• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2767-2780
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• 2016

Video-based human-activity recognition has become increasingly popular due to the prominent corresponding applications in a variety of fields such as computer vision, image processing, smart-home healthcare, and human-computer interactions. The essential goals of a video-based activity-recognition system include the provision of behavior-based information to enable functionality that proactively assists a person with his/her tasks. The target of this work is the development of a novel approach for human-activity recognition, whereby human-body-joint features that are extracted from depth videos are used. From silhouette images taken at every depth, the direction and magnitude features are first obtained from each connected body-joint pair so that they can be augmented later with motion direction, as well as with the magnitude features of each joint in the next frame. A generalized discriminant analysis (GDA) is applied to make the spatiotemporal features more robust, followed by the feeding of the time-sequence features into a Hidden Markov Model (HMM) for the training of each activity. Lastly, all of the trained-activity HMMs are used for depth-video activity recognition.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.86-94
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• 2011

In recent years, there has been a rise in epidemiological evidence suggesting the health benefits of a physically active lifestyle. However, it is not always easy for individuals to personally recognize the optimal conditions for exercise and physical activity. Wearable acceleration-based pedometers have become widely used in estimating the amount of physical activity, and to a limited extent, providing information regarding exercise intensity, but they have never been used to assess adaptation to exercise. In order to realize simultaneous activity monitoring for multiple users exercising outdoors, we developed a prototype wireless local area network (WLAN) based system. In our system, a WLAN is deployed outside, and a user wearing a smart phone and monitoring device exercises freely within the coverage area of the wireless network. By doing so, the developed system is able to monitor the activity of each user andmeasures various parameters including those related to exercise adaptation. In a demonstration experiment, the developed system was evaluated and used to monitor users enjoying a Nordic walk, after which users were immediately able to receive their exercise report. In this paper, we discuss the requirements and issues in developing an activity monitoring system and report the findings we obtained through the demonstration experiment.

• Journal of Fisheries and Marine Sciences Education
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• v.21 no.3
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• pp.347-360
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• 2009

The purpose of this study was to investigate the characteristics of a teacher's questions in each context of musical activity by analyzing those questions in kindergarten music activity qualitatively. The participant in research was a teacher in charge of the class of children aged 7. Analysis was carried out on the data collected for 3 months through participation observance note, recording material, interview material and weekly plan. As a result, the teacher's questions were leaned upon the convergent questions to confirm the reflection of information and the understanding of function in singing and performing activity. On the other hand, the teacher's questions were leaned upon the diffusive questions for the thought of integration of information in composition activity and upon the diffusive questions for representing feeling or image with no relation to musical meaning in appreciation activity. However, the teacher's questions for control were conducted together with one of the questions, the question mentioned ahead. The tacit control question in singing and performing activity and the explicit control question in composition activity were conducted together, and in appreciation activity, the simple questions to lead the class, though not with the purpose to control attention, was conducted together.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.703-706
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• 2007

The real-time monitoring about the activity of the human provides useful information about the activity quantity and an ability. This study developed a system for human physical activity assessment in ambulatory monitoring using portable sensing device combining a tri-axial accelerometer and wireless sensor node. This real-time system is able to identify several postures, posture transitions and movements with classification algorithm. In addition, this system also features fall detection capability. The results of the assessment for evaluating the performance of the system show high identification accuracy.

• Journal of The Korean Society of Integrative Medicine
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• v.2 no.1
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• pp.15-21
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• 2014

Purpose : The aim of this study was to find out differences between muscle activity of quadriceps according to hip angle. Method : 40 healthy adults produced maximum isometric muscle contraction of quadriceps femoris and each part of the quadriceps femoris were measured with a surface EMG in hip joint angle of $90^{\circ}$, $135^{\circ}$, $180^{\circ}$. Result : There was no significant difference between muscle activity of vastus medialis and lateralis according to hip angle. But there was significant difference in muscle activity of rectus femoris and the muscle activity was maximum at 135 degrees of hip angle. Conclusion : In conclusion, maximum muscle activation of rectus femoris is affected by hip angle, and the findings from this study may be helpful for physical therapists in selecting hip position when instructing patients to do Q-setting exercise. So, we suggest that patients perform Q-setting exercise at 135 degrees of hip angle for the best result.

• Journal of Information Management
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• v.42 no.1
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• pp.173-197
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• 2011

As the volunteer activity has become universal, volunteer activities of public libraries have also grown both quantitatively and qualitatively. In this context, this in-depth case study builds a theoretical background on the volunteer activity of public libraries and examines the volunteer activity management of Kwangjin Public Library including its planning, personal management and administration. By so doing, this study aims at enhancing our understanding on the volunteer activity management of public libraries.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.211-220
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• 2023

Surface electromyography (sEMG) is a noninvasive method used to capture electrically muscle activity, which can be easily measured even during exercise. The basic unit of muscle activity is the motor unit, and because an sEMG signal is a superposition of motor unit action potentials, analysis of muscle activity using sEMG should ideally be done from the perspective of motor unit activity. However, conventional techniques can only evaluate sEMG signals based on abstract signal features, such as root-mean-square (RMS) and mean-power-frequency (MPF), and cannot detect individual motor unit activities from an sEMG signal. On the other hand, needle EMG can only capture the activity of a few local motor units, making it extremely difficult to grasp the activity of the entire muscle. Therefore, in this study, a method to visualize the activities of motor units in a single-channel sEMG signal by relocating wavelet coefficients obtained by redundant discrete wavelet analysis is proposed. The information obtained through this method resides in between the information obtained through needle EMG and the information obtained through sEMG using conventional techniques.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.12
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• pp.2280-2286
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• 2007

Information system contains various components, and these components can be categorized into some types. When preparing security level management activity, it is most important to define the target of management activity. And after deciding these targets, security level management activity can be started. This paper defines management targets by dividing information system into some parts, and shows these targets can be managed variously according to operation environments and characteristics.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.1
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• pp.57-64
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• 2015

Activity recognition technology is gaining attention because it can provide useful information follow user's situation. In research of activity recognition before smartphone's dissemination, we had to infer user's activity by using independent sensor. But now, with development of IT industry, we can infer user's activity by using inner sensor of smartphone. So, more animated research of activity recognition is being implemented now. By applying activity recognition system, we can develop service like recommending application according to user's preference or providing information of route. Some previous activity recognition systems have a defect using up too much energy, because they use GPS sensor. On the other hand, activity recognition system which Google released recently (Google Activity Recognition) needs only a few power because it use 'Network Provider' instead of GPS. Thus it is suitable to smartphone application system. But through a result from testing performance of Google Activity Recognition, we found that is difficult to getting user's exact activity because of unnecessary activity element and some wrong recognition. So, in this paper, we describe problems of Google Activity Recognition and propose AGAR(Advanced Google Activity Recognition) applied method to improve accuracy level because we need more exact activity recognition for new service based on activity recognition. Also to appraise value of AGAR, we compare performance of other activity recognition systems and ours and explain an applied possibility of AGAR by developing exemplary program.