• Geomechanics and Engineering
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• v.18 no.4
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• pp.449-457
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• 2019

Physical model tests were first performed to investigate the failure pattern of multiple pillar-roof support system. It was observed in the physical model tests, pillars were design with the same mechanical parameters in model #1, cracking occurred simultaneously in panel pillars and the roof above barrier pillars. When pillars 2 to 5 lost bearing capacity, collapse of the roof supported by those pillars occurred. Physical model #2 was design with a relatively weaker pillar (pillar 3) among six pillars. It was found that the whole pillar-roof system was divided into two independent systems by a roof crack, and two pillars collapse and roof subsidence events occurred during the loading process, the first failure event was induced by the pillars failure, and the second was caused by the roof crack. Then, for a multiple pillar-roof support system, three types of failure patterns were analysed based on the condition of pillar and roof. It can be concluded that any failure of a bearing component would cause a subsidence event. However, the barrier pillar could bear the transferred load during the stress redistribution process, mitigating the propagation of collapse or cutting the roof to insulate the collapse area. Importantly, some effective methods were suggested to decrease the risk of catastrophic collapse, and the deep-hole-blasting was employed to improve the stability of the pillar and roof support system in a room and pillar mine.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.457-465
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• 2019

This study was designed to develop a positive behavior support model for children in child care institutions. For this purpose, a demand survey for PBS was conducted with 55 child care institution staff members. 76% of the respondents responded that PBS is needed to prevent problem behavior and can be a good alternative for personality education, and approximately 70% responded that they are willing to implement PBS. The specifications of the model are suggested as follows. First, the preparation step would consist of establishing a support team, educating staff members about PBS, selecting expected behaviors, assessing the current baseline behavior, and setting up a universal PBS environment. The application step would consist of instructing social skills, implementing reinforcement, personal goal-setting and assessing behavior, educating trouble-making students, and monitoring. Finally, at the outcome assessment period, measuring the change in target behavior from the pre-intervention to the post-intervention stage, change in social skills and academic achievement, and social validity is suggested. It is expected that application of this model to children in child care institution will decrease problem behaviors of students, enhance desirable behaviors, and boost the staff members' efficacy.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.1-8
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• 2021

To simulate a process model in the field of chemical engineering, it is very important to identify the physical properties of novel materials as well as existing materials. However, it is difficult to measure the physical properties throughout a set of experiments due to the potential risk and cost. To address this, this study aims to develop a property prediction model based on the group contribution method for aromatic chemical compounds including benzene rings. The benzene rings of aromatic materials have a significant impact on their physical properties. To establish the prediction model, 42 important functional groups that determine the physical properties are considered, and the total numbers of functional groups on 147 aromatic chemical compounds are counted to prepare a dataset. Support vector regression is employed to prepare a prediction model to handle sparse and high-dimensional data. To verify the efficacy of this study, the results of this study are compared with those of previous studies. Despite the different datasets in the previous studies, the comparison indicated the enhanced performance in this study. Moreover, there are few reports on predicting the physical properties of aromatic compounds. This study can provide an effective method to estimate the physical properties of unknown chemical compounds and contribute toward reducing the experimental efforts for measuring physical properties.

• The Korean Journal of Franchise Management
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• v.12 no.2
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• pp.23-33
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• 2021

Purpose: The purpose of this study is to provide basic data such as development of sustainable support policies and performance management evaluation to support sustainable management of domestic franchises by deriving the sustainable growth cycle of domestic franchises. Research design, data, and methodology: This study is based on systematic review study. We combined search terms such as "Start-up", "Sustainability" and "Success" with four databases, RISS, KISS, e-article and DBpia and searched a total of 1,219 articles published by April 21, 2021. In the process, 35 studies were selected and analyzed after an expert review, excluding documents whose overlapping documents, gray zones (e.g., reports, conference presentations, etc.), degree papers, foreign language literature, and dependent variables were not related to the Sustainability factors. Using ERIS model, which is applied to research on the results of startup, and the franchise's growth cycle, which reflects the growth stage of franchises, we analyzed the factors behind the sustainability of franchise. Result: The results of the study are as follows. First, research on the sustainability of franchise has continued since 2009 in Korea, and has been conducted in various fields such as social welfare in addition to venture, start-up and management. Second, sustainability factors of franchise were analyzed from the ERIS performance model indicating the performance of venture, and the 68 subfactors were derived. Third, it is confirmed that there are important factors that affect the sustainable growth of franchise startups in each franchise's growth cycle. Conclusions: It is significant that through this study, we provided better understanding of the factors that sustain sustainability of franchises, policy suggestions, and presented the direction of future study. Theoretical suggestion is that the main reason for the continuous growth of franchise in each domestic franchise is based on the ERIS performance model. The practical implication is that the headquarters and Franchisor can use it to establish and evaluate performance indicators based on the business growth cycle. The results of this study are expected to be used as basic data for development and performance management evaluation of franchise start-up support policies to support the sustainable management of domestic franchises.

• Knowledge Management Research
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• v.23 no.1
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• pp.187-201
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• 2022

Online reviews written by tourists provide important information for the management and operation of the tourism industry. The star rating of online reviews is a simple quantitative evaluation of a product or service, but it is difficult to reflect the sincere attitude of tourists. There is also an issue; the star rating and review content are not matched. In this study, a star rating prediction model based on online review content was proposed to solve the discrepancy problem. We compared the differences in star ratings and sentiment by continent through sentiment analysis on tourist attractions and hotels written by foreign tourists who visited Korea. Variables were selected through TF-IDF vectorization and sentiment analysis results. Logit, artificial neural network, and SVM(Support Vector Machine) were used for the classification model, and artificial neural network and SVR(Support Vector regression) were applied for the rating prediction model. The online review rating prediction model proposed in this study could solve inconsistency problems and also could be applied even if when there is no star rating.

• International Journal of Computer Science & Network Security
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• v.22 no.8
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• pp.328-342
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• 2022

The Internet of Things (IoT) is a technology that offers lucrative services in various industries to facilitate human communities. Important information on people and their surroundings has been gathered to ensure the availability of these services. This data is vulnerable to cybersecurity since it is sent over the internet and kept in third-party databases. Implementation of data encryption is an integral approach for IoT device designers to protect IoT data. For a variety of reasons, IoT device designers have been unable to discover appropriate encryption to use. The static support provided by research and concerned organizations to assist designers in picking appropriate encryption costs a significant amount of time and effort. IoTES is a web app that uses machine language to address a lack of support from researchers and organizations, as ML has been shown to improve data-driven human decision-making. IoTES still has some weaknesses, which are highlighted in this research. To improve the support, these shortcomings must be addressed. This study proposes the "IoTES with Security" model by adding support for the security level provided by the encryption algorithm to the traditional IoTES model. We evaluated our technique for encryption algorithms with available security levels and compared the accuracy of our model with traditional IoTES. Our model improves IoTES by helping users make security-oriented decisions while choosing the appropriate algorithm for their IoT data.

• Journal of Korea Water Resources Association
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• v.45 no.11
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• pp.1187-1199
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• 2012

A hybrid forecasting scheme based on wavelet decomposition coupled to a support vector machine model is presented for water demand series that exhibit nonlinear behavior. The use of wavelet transform followed by the SVM model of each leading component is explored as a model for water demand data. The proposed forecasting model yields better results than a traditional ARIMA time series forecasting model in terms of self-prediction problem as well as reproducing the properties of the observed water demand data by making use of the advantages of wavelet transform and SVM model. The proposed model can be used to substantially and significantly improve the water demand forecasting and utilized in a real operation.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.1
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• pp.1-8
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• 2004

According to the development of the Internet and the pervasion of Data Base, it is not easy to search for necessary information from the huge amounts of data. In order to do efficient analysis of a large amounts of data, this paper proposes a method for pattern classification based on the effective strategy for dimension reduction for narrowing down the whole data to what users wants to search for. To analyze data effectively, Radial Basis Function Networks based on VC-dimension of Support Vector Machine, a model of statistical teaming, is proposed in this paper. The model of Radial Basis Function Networks currently used performed the preprocessing of Perceptron model whereas the model proposed in this paper, performing independent analysis on VD-dimension, classifies each datum putting precise labels on it. The comparison and estimation of various models by using Machine Learning Data shows that the model proposed in this paper proves to be more efficient than various sorts of algorithm previously used.

• Journal of Family Resource Management and Policy Review
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• v.14 no.2
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• pp.35-58
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• 2010

The purpose of this study was to find the effects and problems in the support projects in multicultural family support centers and to present suggestions for its improvement. For this purpose, 10 specialists in 3 multicultural family support centers in Daegu, who organize and operate projects for female immigrants and their families, were interviewed via focus groups and then interviewed in-depth. The major findings were as follows: 1) the effect of the support projects was an increase in participation and concern of female immigrants and their families; 2)problems of the support projects included lack of flexibility of the projects, and overlap of projects among centers. 3)The results of the study suggest improved operation by extending the support networks to other support centers and facilities within the community, increasing the individualized programs based on their specialties, and promoting integrated projects (such as combining language courses and cultural programs, family-support programs and cultural events). Further studies will be extend to find out model cases from support projects of several centers, expand them to other centers, and verify its effects on operating projects.

• Journal of Korean Academy of Nursing
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• v.42 no.1
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• pp.136-147
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• 2012

Purpose: This study was conducted to compare the degree of depression between men and women and to identify factors influencing their depression. Methods: Participants in this cross-sectional descriptive study were 263 persons over 65 years old (men: 103, women: 160). Data were collected through face to face interviews using questionnaires and were done in two urban areas in 2010. Research instruments utilized in this study were SGDS, MMSE-K, SRH, FILE, sleep pattern scale, family and friend support scale, and social support scale. Multivariate regression analysis was performed to identify factors influencing depression in elders. Results: The proportions of participants with depression were significantly different between men and women (52.4% vs. 67.5%). Regression model for depression in elderly men significantly accounted for 54%; disease stress (32%), economic stress (10%), perceived health status (4%), and family support, educational level, age, and hypertension. Regression model for depression in elderly women significantly accounted for 47%; disease stress (25%), perceived social loneliness (8%), friend support (5%), family stress (4%), and sleep satisfaction, and family support. Conclusion: Results demonstrate that depression is an important health problem for elders, and show gender differences for factors influencing depression. These results could be used in the developing depression prevention programs.