• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.3
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• pp.523-529
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• 2017

In this paper, we propose an efficient sphere decoding scheme that reduces computational complexity by combining receive and transmit ordering techniques in generalized spatial modulation systems, where the indexes of activated transmit antennas as well as the transmit symbols are exploited to transfer information to the receiver. In this scheme, the receive signals are optimally ordered so that the calculation for a candidate solution outside the sphere is terminated early to lower the computational complexity. In addition, the transmit ordering technique is applied to first search for candidate symbols and activated antennas having higher probabilities to further reduce the computational complexity. Simulation results show that the proposed doubly ordered sphere decoding scheme provides the same bit error rate performance with the conventional sphere decoding method and the sphere decoder employing only the receive ordering technique while it requires lower computational complexity.

• Korean Journal of Social Welfare
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• v.62 no.3
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• pp.163-191
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• 2010

The purpose of this study is to explore the factors affecting the welfare needs of the rural marriage migrant females. A survey was conducted on 300 rural marriage migration females using probability sampling and for the analysis stepwise regression was used. The major findings of this study can be summarized as follows. The welfare needs of counselling on husband' behavior problem were higher in cases of worse mental health, better physical health, younger age and lower participation in the meetings with her fellow countrymen. The welfare needs on the children raising and education were relatively higher among the migrant females from Vietnam and younger age. The needs on the job skills training were lower in cases of the migrant females from Philippines, China(the Chinese) and were higher in cases of lower level of family understanding. The welfare needs on the job placement were higher among older and lower community affinity, and were lower in cases of the migrant females from Philippines. The results suggest that the welfare services should be differently provided to the migrant females in reflection of the age, education level, nationality and community resources. Further, the mental health screening test and treatment services for migrant females are needed since the welfare needs increase when the migration females have worse mental health condition.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.27-37
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• 2009

Sensor nodes forming a sensor network have limited energy capacity such as small batteries and when these nodes are placed in a specific field, it is important to research minimizing sensor nodes' energy consumption because of difficulty in supplying additional energy for the sensor nodes. Clustering has been in the limelight as one of efficient techniques to reduce sensor nodes' energy consumption in sensor networks. However, energy saving results can vary greatly depending on election of cluster heads, the number and size of clusters and the distance among the sensor nodes. /This research has an aim to find the optimal set of clusters which can reduce sensor nodes' energy consumption. We use a Genetic Algorithm(GA), a stochastic search technique used in computing, to find optimal solutions. GA performs searching through evolution processes to find optimal clusters in terms of energy efficiency. Our results show that GA is more efficient than LEACH which is a clustering algorithm without evolution processes. The two-dimensional GA (2D-GA) proposed in this research can perform more efficient gene evolution than one-dimensional GA(1D-GA)by giving unique location information to each node existing in chromosomes. As a result, the 2D-GA can find rapidly and effectively optimal clusters to maximize lifetime of the sensor networks.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Journal of Industrial Convergence
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• v.20 no.6
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• pp.27-35
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• 2022

The purpose of this study is to analyze the metaverse-related issues in the news big data from an educational perspective, explore their characteristics, and provide implications for the educational applicability of the metaverse and future education. To this end, 41,366 cases of metaverse-related data searched on portal sites were collected, and weight values of all extracted keywords were calculated and ranked using TF-IDF, a representative term weight model, and then word cloud visualization analysis was performed. In addition, major topics were analyzed using topic modeling(LDA), a sophisticated probability-based text mining technique. As a result of the study, topics such as platform industry, future talent, and extension in technology were derived as core issues of the metaverse from an educational perspective. In addition, as a result of performing secondary data analysis under three key themes of technology, job, and education, it was found that metaverse has issues related to education platform innovation, future job innovation, and future competency innovation in future education. This study is meaningful in that it analyzes a vast amount of news big data in stages to draw issues from an education perspective and provide implications for future education.

• Korean Journal of Culture and Social Issue
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• v.28 no.4
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• pp.691-715
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• 2022

In this study, we investigated the relationship between Finsta use and perceived online social support, self-monitoring, and subjective well-being. Furthermore, we investigated whether the number of Instagram accounts mediates the relationship between self-monitoring and perceived online social support. For this reason, To this end, we conducted an online survey of 396 adults in their 20s. Results indicated that the number of Instagram accounts showed a positive correlation with perceived online social support and self-monitoring, but did not show a significant correlation with subjective well-being. Next, it was found that the higher the level of self-monitoring, the higher the probability of using of Finsta. In addition, the number of Instagram accounts was found to partially mediate the relationship between self-monitoring and perceived online social support. In other words, the higher the self-monitoring was associated with, , the more Instagram accounts were, and many Instagram accounts increased the level of perceived online social support. For the first time in Korea, this study confirmed the relationship between Finsta use and perceived online social support, self-monitoring, and subjective well-being., Also, this study was meaningful because itand explored whether self-monitoring leads to perceived online social support through the number of Instagram accounts. In addition, this studyit has social meaning in that it sheds light on how online interactions are connected to the real world.

• Journal of Science Education
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• v.47 no.2
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• pp.211-224
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• 2023

The purpose of this study is to suggest how to investigate the reliability of the assessment, which consists of items generated by automatic item generation using empirical example data. To achieve this, we analyzed the illustrative assessment data by applying the multivariate generalizability theory, which can reflect the design of responding to different items for each student and multiple error sources in the assessment score. The result of the G-study showed that, in most designs, the student effect corresponding to the true score of the classical test theory was relatively large after residual effects. In addition, in the design where the content domain was fixed, the ranking of students did not change depending on the item types or items. Similarly, in the design where the item format was fixed, the difficulty showed little variation depending on the content domains. The result of the D-study indicated that the original assessment data achieved a sufficient level of reliability. It was also found that higher reliability than the original assessment data could be obtained by reducing the number of items in the content domains of operation, geometry, and probability and statistics, or by assigning higher weights to the domains of letters and formulas, and function. The efficient measurement conditions presented in this study are limited to the illustrative assessment data. However, the method applied in this study can be utilized to determine the reliability and to find efficient measurement conditions for the various assessment situations using automatic item generation based on measurement traits.

• Information Systems Review
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• v.25 no.4
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• pp.89-112
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• 2023

In March 2020, as it was declared a COVID-19 pandemic, various quarantine measures were taken. Accordingly, many changes have occurred in the tourism and hospitality industries. In particular, quarantine guidelines, such as the introduction of non-face-to-face services and social distancing, were implemented in the restaurant industry. For decades, research on restaurant attributes has emphasized the importance of three attributes: atmosphere, service quality, and food quality. Nevertheless, to the best of our knowledge, research on restaurant attributes considering the COVID-19 situation is insufficient. To respond to this call, this study attempted an exploratory approach to classify new restaurant attributes based on understanding environmental changes. This study considered 31,115 online reviews registered in Naverplace as an analysis unit, with 475 general restaurants located in Euljiro, Seoul. Further, we attempted to classify restaurant attributes by clustering words within online reviews through TF-IDF and LDA topic modeling techniques. As a result of the analysis, the factors of "prevention of infectious diseases" were derived as new attributes of restaurants in the context of COVID-19 situations, along with the atmosphere, service quality, and food quality. This study is of academic significance by expanding the literature of existing restaurant attributes in that it categorized the three attributes presented by existing restaurant attributes and further presented new attributes. Moreover, the analysis results have led to the formulation of practical recommendations, considering both the operational aspects of restaurants and policy implications.

• Culinary science and hospitality research
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• v.21 no.6
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• pp.38-48
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• 2015

This study examined the factors that affect the relationship between dessert cafe customer attribute election, relationship quality and behavioral intention. A total of 260 questionnaires were distributed to consumers, of which 250 were deemed suitable for analysis after the removal of 10 unusable responses. In order to perform statistical analyses required by the study, the SPSS 18.0 Statistical Program was employed for frequency analysis, factor analysis, reliability analysis, correlation, and regression analysis. The results of the exploratory factor analysis showed that three factors regarding attributes selection were extracted from all measurements with a KMO of 0.757 and a total cumulative variance of 67.885%, With regard to relationship quality, three factors were extracted with a total cumulative variance of 76.070% and a KMO score of 0.715. One factor for behavioral intention was extracted that accounted for a total cumulative variance of 66.254% and a KMO score of 0.771. All factors were significant to 0.000 and the correlation between variables was significant. Thus, based on the results, the main research hypothesis that identifies the relationships attributes selection between relationship quality and behavioral intention was partially adopted.

• Culinary science and hospitality research
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• v.22 no.3
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• pp.44-54
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• 2016

This study examined the factors that affect the relationship between low price coffee shops service quality and brand image, and rrevisit intention. A total of 225 questionnaires were distributed to consumers, of which 210 were deemed suitable for analysis after the removal of 15 unusable responses. In order to perform statistical analyses required in the study, the SPSS 18.0 Statistical Program was used for frequency analysis, factor analysis, and reliability analysis, correlations, and regression analysis. The results of exploratory factor analysis showed that four factors regarding service quality were extracted from all measurements with a KMO of 0.864 and a total cumulative variance of 73.235%, With regard to brand image, one factor was extracted with a total cumulative variance of 66.497% and a KMO score of 0.885. One factor for revisit intention was extracted that accounted for a total cumulative variance of 60.192% and a KMO score of 0.845. All factors were significant to 0.000 and the correlation between variables was significant. Thus, based on the results, the main research hypothesis that identifies the relationship among service quality, brand image and revisit intention was partially adopted.