• Journal of Korea Game Society
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• v.18 no.4
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• pp.75-82
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• 2018

With the development of information and communication technology, various methods have been tried to provide learners with a fun educational environment through fun and interest. It is a good example to utilize technologies such as games and robots in education for edutainment and game-based learning. In this study, we propose an intelligent rhythm education system using user data collection and analysis for humanoid robot rhythm generation. To do this, the user selects music and inputs rhythm information according to the selected music. The robot utilization data of this user extracts patterns through collection and analysis. Patterns are based on frequency, and FFT similarity comparison method is applied when past data is insufficient. The proposed method is validated through experiments of kindergarten children.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.1-9
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• 2010

Authoring tools for sketching the motion of characters to be animated have been studied. However the natural interface for sound editing has not been sufficiently studied. In this paper, I present a novel method that sound sample is selected by speaking sound-imitation words(onomatopoeia). Experiment with the method based on statistical models, which is generally used for pattern recognition, showed up to 97% in the accuracy of recognition. In addition, to address the difficulty of data collection for newly enrolled sound samples, the GLR Test based on only one sample of each sound-imitation word showed almost the same accuracy as the previous method.

• Journal of Korea Entertainment Industry Association
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• v.5 no.2
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• pp.77-86
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• 2011

This paper is aimed at analyzing the relationship between users' actions in relation to a SNG (Social Network Game), which mainly targets communities, and the motivations that give rise to such selective actions. The subjects of existing researches on game area have rarely dealt with game users but mainly focused on the studies and utilization of game production technologies; and, in cases of studies on games users, their subjects have been hardly more than observations of users' behaviors in relation to the performance to achieve certain goals or themes of a game; for example, upgrading a character's level or obtaining rewards through "defeat". Therefore, it is necessary to analyze the actions of SNS game users from the perspective of behavioral selections caused by various motivations of human beings rather than approaching from the perspective of problem solving methods. In order to accomplish this goal, fist of all, Lazzaro's People Fun model and motivation theory of SNS users will be analyzed. Secondly, relevant materials from 13 SNG cases will be collected. Games' events and the functional actions of users will be classified. Lastly, the primary actions of SNG users will be classified into 8 different types and motivations - action patterns will be analyzed based on the classified materials.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.851-859
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• 2017

Today, with the advent and development of Social Network Service (SNS), various types of information that have been difficult to observe have been pouring out. Recently, Vertical Social Networking Service (SNS), a service that shares specific interests with users' Vertical Social Networking Service) is emerging as a major research area. Especially, various human, social and spatial characteristics can be observed through geolocation data and social data collected through mobile GPS, and it is used in various studies. In this study, we analyze the social data collected through the image - based vertical SNS Instagram, and measure the user 's experience based on the social media based on the user' s spatial context. Therefore, in this study, we investigate what types of spatial patterns exist between experiential elements of sharing experiences and geographical characteristics through social data, and examine a new model of shared experience structure through extracted data.

• Cartoon and Animation Studies
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• s.36
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• pp.553-572
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• 2014

In this paper, for the evaluation of the ease of a particular Web site (www.appbelt.net), insert the log tracking code for Google Analytics in a page of the Web site to collect behavioral data of visitor and has studied the improvement measures for the problems of the Web site, after the evaluation of the overall quality of the Web site through the evaluation of Coolcheck. These findings set the target value of the company's priority (importance) companies want to influence the direction of the business judgment are set up correctly, and the user's needs and behavior will be appropriate for the service seems to help improvement.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.65-72
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• 2020

Today, the Internet of Things is used in many places, including homes, industrial sites, and hospitals, to give us convenience. Many services generate new value through real-time data collection, storage and analysis as devices are connected to the network. Many of these fields are creating services and applications that utilize sensors and communication functions within IoT devices. However, since everything can be hacked, it causes a huge privacy threat to users who provide data. For example, a variety of sensitive information, such as personal information, lifestyle patters and the existence of diseases, will be leaked if data generated by smarwatches are abused. Development of IoT must be accompanied by the development of security. Recently, Differential Privacy(DP) was adopted to privacy-preserving data processing. So we propose the method that can aggregate health data safely on smartwatch platform, based on DP.

• Journal of Digital Policy
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• v.1 no.1
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• pp.15-20
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• 2022

Recently, the healthcare field is trying to develop a model that can improve service quality by reflecting the requirements of various industrial fields. In this paper, we propose an Internet of Behavior (IoB) environment model that can process users' healthcare information in real time in a 5G environment to improve healthcare services. The purpose of the proposed model is to analyze the user's healthcare information through deep learning and then check the health status in real time. In this case, the biometric information of the user is transmitted through communication equipment attached to the portable medical equipment, and user authentication is performed through information previously input to the attached IoB device. The difference from the existing IoT healthcare service is that it analyzes the user's habits and behavior patterns and converts them into digital data, and it can induce user-specific behaviors to improve the user's healthcare service based on the collected data.

• Knowledge Management Research
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• v.23 no.3
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• pp.259-284
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• 2022

In order to help the understanding of web novel users, this study was intended to quantitatively verify the user's behavioral types according to the characteristics of web novels. For this purpose, the direction of the study proceeded as follows. First, the motives of web novel users were investigated by referring to the motives of other digital content users. In addition, specific behavioral types of users were also collected. As a result, the motivation for using web novels was found to be 'interpersonal relationships and information acquisition with others', 'leisure activities', and 'escape from reality/relieve tension'. After that, the groups were classified as to whether there was a difference between groups according to the motives of use. As a result, the 'hobbies' type, a group with a particularly high motivation for using leisure activities, the 'stress relief' type, a group with very high escapism and tension relief characteristics, and a group with high interpersonal relationships and information acquisition with others The 'communication' type was classified as a 'multipurpose' type with high overall motivation characteristics. Then, in order to find out the specific characteristics between the types, personas were constructed based on the different behavior type data. Through this, the theoretical contribution of this study is meaningful in that it revealed the motives of web novel users. As a practical contribution, the persona was formed by combining the users' motives and behavioral patterns and visualized to be close to the actual representative users. These results are expected to help improve the web novel service by providing useful indicators for actual writers, platform managers, and users.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1477-1484
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• 2015

With the growth of financial industry with smartphone, interest on user authentication using smartphone has been arisen in these days. There are various type of biometric user authentication techniques, but gait recognition using accelerometer sensor in smartphone does not seem to develop remarkably. This paper suggests the method of user authentication using accelerometer sensor embedded in smartphone. Specifically, calibrate the sensor data from smartphone with 3D-transformation, extract features from transformed data and do principle component analysis, and learn model with using gaussian mixture model. Next, authenticate user data with confidence interval of GMM model. As result, proposed method is capable of user authentication with accelerometer sensor on smartphone as a high degree of accuracy(about 96%) even in the situation that environment control and limitation are minimum on the research.

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.706-712
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• 2015

These days, much information is provided as a list of summaries through mobile services. In this regard, users consume information in which they are interested by observing the list and not by expressing their interest explicitly or implicitly through rating content or clicking links. Therefore, to appropriately model a user's interest, it is necessary to detect latent interest content. In this study, we propose a method for reasoning latent interest of a user by analyzing mobile content consumption logs of the user. Specifically, since erroneous reasoning will drastically degrade service quality, a unanimity ensemble method is adopted to maximize precision. In this method, an item is determined as the subject of latent interest only when multiple classifiers considering various aspects of the log unanimously agree. Accurate reasoning of latent interest will contribute to enhancing the quality of personalized services such as interest-based recommendation systems.