• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.10
• /
• pp.386-393
• /
• 2018

The Korean military supplies industry tends to become limited in terms of its development to specific areas in line with strategic promotion policies of the local private direct industrial site. However, the relation between base and small cluster is getting lower of the local industrial site. In this study, information related to authorized test reports for munitions was collected through the military quality information system and subjected to social network analysis(SNA). SNA was performed through the relationships among defense quality assurance agencies, test institutions, contracts and cooperative firms through UCINET's Two-Mode Network. In the field of weapon systems, the median technology industry, and the test analysis dependent are high in Seoul, so the analysis revealed that strengthening the infrastructure for test analysis is needed. Also, it was deemed necessary for government-driven political support. Besides, the field support system was efficiently utilizing a relatively local test analysis. It was analyzed that they are overcoming the regional boundaries of small clusters by strategically changing their contract and cooperative firms' status. The research found some spatial inconsistencies between base and small clusters in the military supplies industry, and it was judged that a political suggestion was needed.

• Korean Journal of Culture and Social Issue
• /
• v.12 no.5_spc
• /
• pp.29-43
• /
• 2006

With longevity (75 years plus and still increasing) now commonly achievable, the new challenge for individuals and society is less concerned with adding more years to life, though that remains important, and more with adding life to years. To explore the quality of long life more fully, a concept broader than healthy ageing or active ageing is needed. For this purpose, the present article describes a framework of Positive Ageing, also known as Successful Ageing, which views the quality of long life as comprising good health, physical and cognitive functional independence, and meaningful engagement with life. Narrowly defined, it refers to old people ageing well in all these aspects. More broadly defined, it refers to ageing well from midlife on. The framework also identifiesvariables that may affect the process of ageing positively. These variables include the social-cognitive styles of control, humour and future-time perspective on the one hand, and on the other hand, resources based on finance, social network and lifestyle.

• The Journal of the Korea Contents Association
• /
• v.17 no.11
• /
• pp.60-69
• /
• 2017

Recently, with the rapid development of internet and smart phones, social network services that can create and share various information through relationships among users have been actively used. Especially as the amount of information becomes enormous and unreliable information increases, expert recommendation that can offer necessary information to users have been studied. In this paper, we propose an expert recommendation scheme considering users' interests, human relations, and response quality. The users' interests are evaluated by analyzing their past activities in social network. The human relations are evaluated by extracting the users who have the same interesting fields. The response quality is evaluated by considering the user's response speed and response contents. The proposed scheme determines the user's expert score by combining the users' interests, the human relations, and the response quality. Finally, we recommend proper experts by matching queries and expert groups. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• Journal of Digital Convergence
• /
• v.15 no.9
• /
• pp.415-425
• /
• 2017

The purpose of this study is to examine the effect of perceived enjoyment and user's characteristics on the intention of continuous use when users play social network games on a mobile device. In addition, the study empirically investigated the mediating effect of flow experience in this process. To fulfill the purpose, this study conducted a survey on 244 college students and collected data. When the collected data was analyzed, the followings were known. First, perceived enjoyment, and both self-efficacy and innovation propensity of user's characteristics turned out to have a positive (+) effect on the intention of continuous use in mobile social network game. Second, in the process, it was known that flow experience played a mediating role. These findings are expected to be useful data in developing game contents of high quality or making a marketing strategy for continuous improvement of online social network game industry. In addition, future studies are expected to generalize the research to various age groups.

• Journal of Intelligence and Information Systems
• /
• v.20 no.2
• /
• pp.1-17
• /
• 2014

The proliferation of using social media and social networking services affects the lifestyles of people. These phenomena are useful to companies that wish to promote and advertise new products or services through these social media; these social media venues also come with large amounts of user data. However, studies that analyze the data of social media within the perspective of information exchanges are hard to find. Much of the previous research in this area is focused on measuring the performance of exhibitions using general statistical approaches and piecemeal measures. Therefore, in this study, we want to analyze the characteristics of information exchanges in social media by using Twitter data sets, which are relating to the Mobile World Congress (MWC). Using this methodology provides exhibition organizers and exhibitors to objectively estimate the effect of social media, and establish strategies with social media use. Through a user network analysis, we additionally found that social attributes are as important as the popular attribute regarding the sustainability of information exchanges. Consequently, this research provides a network analysis using the data derived from the use of social media to communicate information regarding the MWC exhibition, and reveals the significance of social attributes such as the degree and the betweenness centrality regarding the sustainability of information exchanges.

• Journal of Korean Academy of Nursing
• /
• v.46 no.1
• /
• pp.50-58
• /
• 2016

Purpose: The purpose of this study was to identify the knowledge structure of cancer survivors. Methods: For data, 1099 articles were collected, with 365 keywords as a Noun phrase extracted from the articles and standardized for analyzing. Co-occurrence matrix were generated via a cosine similarity measure, and then the network analysis and visualization using PFNet and NodeXL were applied to visualize intellectual interchanges among keywords. Results: According to the result of the content analysis and the cluster analysis of author keywords from cancer survivors articles, keywords such as 'quality of life', 'breast neoplasms', 'cancer survivors', 'neoplasms', 'exercise' had a high degree centrality. The 9 most important research topics concerning cancer survivors were 'cancer-related symptoms and nursing', 'cancer treatment-related issues', 'late effects', 'psychosocial issues', 'healthy living managements', 'social supports', 'palliative cares', 'research methodology', and 'research participants'. Conclusion: Through this study, the knowledge structure of cancer survivors was identified. The 9 topics identified in this study can provide useful research direction for the development of nursing in cancer survivor research areas. The Network analysis used in this study will be useful for identifying the knowledge structure and identifying general views and current cancer survivor research trends.

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.238-246
• /
• 2021

The rapid rise of the Internet and social media has resulted in a large number of text-based reviews being placed on sites such as social media. In the age of social media, utilizing machine learning technologies to analyze the emotional context of comments aids in the understanding of QoS for any product or service. The classification and analysis of user reviews aids in the improvement of QoS. (Quality of Services). Machine Learning algorithms have evolved into a powerful tool for analyzing user sentiment. Unlike traditional categorization models, which are based on a set of rules. In sentiment categorization, Bidirectional Long Short-Term Memory (BiLSTM) has shown significant results, and Convolution Neural Network (CNN) has shown promising results. Using convolutions and pooling layers, CNN can successfully extract local information. BiLSTM uses dual LSTM orientations to increase the amount of background knowledge available to deep learning models. The suggested hybrid model combines the benefits of these two deep learning-based algorithms. The data source for analysis and classification was user reviews of Indian Railway Services on Twitter. The suggested hybrid model uses the Keras Embedding technique as an input source. The suggested model takes in data and generates lower-dimensional characteristics that result in a categorization result. The suggested hybrid model's performance was compared using Keras and Word2Vec, and the proposed model showed a significant improvement in response with an accuracy of 95.19 percent.

• The Journal of Korean Association of Computer Education
• /
• v.4 no.2
• /
• pp.13-20
• /
• 2001

To solve modern social problems, it is important that improve the democratic citizenship quality of people. This quality includes the rational and democratic problem-solving capacity, decision-making capacity, democratic skills and attitudes such as human dignity, dialogue, compromise. To use an educational network simulation game that has the merits of game, simulatio and network will help children to improve the democratic citizenship educaiton. This study explorers the structure, flow, system, database, interface and teaching-learning tool for this educational network simulation game.

• Journal of KIISE:Databases
• /
• v.37 no.6
• /
• pp.343-350
• /
• 2010

We can get answers we want to know via questioning in Knowledge Search Service (KSS) based on Q&A Community. However, it is getting more difficult to find credible documents in enormous documents, since many anonymous users regardless of credibility are participate in answering on the question. In previous works in KSS, researchers evaluated the quality of documents based on textual information, e.g. recommendation count, click count and non-textual information, e.g. answer length, attached data, conjunction count. Then, the evaluation results are used for enhancing search performance. However, the non-textual information has a problem that it is difficult to get enough information by users in the early stage of Q&A. The textual information also has a limitation for evaluating quality because of judgement by partial factors such as answer length, conjunction counts. In this paper, we propose the QualityRank algorithm to improve the problem by textual and non-textual information. This algorithm ranks the relevant and credible answers by considering textual/non-textual information and user centrality based on Social Network Analysis(SNA). Based on experimental validation we can confirm that the results by our algorithm is improved than those of textual/non-textual in terms of ranking performance.

• Research in Community and Public Health Nursing
• /
• v.29 no.4
• /
• pp.429-439
• /
• 2018

Purpose: The aim of this study is to identify core keyword of frailty research in the past 35 years to understand the structure of knowledge of frailty. Methods: 10,367 frailty articles published between 1981 and April 2016 were retrieved from Web of Science. Keywords from these articles were extracted using Bibexcel and social network analysis was conducted with the occurrence network using NetMiner program. Results: The top five keywords with a high frequency of occurrence include 'disability', 'nursing home', 'sarcopenia', 'exercise', and 'dementia'. Keywords were classified by subheadings of MeSH and the majority of them were included under the healthcare and physical dimensions. The degree centralities of the keywords were arranged in the order of 'long term care' (0.55), 'gait' (0.42), 'physical activity' (0.42), 'quality of life' (0.42), and 'physical performance' (0.38). The betweenness centralities of the keywords were listed in the order of depression' (0.32), 'quality of life' (0.28), 'home care' (0.28), 'geriatric assessment' (0.28), and 'fall' (0.27). The cluster analysis shows that the frailty research field is divided into seven clusters: aging, sarcopenia, inflammation, mortality, frailty index, older people, and physical activity. Conclusion: After reviewing previous research in the 35 years, it has been found that only physical frailty and frailty related to medicine have been emphasized. Further research in psychological, cognitive, social, and environmental frailty is needed to understand frailty in a multifaceted and integrative manner.