• Journal of Information Processing Systems
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• v.10 no.2
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• pp.271-282
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• 2014

The advancement of knowledge society has enabled the social network community (SNC) to be perceived as another space for learning where individuals produce, share, and apply content in self-directed ways. The content generated within social networks provides information of value for the participants in real time. Thus, this study proposes the social network community activity-based content model (SoACo Model), which takes SNC-based activities and embodies them within learning objects. The SoACo Model consists of content objects, aggregation levels, and information models. Content objects are composed of relationship-building elements, including real-time, changeable activities such as making friends, and participation-activity elements such as "Liking" specific content. Aggregation levels apply one of three granularity levels considering the reusability of elements: activity assets, real-time, changeable learning objects, and content. The SoACo Model is meaningful because it transforms SNC-based activities into learning objects for learning and teaching activities and applies to learning management systems since they organize activities -- such as tweets from Twitter -- depending on the teacher's intention.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.16 no.1
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• pp.285-314
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• 2005

The purpose of this study is to review and analyze the overlapping functions and activities of the nationwide scientific and technical information network system This study is helpful for users to gather information and for librarians and nations to reduce wastage of budgets through discarding the duplicated expenses of performing activities of the network systems. The research targets are KISTI and KERIS, which are functioning as the information network systems in the fields of science and technology. The research methods are literary reviews for theory background and analysis of their activities from internet homepages. As a result of the research, it is found and confirmed that there are some overlapping and duplicating functions and activities in the network systems.

• Architectural research
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• v.4 no.1
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• pp.53-61
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• 2002

The typical Critical Path Method (CPM) leaves it to the construction managers to overcome two problems in developing networks. First, the construction manager needs to prepare information on the type of activities and their precedence relations in order to develop a network schedule. Second, he or she can include space information into the network schedule such as the locations where the activities take place, only with difficulty. These two problems make it difficult for an inexperienced person to create a network. The purpose of this paper is to provide construction managers with set equations of creating a network schedule for multiunit projects. A space-resource combined network creation are presented in this paper, which includes equations for generating a list of required activities, their precedence relations, and information on their location. Information on the space (location) and the resource is the required data for this method. Based on this information, this method divides a project into a number of activities so that each activity contains the information on the location where the activity takes place and the principal resource required for that activity. Precedence relations are then obtained from the sequence of space and resource. This method has the potential to reduce human efforts in scheduling activities.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.246-262
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• 2023

The purpose of this study is to identify the major peacekeeping activities that the Korean armed forces has performed from the past to the present. To do this, we collected 692 press releases from the National Defense Daily over the past 20 years and performed topic modeling and social network analysis. As a result of topic modeling analysis, 112 major keywords and 8 topics were derived, and as a result of examining the Korean armed forces's peacekeeping activities based on the topics, 6 major activities and 2 related matters were identified. The six major activities were 'Northeast Asian defense cooperation', 'multinational force activities', 'civil operations', 'defense diplomacy', 'ceasefire monitoring group', and 'pro-Korean activities', and 'general troop deployment' related to troop deployment in general. Next, social network analysis was performed to examine the relationship between keywords and major keywords related to topic decision, and the keywords 'overseas', 'dispatch', and 'high level' were derived as key words in the network. This study is meaningful in that it first examined the topic of the Korean armed forces's peacekeeping activities over the past 20 years by applying big data techniques based on the National Defense Daily, an unstructured document. In addition, it is expected that the derived topics can be used as a basis for exploring the direction of development of Korea's peacekeeping activities in the future.

• Journal of the Korea Safety Management & Science
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• v.5 no.3
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• pp.179-197
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• 2003

Since 1991, so many women's volunteer centers have established in local self governing body or several women's organizations. The aims are to promote and manage women's volunteer activities. For last 12 years, one of aims has been already attained. But the other one is beyond attainment, because there are few network system among women's volunteer centers. For more efficient management of volunteer activities, it is necessary to construct computer network system in every volunteer center. In this paper, we describe current network situation and suggest network construction method of women's volunteer centers.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.223-232
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• 2023

The purpose of this study is to determine the impact of social network sports community consciousness on loyalty and sports attitude. In order to achieve this research purpose, the population of the study was selected as adult men and women over the age of 20 who are active in the social network sports community in 2022. The sampling method used cluster random sampling to select a total of 300 people, 150 men and 150 women, as research subjects. The survey tool used was the questionnaire method, and the questionnaire whose reliability and validity had been verified in previous studies at home and abroad was used by requoting, modifying, or supplementing it to suit the purpose of this study. It was also structured on a 5-point scale. Frequency analysis, factor analysis, reliability analysis, simple regression analysis, and multiple regression analysis were performed on the collected data using the statistical program SPSS Windows 20.0 Version. The results obtained through this process are as follows. First, social network sports community consciousness was found to have a partial effect on loyalty. Second, social network sports community consciousness was found to have a partial effect on sports attitudes. Third, social network sports community loyalty was found to have a partial effect on sports attitudes. Considering these results, various activities such as decision-making process, relationship formation, and opinion expression of modern people are carried out by the O-line community. In addition, while in the past it was a format that led from offline activities to online activities, currently, there are more and more formats that lead from online activities to offline activities. Therefore, modern people's SNS sports community activities provide many experiences, which creates a sense of community and sports attitudes are formed based on this. This can be said to lead to loyal activities.

• The Journal of Information Systems
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• v.15 no.2
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• pp.173-193
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• 2006

This study first conceptualizes and investigates five dimensions of SCM activities, such as organizational capacity, revitalization support collaboration, appraisal and responsibility, and information system activities. Second, this study develops three dimensions of a supply chain structure, and proposes a balanced scorecard (BSC) model in order to measure business performance. And then, this study establishes too research hypotheses as follows: H1. The SCM activities varies with the supply chain structure. H2. The management performance varies with the supply chain structure. In the questionnaire survey for empirical analysis, this study carefully selected 809 of companies in Korea. We conducted a survey by mail and collected 127 data. Out of 127 data we actually used 103 responses for statistical analysis. After conducting statistical analysis, we could find the results as followed: 1) The supply chain structure was classified into three networks through a clustering procedure, such as supply network, conversion network, and distribution network, and these networks were used to testify hypotheses. As a result the effect of SCM activities varies according to three networks and especially, the companies in distribution network were more active than those in supply and conversion networks doing SCM activities. 2) We may conclude that business performance varies with three networks, and distribution network achieves better performance than supply and conversion networks do.

• The Korean Journal of Ecology
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• v.23 no.2
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• pp.75-81
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• 2000

This paper was prepared to have an overview of the Long-Term Ecological Research (LTER ) activities in Korea in order to facilitate further development of Korea LTER Network in the coming 21th century. After the background for the development of the Korea LTER network was reviewed, the network activities of Korea as well as of the world were introduced for sound management and conservation of ecosystems, which can be ultimately carried out by the long-term ecological researches whose results can secure comparability in the dimension of time and space.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.150-161
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• 2018

We propose a novel deep neural network model for detecting human activities in untrimmed videos. The process of human activity detection in a video involves two steps: a step to extract features that are effective in recognizing human activities in a long untrimmed video, followed by a step to detect human activities from those extracted features. To extract the rich features from video segments that could express unique patterns for each activity, we employ two different convolutional neural network models, C3D and I-ResNet. For detecting human activities from the sequence of extracted feature vectors, we use BLSTM, a bi-directional recurrent neural network model. By conducting experiments with ActivityNet 200, a large-scale benchmark dataset, we show the high performance of the proposed DeepAct model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4176-4197
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• 2020

Botnet is a type of dangerous malware. Botnet attack with a collection of bots attacking a similar target and activity pattern is called bot group activities. The detection of bot group activities using intrusion detection models can only detect single bot activities but cannot detect bots' behavioral relation on bot group attack. Detection of bot group activities could help network administrators isolate an activity or access a bot group attacks and determine the relations between bots that can measure the correlation. This paper proposed a new model to measure the similarity between bot activities using the intersections-probability concept to define bot group activities called as B-Corr Model. The B-Corr model consisted of several stages, such as extraction feature from bot activity flows, measurement of intersections between bots, and similarity value production. B-Corr model categorizes similar bots with a similar target to specify bot group activities. To achieve a more comprehensive view, the B-Corr model visualizes the similarity values between bots in the form of a similar bot graph. Furthermore, extensive experiments have been conducted using real botnet datasets with high detection accuracy in various scenarios.