• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.19-38
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• 2019

This study is a study on the effect of patent management on the performance of new business development, focusing on fusion expert collaboration. In the past, most studies on patent management have been influenced by the quantitative patent index on the business performance. Therefore, research on the effect of patent management on the performance of new business development through the cooperation of fusion experts was very insufficient. Therefore, this study examined the influence of existing patent management on the performance of new business development and the causal relationship between the influence of patent management on new business development performance, focusing on fusion expert collaboration. The results of the hypothesis empirical analysis are as follows. First, patent management showed positive (+) influence on convergence expert cooperation. Patents management has a positive effect on fostering convergence specialists and utilizing convergence experts. Second, patent management has a positive effect on new business development performance. Patent management has a positive effect on the success of the business, the achievement of target sales, the development of new markets, the development of new technologies, and the degree of reflection of customer requirements. Third, patent management mediated by convergence expert cooperation has a negative effect on financial aptitude among new business development outcomes. The results of this study are as follows. First, it is concluded that patent management through mediation of convergence expert cooperation has a positive effect on non - financial performance of new business development performance. Financial performance includes business success and achievement of target sales. Non-financial performance includes new technology development and new market development. Therefore, in order to continuously generate business performance of domestic convergence new business development companies, it suggests that we should make efforts to be linked with new business development performance through revitalization of patent management centered on convergence expert cooperation that has positive (+) influence.

• Journal of the Korea Society for Simulation
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• v.5 no.1
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• pp.67-79
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• 1996

This paper proposes an intelligent simulation generator, called INSIMS, for manufacturing systems. The INSIMS provides an interactive dialogue interactive dialogue interface and code generation tools for modeling and code genration of manufacturing systems. The interactive dialogue interface helps non-expert simulation modeler specify manufacturing systems with ease. After completing the model construction processes, the modeling specifications are automatically converted into SLAM II codes by code generation tools. To validate the usefulness of INSIMS and to illustrate the modeling processes, an example system has been presented.

• 연구논문집
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• s.25
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• pp.99-104
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• 1995

At present, a lot of researches on AS/RS(Automatic Storage and Retrival System) are being performed and also applied to realization of FA, FMS and CIM. Especially facility management and diagnosis of stacker crane that is major equipment of AS/RS, is recognized more importantly. In this paper, Case Base is designed for manager that is non-expert and it is implemented according to possible trouble case for the purpose of trouble diagnosis and maintenance of stacker crane.

• Journal of Korean Academy of Nursing
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• v.37 no.4
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• pp.453-458
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• 2007

Purpose: The purpose of this study was to compare metabolic syndrome (MS) risk factor prevalence by obesity and age in middle-aged women. Method: Two hundred and fifty-one subjects were recruited from the health promotion center of a tertiary care hospital in an urban city. MS was defined by the third report of the national cholesterol education program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults(Adult Treatment Panel III)(ATP III), and obesity was determined by body mass $index(BMI){\geq}25kg/m^2$. Results: The mean blood pressure, fasting glucose, total cholesterol, and triglyceride were significantly higher in the obese group than in the non-obese group. The prevalence of MS, hypertension, and impaired fasting glucose were significantly higher in the obese group than in the non-obese group. In the forties, blood pressure was significantly higher in the obese group than in the non-obese group. In the fifties, body fat, systolic blood pressure, fasting glucose, total cholesterol, and triglyceride were significantly higher in the obese group than in the non-obese group. Conclusions: These results show that the nurse should focus on the obese fifty year old female patients for improvement of the MS risk factors.

• The Journal of Industrial Distribution & Business
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• v.3 no.2
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• pp.5-16
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• 2012

Purpose - Distribution channels cannot function without cooperation. While evidence suggests channel power plays a fundamental role in fostering successful manufacturer-dealer channel cooperation in Western countries distribution systems, little is known empirically as to how dealers' possession of non-mediated powers influence SME manufacturers' cooperation in Asian developing countries. Research design, data, methodology - Drawing upon the extant distribution channels literatures; this study conceptualizes a model and examines the effects of dealer's non-mediated powers on manufacturing SME firms, as well as the mediating influence of trust, relationship satisfaction and commitment. A survey of 400 manufacturing SMEs in Taiwan empirically supports the proposed hypothesis. Results - The model is acceptable in terms of overall goodness of fit. Acceptable model fit are indicated by χ²/(df): 2.35, GFI≧.90; RMSEA values≦ .08; IFI, TLI and CFI values≧.90. Our results indicate that, GFI (0.910), IFI (0.937), TLI (0.903), CFI (0.936), and RMSEA (0.079) and therefore, achieved the suggested thresholds. Conclusions - The results of this study have some managerial implications for managers in the dealer's firms. The overall implication from the findings is that managers can utilize expert, referent and traditional legitimate powers to attain channel cooperation with manufacturing SMEs in addition to garnering their trust, relationship satisfaction and commitment.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.381-389
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• 2016

In this study, we developed evaluation indicators of dam rehabilitation considering climate change in order to prepare for safety of aging dam facilities in accordance with changes in rainfall intensity. The validity and appropriateness of each indicator, and the evaluation criteria were selected for quantitative indicators for each detail through domestic and international case studies, literature review, and expert advice. The survey was carried out to estimate the importance of each indicator for dam rehabilitation. The subjective assessment of the respondents was rearranged using pairwise comparison from the Analytic Hierarchy Process (AHP). The reliability of the survey results was evaluated through consistent verification. In addition, a comparative assessment was carried out which evaluated the reliability importance estimation result to refine the criteria to distinguish rating scales between expert and non-expert groups on dam-related fields.

• The Journal of Korean Medicine
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• v.23 no.2
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• pp.1-18
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• 2002

Objectives : The objective of this study was to examine the academic informationseeking behavior and demand of the oriental medical researcher and to create the base data for establishing a library environment providing a high-quality information service which would aid the activity of such researchers, Methods : We distributed a questionnaire to the one hundred professors of the college of oriental medicine on the method of acquisition of information data, the environment of the library belonging to the college, and the like. Results : $\circled1$ The main class using the academic information service of oriental medicine was revealed to be researchers having a career of 10 to 15 years who had a domestic doctorate in oriental medicine. $\circled2$ When accessing information, the primary information resource used was academic journals. $\circled3$ Of the data forms mentioned in the study, periodicals was used most in number of printed data; computer databases among non-printed data. $\circled4$ The purpose of using an information resource was for performing a research project. $\circled5$ The path of acquisition of information was usually through the materials in their possession. $\circled6$ The greatest difficulty in gathering information was first of all the lack of information owned by the library, and next a lack of time and insufficient knowledge of information search and use. $\circled7$ More than 90% of respondents on the necessity of an expert library answered as "necessary" or "certainly necessary", indicating that the foundation of an expert library is very urgent. Conclusions : This study is beneficial for researchers engaged in oriental medicine to activate the use of information and also it will form a base of data for researchers to establish an environment of expert library in oriental medicine.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.1
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• pp.9-25
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• 1991

This tutorial paper has been written for biologists, physicians or beginners in fuzzy sets theory and applications. This field is introduced in the framework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with linguistic entries or of fuzzy propositions. Relationships between symptoms and diagnoses are interpreted as labels of fuzzy sets. It is shown how possibility measures (soft matching) can be used and combined to derive diagnoses after measurements on collected data. The concepts and methods are illustrated in a biomedical application on inflammatory protein variations. In the case of poor diagnostic classifications, it is introduced appropriate ponderations, acting on the characterizations of proteins, in order to decrease their relative influence. As a consequence, when pattern matching is achieved, the final ranking of inflammatory syndromes assigned to a given patient might change to better fit the actual classification. Defuzzification of results (i.e. diagnostic groups assigned to patients) is performed as a non fuzzy sets partition issued from a "separating power", and not as the center of gravity method commonly employed in fuzzy control. It is then introduced a model of fuzzy connectionist expert system, in which an artificial neural network is designed to build the knowledge base of an expert system, from training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the connections: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through MIN-MAX fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feed forward network is described and illustrated in the same biomedical domain as in the first part.