• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.476-479
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• 2003

The Rough transform (HT) is often used for extracting global features in binary images, for example curve and line segments, from local features such as single pixels. The HT is useful due to its insensitivity to missing edge points and occlusions, and robustness in noisy images. However, it possesses some disadvantages, such as time and memory consumption due to the number of input data and the selection of an optimal and efficient resolution of the accumulator space can be difficult. Another problem of the HT is in the difficulty of peak detection due to the discrete nature of the image space and the round off in estimation. In order to resolve the problem mentioned above, a possibilistic C-means approach to clustering [1] is used to cluster neighboring peaks. Several experimental results are given.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.804-814
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• 2009

In this paper, a novel system for avatar motion controlling by tracking face is presented. The system is composed of three main parts: firstly, LCS (Local Cluster Searching) method based face feature detection algorithm, secondly, HMM based feature points recognition algorithm, and finally, avatar controlling and animation generation algorithm. In LCS method, face region can be divided into many small piece regions in horizontal and vertical direction. Then the method will judge each cross point that if it is an object point, edge point or the background point. The HMM method will distinguish the mouth, eyes, nose etc. from these feature points. Based on the detected facial feature points, the 3D avatar is controlled by two ways: avatar orientation and animation, the avatar orientation controlling information can be acquired by analyzing facial geometric information; avatar animation can be generated from the face feature points smoothly. And finally for evaluating performance of the developed system, we implement the system on Window XP OS, the results show that the system can have an excellent performance.

• Journal of the Korean Magnetics Society
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• v.6 no.2
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• pp.117-121
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• 1996

육각판상 Ba-ferrite의 stacking 현상은 자성도료의 도포 후 자장배향를 행할 때 일어나는 것으로 알려져 있으나 분말의 건식분쇄시에도 일어났다. Edge mill을 사용하여 건식분쇄할 때 치환형 Ba-ferrite 분말의 보자력과 tap density는 거의 비례적으로 증가하였고, 분쇄시간보다는 가해지는 압력에 크게 의존하였다. 이 때 보자력의 증가원인은 분쇄시 생성되는 입자간의 stacking 현상에 기인된 것임을 투과전자현미경 관찰로부터 확인하였다. 분말의 tap density가 증가함에 따라 tape에서 분산초기의 광택도가 크게 감소되어 분산성은 떨어졌으나, 배향도는 tap density 1.3 g/$cm^{3}$에서 최대를 나타내었다. 과도한 건식분쇄에 의해 생성된 강고한 stacked cluster는 자성도료 제조시 분산성과 배향도를 동시에 떨어뜨리는 역할을 함을 알 수 있었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1166-1168
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• 2019

본 논문은 엣지컴퓨팅 환경에서 딥러닝기반 추천모델을 이용한 지능형 디지털 사이니지 플랫폼을 제안한다. 제안하는 플랫폼은 서버와 엣지로 구성되어 있다. 서버는 데이터를 관리하고, 광고추천 모델을 학습시키며, 엣지는 학습된 광고추천 모델을 이용하여 실시간으로 광고될 상품을 결정한다. 광고추천 모델은 상품을 선별하는 단계와 구매확률을 예측하는 단계로 구성되어 있다. 선별단계에서는 DNN에 벡터화된 사용자 기본정보와 상품 메타데이터를 입력하여 구매할 만한 상품을 도출한다. 최종적으로 군집의 예측된 구매확률을 이용하여 가장 적합한 광고를 선정한다. 제안하는 시스템은 서버와 통신하지 않고 엣지에서 학습된 모델로 광고를 결정한다. 이를 다수의 사용자에게 즉각적인 반응을 필요로 하는 디지털 사이니지에 적용했다.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.5
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• pp.25-34
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• 2021

Increase in avian species richness is one of the important issues of urban biodiversity policies, since it can promote diverse ecosystem services such as seed dispersal, education, and pollination. However, though human disturbance can significantly affect avian species richness, there are limited studies on the way to reflect the dynamics of floating population. Therefore, this study analyzed the spatial relationship between avian species richness, floating population, and vegetation cover using telecommunications information to identify the areas that requiring targeted monitoring and restoration action. Bivariate Local Moran's I was applied to identify LISA cluster map that showing representative biotopes, which reflect significant spatial relationship between species richness and population distribution. Edge density and distribution of ndvi were identified for evaluating relative adequacy of selected biotopes to strengthen the robust biodiversity network. This study offers insight to consider human disturbance in spatial context using innovative big data to increase the effectiveness of urban biodiversity measures.

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.616-631
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• 2019

With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.202-210
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• 2019

The obstacles modeling is a fundamental and significant issue for path planning and automatic navigation of Unmanned Surface Vehicle (USV). In this study, we propose a novel obstacles modeling method based on high resolution satellite images. It involves two main steps: extraction of obstacle features and construction of convex hulls. To extract the obstacle features, a series of operations such as sea-land segmentation, obstacles details enhancement, and morphological transformations are applied. Furthermore, an efficient algorithm is proposed to mask the obstacles into convex hulls, which mainly includes the cluster analysis of obstacles area and the determination rules of edge points. Experimental results demonstrate that the models achieved by the proposed method and the manual have high similarity. As an application, the model is used to find the optimal path for USV. The study shows that the obstacles modeling method is feasible, and it can be applied to USV path planning.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.84-85
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• 2023

본 논문에서는 엣지 컴퓨팅에서 다수의 스마트 카메라를 클러스터링하여 협업하며 로드 밸런싱을 수행하는 알고리즘을 제안하고, Kubernetes 환경에서 시뮬레이션을 통해 여러 가지 상황에서 성능을 검증하여 엣지 컴퓨팅에서의 AI 연산을 보다 효율적으로 수행할 수 있는 방법을 제시한다.