• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.313-315
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• 2019

Although Korea's fashion market has negative growth, it has been growing again since 2018. This phenomenon means that people are becoming more interested in fashion. As interest in fashion grows, people visit various community sites for reference to find a suitable coordination for themselves. Most community sites, however, are manually categorizing each garment. Not only do these tasks take a lot of time, but they also make it difficult to search for multiple clothing at the same time. In other words, I can't choose what I want at the same time, and if I choose what I want, I have to look at what the model is wearing and refer to it. The problem with this may not help because the coordination in which the model provided is worn is more likely to be the one that the user does not want. In this paper, when the image is uploaded to improve the problem, the clothing is analyzed with AI analysis model and automatically classified and stored. Therefore, not only can you search for one clothes in the existing way, but you can also search for multiple clothes at the same time. The service is expected to allow more people to easily find and refer to the code for themselves.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.91-104
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• 2021

This study explored users' emotional states identified from the wake-up words -"Hi, KIA!"- using a machine learning algorithm considering the user interface of passenger cars' voice. We targeted four emotional states, namely, excited, angry, desperate, and neutral, and created a total of 12 emotional scenarios in the context of car driving. Nine college students participated and recorded sentences as guided in the visualized scenario. The wake-up words were extracted from whole sentences, resulting in two data sets. We used the soundgen package and svmRadial method of caret package in open source-based R code to collect acoustic features of the recorded voices and performed machine learning-based analysis to determine the predictability of the modeled algorithm. We compared the accuracy of wake-up words (60.19%: 22%~81%) with that of whole sentences (41.51%) for all nine participants in relation to the four emotional categories. Accuracy and sensitivity performance of individual differences were noticeable, while the selected features were relatively constant. This study provides empirical evidence regarding the potential application of the wake-up words in the practice of emotion-driven user experience in communication between users and the artificial intelligence system.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.499-506
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• 2021

Hackers' cyber attack techniques are becoming more sophisticated and diversified, with a form of attack that has never been seen before. In terms of information security vulnerability standard code (CVE), about 90,000 new codes were registered from 2015 to 2020. This indicates that security threats are increasing rapidly. When new security vulnerabilities occur, damage should be minimized by preparing countermeasures for them, but in many cases, companies are insufficient to cover the security management level and response system with a limited security IT budget. The reason is that it takes about a month for analysts to discover vulnerabilities through manual analysis, prepare countermeasures through security equipment, and patch security vulnerabilities. In the case of the public sector, the National Cyber Safety Center distributes and manages security operation policies in a batch. However, it is not easy to accept the security policy according to the characteristics of the manufacturer, and it takes about 3 weeks or more to verify the traffic for each section. In addition, when abnormal traffic inflow occurs, countermeasures such as detection and detection of infringement attacks through vulnerability analysis must be prepared, but there are limitations in response due to the absence of specialized security experts. In this paper, we proposed a method of using the security policy information sharing site "snort.org" to prepare effective countermeasures against new security vulnerability attacks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.1
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• pp.63-72
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• 2010

RFID is one of useful identification technology in ubiquitous environments which can be a replacement of bar code. RFID is basically consisted of tag, reader, which is for perception of the tag, and back-end-database for saving the information of tags. Although the usage of mobile readers in cellular phone or PDA increases, related studies are not enough to be secure for practical environments. There are many factors for using mobile leaders, instead of static leaders. In mobile reader environments, before constructing the secure protocol, we must consider these problems: 1) easy to lose the mobile reader 2) hard to keep the connection with back-end-database because of communication obstacle, the limitation of communication range, and so on. To find the solution against those problems, Han et al. suggest RFID mutual authentication protocol without back-end-database environment. However Han et al.'s protocol is able to be traced tag location by using eavesdropping, spoofing, and replay attack. Passive tag based on low cost is required lots of communication unsuitably. Hence, we analyze some vulnerabilities of Han et al.'s protocol and suggest RFID mutual authentication protocol without online back-end-database in aspect of efficiency and security.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.13-21
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• 2020

The Android author identification study can be interpreted as a method for revealing the source in a narrow range, but if viewed in a wide range, it can be interpreted as a study to gain insight to identify similar works through known works. The problem found in the Android author identification study is that it is an important code on the Android system, but it is difficult to find the important feature of the author due to the meaningless codes. Due to this, legitimate codes or behaviors were also incorrectly defined as malicious codes. To solve this, we introduced the concept of survival network to solve the problem by removing the features found in various Android apps and surviving unique features defined by authors. We conducted an experiment comparing the proposed framework with a previous study. From the results of experiments on 440 authors' identified apps, we obtained a classification accuracy of up to 92.10%, and showed a difference of up to 3.47% from the previous study. It used a small amount of learning data, but because it used unique features without duplicate features for each author, it was considered that there was a difference from previous studies. In addition, even in comparative experiments with previous studies according to the feature definition method, the same accuracy can be shown with a small number of features, and this can be seen that continuously overlapping meaningless features can be managed through the concept of a survival network.

• Korean Journal of Ecology and Environment
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• v.53 no.4
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• pp.380-389
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• 2020

Research on diagnosing and predicting the response of ecosystems caused by environmental changes such as artificial disturbance and climate change is emerging as the most important issue of biodiversity and ecosystem researches. This study aims to clean, standardize, and provide the results of National Ecosystem Survey which should be considered fundamentally in diagnosing and predicting ecosystem changes in the form of dataset. To refine and clean the dataset we developed a simple verification program based on the fifth National Ecosystem Survey Guideline and applied that program to the data from the second (1997~2005), third (2006~2013) and fourth (2014~2018) National Ecosystem Survey. Data quality control processes were implemented including (1) standardization of terminology, (2) similar data table integration, (3) unnecessary attribute and error elimination, (4) unification of different input items, (5) data arrangement in codes, and (6) code mapping for input items. These approaches and methods are the first attempt propose an option for ecological data standardization in Korea. The standardized dataset of National Ecosystem Survey in Korea will be easily accessible, reusable for both researchers and public. In addition, we expect it will contribute to the establishment of diverse environmental policies concerning environmental assessments, habitat conservation, prediction of endangered species distribution and ecological risks due to climate change. The dataset through this study is open freely online via EcoBank (nie-ecobank.kr) which is the first ecological information portal system in Korea developed by National Institute of Ecology.

• Journal of IKEEE
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• v.25 no.2
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• pp.399-407
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• 2021

This paper proposes the DC-link voltage design method of Type 4 wind turbine that minimizes power loss and satisfies the High Voltage Ride Through(HVRT) function requirements of the transmission system operator. The Type 4 wind turbine used for large-capacity offshore wind turbine consists of the Back-to-Back converter in which the converter linked to the power grid and the inverter linked to the wind turbine share the DC-link. When the grid high voltage fault occurs in the Type 4 wind turbine, if the DC-link voltage is insufficient compared to the fault voltage level, the current controller of the grid-side converter can't operate smoothly due to over modulation. Therefore, to satisfy the HVRT function, the DC-link voltage should be designed based on the voltage level of high voltage fault. However, steady-state switching losses increase further as the DC-link voltage increases. Therefore, the considerations should be included for the loss to be increased when the DC-link voltage is designed significantly. In this paper, the design method for the DC-link voltage considered the fault voltage level and the loss is explained, and the validity of the proposed design method is verified through the HVRT function simulation based on the PSCAD model of the 2MVA Type 4 wind turbine.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.25-36
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• 2023

Today, as AI (Artificial Intelligence) technology is introduced in various fields, including security, the development of technology is accelerating. However, with the development of AI technology, attack techniques that cleverly bypass malicious behavior detection are also developing. In the classification process of AI models, an Adversarial attack has emerged that induces misclassification and a decrease in reliability through fine adjustment of input values. The attacks that will appear in the future are not new attacks created by an attacker but rather a method of avoiding the detection system by slightly modifying existing attacks, such as Adversarial attacks. Developing a robust model that can respond to these malware variants is necessary. In this paper, we propose two methods of generating Adversarial attacks as efficient Adversarial attack generation techniques for improving Robustness in AI models. The proposed technique is the XAI-based attack technique using the XAI technique and the Reference based attack through the model's decision boundary search. After that, a classification model was constructed through a malicious code dataset to compare performance with the PGD attack, one of the existing Adversarial attacks. In terms of generation speed, XAI-based attack, and reference-based attack take 0.35 seconds and 0.47 seconds, respectively, compared to the existing PGD attack, which takes 20 minutes, showing a very high speed, especially in the case of reference-based attack, 97.7%, which is higher than the existing PGD attack's generation rate of 75.5%. Therefore, the proposed technique enables more efficient Adversarial attacks and is expected to contribute to research to build a robust AI model in the future.

• Nuclear Engineering and Technology
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• v.26 no.1
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• pp.41-53
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• 1994

A SGTR accident postulated at Kori unit 1 is simulated with Mihama unit experience, which occurred on February 1991, to evaluate the capability of plant to cope with the transient. The system design and plant conditions of Kori Unit 1 are much similar with those of Mihama Unit 2. Therefore, special concern has been given to evaluate the sequence and the resulting consequence of the postulated SGTR accident at the Kori unit 1 An analysis is peformed as realistically as possible, with following the EOP of Kori unit 1. The result indicates that the leak through tube break terminates within about forty minutes, and the Kori unit 1 may be sufficient to cope with SGTR accident with same type of sequence. However, the reconsideration may be required for the design of Kori unit 1 which disconnects non-safety AC power from off-site power on SI signal generation. It may be pointed out that the content of EOP for SGTR accident is not enough to require operator's proper judgements. An analysis of SGTR accident tested in the LSTF which simulated the SGTR accident at the Mihama Unit 2 is peformed using the RELAP5/MOD3. The results indicates that the code yields in general good agreement with the test, except the break flowrate at the early stage of the event.

• Nuclear Engineering and Technology
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• v.27 no.6
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• pp.859-869
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• 1995

The present study is to understand the physical phenomena anticipated during the accident with RHR loss under mid-loop operation in a PWR and, at the same time, to examine the prediction capability of RELAP5/MOD3.1 on such an accident, by simulating an integral test relevant to this accident for reliable analysis in an actual PWR. The selected experiment, i.g. BETHSY Test 6.9a, represents the configuration with the pressurizer manway open and steam generators unavailable during the accident. Accordingly, the results of this ok are sure to contribute to understanding both the key events as well as the sensitive parameters, anticipated in the accident, for validity of the actual analysis. In the simulation result overall behavior as well as major phenomena observed in the experiment have been predicted reasonably by RELAP5/MOD3.1, however, the problem associated with enormous computing time .due to small time step size has been encountered. Besides, the code prediction of higher swollen level in the pressure vessel has given rise to overestimation of both pressurizer level and RCS pressure. Subsequently, overprediction of the break flow through the manway has led to earlier core uncovery than that in the experiment by about 400 seconds. As a whole, it is demonstrated from both the experiment and the analysis that gravity feed has not been sufficient to recover the core level and thus additional forced feed has been necessary in this configuration.