cost and time, recent efforts are being made by integrating underwater images and artificial intelligence (AI). We conducted a comparative study of You Only Look Once Version 5 (YOLOv5) and You Only Look Once Version 7 (YOLOv7) models to detect DMD from underwater images for more accurate and efficient management of DMD. For the detection of the DMD objects such as glass, metal, fish traps, tires, wood, and plastic, the two models showed a performance of over 0.85 in terms of Mean Average Precision (mAP@0.5). A more objective evaluation and an improvement of the models are expected with the construction of an extensive image database.

• Journal of the Korea Institute of Building Construction
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• v.21 no.3
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• pp.203-211
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• 2021

Recently, the insulaton design standards for reducing the energy use of buildings have been strengthened. Althoug insulation work is the most cost-effective method for reducing the primary energy consumption per unit area of a building, there are no evaluation criteria for insulation performance at the time of construction and completion inspection. The purpose of this study is to provide objective data by establishing a standard for an analysis method and a method for easily experimenting with the exterior wall thermal transmittance of an apartment house using a thermal transmittance measuring device(TESTO 435). For the exterior wall of the test subject, the specific heat per unit area exceeded 20kJ/(m²·K), and the data at the end point suitable for ISO 9869-1 were analyzed by the average method. The measured values of the thermal transmittance for 3 consecutive days converged within +5% of the desing value, and the standard deviation of the thermal transmittance by day decreased in the order of 1-Day > 3-Day > 2-Day. The standard deviation of the thermal transmittance by time period decreased in the order of 00:00~24:00 < 19:00~07:00 < 00:00~07:00. The measured value of the thermal transmittance for the time perion of 00:00 to 07:00 per day almost coincided with an error of -3% to + 2% compare to the desing value.