• Steel and Composite Structures
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• v.51 no.4
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.

• Conservation Science in Museum
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• v.31
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• pp.55-70
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• 2024

Style transfer algorithms are currently undergoing active research and are used, for example, to convert ordinary images into classical painting styles. However, such algorithms have yet to produce appropriate results when applied to Korean cultural heritage images, while the number of cases for such applications also remains insufficient. Accordingly, this study attempts to develop a style transfer algorithm that can be applied to styles found among Korean cultural heritage. The algorithm was produced by improving data comprehension by enabling it to learn meaningful characteristics of the styles through representation learning and to separate the cultural heritage from the background in the target images, allowing it to extract the style-relevant areas with the desired color and texture from the style images. This study confirmed that, by doing so, a new image can be created by effectively transferring the characteristics of the style image while maintaining the form of the target image, which thereby enables the transfer of a variety of cultural heritage styles.

• Journal of the Korea Society of Computer and Information
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• v.18 no.9
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• pp.21-31
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• 2013

ECU(Electric Control Unit) on the important features of the vehicle is equipped, ECU between sending and receiving messages is connected to one of the internal network(CAN BUS), but this network easily accessible from the outside and not intended to be able to receive attacks from an attacker, In this regard, the development of tools that can be used in order to verify the possibility of attacks on attacks from outside, However, the time costs incurred for developing tools and time to analyze from actual car for CAN messages to be used in the attack to find. In this paper, we want to solve it, propose a method to generate test cases required for the attack is publicly available tool called Sulley and it explains how to find the CAN messages to be used in the attack. Sulley add the CAN messages data generated library files in provided library file and than Sulley execute that make define and execute file conform to the CAN communication preferences and create message rules. Experiments performed by the proposed methodology is applied to the actual car and result, test cases generated by the CAN messages fuzzing through Sulley send in the car and as a result without a separate tool developed was operating the car.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.125-140
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• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Korean journal of communication and information
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• v.45
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• pp.220-254
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• 2009

Presidential TV debates serve as an important instrument for the general viewers to evaluate the candidates’ character, to examine their policy, and finally to make an important political decisions to cast ballots. Every words candidates utter in the course of entire election campaign exert influence of a certain significance by delivering their ideas and by creating clashes with their respective opponents. This study focuses on the conceptual venue, coined as ‘stasis’ by ancient rhetoricians, in which the clashes take place, and examines the words selection made by each candidates, the manners in which they form stasis, call for evidence, educate the public, and finally create a legitimate form of political argumentation. The study applied computer based content analysis using KrKwic and UCINET software to analyze semantic networks among the candidates. The results showed three major candidates, namely Lee Myung Bak, Jung Dong Young, and Lee Hoi Chang, displayed separate patterns in their use of language, by selecting the words that are often neglected by their opponents. Apparently, the absence of stasis and the lack of speaking mutual language significantly undermined the effects of debates. Central questions regarding issues of North Korea failed to meet basic requirements, and the respondents failed to engage in effective argumentation process.

• Spatial Information Research
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• v.21 no.2
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• pp.23-33
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• 2013

W ith the recent advancement of IoT (Internet of Things) technology, there has been much interest in the spatial query processing which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. Therefore, various kinds of spatial query processing algorithms and distributed spatial indexing methods have been proposed. They can minimize energy consumption of sensor nodes by reducing wireless communication among them using in-network spatial filtering technology. However, they cannot optimize multiple spatial queries which w ill be w idely used in IoT, because most of them have focused on a single spatial query optimization. Therefore, we propose a new multiple spatial query optimization algorithm which can energy-efficiently process multiple spatial queries in a sensor network. The algorithm uses a concept of 'query merging' that performs the merged set after merging multiple spatial queries located at adjacent area. Here, our algorithm makes a decision on which is better between the merged and the separate execution of queries. For such the decision making, we additionally propose the cost estimation method on the spatial query execution. Finally, we analyze and clarify our algorithm's distinguished features using the spatial indexing methods of GR-tree, SPIX, CPS.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.165-172
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• 2013

Convergence is increasingly prevalent in the IT world which generally refers to the combination of two or more different technologies in a single device. Especially, the spectrum scarcity is becoming a big issue because there are exponential growth of broadcasting and communication systems in the spectrum demand. Cognitive radio (CR) is a convergence technology that is envisaged to solve the problems in wireless networks resulting from the limited available spectrum and the inefficiency in the spectrum usage by exploiting the existing wireless spectrum opportunistically. However, the very process of convergence is likely to expose significant security issues due to the merging of what have been separate services and technologies and also as a result of the introduction of new technologies. The main purpose of this research is focused on devising an adaptive security framework based on carousel for CR networks as a distinct telecommunication convergence application, which are still at the stage of being developed and standardized with the lack of security concerns. The framework uses a secure credential, named as carousel, initialized with the location related information from objects position, which is used to design security mechanisms for supporting privacy and various securities based on it. The proposed adaptive security framework could be used as a security building block for the CR network standards and various convergence applications.

• Journal of Korean Home Economics Education Association
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• v.31 no.3
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• pp.73-90
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• 2019

The purpose of this study was to explore the differences in perceptions of male and female students about population problems and to draw up implications for population education. Using text mining, the report about population problem, which had written by students in population education class, were analysed. After extracting key words, semantic networks were visualized. The results were as follows. First, the high frequency words were the same for each gender. Second, key words based on frequency did not differ depending on gender. And the key words extracted by the correlation analysis and bigram were different. That is, in the semantic network of girls' words, the network of "life"-"marriage"-"birth"-"pregnancy" appeared independently, distinguishing it from male students who showed separate objective links to population problems. Therefore, it drew suggestions that male and female students should be viewed as heterogeneous groups with different cognitive structures on population problems and that the content and methods of population education should be approached differently depending on gender.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.246-252
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• 2018

Hand gestures are attracting attention as a NUI (Natural User Interface) of wearable devices such as smart glasses. Recently, to support efficient media consumption in IoT (Internet of Things) and wearable environments, the standardization of IoMT (Internet of Media Things) is in the progress in MPEG. In IoMT, it is assumed that hand gesture detection and recognition are performed on a separate device, and thus provides an interoperable interface between these modules. Meanwhile, deep learning based hand gesture recognition techniques have been recently actively studied to improve the recognition performance. In this paper, we propose a method of hand gesture recognition based on CNN (Convolutional Neural Network) for various applications such as media consumption in wearable devices which is one of the use cases of IoMT. The proposed method detects hand contour from stereo images acquisitioned by smart glasses using depth information and color information, constructs data sets to learn CNN, and then recognizes gestures from input hand contour images. Experimental results show that the proposed method achieves the average 95% hand gesture recognition rate.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.377-386
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• 2003

In this paper, we present an application layer protocol to support secure wireless Internet services, called Application Layer Security(ALS). The drawbacks of the two traditional approaches to secure wireless applications motivated the development of ALS. One is that in the conventional application-specific security protocol such as Secure HyperText Transfer Protocol(S-HTTP), security mechanism is included in the application itself. This gives a disadvantage that the security services are available only to that particular application. The other is that a separate protocol layer is inserted between the application and transport layers, as in the Secure Sockets Layer(SSL)/Transport Layer Security(TLS). In this case, all channel data are encrypted regardless of the specific application's requirements, resulting in much waste of network resources. To overcome these problems, ALS is proposed to be implemented on top of HTTP so that it is independent of the various transport layer protocols, and provides a common security interface with security applications so that it greatly improves the portability of security applications. In addition, since ALS takes advantages of well-known TLS mechanism, it eliminates the danger of malicious attack and provides applications with various security services such as authentication, confidentiality integrity and digital signature, and partial encryption. We conclude this paper with an example of applying ALS to the solution of end-to-end security in a present commercial wireless protocol stack, Wireless Application Protocol.