• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.121-132
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• 2021

This study analyzed the effect of the extracurricular activity management system on user satisfaction. For this purpose, the effects of content, navigation, screen frame, design, interaction, and error handling factors on user satisfaction were analyzed. A survey was conducted on 321 students of K University located in Chungcheongbuk-do, and the research results based on the survey contents are as follows. First, content, navigation, screen frame, interactivity, and error handling, which are major elements of the extracurricular activity management system, showed statistically significant results. Second, interactivity and error handling were found to have the greatest influence on the factors affecting user satisfaction of the extracurricular activity management system. In this study, it was found that the interaction of the whole system including contents is important for continuous improvement of the extracurricular activity management system, and that it has a positive effect on user satisfaction when prompt error handling is possible.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.9
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• pp.629-642
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• 2013

Recently, with the advent of smart phones, it brought many changes in lives of modern people. Especially, application utilizing the sensor information of smart phone, which provides the service adapted by user situations, has been emerged. Sensor data of smart phone can be used for recognizing the user situation, Because it is closely related to the behavior and habits of the user. currently, GPS sensor one of mobile sensor has been utilized a lot to recognize basic user activity. But, depending on the user situation, activity recognition system cannot receive GPS signal, and also not collect received data. So utilization is reduced. In this paper, for solving this problem, we suggest a method of user activity recognition that focused on the accelerometer sensor data using smart phone. Accelerometer sensor is stable to collect the data and it's sensitive to user behavior. Finally this paper suggests a noble approach to use state transition diagrams which represent the natural flow of user activity changes for enhancing the accuracy of user activity recognition.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• Journal of Korean Library and Information Science Society
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• v.43 no.1
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• pp.221-239
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• 2012

The information that has been created according to the complex environment and usage pattern of library user can provide context-aware information service through knowledge structuralization on whether it is a suitable situation for user. Accordingly, the development of a context model for defining the various contexts of library user and for the structuralization of interrelated context information is an essential requirement. This study examined the context concept and context modeling, and utilizing the concept of Activity Theory by Engestrom, the activity model of library user was designed as 1) subject, 2) object, 3) tools, 4) divison of labor, 5) community, and 6) rules. In addition, for the purpose of analyzing the context of library user, activity information was tracked to utilize the Shadow Tracking for observing and recording their forms, and the methodology of CAbAT (Context Analysis based on Activity Theory) was utilized for the collected activity information to analyze the user context model.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.339-341
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• 2012

This paper presents a method for generating an autonomous activity-based diary in the environment including a personal computer (PC). In order to record a user's various tasks in front of a PC, we consider the contextual information such as current time, opened programs, and user interactions. As one modality for the user interaction, a motion sensor was applied to recognize a user's hand gestures in case that the activity is conducted without interaction between the user and the PC. Moreover, we propose a temporal clustering method to recapitulate the sequential and meaningful activity in the stream of extracted PC usage logs. By combining those two processes, we summarize the user activities in the PC environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.36-42
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• 2009

In the mobile device environment, the context-aware computing has been emerging as a core technology of ubiquitous computing. Compared with a desktop computer, a user interface and resource of mobile device is very limited. Traditional desktop-based user interface has been developed on the basis that a user's activity is static state. In contrast, mobile devices are not able to utilize representative desktop-based interaction mechanisms such as a keyboard and mouse, not only because the activity of a user is dynamic state, but mobile devices have limited resources and small LCD display. In this paper, we introduce an intelligent control system for the mobile device that can utility effectively the limited resource and complement the poor user interface by using an accelerometer being able to sense the physical activity and posture. The proposed system can estimate the user activity, static and dynamic states, and posture watching the PDA at the same time, and the proposed intelligent control system as its application, the backlight ON/OFF on the PDA, is run by the result of the user's behavior.

• Journal of Communications and Networks
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• v.15 no.3
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• pp.283-291
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• 2013

In this paper, we propose new multiuser detectors (MUDs) based on compressed sensing approaches for the large-scale multiple antenna systems equipped with dozens of low-power antennas. We consider the scenarios where the number of receiver antennas is smaller than the total number of users, but the number of active users is relatively small. This prior information motivates sparsity-embracing MUDs such as sparsity-embracing linear/nonlinear MUDs where the detection of active users and their symbol detection are employed. In addition, sparsity-embracing MUDs with maximum a posteriori probability criterion (MAP-MUDs) are presented. They jointly detect active users and their symbols by exploiting the probability of user activity, and it can be solved efficiently by introducing convex relaxing senses. Furthermore, it is shown that sparsity-embracing MUDs exploiting common users' activity across multiple symbols, i.e., frame-by-frame, can be considered to improve performance. Also, in multiple multiple-input and multiple-output networks with aggressive frequency reuse, we propose the interference cancellation strategy for the proposed sparsity-embracing MUDs. That first cancels out the interference induced by adjacent networks and then recovers the desired users' information by exploiting the low user activity. In simulation studies for binary phase shift keying modulation, numerical evidences establish the effectiveness of our proposed MUDs exploiting low user activity, as compared with the conventional MUD.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.2
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• pp.61-68
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• 2010

As a result of the growth of mobile devices such as PDA and cellular phone, a user can utilize various digital contents everywhere and anytime. However, mobile devices have the limited resources and interaction mechanisms. This paper introduces the schema for a user activity estimation and its application in order to overcome the poor user interface and limited resource problems. We are able to supplement lacking the user interface of mobile devices by using the user activity estimation proposed in this paper, and its application is a intelligent control interface for the display power on or off which can effectively utility the battery of the mobile device.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.570-575
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• 2013

Enhancing utilization of buildings is gaining in importance in response to a challenging economy; thus, there is a need for a method that analyzes space, user, and user activity in an integrated way to provide project stakeholders with utilization information to support their decision-making about buildings. Conventional methods, such as architectural programming and post-occupancy evaluation, lack a formal relationship between user activity and other information, and therefore, are coarse-grained. This relationship has been formalized by two relatively new methods that provide fine-grained utilization information: workplace planning and space-use analysis. We characterize these two methods with focuses on their usage in different phases (i.e., planning, design, occupancy), required information that needs to be gathered, and the achievement and limitations in terms of three criteria, i.e., consistency, efficiency, and transparency. This characterization would not only help project stakeholders select and use a method that best meets their purposes for enhancing utilization of their buildings, but also provide researchers with promising research topics regarding enhancing utilization of buildings.

• Journal of Korea Multimedia Society
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• v.17 no.4
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• pp.506-513
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• 2014

In recent years, research on user's activity recognition using a smart phone has attracted a lot of attentions. A smart phone has various sensors, such as camera, GPS, accelerometer, audio, etc. In addition, smart phones are carried by many people throughout the day. Therefore, we can collect log data from smart phone sensors. The log data can be used to analyze user activities. This paper proposes an approach to inferring a user's physical activities based on the tri-axis accelerometer of smart phone. We propose recognition method for four activity which is physical activity; sitting, standing, walking, running. We have to convert accelerometer raw data so that we can extract features to categorize activities. This paper introduces a recognition method that is able to high detection accuracy for physical activity modes. Using the method, we developed an application system to recognize the user's physical activity mode in real-time. As a result, we obtained accuracy of over 80%.