• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.133-164
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• 2005

Mobile games have emerged as the most innovative entertainment technology, adding new revenue streams, taking advantage of the potential of wireless applications and service offerings. Mobile games, like any other types of computer game, offer a unique value for users in providing an exciting digital experience in virtual worlds. Players can become empowered through the development of new characters and strategies within games to achieve rewarding successes against the computers and other players. The overall trend for mobile games is towards bigger, more colorful, more involving and exciting contents, which will build upon the developing capabilities of mobile phones and networks in order to bring new styles, concepts and experiences of game play to the users. In this paper, we attempt to investigate the demographic factors which play critical roles in determining the level of playing times; classify mobile gamers based on their motives for playing games; and empirically test differences in their demographic factors and mobile game usage. Statistical results show that significant differences in playing times exist, depending upon their age, gender, mobile device, mobile phone usage, mobile game experiences, and preferred games genres. Applying Factor analysis, we have identified Escape, Social interaction, Challenge and Competition, Fantasy, Diversion and Relaxation, Ease of Accessibility as key motivators for playing mobile games. Additional cluster analysis shows that the categorization of gamers, according to their usage habits and the key motivators for playing, can be made as follows: M-gamers, Multi-gamers and Communication-focused gamers. Further correlation of these grouping with socio-economic data shows the significant differences in gaming habits and patterns of mobile phone use.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.572-578
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• 2017

As the demand of high accuracy positioning for dynamic users increases, Network RTK is actively researched for dynamic users. Network RTK is a system which provides precise positioning in the range of about 50 to 70km radius using carrier phase measurements from several reference stations. By configuring multiple clusters, which provide Network RTK corrections independently, as a single system, it could provide precise positioning for a wider area. In this paper, we have studied how to efficiently operate multiple clusters in the Korean Peninsula. We analyzed the computational load according to the configuration of a multi-cluster system and proposed a method of selecting the main reference station and system infrastructure configuration for efficient operation. In order to analyze the effects of each proposed method, 71 clusters were constructed using the reference stations of the National Geographic Information Institute and simulations were conducted. As a result of the simulation, system computation amount was reduced by 66 % and system configuration cost was reduced by 90 %.

• Korea Journal of Hospital Management
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• v.8 no.1
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• pp.95-111
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• 2003

The purpose of this study was to evaluate the information searching behavior of consumer by type of medical institution. A questionnaire survey was conducted of 1,507 persons who were selected through a multi-stage stratified area cluster sampling in nationwide level, excluding Jeju-Do. Personal survey was conducted through door-to door survey from 27 July to 10 August 1999. The main results of this research was as following; 1. The proportion of information searching of respondents ranged from 91.5-95.2%. Even though the proportion of user in university hospital was slightly high, there was not significant statistically by type of medical institution. In terms of information source, personal informer was most common information source in all type of medical institution. Public informers were more frequently used in university hospital visitors and professional informer in general and university hospital visitors. 2. Comparing to searching intensity, user informer and professional informer's influences were more powerful, but not statistically significant. In analysis of unit influence for information source, written informer or public informer was more powerful in clinic visitor, professional informer and written informer in university hospital visitor. 3. Information which consumer want to know mostly were about on special potential and career of physician. The clinic visitor wanted to know about institutional location and kindness of medical personnel. The university hospital visitor also wanted to know about facilities and convenience of process. Comparing to institution selection criteria of consumers at 1991, quality related criteria were recognized more importantly in outpatient and dental services. But in case of inpatient services, convenience factor was recognized more importantly. In conclusion, the effort for specific marketing plan by type of medical institution should be needed. And more concern on information searching behavior of consumer will be needed.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.77-85
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• 2015

Recently, wireless sensor network(WSN) have been used in various fields to implement ubiquitous computing environment. WSN uses small, low cost and low power sensors in order to collect information from the sensor field. This paper proposes a clustering algorithm for energy efficiency of sensor nodes. The proposed algorithm is based on conventional LEACH, the representative clustering protocol for WSN and it prolongs network and nodes life time using sleep technique and changable transmission mode. The nodes of the proposed algorithm first calculate their clustering participation value based on the distance to the neighbor nodes. The nodes located in high density area will have clustering participation value and it can turn to sleep mode. Besides, proposed algorithm can change transmission method from conventional single-hop transmission to multi-hop transmission according to the energy level of cluster head. Simulation results show that the proposed clustering algorithm outperforms conventional LEACH, especially non-uniformly deployed network.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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• pp.1913-1918
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• 2014

Background: The study is the first of its kind to be conducted in Saudi Arabia (KSA), aiming to analyze the effectiveness of an intervention program in improving the knowledge of oral cancer among the youth. Materials and Methods: A total of 1,051 young Saudis (57% males and 43% females with a mean age of $20.4{\pm}1.98$) were selected using multi-stage cluster sampling. Knowledge assessment was accomplished using a closed-ended questionnaire which was subjected to reliability tests. Prevalence of risk factors in relation to gender was analyzed using the chi-squared test. Effectiveness was calculated by comparing the pre- and post-intervention means, using the two-tailed paired t-test. Multiple logistic regression was employed in order to determine factors associated with awareness of risk habits, signs/symptoms and prevention of oral cancer. The significance level in this study was set at 0.05. Results: Females were seen to be more into the habit of sheesha smoking (3.3% rather than the use of other forms of risk factors. Prevalence of diverse risk factors such as cigarette smoking (20%), sheesha (15.3%), khat (27%) and shamma (9%) was seen among males. Gender and the use of modifiable risk factors among the study sample were significantly (p<0.001) associated with effectiveness of the intervention. The intervention program was highly effective (p<0.001) in improving the knowledge of oral cancer among the youth in Jazan, KSA. Multivariate analysis revealed that age and gender are the most significant factors affecting knowledge. Conclusions: The study gives a direction for further public health initiatives in this oral cancer prone region.

• Safety and Health at Work
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• v.4 no.2
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• pp.111-116
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• 2013

Background: The aim of this study was to evaluate the quality of the Second Korean Working Conditions Survey (KWCS), focusing on its validity and reliability. Methods: The external validity was evaluated by the assessment of sampling procedures and the response rate, in order to investigate the representativeness of the sample. The content validity was evaluated by the assessment of the development of the questionnaire, and the consistency of questions for the selected construct. The test-retest method was used to evaluate the reliability by means of a phone call survey of 30% of the respondents, who were randomly selected. The respondents' satisfaction regarding the survey procedures and interview time were analyzed to evaluate the quality of survey data. Results: The external validity was assured by an acceptable sampling procedure, rigid multi-stage stratified cluster random sampling. The content validity was also guaranteed by a reasonable procedure for the development of the questionnaire with a pretest. The internal consistency of the questions for work autonomy was maintained, with 0.738 of Cronbach's alpha. The response rate of 36% was lower than that of the European Working Conditions Survey (EWCS), with a contact rate of 66%, compared to 76% for the EWCS. The matching rates of the five retested questions were more than 98% reliable. Conclusion: The quality of the second KWCS was assured by the high external and content validity and reliability. The rigid sampling procedure and development of the questionnaire contributed to quality assurance. The high level of reliability may be guaranteed by the sophisticated field survey procedures and the development of a technical manual for interviewers. The technical strategies for a high response rate should be developed for future surveys.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.8-16
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• 2009

The holistic inversion approach for frequency domain airborne electromagnetic data has previously been employed to simultaneously calibrate, process and invert raw frequency-domain data where prior information was available. Analternative formulation has been developed, which is suitable in the case where explicit prior information is not available. It incorporates: a multi-layer vertically-smooth conductivity model; a simplified bias parameterisation; horizontal smoothing with respect to elevation; and cluster computer parallelisation. Without using any prior data, an inversion of 8.0 million data for 3.4 million parameters yields results that are consistent with independently derived calibration parameters, downhole logs and groundwater elevation data. We conclude that the success of the holistic inversion method is not dependent on a sophisticated conceptual model or the direct inclusion of survey-area specific prior information. In addition, acquisition costs could potentially be reduced by employing the holistic approach which largely eliminates the need for high altitude zero-level measurements.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.633-650
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• 2013

All the imputation techniques proposed so far in literature for data imputation are offline techniques as they require a number of iterations to learn the characteristics of data during training and they also consume a lot of computational time. Hence, these techniques are not suitable for applications that require the imputation to be performed on demand and near real-time. The paper proposes a computational intelligence based architecture for online data imputation and extended versions of an existing offline data imputation method as well. The proposed online imputation technique has 2 stages. In stage 1, Evolving Clustering Method (ECM) is used to replace the missing values with cluster centers, as part of the local learning strategy. Stage 2 refines the resultant approximate values using a General Regression Neural Network (GRNN) as part of the global approximation strategy. We also propose extended versions of an existing offline imputation technique. The offline imputation techniques employ K-Means or K-Medoids and Multi Layer Perceptron (MLP)or GRNN in Stage-1and Stage-2respectively. Several experiments were conducted on 8benchmark datasets and 4 bank related datasets to assess the effectiveness of the proposed online and offline imputation techniques. In terms of Mean Absolute Percentage Error (MAPE), the results indicate that the difference between the proposed best offline imputation method viz., K-Medoids+GRNN and the proposed online imputation method viz., ECM+GRNN is statistically insignificant at a 1% level of significance. Consequently, the proposed online technique, being less expensive and faster, can be employed for imputation instead of the existing and proposed offline imputation techniques. This is the significant outcome of the study. Furthermore, GRNN in stage-2 uniformly reduced MAPE values in both offline and online imputation methods on all datasets.

• The Journal of the Korea Contents Association
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• v.19 no.4
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• pp.682-689
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• 2019

This study aims to spatialize the gap between obesity levels through the body mass index, an objective indicator of the level of health among vulnerable people. Thus, areas where the BMI showed cluster patterns with spatial high and low values were extracted and the characteristics of the region were analyzed. The analysis showed that the I statistics for the obesity rate were 0.07 and the z-score was 4.39, confirming spatial autocorrelation. For z-score, it was much larger than the maximum threshold of 2.57. This means that the rate of obesity among the socially vulnerable is regional, and this gap is spatially significant. The results of comparing and analyzing the local environment for these areas of obesity and health care were found to be areas with poor public transportation, less readily available parks, and a concentration of single and multi-generation housing. The analysis results of this study are meaningful in that they provide spatial implications for the health of the socially vulnerable class that previous studies have neglected.

• Progress in Medical Physics
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• v.14 no.2
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• pp.141-148
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• 2003

The purpose of this study is to evaluate the distribution of clusters and blood flow rate in ADHD SPECT brain blood flow images of children using statistical parametric mapping (SPM99). We studied 64 ADHD children (4-15 y, $8.03{\pm}2.57$ y. male/female:52/12) and compared them with a control group of 12 children (6-l7 y, $9.42{\pm}3.37$ y, male/female:8/4). We injected blood flow tracer $^{99m}Tc$-ethylcysteinate dimer (ECD) as a rCBF agent and took blood flow images after 30 min. by SPECT camera. In the case of hyperperfusion of rCBF in the ADHD group, we found 3 clusters clearly separated at the cingulate gyrus, Rt.cerebral occipital lobe and Lt.cerebellar post. lobe, on probability level 0.05 (P<0.05). Thirty-six ADHD patients with average hyperfusion rates between 18.72-19.30% in each cluster had more increase in blood flow than the average perfusion rate at the Rt. cerebral occipital lobe. These levels were influenced by P-value. In the case of hypoperfusion in the ADHD children, 4 decreased clusters on Lt. and Rt. cerebral frontal lobe, Lt. cerebral claustrum and Rt. cerebral, sup. temporal gyrus at P<0.01 can be seen. The average hypoperfusion rates for the ADHD children were 18.41-18.69% in each cluster, which showed more hypopefusion than the average perfusion rate at the Lt. Cerebrum inf. Frontal gyrus. The perfusion rates and the number of patients were not affected by P-value. The result of this study shows significant hyperpefusion clusters at the probability level of P:0.05 and hypoperfusion clusters at P:0.01. The number of ADHD patients in each clusters and the perfusion rate were not affected by P-value.