• Wind and Structures
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• v.13 no.5
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• pp.413-431
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• 2010

The focus of this article is on the assessment of vertical wind vector components and their aerodynamic impact on lattice framework, specifically two distinct sections of a guyed transmission tower. Thunderstorm winds, notably very localized events such as convective downdrafts (including downbursts) and tornadoes, result in a different load on a tower's structural system in terms of magnitude and spatial distribution when compared to horizontal synoptic winds. Findings of previous model-scale experiments are outlined and their results considered for the development of a testing rig that allows for rotation about multiple body axes through a series of wind tunnel tests. Experimental results for the wind loads on two unique experimental models are presented and the difference in behaviour discussed. For a model cross arm with a solidity ratio of approximately 30%, the drag load was increased by 14% when at a pitch angle of $20^{\circ}$. Although the effects of rotation about the vertical body axis, or the traditional 'angle of attack', are recognized by design codes as being significant, provisions for vertical winds are absent from each set of wind loading specifications examined. The inclusion of a factor to relate winds with a vertical component to the horizontal speed is evaluated as a vertical wind factor applicable to load calculations. Member complexity and asymmetric geometry often complicate the use of lattice wind loading provisions, which is a challenge that extends to future studies and codification. Nevertheless, the present work is intended to establish a basis for such studies.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1672-1677
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• 2004

Leading edge extension(LEX) in a highly swept shape applied to a delta wing features the modem air-fighters. The LEX vortices generated upon the upper surface of the wing at high angle of attack enhance the lift force of the delta wing by way of increased negative suction pressure over the surfaces. The present 3-D stereo PIV includes the Identification of 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criterion and so on. A delta wing model with or without LEX was immersed in a circulating water channel. Two high-resolution, high-speed digital cameras($1280pixel{\times}1024pixel$) were used to allow the time-resolved animation work. The present dynamic stereo PIV represents the complicated vortex behavior, especially, in terms of time-dependent characteristics of the vortices at given measuring sections. Quantities such as three velocity vector components, vorticity and other flow information can be easily visualized via the 3D time-resolved post-processing to make the easy understanding of the LEX effect or vortex emerging and collapse which are important phenomena occurring in the field of delta wing aerodynamics.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.15-21
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• 2018

In this study, we try to detect anomalies on the network intrusion detection system by learning only one class. We use KDD CUP 1999 dataset, an intrusion detection dataset, which is used to evaluate classification performance. One class classification is one of unsupervised learning methods that classifies attack class by learning only normal class. When using unsupervised learning, it difficult to achieve relatively high classification efficiency because it does not use negative instances for learning. However, unsupervised learning has the advantage for classifying unlabeled data. In this study, we use one class classifiers based on support vector machines and density estimation to detect new unknown attacks. The test using the classifier based on density estimation has shown relatively better performance and has a detection rate of about 96% while maintaining a low FPR for the new attacks.

• Wind and Structures
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• v.38 no.2
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• pp.109-118
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• 2024

A solar concentrator is a reflective surface in the shape of a parabola that collects solar rays in a focal area. This concentrator follows the path of the sun during the day with the help of a tracking system. One of the most important issues in the design and construction of these reflectors is the force exerted by the wind. This force can sometimes disrupt the stability of the concentrator and overturn the entire system. One of the ways to estimate the force is to use the numerical solution of the air flow in three dimensions around the dish. Ansys Fluent simulation software has been used for modeling several angles of attack between 0 and 180 with respect to the horizon. From the comparison of the velocity vector lines on the dish at angles of 90 to - 90 degrees, it was found that the flow lines are more concentrated inside the dish and there is a tendency for the flow to escape around in the radial direction, which indicates the presence of more pressure distribution inside the dish. It was observed that the pressure on the concave surface was higher than the convex one. Then, the effect of adding a hole with various diameter of 200, 300, 400, 500, and 600 mm on the dish was investigated. By increasing the diameter up to the optimized size of 400 mm, a decrease in the maximum pressure value in the pressure distribution was shown inside the dish. This pressure drop decreased the drag coefficient. The effect of the hole on the dish was also investigated for the 30-degree angled dish, and it was found that the results of the 90-degree case should be considered as the basis of the design.

• Parasites, Hosts and Diseases
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• v.30 no.4
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• pp.329-340
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• 1992

In order to determine population dynamics of Anopheles sinensis, a survey based on average number of female mosquitoes per trap-night was carried out during the period of 5 years from 1987 to 1991, A. sinensis Birst appeared between the 2nd and 20th April, and were trapped in large number between the 5th and 12th July. The number of trapped mosquitoes began to decrease from mid-August, and a few were collected until mid-November, each year. The average number of A. sinensis in July was 542.6 per trap-night in 1987, but in 1989 increased abruptly to 1,331.4, and then decreased to considerably lower levels, 271, 9 in 1990 and 372. 1 in 1991. The nocturnal activity of A. sinensis to attack humans was found to become active in the early night, and it was gradually decreasing at mid·night, however, then slightly increasing toward dawn. The immature stage of A. sinensis in the rice paddies was Birst found in the correlation pattern with peak adult densities in early July. The highest larval density of A. sinensis in the study area was 21,226×103 in early July 1990. The larval A. sinensis showed high resistance level and resistance ratios against 3 kinds of organo- phosphorous compounds, diazinon, malathion, and fenitrothion, but low resistance against fenthion. The present results indicated that the population density of A, sinensis in Kyongbuk area is decreasing over the five·year from 1987 to 1991. Key words: Anopheles sinensis, seasonal prevalence, population dynamics, Kyongbuk Province.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.5
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• pp.57-70
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• 2009

A CAD design drawing based on vector data that is very important art work in industrial fields has been considered to content that the copyright protection is urgently needed. This paper presents a watermarking scheme based on k-means++ for CAD design drawing. One CAD design drawing consists of several layers and each layer consists of various geometric objects such as LINE, POLYLINE, CIRCLE, ARC, 3DFACE and POLYGON. POLYLINE with LINE, 3DFACE and ARC that are fundamental objects make up the majority in CAD design drawing. Therefore, the proposed scheme selects the target object with high distribution among POLYLINE, 3DFACE and ARC objects in CAD design drawing and then selects layers that include the most target object. Then we cluster the target objects in the selected layers by using k-means++ and embed the watermark into the geometric distribution of each group. The geometric distribution is the normalized length distribution in POLYLINE object, the normalized area distribution in 3DFACE object and the angle distribution in ARC object. Experimental results verified that the proposed scheme has the robustness against file format converting, layer attack as well as various geometric editing provided in CAD editing tools.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.271-278
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• 2021

As the current cyber attacks become more intelligent, the existing Intrusion Detection System is difficult for detecting intelligent attacks that deviate from the existing stored patterns. In an attempt to solve this, a model of a deep learning-based intrusion detection system that analyzes the pattern of intelligent attacks through data learning has emerged. Intrusion detection systems are divided into host-based and network-based depending on the installation location. Unlike network-based intrusion detection systems, host-based intrusion detection systems have the disadvantage of having to observe the inside and outside of the system as a whole. However, it has the advantage of being able to detect intrusions that cannot be detected by a network-based intrusion detection system. Therefore, in this study, we conducted a study on a host-based intrusion detection system. In order to evaluate and improve the performance of the host-based intrusion detection system model, we used the host-based Leipzig Intrusion Detection-Data Set (LID-DS) published in 2018. In the performance evaluation of the model using that data set, in order to confirm the similarity of each data and reconstructed to identify whether it is normal data or abnormal data, 1D vector data is converted to 3D image data. Also, the deep learning model has the drawback of having to re-learn every time a new cyber attack method is seen. In other words, it is not efficient because it takes a long time to learn a large amount of data. To solve this problem, this paper proposes the Siamese Convolutional Neural Network (Siamese-CNN) to use the Few-Shot Learning method that shows excellent performance by learning the little amount of data. Siamese-CNN determines whether the attacks are of the same type by the similarity score of each sample of cyber attacks converted into images. The accuracy was calculated using Few-Shot Learning technique, and the performance of Vanilla Convolutional Neural Network (Vanilla-CNN) and Siamese-CNN was compared to confirm the performance of Siamese-CNN. As a result of measuring Accuracy, Precision, Recall and F1-Score index, it was confirmed that the recall of the Siamese-CNN model proposed in this study was increased by about 6% from the Vanilla-CNN model.