• Knowledge Management Research
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• v.14 no.3
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• pp.1-13
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• 2013

This study investigates how relational activities within MNC network affect knowledge transfer and performance of subsidiary. We separated the possible relationships between headquarter and overseas subsidiaries by support level, interaction level, and conflict level, and compared the impact on knowledge transfer, and performance. To understand the knowledge sharing, development and performance, we use structural equation modeling to analyze data from subsidiaries in China.

• Health Policy and Management
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• v.16 no.4
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• pp.68-85
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• 2006

With the competitive environment accelerating in healthcare industry, the hospital network system is considered as one of the strategies for clinical and managerial efficiency. This study was intended to offer a theoretical view on the hospital network system and to analyze the current network status of hospitals in Korea. Specifically, network types were classified based on the criteria modified from previous studies, and were used to describe and compare the scope and intensity of associated activities. The questionnaire survey was conducted with 237 hospitals during the period of December 27 2005 to January 25 2006. Above 90% of tertiary and secondary care hospitals were under the network system, while only 20% of primary care clinics were affiliated. In general, the scope and intensity of network activities was limited. Vertical and/or clinical integration was more common than horizontal and/or managerial integration. Three most frequent types of hospital network systems were clinical-vertical integration (Type A), clinical/managerial-vertical integration(Type B), and clinical/managerial-horizontal /vertical integration (Type C). Such network types differentiated significantly different features of affiliated hospitals and network systems. The affiliation duration to the network system was the only significant factor influencing on the network type. The strategic approach to the network system was emphasized for hospitals to increase the potential advantage of hospital network systems.

• Journal of Families and Better Life
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• v.14 no.1
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• pp.163-176
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• 1996

This study explores the overall social activities of the middle-aged women. The middle-aged married women of this study are the 40-59 years old and having youngest child above 10 years. Their social activities are categorized into work activities leisure avtivities social network with kin friends and neighbors and religious activities. The results are summarized as follows: (1) The work activities of he middle-aged married women are characterized by stable employment preparation of reentry to the job worries of unemployment and preparation of retirement(2) The leisure activities of the middle-aged married women are devided into two styles; family oriented activities and self developing activities. (3) In social networks especially the social relation with neighbor are increased and the relation with kinship tends to be bilineages. (4) Their religious activities are more supported by families than other activities. From he result this study suggests that : (1) The middle-aged m rried women might accept their midlife as a developmental stage. (2) The volunteer activities might be extended throughout the social activities (3) New social education programs for helping women's growth might be developed.

• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.133-143
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• 2011

It seems required to determine what might affect the technological innovation activities of manufacturing companies and what kind of role they could play for them to carry out technological innovation activities in an effective way. The objective of the present study is thus to conduct a depth empirical analysis of the structural relations among business environment, technological innovation activities and performance of manufacturing companies. From the analysis, following outcomes could be drawn: First, with regard to the relationship between business environment and technological innovation activities of manufacturing companies, it has become clear that the external environment is a factor that can influence technological innovation activities such as management of technical property, technological innovation system as well as technical network, while it exercises no impact upon adaptation of manufacturers to new technologies. The internal environment, on the other hand, turns out to have influence on such overall factors of technological innovation activities as management of technical property, technological innovation system, adaptation to new technologies and technical network; and Second, as for the relationship between technological innovation activities and their performance, it has been obvious that management of technical property and technological innovation system, both factors of technological innovation activities, affect the performance of product development and financial achievements of manufacturing companies. Their adaptation to new technologies will also affect their performance of product development as well as financial achievements. These findings suggest that it is important for manufacturing companies to set up an operating system that may be able to upgrade the practical applicability of their technological development activities in an attempt to promote performance of their technological innovation activities.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.234-240
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• 2022

This paper proposes a customized AI exercise recommendation service for balancing the relative amount of exercise according to the working environment by each occupation. WISDM database is collected by using acceleration and gyro sensors, and is a dataset that classifies physical activities into 18 categories. Our system recommends a adaptive exercise using the analyzed activity type after classifying 18 physical activities into 3 physical activities types such as whole body, upper body and lower body. 1 Dimensional convolutional neural network is used for classifying a physical activity in this paper. Proposed model is composed of a convolution blocks in which 1D convolution layers with a various sized kernel are connected in parallel. Convolution blocks can extract a detailed local features of input pattern effectively that can be extracted from deep neural network models, as applying multi 1D convolution layers to input pattern. To evaluate performance of the proposed neural network model, as a result of comparing the previous recurrent neural network, our method showed a remarkable 98.4% accuracy.

• The Journal of Bigdata
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• v.6 no.2
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• pp.109-124
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• 2021

In this paper, the structural characteristics of Industry-University cooperation networks are analyzed using network analysis. Recent studies have shown that technological cooperation and joint research has a positive effect on R&D performance. In order to boost innovation performance, various types of cooperative activities and governmental policy supports for major R&D stakeholders(i.e. universities, laboratories, etc.) are provided. However, despite these efforts, the outcome is still insufficient, so it is time to prepare for a plan to build an innovative network to strengthen university-centered Industry-University cooperation activities. Specifically, this study builds the networks according to the form of Industry-University cooperations(i.e. patent, paper, joint research, and technology transfer), and different types of Industry-University cooperation networks are analyzed from a statistical viewpoint by using QAP correlation and regression analyses. The analysis results show that joint research network is closely related to paper network, and is related to other Industry-University cooperation networks. This study is expected to shed a light on supporting innovation activities such as establishing Industry-University cooperation strategies and discovering cooperative partners necessary for creating new growth engines for universities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.605-608
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• 2010

An Ad-hoc network will operate properly and provide smooth communication when nodes cooperate mutually with each of them having equal authority. Although it is possible to form a network conisting only of authenticated nodes in order to ensure reliability, authentication by itself is not sufficient to remove malicious nodes and their activities jeopardizing the whole network. Detection and prevention of such activities are vital for maintaining a safe and reliable network, but research on this matter is relatively lacking. Hence a suggestion is made on how to detect and prevent malicious or uncooperative ones among the nodes forming a network by a relationship of mutual trust, thereby maintaining safety and stability of the network and improving its processing abilities

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.9-16
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• 2021

This study aims to develop a human activity recognition (HAR) system as a Deep-Learning (DL) classification model, distinguishing various human activities. We solely rely on the signals from a wristband accelerometer worn by a person for the user's convenience. 3-axis sequential acceleration signal data are gathered within a predefined time-window-slice, and they are used as input to the classification system. We are particularly interested in developing a Deep-Learning model that can outperform conventional machine learning classification performance. A total of 13 activities based on the laboratory experiments' data are used for the initial performance comparison. We have improved classification performance using the Convolutional Neural Network (CNN) combined with an auto-encoder feature reduction and parameter tuning. With various publically available HAR datasets, we could also achieve significant improvement in HAR classification. Our CNN model is also compared against Recurrent-Neural-Network(RNN) with Long Short-Term Memory(LSTM) to demonstrate its superiority. Noticeably, our model could distinguish both general activities and near-identical activities such as sitting down on the chair and floor, with almost perfect classification accuracy.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.203-219
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• 2020

The primary purpose of this study is to identify spatial distribution patterns of co-authoring activities in Korean cadastral science. The analysis showed that a small number of researchers played an essential role in the Korean cadastral co-authorship network. In particular, some authors not only had a significant influence on other nodes in the network but also served as intermediaries between researchers. Moreover, the distance between researchers influenced co-authorship decisions to a limited extent. This study differs considerably from previous studies in that it used spatial analysis techniques to identify spatial distribution patterns of co-authoring activities. However, this research is limited in that it applied only 2019 data to determine the spatial distribution pattern of co-authoring activities. We can overcome this limitation if we analyze the spatial distribution patterns of co-authoring activities using multi-year data in future studies.

• International Journal of Contents
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• v.14 no.3
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• pp.27-31
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• 2018

Social network service (SNS) data related to green tourism were used to estimate preferred tour sites and users' interests. Keywords related with green tour activities were employed to search the SNS data. SNS data were collected from Korean blogs such as Naver and Daum from June $1^{st}$ to August $31^{st}$ between 2015 and 2017 using text-mining solution. During the study period, seven hundred and five posts were analyzed. Associated words that frequently co-occurred with keywords were classified into different categories depending on the nature of associated words. Associated words included swimming pools and camping sites (location); experience and swimming pools (attribute); and water play and culture (culture/leisure). Our data suggest that SNS users with experience of green tourism in Korea exhibited interest in green tourism with swimming pools, camping sites, experience, water play and/or culture rather than particular popular sites. Based on the findings, it is recommended that preferred facilities such as swimming pools should be provided at green tourism sites to meet the users' needs and to facilitate green tourism.