• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.115-132
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• 2008

Metal industry is one of the most representative heavy industries and the median sales volume of steel and nonferrous metal companies is over one billion dollars in the case America [Forbes 2006]. As seen in the recent business market situation, an increasing number of industrial manufacturers and suppliers are moving from adversarial to cooperative exchange attitudes that support the long-term relationships with their customers. This article presents the results of an empirical study of the antecedent factors of business relationships in metal industry of the United States. Commitment has been reviewed as a significant and critical variable in research on inter-organizational relationships (Hong et al. 2007, Kim et al. 2007). The future stability of any buyer-seller relationship depends upon the commitment made by the interactants to their relationship. Commitment, according to Dwyer et al. [1987], refers to "an implicit or explicit pledge of relational continuity between exchange partners" and they consider commitment to be the most advanced phase of buyer-seller exchange relationship. Bonds are made because the members need their partners in order to do something and this integration on a task basis can be either symbiotic or cooperative (Svensson 2008). To the extent that members seek the same or mutually supporting ends, there will be strong bonds among them. In other words, the principle that affects the strength of bonds is 'economy of decision making' [Turner 1970]. These bonds provide an important idea to study the causes of business long-term relationships in a sense that organizations can be mutually bonded by a common interest in the economic matters. Recently, the framework of structural bonding has been used to study the buyer-seller relationships in industrial marketing [Han and Sung 2008, Williams et al. 1998, Wilson 1995] in that this structural bonding is a crucial part of the theoretical justification for distinguishing discrete transactions from ongoing long-term relationships. The major antecedent factors of buyer commitment such as technology, CLalt, transaction-specific assets, and importance were identified and explored from the perspective of structural bonding. Research hypotheses were developed and tested by using survey data from the middle managers in the metal industry. H1: Level of technology of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H2: Comparison level of alternatives is negatively related to the level of structural bonding between the buyer and the seller. H3: Amount of the transaction-specific assets is positively related to the level of structural bonding between the buyer and the seller. H4: Importance of the relationship partner is positively related to the level of structural bonding between the buyer and the seller. H5: Level of structural bonding is positively related to the level of commitment to the relationship. To examine the major antecedent factors of industrial buyer's structural bonding and long-term relationship, questionnaire was prepared, mailed out to the sample of 400 purchasing managers of the US metal industry (SIC codes 33 and 34). After a follow-up request, 139 informants returnedthe questionnaires, resulting in a response rate of 35 percent. 134 responses were used in the final analysis after dropping 5 incomplete questionnaires. All measures were analyzed for reliability and validity following the guidelines offered by Churchill [1979] and Anderson and Gerbing [1988]., the results of fitting the model to the data indicated that the hypothesized model provides a good fit to the data. Goodness-of-fit index (GFI = 0.94) and other indices ( chi-square = 78.02 with p-value = 0.13, Adjusted GFI = 0.90, Normed Fit Index = 0.92) indicated that a major proportion of variances and covariances in the data was accounted for by the model as a whole, and all the parameter estimates showed statistical significance as evidenced by large t-values. All the factor loadings were significantly different from zero. On these grounds we judged the hypothesized model to be a reasonable representation of the data. The results from the present study suggest several implications for buyer-seller relationships. Theoretically, we attempted to conceptualize the antecedent factors of buyer-seller long-term relationships from the perspective of structural bondingin metal industry. The four underlying determinants (i.e. technology, CLalt, transaction-specific assets, and importance) of structural bonding are very critical variables of buyer-seller long-term business relationships. Our model of structural bonding makes an attempt to systematically examine the relationship between the antecedent factors of structural bonding and long-term commitment. Managerially, this research provides industrial purchasing managers with a good framework to assess the interaction processes with their partners and, ability to position their business relationships from the perspective of structural bonding. In other words, based on those underlying variables, industrial purchasing managers can determine the strength of the company's relationships with the key suppliers and its state of preparation to be a successful partner with those suppliers. Both the supplying and customer companies can also benefit by using the concept of 'structural bonding' and evaluating their relationships with key business partners from the structural point of view. In general, the results indicate that structural bonding gives a critical impact on the level of relationship commitment. Managerial implications and limitations of the study are also discussed.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Tuberculosis and Respiratory Diseases
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• v.39 no.6
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• pp.453-473
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• 1992

Background: National survey was performed to estimate the incidence of sarcoidosis in Korea. The clinical data of confirmed cases were analysed for the practice of primary care physicians and pulmonary specialists. Methods: The period of study was from January 1991 to December 1992. Data were retrospectively collected by correspondence with physicians in departments of internal medicine, dermatology, ophthalmology and neurology of the hospitals having more than 100 beds using returning postcards. In confirmed and suspicious cases of sardoidosis, case record chart for clinical and laboratory findings were obtained in detail. Results: 1) Postcards were sent to 523 departments in 213 hospitals. Internal medicine composed 41%, dermatology 20%, ophthalmology 20% and neurology 19%. 2) Postcards were returned from 241 departments (replying rates was 48%). 3) There were 113 confirmed cases from 50 departments and 10 cases. The cases were composed from internal medicine (81%), dermatology (13%), ophthalmology (3%) and neurology (3%). 78 confirmed cases were analysed, which were composed from department of internal medicine (92%), dermatology (5%), and neurology (3%). 4) The time span for analysed cases was 1980 to 1992. one case was analysed in 1980 and the number gradually increased to 18 cases in 1991. 5) The majority of patients (84.4%) were in the age group of 20 to 49 years. 6) The ratio of male to female was 1 : 1.5. 7) The most common chief complains were respiratory symptoms, dermatologic symptoms, generalized discomforts, visual changes, arthralgia, abdominal pains, and swallowing difficulties in order. 16% of the patients were asymptomatic. 8) Mean duration between symptom onset and diagnosis was 2 months. 9) The most common symptoms were respiratory, general, dermatologic, ophthalmologic, neurologic and cardiac origin in order. 10) Hemoglobin, hematocrits and platelet were in normal range. 58% of the patients had lymphopenia measuring less than 30% of white cell count. The ratio of CD4 to CD8 lymphocytes was $1.73{\pm}1.16$ with range of 0.43 to 4.62. ESR was elevated in 43% of the cases. 11) Blood chemistry was normal in most cases. Serum angiotensin converting enzyme (S-ACE) was $66.8{\pm}58.6\;U/L$ with the range of 8.79 to 265 U /L. Proteinuria of more than 150 mg was found in 42. 9% of the patients. 12) Serum IgG was elevated in 43.5%, IgA in 45.5%, IgM in 59.1% and IgE in 46.7%. The levels of complement C3 and C4 were in the normal range. Anti-nuclear antibody was detected in 11% of the cases. Kweim test was performed in 3 cases, and in all cases the result was positive. 13) FVC was decreased in 17.3%, FEV1 in 11.5%, FEV1/FVC in 10%, TLC in 15.2%, and DLco in 64.7%. 14) PaO2 was decreased below 90 mmHg in 48.6% and PaCO2 was increased above 45 mmHg in 5.7%. 15) The percentage of macrophages in BAL fluid was $51.4{\pm}19.2%$, lymphocytes $44.4{\pm}21.1%$, and the ratio of CD4 to CD8 lymphocytes was $3.41{\pm}2.07$. 16) There was no difference in laboratory findings between male and female. 17) Hilar enlargement on chest PA was present in 87.9% (bilaterally in 78.8% and unilaterally in 9.1%). 18) According to Siltzbach's classification, stage 0 was 5%, stage 158.3%, stage 228.3%, and stage 38.3%. 19) Hilart enlargement on chest CT was present in 92.6% (bilaterally 76.4% and unilaterally in 16.2%). 20) HRCT was done in 16 cases. The most common findings were nodules, interlobular thickening, focal patchy infiltrations in order. Two cases was normal finding. 21) Other radiologic examinations showed bone change in one case and splenomegaly in two cases. 22) Gallium scan was done in 12 cases. Radioactivity was increased in hilar and mediastinal lymph nodes in 8 cases and in parenchyme in 2 cases. 23) The pathologic diagnosis was commonly performed by transbrochial lung biopsy (TBLB, 47.3%), skin and mediastinal lymph nodes biopsy (34.5%), peripheral lymph nodes biopsy (23.6%), open lung biopsy (18.2%) and bronchial biopsy in order. 24) The most common findings in pathology were non·caseating granuloma (100%), multi-nucleated giant cell (47.3%), hyalinized acellular scar (34.5%), reticulin fibrin network (20%), inclusion body (10.9%), necrosis (9.1%), and lymphangitic distribution of granuloma (1.8%) in order. Conclusion: Clinical, laboratory, radiologic and pathologic findings were summarized. This collected data will assist in finding a test for detection and staging of sarcoidosis in Korea in near future.