• Clinical and Experimental Pediatrics
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• v.46 no.8
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• pp.751-757
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• 2003

Purpose : Obesity is a significant health problem with medical and psychological consequences for children and adolescents. The purpose of this study was to assess the correlation between body fat percent using bioelectrical impedance(BI) and other variable methods. Methods : We measured height, weight, body mass index(BMI) and body fat percent by skinfold thickness(ST) and BI in 1,035(496 male; 539 female) children from seven to 18 years of age. The correlation coefficients between BI and each of the other different methods were obtained. The sensitivity and specificity to predict obesity by these several methods were studied. Results : Fat percent estimated by BI analysis and BMI showed a strong correlation(r=0.749). Fat percent estimated by BI analysis and ST showed a very strong correlation(r=0.835). At the 95th percentile cut-off point for BI, ST showed a sensitivity of 57.7%, and a specificity of 97.6% for estimating body fat. At the 95th percentile cut-off point for BI, BMI showed a sensitivity of 84.9%, and a specificity of 99.3% for estimating body fat. Conclusion : The fat percent estimated by BI analysis correlated strongly with ST or BMI. BI analysis is an objective and accurate method for estimating body fat in childhood obesity.

• Journal of the Korean Institute of Gas
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• v.24 no.2
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• pp.1-8
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• 2020

Centrifugal pump is a facility that transfers energy to fluid through centrifugal force, which is usually generated by rotating the impeller at high speed, and is a major process facility used in many LNG production bases such as vaporization seawater pump, industrial water and fire extinguishing pump using seawater. to be. Currently, pumps in LNG plant sites are subject to operating conditions that vary depending on the amount of supply desired by the customer for a long period of time. Pumps in particular occupy a large part of the consumption strategy at the plant site, and if the optimum operation condition is not available, it can incur enormous energy loss in long term plant operation. In order to solve this problem, it is necessary to identify the performance deterioration factor through the flow analysis and the result analysis according to the fluctuations of the pump's operating conditions and to determine the optimal operation efficiency. In order to evaluate operation efficiency through experimental techniques, considerable time and cost are incurred, such as on-site operating conditions and manufacturing of experimental equipment. If the performance of the pump is not suitable for the site, and the performance of the pump needs to be reduced, a method of changing the rotation speed or using a special liquid containing high viscosity or solids is used. Especially, in order to prevent disruptions in the operation of LNG production bases, a technology is required to satisfy the required performance conditions by processing the existing impeller of the pump within a short time. Therefore, in this study, the rotation difference of the pump was applied to the ANSYS CFX program by applying the modified 3D modeling shape. In addition, the results obtained from the flow analysis and the curve fitting toolbox of the MATLAB program were analyzed numerically to verify the outer diameter correction theory.

• Management & Information Systems Review
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• v.35 no.1
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• pp.85-116
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• 2016

The present study aims to explore the causes of employment difficulty on the basis of job applicant's interest from P-E (person-environment) fit perspective. Our approach relied on a textual analytic method to reveal insights from their situational interests in a job search during the change of labor market. Thus, to investigate the type of major interests and psychological responses, user-generated texts in a social community were collected for analysis between January 1, 2013 through December 31, 2015 by crawling the online-community in regard to job seeking and sharing information and opinions. The results of topic analysis indicated user's primary interests were divided into four types: perception of vocation expectation, employment pre-preparation behaviors, perception of labor market, and job-seeking stress. Specially, job applicants put mainly concerns of monetary reward and a form of employment, rather than their work values or career exploration, thus youth job applicants expressed their psychological responses using contextualized language (e.g., slang, vulgarisms) for projecting their unstable state under uncertainty in response to environmental changes. Additionally, they have perceived activities in the restricted preparation (e.g., certification, English exam) as determinant factors for success in employment and suffered form job-seeking stress. On the basis of these findings, current unemployment matters are totally attributed to the absence of pursing the value of vocation and job in individuals, organizations, and society. Concretely, job seekers are preoccupied with occupational prestige in social aspect and have undecided vocational value. On the other hand, most companies have no perception of the importance of human resources and have overlooked the needs for proper work environment development in respect of stimulating individual motivation. The attempt in this study to reinterpret the effect of environment as for classifying job applicant's interests in reference to linguistic and psychological theories not only helps conduct a more comprehensive meaning for understanding social matters, but guides new directions for future research on job applicant's psychological factors (e.g., attitudes, motivation) using topic analysis.

• Journal of the Korean GEO-environmental Society
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• v.15 no.2
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• pp.67-74
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• 2014

Recently, the number of road construction is increasing by industrial development. According to this industrial tendency, the number of traffic accidents are consistently increasing due to increasing number of vehicle on the road. This is mainly because traffic accidents are occurred by various parameter such as negligence of driver, vehicle defects, state of unstable road, natural environment etc. Lane department of vehicles from guardrail is occurring frequently. This type of accident is caused by vehicle performance improvement and shape of vehicle, weak guardrail installation and maintenance. Guardrail has the purpose on prevention such as prevention of traffic accident and prevention of deviating out of road, minimizing damage of driver and vehicle by collision as well as entry into the road through guardrail. Stability evaluation test of guardrail verifies the behavior of guardrail through the crash of truck. At this time, the crash condition has 100 km/h of velocity and $15^{\circ}$ of impact angle. In the case of ground condition, filling slope condition has relatively high bearing capacity of infinite ground towards the test. Guardrail is generally installed on road of shoulder in fill slope in korea. It is possible for stability problem to deteriorate ground bearing capacity in Guardrail in fill slope. The existed study towards stability of guardrail has been carried out in the infinite ground. However, the study on the behavior of fill slope with guardrail is not performed by vehicle collision. Therefore, In this study, the numerical analysis using LS-DYNA was executed for verification on behavior of fill slope with guardrail through vehicle collision. This numerical analysis was carried out with change of embedded depth on installed guardrail post in shoulder of fill slope by vehicle collision and 8 tonf truck crash providing at NCAN (National Crash Analysis Center). As the result, displacement and stress on fill slope are decreased in accordance with the increase of embedded depth of guardrail post. Ground bearing capacity is deteriorated at depth of 450 mm form shoulder of road on fill slope.

• FLOWER RESEARCH JOURNAL
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• v.18 no.4
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• pp.315-322
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• 2010

To analyze our country's education program for flower decoration and occupational satisfaction of florist, 60 present florists and 60 applicants were surveyed. To investigate satisfaction of florist, the questionnaire items consisted of satisfaction for occupation etc. experienced by attendants, contents of related education, recognition from society, social treatment. And this study analyzed followings : considerations to select occupation, satisfaction on job of person who majored in related subject and non- person without such an educational background, satisfaction on present occupation, satisfaction on education period, significance of florist ability, significance of requirements for occupational development. The points which present florists and applicants consider as important were aptitude for gardening and prospect. From the analysis by major of florists, majored persons had more satisfaction than non-majored persons but there was no statistically significant difference between them. From the analysis by applicant, as in present florists, majored persons had more satisfaction than non-majored persons. For the satisfaction by career and education period of present florists and applicants, the satisfaction on education related to flower decoration or learning experiences and lecturer's teaching method showed that the lower the career is, the less the satisfaction is. Seeing the result by education period of applicants, the satisfaction on job was similar each other regardless of education period. For difference in recognition on ability by major of present florists and applicants, the result of analysis by major of present florists showed that majored persons considered the ability more important comparing to non-majored persons in the fields of gardening and making decorations. In the other hand, in the fields of quality maintenance, flower decoration, and flower distribution and management, there was no significance difference between majored and non-majored persons about the recognition of ability. The result of analysis by major of applicants showed that majored persons considered the ability more important comparing to non-majored persons in the fields of gardening, flower decoration, making decorations, flower distribution and management. For the significance of quality maintenance, majored persons wholly considered the significance more important comparing to non-majored persons but there was no significant difference. Based on the results of this study, in working as a florist, persons who majored in flower decoration had more occupational satisfaction than non-majored persons. And among the contents of education, the education related to gardening was recognized as most important. But at present the systematic and special education programs to cultivate professional florists are deficient. Therefore it is suggested that courses based on systematic educational contents which integrate theory and practice are needed to solve education problem related to flower decoration in this rapidly changing society.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.61-78
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• 2019

This study is about the effect of the founder's self-efficacy on the sales of the founding company by focusing on the factors that are currently emphasized in the founding education. In particular, this paper starts from the consciousness of the problem that the education that is being implemented to achieve the purpose of successful start-up among various government-based start-up support projects is failing to produce many start-up failures. Entrepreneurs cannot be assessed by objective financial data, but there is a high degree of uncertainty that should be determined based on their personal and learning abilities. In addition, many previous studies, which are likely to be successful when there is a high self-efficacy in a specific field due to the influence of factors such as personal experience or learning, will answer the direction of support for start-up companies. This study focuses on the impact of the founder's self-efficacy on the sales of the founding firms, especially the sales that are the key to the survival of the founding firms. This study has six major studies. First, to analyze whether the self-efficacy of entrepreneurs with respect to entrepreneurship affects the sales of entrepreneurs. Second, to analyze whether the self-efficacy of entrepreneurs with respect to market orientation affects the sales of entrepreneurs. Analysis of whether the founder's self-efficacy affects the sales of the founding firms. Fourth, analysis of whether the founder's self-efficiency affects the sales of the founding firms' understanding of management environment changes. An analysis of whether efficacy affects the sales of a start-up company, and sixth, an analysis of whether the founder's self-efficacy of business model building ability affects the sales of a start-up company. As a result of the empirical analysis, this study found that the self-efficacy of entrepreneurs on product differentiation capability and business model building capacity had a positive influence on the sales of entrepreneurs. The self-efficacy had a positive effect on self-efficacy, and the customer orientation had a positive effect on self-efficacy on business model building capacity. Also, it was confirmed that a path exists between the components of self-efficacy and that self-efficacy through the path has a positive effect on the sales of the start-up company. Therefore, the results of this study suggest the implications of establishing such a path and strengthening self-efficacy to create the survival and start-up performance of a start-up company if the goal of the start-up company is to survive when implementing various support projects for the start-up company.

• Cross-Cultural Studies
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• v.52
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• pp.53-78
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• 2018

In the moral culture of the West, love and justice are two commands with roots in ancient times. One is the heritage of Hebraism, and the other belongs to the tradition of Hebraism and Hellenism. The two concepts are the most important virtues required for preserving stability in society. These two commands are compatible, in an exclusive relationship to each other. To ultimately seek their reconciliation, the precise concept analysis and understanding of each of them should be premised on, due to the multi-layered meaning of implications of the two concepts. To this end, we first have started with a lexical meaning and have done a conceptual analysis of what these two concepts are expressing. We have looked at Paul $Ric{\oe}ur$ in his interpretation of the discourse of love and justice. Finally, we looked at how these two concepts are narrated in literature. Through the literary works of Stendal, Albert Camus, and Dostoevsky, we have seen examples of literary configurations that have been embodied in life. In this way, through conceptual analysis, discourse analysis, and narrative analysis of the two concepts, the following conclusions were drawn. Love and justice were not a matter of choice. We could see coldness and unrealism of a society lacking love or with a problem of unclean love, through Stendhal's and Albert Camus' novels and their actual debate. In addition, in unclean paternalism, risk of the power of love blocking certain a certain touch of justice was also confirmed. So, it was necessary for a healthy future society to explore the possibility of the coexistence of love and justice. We confirmed the possibility of compatibility in a 'considerate balance' wherein the 'moral judgment in situation' is required, as Paul $Ric{\oe}ur$ expressed. This ideal situation may be realized when forms of love involving solidarity, mutual care, and compassion with pain like Dostoevsky are combined with the principle of distributional justice. When Albert Camus pursued justice and eventually faced reality and mentioned the need for mercy, he could have made a moral judgment based on this situation. In the end, love protects justice, and justice contributes to the realization of love. Justice reduces super-ethical love to moral categories, and love plays a role in enabling justice to exert its full force.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.