• Journal of Contemporary Eastern Asia
• /
• 제16권1호
• /
• pp.69-81
• /
• 2017

This study examines how South Korean governments responded to the outbreak of Middle East Respiratory Syndrome Coronavirus (MERS) using the adaptive governance framework. As of November 24, 2015, the MERS outbreak in South Korea resulted in the quarantine of about 17,000 people, 186 cases confirmed, and a death of 38. Although the national government had overall responsibility for MERS response, there is no clear understanding of how the ministries, agencies, and subnational governments take an adaptive response to the public health crisis. The paper uses the adaptive governance framework to understand how South Korean governments respond to the unexpected event regarding the following aspects: responsiveness, public learning, scientific learning, and representativeness of the decision mechanisms. The framework helps understand how joint efforts of the national and subnational governments were coordinated to the unexpected conditions. The study highlights the importance of adaptive governance for an effective response to a public-health related extreme event.

• 지식경영연구
• /
• 제19권1호
• /
• pp.133-146
• /
• 2018

This study develops an Education framework for users who need public open data for workplace etiquette education in a timely manner by mobile application. It facilitates utilizing efficiently Workplace etiquette contents that scattered in various platforms such as blogs, Youtube and web-sites run by private education agencies. Furthermore, it makes Public open data for workplace etiquette through gathering 'metadata', which is a comprehensive source of workplace etiquette. Accordingly, framework changes recognition about necessity of workplace etiquette education positively and suggests method that can promote effective workplace etiquette education. If the system in the study can provide public open data of workplace etiquette education, many young job applicants and workers will have a proper perception on it and sound workplace etiquette culture will be settled in the companies. Public data has been rising as a vital national strategic asset these days. Hopefully the public data will pave a way to discover the blue ocean in the market and open up a new type of businesses.

• ETRI Journal
• /
• 제42권6호
• /
• pp.965-975
• /
• 2020

This paper proposes a new framework for the development and deployment of honeypots for evolving malware threats. As new technological concepts appear and evolve, attack surfaces are exploited. Internet of things significantly increases the attack surface available to malware developers. Previously independent devices are becoming accessible through new hardware and software attack vectors, and the existing taxonomies governing the development and deployment of honeypots are inadequate for evolving malicious programs and their variants. Malware-propagation and compromise methods are highly automated and repetitious. These automated and repetitive characteristics can be exploited by using embedded reinforcement learning within a honeypot. A honeypot for automated and repetitive malware (HARM) can be adaptive so that the best responses may be learnt during its interaction with attack sequences. HARM deployments can be agile through periodic policy evaluation to optimize redeployment. The necessary enhancements for adaptive, agile honeypots require a new development and deployment framework.

• 한국콘텐츠학회논문지
• /
• 제10권8호
• /
• pp.1-10
• /
• 2010

가상교육 환경에 있어서 보다 효과적인 지식 전달을 위해서는 시청각적 정보에만 의존하는 기존의 학습 매체에서 탈피하여 상황에 맞는 촉각 피드백이 포함된 '실감형 교과서'의 도입이 필요하다. 그러나 저작 및 재생 환경상의 제약으로 인해 실감형 교과서를 위한 학습 콘텐츠의 확보와 활용은 아직 요원한 실정이다. 우리는 이러한 문제점에 착안하여 실감형 교과서를 위한 접근성 높은 멀티모달 학습 콘텐츠 저작 및 재생 프레임워크를 제안하였다. 본 프레임워크는 직관적인 콘텐츠 저작을 위한 스크립트 포맷과 이를 재생하기 위한 콘텐츠 재생부로 구성되어 있다. 스크립트 규격 정의 단계에서는 학습 콘텐츠에 요구되는 요소들을 규명하고 이를 반영한 XML 기반의 메타언어를 정의하였다. 그리고 콘텐츠 재생부는 작성된 콘텐츠를 해석하고 사용자로부터의 입력에 대응하여 시각 및 촉각 렌더링 루프를 통해 사용자에게 멀티모달피드백을 제공하도록 설계되었다. 이렇게 제안된 내용을 바탕으로 프로토타입을 구현하고 사용자 평가를 수행하여 본 프레임워크의 효용성을 검증하는 한편 앞으로의 개선 방향에 대해 논의하였다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제10권9호
• /
• pp.339-348
• /
• 2021

최근 소프트웨어 결함 예측 연구는 교차 프로젝트 간의 결함 예측뿐만 아니라 교차 버전 프로젝트 간의 결함 예측 또한 이루어지고 있다. 종래의 교차 버전 결함 예측 연구들은 WP(Within-Project)로 가정한다. 하지만, CV(Cross-Version) 환경에서는 프로젝트 버전 간의 분포 차이의 중요성을 고려한 연구들이 없다. 본 연구에서는 다른 버전 간의 분포 차이까지 고려하는 자동화된 베이지안 최적화 프레임워크를 제안한다. 이를 통해 분포차이에 따라 전이 학습(Transfer Learning) 수행 여부를 자동으로 선택하여 준다. 해당 프레임워크는 버전 간의 분포 차이, 전이 학습과 분류기(Classifier)의 하이퍼파라미터를 최적화하는 기법이다. 실험을 통해 전이 학습 수행 여부를 분포차 기준으로 자동으로 선택하는 방법이 효과적이라는 것을 알 수 있다. 그리고 최적화를 이용하는 것이 성능 향상에 효과가 있으며 이러한 결과 소프트웨어 인스펙션 노력을 감소할 수 있다는 것을 확인할 수 있다. 이를 통해 교차 버전 프로젝트 환경에서 신규 버전 프로젝트에 대하여 효과적인 품질 보증 활동 수행을 지원할 것으로 기대된다.

• 한국과학교육학회지
• /
• 제30권5호
• /
• pp.647-667
• /
• 2010

이 연구의 목적은 과학 교수-학습프로그램을 평가하기 위한 두뇌기반 분석틀을 개발하는 것이다. 분석틀의 개발을 위해, 이 연구는 과학 교수-학습과 관련된 선행연구들로부터 교수-학습 프로그램의 분석항목을 3가지로 범주화 하였다: 인지, 동기, 감성. 첫 번째로, 각 항목에 관련된 두뇌활성 영역을 파악하기위하여 과학수업과 관련된 두뇌 기능에 대한 93편의 뇌과학 문헌들을 분석하였다. 두 번째로, 두뇌의 해부학적 영역별로 범주화된 연구결과를 바탕으로 과학 교수-학습프로그램 분석을 위한 분석틀을 제작하였다. 분석틀의 제작은 R & D 방법을 따랐다. 그 결과, 두뇌활성 결과들은 대뇌 피질, 보상계, 변연계의 세 영역으로 범주화되어 나타났다. 이를 바탕으로 개발된 두뇌기반 과학 교수-학습 프로그램 분석틀인 'CORE Brain Map'은 양측 배외측전전두피질, 양측 복외측 전전두피질, 양측 안와전두피질, 전대상이랑, 양측 두정피질, 양측 측두피질, 양측 후두피질, 양측 해마, 양측 편도체, 양측 측좌핵, 양측 선조체 그리고 중뇌영역으로 구성된다. 두뇌기반 과학 교수-학습프로그램 분석틀은 다양한 과학 교수-학습프로그램의 분석 및 진단에 활용 가능할 것으로 전망된다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제15권4호
• /
• pp.217-231
• /
• 2015

A novel fuzzy learning framework that employs fuzzy inference to solve the problem of Multiple Instance Learning (MIL) is presented. The framework introduces a new class of fuzzy inference systems called Multiple Instance Mamdani Fuzzy Inference Systems (MI-Mamdani). In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are known but not those of individual instances. MIL deals with learning a classifier at the bag level. Over the years, many solutions to this problem have been proposed. However, no MIL formulation employing fuzzy inference exists in the literature. Fuzzy logic is powerful at modeling knowledge uncertainty and measurements imprecision. It is one of the best frameworks to model vagueness. However, in addition to uncertainty and imprecision, there is a third vagueness concept that fuzzy logic does not address quiet well, yet. This vagueness concept is due to the ambiguity that arises when the data have multiple forms of expression, this is the case for multiple instance problems. In this paper, we introduce multiple instance fuzzy logic that enables fuzzy reasoning with bags of instances. Accordingly, a MI-Mamdani that extends the standard Mamdani inference system to compute with multiple instances is introduced. The proposed framework is tested and validated using a synthetic dataset suitable for MIL problems. Additionally, we apply the proposed multiple instance inference to fuse the output of multiple discrimination algorithms for the purpose of landmine detection using Ground Penetrating Radar.

• 국제학술발표논문집
• /
• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
• /
• pp.241-248
• /
• 2011

Past theories on construction price formation have been shown to be inadequate in terms of their ability to represent real-life industry practice and price formation predictability. In this paper, we develop a theoretical framework on construction price formation that integrates four theories within the domains of marketing, learning, resource management and economics. These are: (i) marketing pricing theory; (ii) experiential and organisational learning theory; (iii) resourced based theory and (iv) microeconomic theory. Utilising pricing theory from marketing, a foundation is able to be created for the procedure of construction price formation, namely: (i) identifying the objectives; (ii) assessing the tendering environment; and (iii) formation of the price. However, understanding contractors' decision making process in tender pricing as such can be attributed to theories of experiential learning and consequently organisational learning. It is argued that contractors do learn from past experience and history and are able to adapt to different market conditions. In formation of the price, neoclassical microeconomics is able to provide additional insight in terms of the supply and demand model and consideration of the market conditions. Interrelated with the microeconomic concept of scarcity, we appreciate that contractors do have limited resources that affect their tender pricing decisions and resource based theory is used to substantiate this. Integrating the various theories as a unity allows the broader reality to be visualised and add to our theoretical understanding of construction price formation.

• ETRI Journal
• /
• 제45권6호
• /
• pp.963-973
• /
• 2023

Non-orthogonal multiple access (NOMA) is considered a key candidate technology for next-generation wireless communication systems due to its high spectral efficiency and massive connectivity. Incorporating the concepts of multiple-input-multiple-output (MIMO) into NOMA can further improve the system efficiency, but the hardware complexity increases. This study develops an energy-efficient (EE) subchannel assignment framework for MIMO-NOMA systems under the quality-of-service and interference constraints. This framework handles an energy-efficient co-training-based semi-supervised learning (EE-CSL) algorithm, which utilizes a small portion of existing labeled data generated by numerical iterative algorithms for training. To improve the learning performance of the proposed EE-CSL, initial assignment is performed by a many-to-one matching (MOM) algorithm. The MOM algorithm helps achieve a low complex solution. Simulation results illustrate that a lower computational complexity of the EE-CSL algorithm helps significantly minimize the energy consumption in a network. Furthermore, the sum rate of NOMA outperforms conventional orthogonal multiple access.

• 한국IT서비스학회지
• /
• 제18권5호
• /
• pp.85-97
• /
• 2019

In this study, we developed the Field-Experiential Learning Framework Using the Location Based Mobil-learning System (LBMS) and it is mobile Augmented Reality (AR) for smart learning system which is advanced e-learning. AR is technology that seamlessly overlays computer graphics on the real world. LBMS-AR has become widely available because of mobile AR. Mobile AR is possible to get information from real world anytime, anywhere. Nowadays, there are various areas using AR such as entertainment, marketing, location-based AR. We analysed the result of survey and implemented the functions. Also, for survey about application's effectiveness, we have focus group interview (FGI). Then we demonstrated and explained the application to them. The result of survey about application's effectiveness shows that application have higher utilization in education area. One of the most promising areas is education. AR in education shows lifelike images to users for realism. It's a good way for improving concentration and attention. We utilize only a beacone for image-based AR without other sensor.