• 대한간호학회지
• /
• 제34권5호
• /
• pp.881-890
• /
• 2004

Purpose: The purpose of this study was to explore women caregivers' lived experiences in caring at home for a family member with dementia and to identify conditions that oppress women in the context of family caregiving. Method: This study was conducted within the feminist perspectives using qualitative secondary data. Ten secondary data conveying self reflective contents were selected from the 25 original data obtained in 1999 to 2000. Result: Six themes that emerged from the qualitative thematic content analysis were; androcentric view of family caregiving, undervalued family caregiving by the family members, Self rationalization in the context of family caregiving, family-centric care mechanism, exemplary caring within the family context, and inter-familial relationships among women. Conclusion: The main focus of feminist research is to provide empowerment for the women, research participants and to bring about social change of oppressive constraint through some actions. On the basis of the research findings, therefore, action strategies from feminist perspectives were suggested in some aspects of health care delivery sectors, nursing education and research sectors, and administrative sectors.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 2010년도 정기 학술대회
• /
• pp.238-241
• /
• 2010

This paper proposed an approach to integrate bridge condition assessment related information with a 3D bridge model to visualize bridge condition assessment information in the 3D bridge model. In this approach, bridge information model plays a centric role in the data access and realizes the integration of bridge initial design and historical bridge maintenance records. Behind the bridge information model is a rational database. After the system requirements for this approach, several IFC data model extensions are suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권10호
• /
• pp.4054-4071
• /
• 2015

Named-Data Networking (NDN) is one of the promising approaches for the Future Internet to cope with the explosion and current usage pattern of Internet traffic. Content provider mobility in the NDN allows users to receive real-time traffic when the content providers are on the move. However, the current solutions for managing these mobile content providers suffer several issues such as long handover latency, high cost, and non-optimal routing path. In this paper, we survey main approaches for provider mobility in NDN and propose an optimal scheme to support the mobile content providers in the large-scale NDN domain. Our scheme predicts the movement of the provider and uses state information in the NDN forwarding plane to set up an optimal new routing path for mobile providers. By numerical analysis, our approach provides NDN users with better service access delay and lower total handover cost compared with the current solutions.

• 한국멀티미디어학회논문지
• /
• 제17권5호
• /
• pp.590-600
• /
• 2014

In the wireless sensor network environment, clustering scheme has a problem that a large amount of energy is unnecessarily consumed because of frequently occurred entire re-clustering process. Some of the studies were attempted to improve the network performance by getting rid of the entire network setup process. However, removing the setup process is not worthy. Because entire network setup relieves the burden of some sensor nodes. The primary aim of our scheme is to cut down the energy consumption through minimizing entire setup processes which occurred unnecessarily. Thus, we suggest a re-clustering scheme that considers event detection, transmitting energy, and the load on the nodes. According to the result of performance analysis, our scheme reduces energy consumption of nodes, prolongs the network lifetime, and shows higher data collection rate and higher data accuracy than the existing schemes.

• 한국컴퓨터정보학회논문지
• /
• 제23권9호
• /
• pp.73-80
• /
• 2018

In this paper, we propose a new type of client server environment to improve the architecture vulnerable to hacking in an existing client server environment. On the server side, move the existing Web server to the client side and This is a way for clients to communicate only the data they need and suggests a structure that completely blocks the web attack itself to the server. This can completely prevent a server from being hacked, spreading malicious code and hacking data on a server. It also presents a new paradigm that will not affect servers even if malware is infected with client PCs. This paper validates the proposed environment through BBS (Big Bad Stick) hardware in the form of USB on the client side. This study proof that secure services are provided through encryption communication with server-side security equipment, indicating that this study is a system with new security.

• 한국멀티미디어학회논문지
• /
• 제21권11호
• /
• pp.1353-1361
• /
• 2018

With the availability of real-time educational data collection and analysis techniques, the education paradigm is shifting from educator-centric to data-driven lectures. However, most offline and online education frameworks collect students' feedback from question-answering data that can summarize their understanding but requires instructor's attention when students need additional help during lectures. This paper proposes a content restructure recommendation framework based on collected student feedback. We list the types of student feedback and implement a web-based framework that collects both implicit and explicit feedback for content restructuring. With a case study of four-week lectures with 50 students, we analyze the pattern of student feedback and quantitatively validate the effect of the proposed content restructuring measured by the level of student engagement.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
• /
• 제11권7호
• /
• pp.233-240
• /
• 2022

최근 대부분의 인공지능 연구는 AI 모델 개발에 중점을 두고 있다. 하지만 최근 인공지능 연구가 모델 중심에서 데이터 중심으로 점차 변경되고 이런 추세를 바탕으로 학습데이터의 중요성이 크게 주목 받고 있다. 그러나 학습데이터의 준비과정이 전체 과정의 상당 부분을 차지하고 라벨링 데이터 생성 또한 개발 목적에 따라 다르기 때문에 많은 시간과 노력이 필요하다. 따라서 기존의 미충족을 해결하기 위한 다양한 라벨링 기능을 갖는 도구 개발이 필요하다. 본 논문에서는 의료영상의 라벨링 데이터를 정교하고 빠르게 생성하기 위한 라벨링 시스템에 대해서 기술한다. 이를 구현하기 위해서 Back Projection, GrabCut 기법을 이용한 반자동 방식과 기계학습 모델을 통해서 예측한 자동 방식의 라벨링 기능을 구현하였다. 우리는 제안한 시스템의 라벨링 데이터 생성에 대한 수행시간의 장점을 보였을뿐만 아니라 정확성에 대한 비교평가를 통해 우수성을 보였다. 또한 1,000여명의 환자 영상 데이터셋을 분석하여 근감소증 진단에 남성과 여성에 의미있는 진단지표를 제시하였다.

• 디자인학연구
• /
• 제13권3호
• /
• pp.313-320
• /
• 2000

현재 정보화의 물결은 모든 분야에 지대한 영향을 미치고 있다. 디자인 분야에서도 정보의 단순 사용 단계를 벗어나 체계적으로 디자인 정보를 유지, 관리하여 지식의 축적에 힘을 모아야 할 때이다. 통신 속도의 발전과 압축기술의 발달로 문자 정보 중심의 데이터는 이미지, 동영상 등 멀티미디어 데이터로 발전하고 있으며 이와 관련한 효과적인 정보 활용을 위한 여러 방법론이 필요한 시점에 이른 것이다. 이미지 정보의 가공은 기존의 문헌 정보 위주의 정보 가공 및 축적 방식에서 탈피하여 이미지 정보의 고유 특성 및 활용에 적합한 방식을 연구해야 한다. 본 연구에서는 디자인 이미지 자료를 분석하여 디자인 이미지 자체의 정보 요소를 추출하고 시스템에 적용한 사례를 통해 디자인 이미지 정보의 자료 색인과 구현 체계를 제안하고자 한다

• The Journal of Asian Finance, Economics and Business
• /
• 제7권7호
• /
• pp.475-487
• /
• 2020

The paper aims to facilitate a discussion around how big data technologies and data from citizens can be used to help public administration, society, and policy-making to improve community's lives. This paper discusses opportunities and challenges of big data strategies for government, society, and policy-making. It employs the presentation of numerous practical examples from different parts of the world, where public-service delivery has seen transformation and where initiatives have been taken forward that have revolutionized the way governments at different levels engage with the citizens, and how governments and civil society have adopted evidence-driven policy-making through innovative and efficient use of big data analytics. The examples include the governments of the United States, China, the United Kingdom, and India, and different levels of government agencies in the public services of fraud detection, financial market analysis, healthcare and public health, government oversight, education, crime fighting, environmental protection, energy exploration, agriculture, weather forecasting, and ecosystem management. The examples also include smart cities in Korea, China, Japan, India, Canada, Singapore, the United Kingdom, and the European Union. This paper makes some recommendations about how big data strategies transform the government and public services to become more citizen-centric, responsive, accountable and transparent.

• International journal of advanced smart convergence
• /
• 제8권3호
• /
• pp.46-53
• /
• 2019

When a partitioned structure is derived from a data set using a clustering algorithm, it is not unusual to have a different set of outcomes when it runs with a different order of data. This problem is known as the order bias problem. Many algorithms in machine learning fields try to achieve optimized result from available training and test data. Optimization is determined by an evaluation function which has also a tendency toward a certain goal. It is inevitable to have a tendency in the evaluation function both for efficiency and for consistency in the result. But its preference for a specific goal in the evaluation function may sometimes lead to unfavorable consequences in the final result of the clustering. To overcome this bias problems, the first clustering process proceeds to construct an initial partition. The initial partition is expected to imply the possible range in the number of final clusters. We apply the data centric sorting to the data objects in the clusters of the partition to rearrange them in a new order. The same clustering procedure is reapplied to the newly arranged data set to build a new partition. We have developed an algorithm that reduces bias effect resulting from how data is fed into the algorithm. Experiment results have been presented to show that the algorithm helps minimize the order bias effects. We have also shown that the current evaluation measure used for the clustering algorithm is biased toward favoring a smaller number of clusters and a larger size of clusters as a result.