• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.59-83
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• 2018

With the increasing importance of sentiment analysis to grasp the needs of customers and the public, various types of deep learning models have been actively applied to English texts. In the sentiment analysis of English texts by deep learning, natural language sentences included in training and test datasets are usually converted into sequences of word vectors before being entered into the deep learning models. In this case, word vectors generally refer to vector representations of words obtained through splitting a sentence by space characters. There are several ways to derive word vectors, one of which is Word2Vec used for producing the 300 dimensional Google word vectors from about 100 billion words of Google News data. They have been widely used in the studies of sentiment analysis of reviews from various fields such as restaurants, movies, laptops, cameras, etc. Unlike English, morpheme plays an essential role in sentiment analysis and sentence structure analysis in Korean, which is a typical agglutinative language with developed postpositions and endings. A morpheme can be defined as the smallest meaningful unit of a language, and a word consists of one or more morphemes. For example, for a word '예쁘고', the morphemes are '예쁘(= adjective)' and '고(=connective ending)'. Reflecting the significance of Korean morphemes, it seems reasonable to adopt the morphemes as a basic unit in Korean sentiment analysis. Therefore, in this study, we use 'morpheme vector' as an input to a deep learning model rather than 'word vector' which is mainly used in English text. The morpheme vector refers to a vector representation for the morpheme and can be derived by applying an existent word vector derivation mechanism to the sentences divided into constituent morphemes. By the way, here come some questions as follows. What is the desirable range of POS(Part-Of-Speech) tags when deriving morpheme vectors for improving the classification accuracy of a deep learning model? Is it proper to apply a typical word vector model which primarily relies on the form of words to Korean with a high homonym ratio? Will the text preprocessing such as correcting spelling or spacing errors affect the classification accuracy, especially when drawing morpheme vectors from Korean product reviews with a lot of grammatical mistakes and variations? We seek to find empirical answers to these fundamental issues, which may be encountered first when applying various deep learning models to Korean texts. As a starting point, we summarized these issues as three central research questions as follows. First, which is better effective, to use morpheme vectors from grammatically correct texts of other domain than the analysis target, or to use morpheme vectors from considerably ungrammatical texts of the same domain, as the initial input of a deep learning model? Second, what is an appropriate morpheme vector derivation method for Korean regarding the range of POS tags, homonym, text preprocessing, minimum frequency? Third, can we get a satisfactory level of classification accuracy when applying deep learning to Korean sentiment analysis? As an approach to these research questions, we generate various types of morpheme vectors reflecting the research questions and then compare the classification accuracy through a non-static CNN(Convolutional Neural Network) model taking in the morpheme vectors. As for training and test datasets, Naver Shopping's 17,260 cosmetics product reviews are used. To derive morpheme vectors, we use data from the same domain as the target one and data from other domain; Naver shopping's about 2 million cosmetics product reviews and 520,000 Naver News data arguably corresponding to Google's News data. The six primary sets of morpheme vectors constructed in this study differ in terms of the following three criteria. First, they come from two types of data source; Naver news of high grammatical correctness and Naver shopping's cosmetics product reviews of low grammatical correctness. Second, they are distinguished in the degree of data preprocessing, namely, only splitting sentences or up to additional spelling and spacing corrections after sentence separation. Third, they vary concerning the form of input fed into a word vector model; whether the morphemes themselves are entered into a word vector model or with their POS tags attached. The morpheme vectors further vary depending on the consideration range of POS tags, the minimum frequency of morphemes included, and the random initialization range. All morpheme vectors are derived through CBOW(Continuous Bag-Of-Words) model with the context window 5 and the vector dimension 300. It seems that utilizing the same domain text even with a lower degree of grammatical correctness, performing spelling and spacing corrections as well as sentence splitting, and incorporating morphemes of any POS tags including incomprehensible category lead to the better classification accuracy. The POS tag attachment, which is devised for the high proportion of homonyms in Korean, and the minimum frequency standard for the morpheme to be included seem not to have any definite influence on the classification accuracy.

• Explosives and Blasting
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• v.9 no.1
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• pp.3-13
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• 1991

The cautious blasting works had been used with emulsion explosion electric M/S delay caps. Drill depth was from 3m to 6m with Crawler Drill ${\phi}70mm$ on the calcalious sand stone (soft -modelate -semi hard Rock). The total numbers of test blast were 88. Scale distance were induced 15.52-60.32. It was applied to propagation Law in blasting vibration as follows. Propagtion Law in Blasting Vibration $V=K(\frac{D}{W^b})^n$ were V : Peak partical velocity(cm/sec) D : Distance between explosion and recording sites(m) W : Maximum charge per delay-period of eight milliseconds or more (kg) K : Ground transmission constant, empirically determind on the Rocks, Explosive and drilling pattern ets. b : Charge exponents n : Reduced exponents where the quantity $\frac{D}{W^b}$ is known as the scale distance. Above equation is worked by the U.S Bureau of Mines to determine peak particle velocity. The propagation Law can be catagorized in three groups. Cubic root Scaling charge per delay Square root Scaling of charge per delay Site-specific Scaling of charge Per delay Plots of peak particle velocity versus distoance were made on log-log coordinates. The data are grouped by test and P.P.V. The linear grouping of the data permits their representation by an equation of the form ; $V=K(\frac{D}{W^{\frac{1}{3}})^{-n}$ The value of K(41 or 124) and n(1.41 or 1.66) were determined for each set of data by the method of least squores. Statistical tests showed that a common slope, n, could be used for all data of a given components. Charge and reduction exponents carried out by multiple regressional analysis. It's divided into under loom over loom distance because the frequency is verified by the distance from blast site. Empirical equation of cautious blasting vibration is as follows. Over 30m ------- under l00m ${\cdots\cdots\cdots}{\;}41(D/sqrt[2]{W})^{-1.41}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}A$ Over 100m ${\cdots\cdots\cdots\cdots\cdots}{\;}121(D/sqrt[3]{W})^{-1.66}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}B$ where ; V is peak particle velocity In cm / sec D is distance in m and W, maximLlm charge weight per day in kg K value on the above equation has to be more specified for further understaring about the effect of explosives, Rock strength. And Drilling pattern on the vibration levels, it is necessary to carry out more tests.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.4
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• pp.77-85
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• 2014

A goal of Bizcool entrepreneurship education targeting on the youth falls on letting understand the process of starts-up, enhance entrepreneurship will and their business creativities rather than training trivial starts-up skills such as writing business plan for successful starts-up. The effects of education enable Bizcoo students to recognize rightly the concept of starts-up training and lead to spread out demand for entrepreneurship education. The feedback check-up for how entrepreneurship education affects students getting through of it is necessary and possible to bring its' improvement alternatives. Despite of such highlight, not many measuring tools and indexes of evaluating an effectiveness of entrepreneurship education are developed and studied up until. This research suggests for the optimal indexes for them. In specific, this research 49 the first question sets of evaluating an effectiveness of entrepreneurship education classified 3 large categories and 11 following sub categories each of them such as entrepreneurship orientation, creativity, entrepreneurship preparing activities etc,. representing embedding education effects though entrepreneurship education. This research carry out the empirical survey research utilizing driven question sets against 5 different Bizcools sampling 287 students. The survey research delivers the final 3 large categories and 8 following sub categories(Innovativeness, risk-taking, problem-solving potent, cooperative decision-making potent, efficient behavior capacity, data collecting potent, career search, starts-up search and preparation), and 38 measuring indexes by search and confirming factor analysis. This research never drop the confidence test over each indexes and obtain the proper figures. Last but not least, this research confirm the gap between starts-up club members and non members as to an effectiveness of entrepreneurship education and 9 different indexes.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.107-134
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• 2007

This paper tests the relationship among returns, volatilities, contracts and open interests of KOSPI 200 futures markets with the various dynamic models such as granger-causality, impulse response, variance decomposition and ARMA(1, 1)-GJR-GARCH(1, 1)-M. The sample period is from July 7, 1998 to December 29, 2005. The main empirical results are as follows; First, both contract change and open interest change of KOSPI 200 futures market tend to lead the returns of that according to the results of granger-causality, impulse response and variance decomposition with VAR. These results are likely to support the KOSPI 200 futures market seems to be inefficient with rejecting the hypothesis 1. Second, we also find that the returns and volatilities of the KOSPI 200 futures market are effected by both contract change and open interest change of that due to the results of ARMA(1,1)-GJR-GARCH(1,1)-M. These results also reject the hypothesis 1 and 2 suggesting the evidences of inefficiency of the KOSPI 200 futures market. Third, the study shows the asymmetric information effects among the variables. In addition, we can find the feedback relationship between the contract change and open interest change of KOSPI 200 futures market.

• CRM연구
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• v.3 no.2
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• pp.43-68
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• 2010

One of the recent research trends that universities are increasingly adopting the concept of 'customer' and the customer-oriented strategy has urged us to research enterprise-wide CRM strategy adaptable to university administration. As the first step of CRM strategy for university management, we try to validate the difference of CRM strategic factors among university types. Drawing upon both CRM process and customer equity drivers, which have been recognized as core frameworks for CRM strategy, we developed those survey instruments adoptable into university industry, and validated statistically-significant difference among 12 types of university group constructed by the levels of university evaluation and the location of the universities. We collected 261 responses from 177 universities from all over the country and analyzed the data to see the levels of CRM processes consisting of customer acquisition, retention, and expansion, and customer equity drivers consisting of value equity, brand equity, and relationship equity by using multivariate ANOVA(MANOVA). The result confirms the explicit differences of the levels of CRM processes and customer equity drivers between the groups by university evaluation levels(high/middle/low). However, the analysis failed to show the significant differences of those between the group by university locations(the capital/the suburbs/the six megalopolises/other countries). More specifically, the level of activities for customer acquisition and retention of the universities in the higher-graded group are significantly different from those in the lower-graded group from the perspective of CRM process. In terms of customer equity drivers, the levels of both brand equity and relationship equity of the higher-graded group are significantly higher than those of both middle and lower-graded group. In addition, we found that the value equity between the higher and lower-graded groups, and the brand equity between the middle and lower-graded groups are different each other. This study provides an important meaning in that we tried to consider CRM strategy which has been mainly addressed in profit-making industries in terms of non-profit organization context. Our endeavors to develop and validate empirical measurements adoptable to university context could be an academic contribution. In terms of practical meaning, the processes and results of this study might be a guideline to many universities to build their own CRM strategies. According to the research results, those insights could be expressed in several messages. First, we propose to universities that they should plan their own differentiated CRM strategies according to their positions in terms of university evaluation. For example, although it is acceptable that a university in lower-level group might follow the CRM process strategy of the middle-level group universities, it is not a good idea to imitate the customer acquisition and retention activities of the higher-level group universities. Moreover, since this study reported that the level of universities' brand equity is just correlated with the level of university evaluation, it might be pointless for the middle or lower-leveled universities if they just copy their brand equity strategies from those of higher-leveled ones even though such activities are seemingly attractive. Meanwhile, the difference of CRM strategy by university position might provide universities with the direction where they should go for their CRM strategies. For instance, our study implies that the lower-positioned universities should improve all of the customer equity drivers with concerted efforts because their value, brand, and relationship equities are inferior compared with the higher and middle-positioned universities' ones. This also means that they should focus on customer acquisition and expansion initiatives rather than those for customer retention because all of the customer equity drivers could be influenced by the two kinds of CRM processes (KIm and Lee, 2010). Surely specific and detailed action plans for enhancing customer equity drivers should be developed after grasping their customer migration patterns illustrated by the rates of acquisition, retention, upgrade, downgrade, and defection for each customer segment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.6
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• pp.59-76
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• 2019

Most technology-based entrepreneurship(TBE) go through an process of decline or disappear without overcoming the valley of death(VoD). The purpose of this study is to identify the growth dimension of TBE and to test the influence of firms activities on firms growth over time. This study identified the two-dimensional growth dimension divided by size and profit through exploratory factor analysis(EFA) of a number of growth indicators. Then, we defined the discrete state of growth firm in four states, divided by size and profit, and five states, including the closure of business. Multi-nomial logit model is used to predict the effect of TBE activities on a discrete state of growth firm(size×profit, closure of business) based on multiple independent variables. The independent variables are based on five representative firms activities: employment, marketing, R&D, financial activities, and general management activities. The growth stage of TBE over time has been categorized into three stages: early stage, middle stage, and late stage of business, taking into account the main periods during which the survival rate of startups sharply decreases. The analytical data of this study was based on the secondary data of the start-up supporting companies of government and public institutions. The subjects of analysis were TBE within 10 years. As a result of the empirical analysis, the employment and marketing activities of TBE show that early and mid-term activities had an effect on the state of firms growth. However, if there is a difference, employment activities have both positive and negative effects, while marketing activities have only a positive effect on size and profit growth. And besides, R&D activities, financial activities, and general management activities throughout the entire process of firms growth were found to be firms activities that have both positive and negative effects on firms growth. In addition, the age of the founder, the firms' industry, and the geographic location of the firms, which are general characteristics of the company, were found to have a distinctive effect on the growth status of the firms according to the growth stage.

• The Korean Journal of Financial Management
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• v.25 no.1
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• pp.1-22
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• 2008

This study is to evaluate, to the extent to, which advanced currency futures and emerging currency futures markets can predict accurately the future spot rate. To this end, Johansen's the maximum-likelihood cointegration method(1988, 1991) is adopted to test the unbiasedness and efficiency hypothesis. Also, this study is to estimate and compare a quantitative measure of relative efficiency as a ratio of the forecast error variance from the best-fitting quasi-error correction model to the forecast error variance of the futures price as predictor of the spot price in advanced currency futures with in emerging currency futures market. Advanced currency futures is British pound and Japan yen. Emerging currency futures includes Korea won, Mexico peso, and Brazil real. The empirical results are summarized as follows : First, the unbiasedness hypothesis is not rejected for Korea won and Japan yen futures exchange rates. This indicates that the emerging currency Korea won and the advanced currency Japan yen futures exchange rates are likely to predict accurately realized spot exchange rate at a maturity date without the trader having to pay a risk premium for the privilege of trading the contract. Second, in emerging currency futures markets, the unbiasedness hypothesis is not rejected for Korea won futures market apart from Mexico peso and Brazil real futures markets. This indicates that in emerging currency futures markets, Korea won futures market is more efficient than Mexico peso and Brazil real futures markets and is likely to predict accurately realized spot exchange rate at a maturity date without risk premium. Third, this findings show that the results of unbiasedness hypothesis tests can provide conflicting finding. according to currency futures class and forecasts horizon period, Fourth, from the best-fitting quasi-error correction model with forecast horizons of 14 days, the findings suggest the Japan yen futures market is 27.06% efficient, the British pound futures market is 26.87% efficient, the Korea won futures market is 20.77% efficient, the Mexico peso futures market is 11.55%, and the Brazil real futures market is 4.45% efficient in the usual order. This indicates that the Korea won-dollar futures market is more efficient than Mexico peso, and Brazil real futures market. It is therefore possible to concludes that the Korea won-dollar currency futures market has relatively high efficiency comparing with Mexico peso and Brazil real futures markets of emerging currency futures markets.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.207-228
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• 2007

Measuring Information Technology(IT) organizations' activities have been limited to mainly measure financial indicators for a long time. However, according to the multifarious functions of Information System, a number of researches have been done for the new trends on measurement methodologies that come with financial measurement as well as new measurement methods. Especially, the researches on IT Balanced Scorecard(BSC), concept from BSC measuring IT activities have been done as well in recent years. BSC provides more advantages than only integration of non-financial measures in a performance measurement system. The core of BSC rests on the cause-and-effect relationships between measures to allow prediction of value chain performance measures to allow prediction of value chain performance measures, communication, and realization of the corporate strategy and incentive controlled actions. More recently, BSC proponents have focused on the need to tie measures together into a causal chain of performance, and to test the validity of these hypothesized effects to guide the development of strategy. Kaplan and Norton[2001] argue that one of the primary benefits of the balanced scorecard is its use in gauging the success of strategy. Norreklit[2000] insist that the cause-and-effect chain is central to the balanced scorecard. The cause-and-effect chain is also central to the IT BSC. However, prior researches on relationship between information system and enterprise strategies as well as connection between various IT performance measurement indicators are not so much studied. Ittner et al.[2003] report that 77% of all surveyed companies with an implemented BSC place no or only little interest on soundly modeled cause-and-effect relationships despite of the importance of cause-and-effect chains as an integral part of BSC. This shortcoming can be explained with one theoretical and one practical reason[Blumenberg and Hinz, 2006]. From a theoretical point of view, causalities within the BSC method and their application are only vaguely described by Kaplan and Norton. From a practical consideration, modeling corporate causalities is a complex task due to tedious data acquisition and following reliability maintenance. However, cause-and effect relationships are an essential part of BSCs because they differentiate performance measurement systems like BSCs from simple key performance indicator(KPI) lists. KPI lists present an ad-hoc collection of measures to managers but do not allow for a comprehensive view on corporate performance. Instead, performance measurement system like BSCs tries to model the relationships of the underlying value chain in cause-and-effect relationships. Therefore, to overcome the deficiencies of causal modeling in IT BSC, sound and robust causal modeling approaches are required in theory as well as in practice for offering a solution. The propose of this study is to suggest critical success factors(CSFs) and KPIs for measuring performance for IT organizations and empirically validate the casual relationships between those CSFs. For this purpose, we define four perspectives of BSC for IT organizations according to Van Grembergen's study[2000] as follows. The Future Orientation perspective represents the human and technology resources needed by IT to deliver its services. The Operational Excellence perspective represents the IT processes employed to develop and deliver the applications. The User Orientation perspective represents the user evaluation of IT. The Business Contribution perspective captures the business value of the IT investments. Each of these perspectives has to be translated into corresponding metrics and measures that assess the current situations. This study suggests 12 CSFs for IT BSC based on the previous IT BSC's studies and COBIT 4.1. These CSFs consist of 51 KPIs. We defines the cause-and-effect relationships among BSC CSFs for IT Organizations as follows. The Future Orientation perspective will have positive effects on the Operational Excellence perspective. Then the Operational Excellence perspective will have positive effects on the User Orientation perspective. Finally, the User Orientation perspective will have positive effects on the Business Contribution perspective. This research tests the validity of these hypothesized casual effects and the sub-hypothesized causal relationships. For the purpose, we used the Partial Least Squares approach to Structural Equation Modeling(or PLS Path Modeling) for analyzing multiple IT BSC CSFs. The PLS path modeling has special abilities that make it more appropriate than other techniques, such as multiple regression and LISREL, when analyzing small sample sizes. Recently the use of PLS path modeling has been gaining interests and use among IS researchers in recent years because of its ability to model latent constructs under conditions of nonormality and with small to medium sample sizes(Chin et al., 2003). The empirical results of our study using PLS path modeling show that the casual effects in IT BSC significantly exist partially in our hypotheses.

• Tuberculosis and Respiratory Diseases
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• v.53 no.5
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• pp.510-518
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• 2002

Background : Bronchial anthracofibrosis (BAF) is a dark black or brown pigmentation of multiple large bronchi associated with a fibrotic stenosis or obliteration that is incidentally found during a diagnostic bronchoscopy some reporters have suggested endobronchial tuberculosis or tuberculous lymphadenitis as a possible cause of BAF. However, some BAF patients do not have any medical history of tuberculosis. The aim of this study was to elucidate the clinical features of simple BAF patients, which were not associated with tuberculosis. Methods : We reviewed the patients' charts retrospectiely and interviewed all BAF patients who were followed up for 1 year or more. Among the 114 BAF patients, 43 patents (38 %) had no associated tuberculosis, cancer and pneumoconiosis. The clinical characteristics, radiological findings and associated pulmonary diseases of these patients were evaluated. Results : Most patients were non-smokers, old aged, housewifes who resided in a farming village. The common respiratory symptoms were dyspnea, cough and hemoptysis. The predominant X-ray findings were a multiple bronchial wall thickening(89%), bronchial narrowing or atelectasis (76%) and a mediastinal lymph node enlargement with/without calcification (78%). Pulmonary function test usually showed mild obstructive ventilatory abnormalities but no patient showed a restrictive ventilatory pattern and the patients were frequently affected with chronic bronchitis(51%), post-obstructive pneumonia(40%) and chronic asthma(4%). Conclusion : Because BAF is frequently associated with chronic bronchitis and obstructive pneumonia as well as tuberculosis, a careful clinical evaluation and accurate differential diagnosis is more essential than empirical anti-tuberculous medication.

• Archives of design research
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• v.18 no.2 s.60
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• pp.155-164
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• 2005

Home-service robots need to have sufficient spatial information about the surroundings for interacting with human intelligently and performing services efficiently. It is very important to investigate the efficient interaction style that supports map building task through human-robot collaboration. We first analyzed map building task with a cleaning robot and drew 4 design factors and tentative solutions, including map building procedure (task-preferred procedure/space- preferred procedure), LCD display installation (robot/robot+remote control), navigation method (push type/pull type), feedback modality(GUI/GUI+TTS). The design factors and tentative solutions were defined as independent variables and levels. This research investigated how those variables affect to the human task performance and behavior in map building tast. 8 kinds of experiment prototypes were built and usability test among 16 house wives was conducted for acquiring empirical data. As the experiment result, in terms of map building procedure, space-preferred procedure indicated better task performance than task-proffered procedure as we expected. For the LCD display installation factor, remote control with LCD display indicated higher task performance and subjective satisfaction. In robot navigation method, it was very difficult to find a significant difference between push type and pull type which contrary to our expectation. In fact, push type indicated higher subjective satisfaction. Also in feedback modality, we have acquired negative feedback an additional TTS operation guidance. It seems that robot's autonomy before achieving spatial information is rudiment condition which means users are just interacting with a mobile appliance. Thus they prefer remote-control-based interaction style in robot map building process as they used in traditional appliance control.