• Journal of KIISE:Computing Practices and Letters
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• v.9 no.2
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• pp.166-181
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• 2003

With the rapid growth of Internet, many devices such as Web TVs, PDAs and Web phones, begin to be directly connected to the Internet. These devices need real-time operating systems (RTOS) to support complex real-time applications running on them. Development of such real-time applications called embedded internet applications, is difficult due to the lack of adequate tools, especially debuggers. In this paper we present a new tracepoint debugging tool for the Qplus-T RTOS embedded system, which facilitates the instrumentations of the real-time software applications with timing trace-points. Compared with traditional breakpoint debugger, this trace-point debugger provides the ability to dynamically collect and record application data for on-line examination and for further off-line analysis. And, the trace-points can also provide the means for assigning new values to the running application's variables, without neither halting its execution nor interfering with its natural execution flow. Our trace-point debugger provides a highly efficient method for adding numerous monitoring trace-points within a real time target application such as Qplus-T internet applications, utilizing these trace-points to monitor and to analyze the application's behavior while it is running. And also, our trace debugger is different from previous one in that we can specify and detect the timing violations using its RTL (Real-Time Logic) trace experiments.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.95-104
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• 2019

Various kinds of devices are used for the Internet of Things (IoT) service, and IoT devices mainly use communication technology that uses the frequency of the unlicensed band. There are several types of communication technology in the unlicensed band, but WiFi is most commonly used. Devices used for IoT services vary in computing resources from devices with limited capabilities to smartphones and provide services over wireless networks such as WiFi. Most IoT devices can't perform complex operations for network control, thus they choose a WiFi access point (AP) based on signal strength. This causes a decrease in IoT service efficiency. In this paper, an intelligent AP system that can efficiently control the WiFi connection of the IoT devices is implemented. Based on the network information measured by the IoT device, the access point learns using a feed forward neural network algorithm, and predicts a network connection state to control the WiFi connection. By controlling the WiFi connection at the AP, the service efficiency of the IoT device can be improved.

• Convergence Security Journal
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• v.18 no.3
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• pp.19-25
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• 2018

Endpoint security is a method of ensuring network security by thoroughly protecting multiple individual devices connected to the network. In this study, we survey the functions and features of various commercial products of endpoint security. Also we emphasizes the importance of endpoint security to respond to the increasingly intelligent and sophisticated security threats against the cloud, mobile, artificial intelligence, and IoT based sur-connection era. and as a way to improve endpoint security, we suggest the ways to improve the life cycle of information security such as preemptive security policy implementation, real-time detection and filtering, detection and modification.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.289-296
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• 2019

In the era of M-ICT (mobile information communication technology), it is becoming more and more important to establish a city brand image that is "user-centered" and creates a new experience of "interaction between people, people and things, and people and space". The experience of city users on the brand image of a city is the key factor to determine the competitiveness of the city, among which the user's research on the touch point of the city brand is particularly important. The purpose of this study is to enhance the user's brand experience and enhance the city's brand competitiveness. The research methods of this paper are literature review and investigation. Firstly, the background and purpose of the study are expounded, then the characteristics and ways of user experience touch points are defined through the document review, and the multi-latitude composition model of city brand touch points is proposed. By means of user investigation, the structural characteristics of high frequency touch points between digital touch points and physical touch points are obtained. According to the problems found in the investigation, the optimal design strategy of touch point is put forward in combination with the case. The innovation of this study is to study the relationship between the city brand and the touch point of user experience from the perspective of user experience, and propose a multi-latitude model of the touch point of city brand.

• The Research Journal of the Costume Culture
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• v.13 no.5 s.58
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• pp.777-789
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• 2005

Mix & Match Visual Image, appearing in T-shirt one-point graphics, is a new visual image emerged as a result of several trends: development of cutting-edge machinery and computer programs, various needs of consumers, and an international trend of fusion concept. Thus, a concrete research of Mix & Match Visual Images is demanding. This paper studies one-point graphic, which appeared in the SamsungDesignNet, Interfashion Planning, and firstviewkorea, with a focus on apparel T-shirt of women's wear and casual wear from 2001 to 2004. The study shows that the most preferred independent visual image in Mix & Match Visual Images is a typography, and next is in the order of marks, symbols, geometric diagrams and abstract shapes, animals and plants, characters, materials, and collages. As Mix & Match of independent visual images was mainly combined typography with other independent visual images, we need to develop more Mix & Match Visual Images using various independent visual images's mix and match. Then, T-shirt will be one of the most representative items in Korean fashion trend that enable consumers to express their characters, escaping from the old-fashioned concept that T-shirt is just a T-shirt.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.793-795
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• 2020

본 논문에서는 스파이킹 뉴론(Spiking Neuron)들이 쿨롱에너지 포텐셜 (Coulomb Energy Potential)을 가지는 스파이킹 신경회로망에서의 학습알고리즘을 일반화하여 구간연산(Interval Arithmetic)의 학습이 가능한 학습알고리즘을 제안한다. 제안하는 학습알고리즘은 입력 데이터로서 구간(Interval) 데이터와 포인트(Point) 데이터를 모두 학습 할 수 있는 일반화된 학습알고리즘으로서 간단한 컴퓨터 시뮬레이션을 통하여 범위(Lower bound & Upper bound)를 가지는 구간데이터와 포인트데이터의 통합적인 학습이 가능하고 전문가시스템(expert system)에서의 "don't care attributes"의 학습 등에도 활용이 가능함을 보인다.

• Review of KIISC
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• v.27 no.6
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• pp.29-32
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• 2017

현대 사회에서 주요 사회적 이슈가 되는 CCTV, 네트워크 프린터, 스마트 가전기기 등 IoT 장비 해킹 사고의 발생 횟수 및 피해 규모는 지속적으로 증가하고 있다. 최근 침해사고 사례를 살펴보면, 엔드포인트에 해당하는 IoT 장비의 허술한 보안대책으로 인하여 악성코드 설치 및 실행을 탐지하지 못한 피해가 대부분이다. 이로 인해 IoT 장비에 대한 악성 프로세스 실행 제어 제품이 개발되어 도입되는 추세이지만, 아직까지 안전성 평가에 대한 연구가 부족한 실정이다. 따라서 본 논문에서는 IoT 장비에 대한 악성 프로세스 실행 제어 제품의 기본 보안요구사항을 식별하고, 필요한 시험항목과 시험 시 유의사항에 대해 제안한다.

• Korean Journal of Head & Neck Oncology
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• v.33 no.1
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• pp.1-5
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• 2017

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer globally with high morbidity and mortality. Immune surveillance is well recognized as an important mechanism to prevent development or progression of HNSCC. HNSCC can escape the immune system through multiple mechanisms including development of tolerance in T cells and inhibition of T-cell-related pathways, generally referred to as checkpoint inhibitors. Recent clinical trials have demonstrated a clear advantage in advanced HNSCC patients treated with immune checkpoint blockade. Right at the front of the new era of immunotherapy, we will review current knowledge of immune escape mechanisms and clinical implication for HNSCC.

• Journal of the Korean Society of Costume
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• v.55 no.8 s.99
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• pp.15-29
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• 2005

In these days, T-shirt is not only the simple wearing goods but also the suggestive communication, which is not showed outward as well as being intended. Also, it indicates expression of contemporary sensitive living, expression of substantial oneself, and the effective commercial promotion fer advertising fashion brand and promoting the object's sale. Following the above concept, the aim of this study is to understand the outstanding tendency of ' The T-shirt one-point graphic's functions and visual image ', which is appeared after 2001 in the fashion industry's commercial aspects. The visual image's applicative rate of the T-shirt one point graphic is the following; The best applicative rate on T-shirt one- point graphic is the visual image using the mix & match technique shown 42.8 percent applicative rate. The second one is the visual image using the typography shown 38.7 percent. The third one is the visual image using the animals and plants shown 8.5 percent. The fourth one is the visual image using the person's character shown 3.8 percent. The fifth one is the visual image using the geometry shown 2.4 percent. The least one is the visual image using the cartoon character shown 1.6 percent. On the other hand, another important function of t-shirt one-point graphic is the following; 1, The essential function as t-shirt design factor. 2, The promotional function as brand image marketing and brand advertisement. 3. The communicative function as discriminative strategy of object. 4. The achievable function as value added goods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.449-451
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• 2021

Cyber-attacks targeting endpoints have developed sophisticatedly into targeted and intelligent attacks, Advanced Persistent Threat (APT) targeting the Industrial Internet of Things (IIoT) has increased accordingly. Machine learning-based Endpoint Detection and Response (EDR) solutions combine and complement rule-based conventional security tools to effectively defend against APT attacks are gaining attention. However, universal EDR solutions have a high false positive rate, and needs high-level analysts to monitor and analyze a tremendous amount of alerts. Therefore, the process of optimizing machine learning-based EDR solutions that consider the characteristics and vulnerabilities of IIoT environment is essential. In this study, we analyze the flow and impact of IIoT targeted APT cases and compare the method of machine learning-based APT detection EDR solutions.