• Journal of Advanced Marine Engineering and Technology
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• v.41 no.3
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• pp.209-215
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• 2017

A large floating offshore wind-wave hybrid power generation system with an area of 150 m2 and four 3 MW class wind turbine generators was installed at each column top. In accordance with the wind turbine arrangement, the wake generated from upstream turbines can adversely affect the power performance and load characteristics of downstream turbines. Therefore, an optimal arrangement design, obtained through a detailed flow analysis focusing on wake interference, is necessary. In this study, to determine the power characteristics and annual energy production (AEP) of individual wind turbines, transient computational fluid dynamics, considering wind velocity variation (8 m/s, 11.7 m/s, 19 m/s, and 25 m/s), was conducted under different platform conditions ($0^{\circ}$, $22.5^{\circ}$, and $45^{\circ}$). The AEP was calculated using a Rayleigh distribution, depending on the wind turbine arrangement. In addition, we suggested an optimal arrangement design to minimize wake losses, based on the AEP.

• Journal of Preventive Medicine and Public Health
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• v.38 no.1
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• pp.71-81
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• 2005

Objective : To elucidate the correlates of self-rated fatigue in Korean employees. Methods : The data for 10,176 (men, 7,984; women, 2,192; mean age, 34.2; SD: 8.8) employees recruited from a nationwide sample were examined. A structured questionnaire was used to measure the participants' fatigue, sociodemographics (sex, age, education, and marital status), job-related characteristics (work duration, grade at work, work hours, shiftwork, employment type, and magnitude of workplace), and health-related habits (smoking, drinking, coffee intake, and exercise). Two types of measurement for fatigue were used to evaluate the magnitude of fatigue: self-rated question and a standardized measurement tool (Multidimensional Fatigue Scale: MFS). Results : According to the self-rated fatigue, 32% of employees reported that they felt fatigue for the past two weeks, and 9.6% of males and 8.7% of females had experienced excessive fatigue (6 months or more). Hierarchical multiple regression analysis showed that fatigue measured by MFS was more common in women, younger, college or more graduated, single, and employees who do not regularly exercise. Fatigue was also associated with long work hours, and the size of the workplace (<1,000 employees). Conclusions : These results suggest that fatigue has been considered as a common complaint, and that it is affected by job-related factors like work hours and the workplace size as well as sociodemographics or health-related behaviors. Further research is needed to clarify the effects of fatigue on adverse health outcomes, work performance, work disability, sick absence and medical utilization, and to examine the relationship of job characteristics (e.g.: work demand, decision latitude) to fatigue.

• The Korean Journal of Franchise Management
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• v.10 no.4
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• pp.19-29
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• 2019

Purpose: In beauty industry, service quality is very critical, because it impacts on the customer's positive attitude and behavior to the beauty salon or beauty brand. Thus, this research examines the effects of service attributes on customer satisfaction and loyalty in beauty salon. This research suggests the guidelines for how beauty salons should manage their physical environment, price policy, professional skills, and employees that improve management and business performance. Research design, data, and methodology: This study examines the structural relationship between service attributes, customer satisfaction, and loyalty. Service attributes divide into four sub-dimensions such as servicescape, price service, technical service, and employee service. In order to test the purposes of this research, research model and hypotheses were developed. All constructs were measured with multiple items developed and examined in previous studies. A total of 160 questionnaires were distributed and collected, and 150 were used for analysis except 10 that were unresponsive or unfaithful. The data were analyzed using SPSS 22.0 and SmartPLS 3.0 statistical package program. Result: The results of this research are as follows. First, all sub-dimensions of service attributes such as servicescape, price service, technical service, and employee service have significant positive impacts on satisfaction. Second, customer satisfaction have significant impact on loyalty. Conclusions: This study suggests an integrated model of the relationship that the characteristics of beauty salon service attributes affect customer loyalty through satisfaction, and suggests how to manage and allocate limited resources in the beauty industry. The findings of this research indicate that the level of customer satisfaction is shown to be increased by servicescape, technical characteristics, value of money, and human attributes. Thus, beauty salon management should focus on the relationship with their customers how to improve customer loyalty through satisfaction. The quality of beauty service influences customer's attitudes and behaviors toward beauty salon. Considering the beauty business, where the quality and customer satisfaction of beauty services are determined by the hairdresser's beauty skills,, the beauty salons must find ways to improve their skills and new trend of hair style. If beauty salon customers perceive the high quality of beauty service, they revisit beauty salon and recommend it to others.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.572-577
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• 2009

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. To prune the redundant speech segments in a large speech segment DB, we can utilize a decision-tree based triphone clustering algorithm widely used in speech recognition area. But, the conventional methods have problems in representing the acoustic transitional characteristics of the phones and in applying context questions with hierarchic priority. In this paper, we propose a new clustering algorithm to downsize the speech DB. Firstly, three 13th order MFCC vectors from first, medial, and final frame of a phone are combined into a 39 dimensional vector to represent the transitional characteristics of a phone. And then the hierarchically grouped three question sets are used to construct the triphone trees. For the performance test, we used DTW algorithm to calculate the acoustic similarity between the target triphone and the triphone from the tree search result. Experimental results show that the proposed method can reduce the size of speech DB by 23% and select better phones with higher acoustic similarity. Therefore the proposed method can be applied to make a small sized TTS.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.400-405
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• 2024

When cavitation noise occurs in ship propellers, the level of underwater radiated noise abruptly increases, which can be a critical threat factor as it increases the probability of detection, particularly in the case of naval vessels. Therefore, accurately and promptly assessing cavitation signals is crucial for improving the survivability of submarines. Traditionally, techniques for determining cavitation occurrence have mainly relied on assessing acoustic/vibration levels measured by sensors above a certain threshold, or using the Detection of Envelop Modulation On Noise (DEMON) method. However, technologies related to this rely on a physical understanding of cavitation phenomena and subjective criteria based on user experience, involving multiple procedures, thus necessitating the development of techniques for early automatic recognition of cavitation signals. In this paper, we propose an algorithm that automatically detects cavitation occurrence based on simple statistical features reflecting cavitation characteristics extracted from acoustic signals measured by sensors attached to the hull. The performance of the proposed technique is evaluated depending on the number of sensors and model test conditions. It was confirmed that by sufficiently training the characteristics of cavitation reflected in signals measured by a single sensor, the occurrence of cavitation signals can be determined.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.59-70
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• 2020

This study was proceeded to empirically identify the start-up support policy as an element that affects the performance of the early start-ups and measure the effectiveness of the current start-up support policy, in order to suggest the direction future policies according to the study. To accomplish this the influence of the start-up support policy on the early start-ups was analyzed, and the differences according to the industry and growth stage of the start-ups, as the characteristics of the start-ups, were identified. The research subjects collected real data of 297 start-ups of the past three years that were selected for the Initial Start-Up Package project, and performed multiple regression analysis on the influence between variables, and hierarchical regression analysis on moderating effects. The summary of the study is as follows. First, as a result of identifying the influential relationship between the start-up support policy and the performance of the start-up, sales had made a significant impact on the start-up fund, start-up mentoring, and start-up infrastructure(space), while start-up education failed to show a significant effect on the increase in sales. In terms of employment, start-up mentoring was the only field that showed a significant influential relationship. Second, as a result of identifying the moderating effect of the start-up's industry and growth stage, the industry did not have a statistically significant influence, but the interactive effect was seen in start-up education. To be more specific in terms of the sales relationship of each industry, knowledge services turned out to be helpful in improving sales, while manufacturing turned out to be effective in improving sales regardless of being supported with start-up mentoring and start-up infrastructure (space). The sales relationship regarding the start-up growth stage was identified to be statistically significant. The preliminary stage was not statistically significant, while providing start-up mentoring and start-up funding were effective for start-up stage and growing stage, respectively. On the other hand, employment did not perform a significant influence on the start-up growth stage. This study analyzes the effectiveness the start-up support policy for early start-ups, identifies the need in differentiated support policies according to the characteristics of the start-ups, and suggests implications for the direction in which future policies should be made towards.

• Management & Information Systems Review
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• v.35 no.4
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• pp.1-19
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• 2016

The researchers in strategic management have focused on identifying the effects of CEO's demographic characteristics and experience on the strategic choices and performance of firms. On the other hand, they have failed to identifying the effects of CEO's psychological characteristics on them because of the difficulties over data collection and measurement for variables. To overcome this limitation of prior researches, this study is designed to achieve two specific objectives. The first is to examine the effect of CEO narcissism on diversification strategy and performance of listed corporations on Korean securities market in an economic downturn. The other is to examine the moderating effects of various corporate governance systems that are related to board and/or ownership structures on those relationships. The empirical setting for this study was drawn from a multi-year(2011~2014) sample of large listed corporations in Korean securities market. To achieve the objectives, the hypotheses of research are analyzed by implementing multiple regression analyses in two separate models. The results of these analyses show that CEO narcissism is positively related to the diversification of listed large corporations in Korean securities market. Regrading the moderating effects, the stake of institutional investors weakens the positive relationship between CEO narcissism and firm's diversification. The findings of this research imply that CEO narcissism can intensify the tendency of Korean corporations to adopt high-risk and high return strategy in an economic downturn. Thus, firms might be able to use CEO narcissism to drastically restructure the business portfolio in an economic downturn. However, Korean corporations should be very cautions to maximize the positive effect of CEO narcissism. They might be use the institutional investors as their corporate governance system to monitor and control the opportunism of CEO in the decision for diversification in an economic downturn.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.12 s.148
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• pp.1571-1581
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• 2005

In a highly competitive marketplace, U.S. retailers are challenged to attract, recruit, and retain a skilled workforce. The purpose of our research was to examine the impact of young retail employees' work experiences on their job performance, job satisfaction, and career intention using a comprehensive approach to model development. The model was developed in three phases over a four-year period using both qualitative and quantitative methodologies. During Phase 1, we conducted focus group interviews to guide the development of the questionnaire. Work experience was initially operationalized as role conflict, role ambiguity, supervisory support, and work involvement. Using a student sample(n=470) from U.S. universities, we employed multiple regression to determine the significance of relationships between their work experience, job satisfaction, and retail career intention. During Phase 2, we expanded our investigation to include retail work experiences of teens employed while they were in high school. The teen sample(n=898) was drawn from students enrolled in work-study programs in 16 U.S. high schools, and data were analyzed using structural equation modeling (hereafter SEM). During Phase 3, we expanded our model to include two new variables, job characteristics and job performance. Based on a national sample(n=803) of U.S. university students, we employed SEM to holistically determine if retail employees' work experience impacted their job performance, job satisfaction, and retail career intention. During each phase, job satisfaction consistently was the superior antecedent of retail career intention. Among the work experience variables, supervisory support had a positive impact on job satisfaction, while role conflict, role ambiguity, and work involvement exhibited inconsistent effects on job outcomes. The strong relationship between job satisfaction and retail career intention should make job satisfaction a priority for retailers.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.