• Journal of the Korean Home Economics Association
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• v.41 no.8
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• pp.97-121
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• 2003

The reciprocal relationship between the interpersonal tie and the internet dependency is focused in the study. Mainly, chi-squire test and ANOVA are used in testing the hypothesized relationship of the internet dependency with the interpersonal tie before and after using internet. The strong relationship with the internet dependency is found in internet's both-directional communicating function such as chatting, game, gambling, etc. The level of internet dependency is high when individual's tie with friends, colleagues, or neighbors is strong; but it is lower when individual's emotional tie with family members is stronger. It is confirmed that excessive usage of internet damages family relationship. Conversely, it is also clear that the emotional support from family members is essential for preventing or enhancing internet dependency. This implies that internet dependency is not an individual problem, but that it should be treated under the consideration of his/her family system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4856-4872
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• 2018

The mobile internet has grown ubiquitous across the globe with the widespread use of smart devices. However, the designs of modern mobile operating systems and their applications limit content retrieval with mobile applications. The mobile internet is not as accessible as the traditional web, having more man-made restrictions and lacking a unified approach for crawling and content retrieval. In this study, we propose an automatic and scalable mobile application content crawler, which can recognize the interaction paths of mobile applications, representing them as interaction graphs and automatically collecting content according to the graphs in a parallel manner. The crawler was verified by retrieving content from 50 non-game applications from the Google Play Store using the Android platform. The experiment showed the efficiency and scalability potential of our crawler for large-scale mobile internet content retrieval.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.16-20
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• 2012

The purpose of this thesis is to develop a performance rating training tool for the time and motion study. It is widely recognized that rating training tools based on films were made several decades ago and introduced to Korea. However, to the best of our knowledge, those films are not used for rating training in Korea any more. Furthermore, although rating is still important method for the efficient operational management study, it is briefly mentioned without any training or exercise. In this paper, we propose a simple rating training tool based on Excel with VBA. The mottoes of our development are the ease of acquisition and trainees' motivation. Test results show that trainees can obtain the concept of rating and the ability of accurate and consistent rating as they play a computer game sitting in front of the personal computer.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.203-211
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• 2020

This study proposes a method for estimating gender and age that is robust to various external environment changes by applying deep learning-based learning. To improve the accuracy of the proposed algorithm, an improved CNN network structure and learning method are described, and the performance of the algorithm is also evaluated. In this study, in order to improve the learning method based on CNN composed of 6 layers of hidden layers, a network using GoogLeNet's inception module was constructed. As a result of the experiment, the age estimation accuracy of 5,328 images for the performance test of the age estimation method is about 85%, and the gender estimation accuracy is about 98%. It is expected that real-time age recognition will be possible beyond feature extraction of face images if studies on the construction of a larger data set, pre-processing methods, and various network structures and activation functions have been made to classify the age classes that are further subdivided according to age.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.3
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• pp.170-177
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• 2010

Poker is a game of imperfect information where competing players must deal with multiple risk factors stemming from unknown information while making the best decision to win, and this makes it an interesting test-bed for artificial intelligence research. This paper introduces a new learning AI algorithm with embedded opponent modeling that can be used for these types of situations and we use this AI and apply it to a poker program. The new AI will be based on several graphs with each of its nodes representing inputs, and the algorithm will learn the optimal decision to make by updating the weight of the edges connecting these nodes and returning a probability for each action the graphs represent.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.189-202
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• 2013

Recently, Smartphone is not only used as a communication medium, but also provide mobile service tool enabling game, internet surfing, DMB, navigation services, and so on. A lot of smartphone's applications are using for our daily lives. The purpose of this study was analyze affecting factors such as innovativeness, Self-Efficacy and Social-Influence on adoption behavior of smartphone application. This survey was carried out with university students. Data were obtained from 293 students who have smartphone. To Find difference among variables, exploratory factor analysis, t-test and multiple regression was carried out with collected data. Result shows that the distinction of sex is significantly difference in innovativeness and self-efficacy. And self-efficacy and social influence are significantly affect to smartpjone adoption. Therefore, self-efficacy and social influence are import consider factors to reconsider marketing strategy for smartphone business.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.389-405
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• 2015

Most traditional database systems exploit a record-oriented model where the attributes of a record are placed contiguously in a hard disk to achieve high performance writes. However, for read-mostly data warehouse systems, the column-oriented database has become a proper model because of its superior read performance. Today, flash memory is largely recognized as the preferred storage media for high-speed database systems. In this paper, we introduce a column-oriented database model based on flash memory and then propose a new column-aware flash indexing scheme for the high-speed column-oriented data warehouse systems. Our index management scheme, which uses an enhanced $B^+$-Tree, achieves superior search performance by indexing an embedded segment and packing an unused space in internal and leaf nodes. Based on the performance results of two test databases, we concluded that the column-aware flash index management outperforms the traditional scheme in the respect of the mixed operation throughput and its response time.

• Korean Journal of Applied Biomechanics
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• v.24 no.4
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• pp.455-461
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• 2014

The purposes of this study were to reveal the kinematic and kinetic difference of hard ground soccer shoe, firm ground soccer shoe and soft ground soccer shoe. Soccer players were shoes of varying stud designs with some preferring the bladed studs while others opting for the conventional studded stud. Statistics were used one way-ANOVA and Tukey's Honestly Significant Difference Method. Seven healthy college soccer players were attended a test. All parameters were recorded using the Zebris system. Spatio-temporal variables were no significant difference. Lateral symmetry was statistically significant differences (p<.05). Vertical GRF parameters were no significant difference. Medial midfoot pressure, lateral midfoot pressure and central forefoot pressure were statistically significant differences (p<.05). This study demonstrates that playing surface significantly affects difference soccer shoes during soccer game. Furthermore, epidemiological investigation is warranted to determine the effects of playing surfaces on sport specific injury mechanisms.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.131-137
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• 2019

This study proposes a method of learning and recognizing the characteristics that are the classification criteria of Hangul using Mask R-CNN, one of the deep learning techniques, to recognize and classify atypical Hangul characters. The atypical characters on the Hangul signboard have a lot of deformed and colorful shapes beyond the general characters. Therefore, in order to recognize the Hangul signboard character, it is necessary to learn a separate atypical Hangul character rather than the existing formulaic one. We selected the Hangul character '닭' as sample data and constructed 5,383 Hangul image data sets and used them for learning and verifying the deep learning model. The accuracy of the results of analyzing the performance of the learning model using the test set constructed to verify the reliability of the learning model was about 92.65% (the area detection rate). Therefore we confirmed that the proposed method is very useful for Hangul signboard character recognition, and we plan to extend it to various Hangul data.

• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2781-2792
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• 2018

From a cognitive perspective, this study investigates the role of emergent leaders in developing team cognition and affecting team performance. With application of the cognitive complexity theory, this study hypothesizes that emergent leaders' cognitive complexity will be positively associated with team cognitive complexity, and that team cognitive complexity will be positively associated with team performance. In addition, team cognitive complexity is hypothesized to mediate the effect of the cognitive complexity of emergent leaders on team performance. To test the research hypotheses, data were obtained from 100 teams comprising a total of 339 undergraduate students who participated in a business simulation game. The findings of this study suggests that the cognitive complexity of emergent leaders is a significant predictor of team cognitive complexity, and that team cognitive complexity is positively related to team performance. Moreover, team cognitive complexity significantly mediates the effect of emergent leaders' cognitive complexity and team performance.