• Journal of IKEEE
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• v.22 no.1
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• pp.162-167
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• 2018

In this paper, we propose a method to classify radar signals according to the jamming technique by applying the machine learning to parameter data extracted from received radar signals. In the present army, the radar signal is classified according to the type of threat based on the library of the radar signal parameters mostly built by the preliminary investigation. However, since radar technology is continuously evolving and diversifying, it can not properly classify signals when applying this method to new threats or threat types that do not exist in existing libraries, thus limiting the choice of appropriate jamming techniques. Therefore, it is necessary to classify the signals so that the optimal jamming technique can be selected using only the parameter data of the radar signal that is different from the method using the existing threat library. In this study, we propose a method based on machine learning to cope with new threat signal form. The method classifies the signal corresponding the new jamming method for the new threat signal by learning the classifier composed of the hidden Markov model and the neural network using the existing library data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.6
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• pp.43-54
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• 2016

The occurrence of cyber crime is on the rise every year, and the security control center, which should play a crucial role in monitoring and early response against the cyber attacks targeting various information systems, its importance has increased accordingly. Every endeavors to prevent cyber attacks is being attempted by information security personnel of government and financial sector's security control center, threat response Center, cyber terror response center, Cert Team, SOC(Security Operator Center) and else. The ordinary method to monitor cyber attacks consists of utilizing the security system or the network security device. It is anticipated, however, to be insufficient since this is simply one dimensional way of monitoring them based on signatures. There has been considerable improvement of the security control system and researchers also have conducted a number of studies on monitoring methods to prevent threats to security. In accordance with the environment changes from ESM to SIEM, the security control system is able to be provided with more input data as well as generate the correlation analysis which integrates the processed data, by extraction and parsing, into the potential scenarios of attack or threat. This article shows case studies how to detect the threat to security in effective ways, from the initial phase of the security control system to current SIEM circumstances. Furthermore, scenarios based security control systems rather than simple monitoring is introduced, and finally methods of producing the correlation analysis and its verification methods are presented. It is expected that this result contributes to the development of cyber attack monitoring system in other security centers.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.315-326
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• 2020

Corporate efforts to build strong brands have made consumers interested in brand love. In the field of brand love, however, there is a lack of systematic research on the multidimensionality of the concept of brand love and on the scale development to measure it. Thus, based on the methodological research design of Churchill(1979) and DeVellis(1991), this study explored properties of brand love and classified them into two levels - 'emotion' and 'relationship' - and generated corresponding measurement items. To do this, the research was conducted in a total of eight stages, including preliminary studies such as literature review, open surveys, and in-depth interviews, as well as the main study process in which the factors were analyzed step by step. As a result, the level of emotion appeared to have five subcomponents (self-esteem, warmth, interest, responsibility, pleasure) with 19 items, and the level of relationship - three subcomponents (unchanging, sharing/supporting, understanding) with 11 items, adding up to a total of 30 measurement items for brand love with reliability, convergent and discriminant validity, and nomological validity. Additionally, we intended to expand the scope of research related to brand love by presenting the result model of organic interaction between the concepts that constitute brand love and proposing '4 categories of brand love strength' based on it.

• Journal of Korea Multimedia Society
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• v.7 no.4
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• pp.518-531
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• 2004

This paper discusses a testbed architecture for implementing scalable service differentiation in the Internet. The differentiated services (DiffServ) testbed architecture is based on a model in which a bandwidth broker (BB) can control network resources, and the ALTQ can reserve resources in a router to guarantee a Quality of Service (QoS) for incoming traffic to the testbed. The reservation and releasemessage for the ALTQ is contingent upon a decision message in the BE. The BB has all the information in advance, which is required for a decision message, in the form of PIB. A signaling protocol between the BB and the routers is the COPS protocol proposed at the IETF. In terms of service differentiation, a user should make an SLA in advance, and reserve required bandwidth through an RAR procedure. The SLA and RAR message between a user and the BB has implemented with the COPS extension which was used between a router and the BB. We evaluates the service differentiation for the video streaming in that the EF class traffic shows superb performance than the BE class traffic where is a network congestion. We also present the differentiated service showing a better packet receiving rate, low packet loss, and low delay for the EF class video service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.117-130
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• 2017

Bicycles are leading to serious accidents in the event of a side collision, and it is very important to prevent accidents in advance because it is difficult to actively deal with them in a dangerous situation. As a part of the bicycle safety driving support technology, this study establishes bicycle accidents dangerous zone based on bicycle accident data and road property information of digital map nationwide and provides timely safety information to cyclists. The point selected by using actual accident data was called 'dangerous zone', and the potential accident occurrence point generated by modeling based on this 'dangerous zone' was called 'logical dangerous zone'. As a result of the research on the Designation of Logical Bicycle Accident Dangerous Zone, the regional specificity of the bicycle accident points across the nation was generalized to the form of the logical dangerous zone through the network data.

• Journal of Gifted/Talented Education
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• v.24 no.3
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• pp.421-444
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• 2014

In STEAM education, contents that has been extracted from a variety of areas, so it can work closely and systematically. Therefore STEAM education requires systems thinking that can be grasped effectively these different disciplines. The purposes of this study are to develop a STEAM program based on systems thinking, and apply the program to the secondary science gifted student in order to investigate the educational effect. A model of the Program developed from previous research and theoretical contents of systems thinking and STEAM. A draft of the STEAM program was developed on the theme of "rocket". A total of 113 students was participated in this study. 100 seventh and 13 eighth graders were enrolled at seigy. A single group pre-post test paired t-test was conducted on them in systems thinking skills. Result of applying the program to the students as follows. The systems thinking ability was improved after the application of the program. 'Mental Model', 'Personal Skill', 'Team Learning', and 'System Analysis', 'Shared Vision' emerged for both improved significantly. In conclusion, the STEAM program based on system thinking improves students' systems thinking skills. This program of results can be helpful in cultivate human resources with the problem solving ability based on system thinking and STEAM literacy by used in public education curriculum.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.187-193
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• 2015

The ICT healing platform sets a couple of goals including preventing chronic diseases and sending out early disease warnings based on personal information such as bio-signals and life habits. The 2-step open system(TOS) had a relay designed between the healing platform and the storage of personal health data. It also took into account a publish/subscribe(pub/sub) service based on large-scale connections to transmit(monitor) the data processing process in real time. In the early design of TOS pub/sub, however, the same buffers were allocated regardless of connection idling and type of message in order to encode connection messages into a deflate algorithm. Proposed in this study, the dynamic buffer allocation was performed as follows: the message transmission type of each connection was first put to queuing; each queue was extracted for its feature, computed, and converted into vector through tf-idf, then being entered into a k-means cluster and forming a cluster; connections categorized under a certain cluster would re-allocate the resources according to the resource table of the cluster; the centroid of each cluster would select a queuing pattern to represent the cluster in advance and present it as a resource reference table(encoding efficiency by the buffer sizes); and the proposed design would perform trade-off between the calculation resources and the network bandwidth for cluster and feature calculations to efficiently allocate the encoding buffer resources of TOS to the network connections, thus contributing to the increased tps(number of real-time data processing and monitoring connections per unit hour) of TOS.

• Korean Association of Arts Management
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• no.52
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• pp.107-133
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• 2019

This article is aimed at exploring what factors influence the perception change of the consumers for the cultural heritage values in the case of the cultural heritage policy program entitled with the cultural heritage Yahaeng. The consumers is considered as a key factor in the value creation system of the cultural heritage Yahaeng. It is necessary that the priority of the cultural heritage Yahaeng should be shifted from the supplies to the consumers. The consumer-based model of cultural heritage utilization is used as a theoretical framework. This study examines the influence of cultural heritage authenticity, cultural motivation, management system, loyalty on the perception change of the consumers for the cultural heritage values. This study is empirically examined by the means of a survey conducted on 205 visitors in the case of the Suncheon Yahaeng. The results indicate that the cultural heritage Yahaeng positively influences the perception change of the consumers for the cultural heritage values. In addition, the results indicate that cultural heritage authenticity is the most important factor which positively influences the perception change of the consumers for the cultural heritage values. In addition, the results indicate that cultural motivation positively influences on the perception change of the consumer for the cultural heritage values through the mediating variable of the loyalty. In line with its results, the article recommends that the significance based management system, evaluation system focused on the perception of the consumers for the cultural heritage should be established in the future. The article concludes that the local residents should be importantly considered as consumers and the collaborative partners in the cultural heritage Yahaeng.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.447-455
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• 2017

At the modern industry, the composite material has been widely used. Particularly, the material of carbon fiber reinforced plastic hardened with resin on the basis of fiber is excellent. As the specific strength and rigidity are also superior, it receives attention as the light material. Among these materials, the carbon fiber reinforced plastic using carbon fiber has the superior mechanical property different from another fiber. So, it is utilized in vehicle and airplane at which high strength and light weight are needed at the same time. In this paper, the tensile property due to the fiber design is investigated through the analysis study with CT specimen composed of carbon plastic reinforced plastic. At the stress analysis of CFRP composite material with hole, the fracture trend at the tensile environment is examined. Also, it is shown that the lowest stress value happens and the deformation energy of the pre-crack becomes lowest at the analysis model composed of the stacking angle of 60° through the result due to the stacking angle. On the basis of this study result, it is thought to apply the foundation data to anticipate the fracture configuration at the structure applied with the practical experiment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.1
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• pp.229-249
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• 2022

This paper investigates machine learning models for predicting the designation of administrative issues in the KOSDAQ market through various techniques. When a company in the Korean stock market is designated as administrative issue, the market recognizes the event itself as negative information, causing losses to the company and investors. The purpose of this study is to evaluate alternative methods for developing a artificial intelligence service to examine a possibility to the designation of administrative issues early through the financial ratio of companies and to help investors manage portfolio risks. In this study, the independent variables used 21 financial ratios representing profitability, stability, activity, and growth. From 2011 to 2020, when K-IFRS was applied, financial data of companies in administrative issues and non-administrative issues stocks are sampled. Logistic regression analysis, decision tree, support vector machine, random forest, and LightGBM are used to predict the designation of administrative issues. According to the results of analysis, LightGBM with 82.73% classification accuracy is the best prediction model, and the prediction model with the lowest classification accuracy is a decision tree with 71.94% accuracy. As a result of checking the top three variables of the importance of variables in the decision tree-based learning model, the financial variables common in each model are ROE(Net profit) and Capital stock turnover ratio, which are relatively important variables in designating administrative issues. In general, it is confirmed that the learning model using the ensemble had higher predictive performance than the single learning model.