• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.113-123
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• 2007

In Ubiquitous communication environment, various conversions of images are essential, and most digital images are compressed by standard methods such as the Joint Photographic Expert Group (JPEG) and Motion Picture Expert Group (MPEG) which are based on the discrete cosine transform (DCT). In this paper, various image resizing algorithms in the DCT domain are analyzed, and a new image resizing algorithm, which shows superior performance compared with the conventional methods, is proposed. For arbitrary-ratio image resizing in the DCT domain, several blocks of $8{\times}8$ DCT coefficients are converted into one block using the conversion formula in the proposed algorithm, and the size of the inverse discrete cosine transform (IDCT) is decided optimally. The performance is analyzed by comparing the peak signal to noise ratio (PSNR) between original images and converted images. The performance of the proposed algorithm is better than that of the conventional algorithm, since the correlation of pixels in images is utilized more efficiently.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.653-659
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• 1994

Human experts have the various own knowledges to be applied in specialized domains. The fact that knowledge itself becomes more critical in the context of textile knowledge with rapid development of new fibers, automated equipments, processes and applications. Diversity of worsted spun yarns, lack of human expertise, and inconsistency among manually generated process plans in consequency of adjustment machine parameters owing to change up raw materials frequently increase the necessity of developing computer aided process planning(CAPP) systems for spinning process. Expert systems offer one of techniques to develop CAPP systems which would behave in a knowledgeable manner. Expert systems are the problem-solving computer program that can reach a level of performance comparable to that of a human expert in some specialized problem domain. This paper is described as job justification module. The job justification module performs to consult with users on which worsted spun yarn manufacturing process planning under the various factors, e.g., raw materials, machine parameters and required yarn counts. Also, the developed module informs the various knowledges relevant process planning. The job justification module offers the control parameters at each process and includes the various standard process plans as database. These knowledges are generated by facts and rules within rule bases.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.355-359
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• 2007

For the decision making of governmental policy about science and technology, domain expert is needed. To choose the expert, the fairness, diversity and speciality is very important. In this research, systematical approach is proposed in the establishment and management of expert database, and recommendation of member of committee for specific field. Additionally, this approach includes the development of tools for the management of governmental committee and the constituents.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.161-170
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• 1995

In this paper, we define schematic User Interface Task(SUIT) as a scheme which is a conceptual unit to specify the dialogue between man and machine. Using a set of SUITs, the user interface can be described separately from domain applications and can be realized through SUIT Manager(SUITMAN), an execution module devised to interprete and process the descriptions of SUITs. SUIT makes it possible to describe conceptual behaviors performed on the interactions of user interface in early stages of expert system development. SUITMAN analyzes the specification described in SUITs and automatically implements the user interface by using the functions in MOTIF library of X-Window system. By an example of SUIT and SUITMAN to the user interface, we applied them into an expert system, 'Circuit Provisioning Expert System'.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.212-219
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• 2006

The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.

• International Journal of CAD/CAM
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• v.5 no.1
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• pp.99-109
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• 2005

This paper introduces an approach to an ontology-based multi-level knowledge framework for a knowledge management system for discrete-product development. Participants in a product life cycle want to share comprehensive product knowledge without any ambiguity and heterogeneity. However, previous knowledge management approaches are limited in providing those aspects: therefore, we suggest an ontology-based multi-level knowledge framework (OBMKF). The bottom level, the axiom, specifies the semantics of concepts and relations of knowledge so ambiguity can be alleviated. The middle level is a product development knowledge map; it defines the concepts and the relations of the product domain knowledge and guides the engineer to process their engineering decisions. The middle level is then classified further into more detailed levels, such as generic product level, specific product level, product version level, and manufactured item level, according to the various viewpoints. The top level is specialized knowledge for a specific domain that gives the solution of a specific task or problem. It is classified into three knowledge types: expert knowledge, engineering function knowledge, and data-analysis-based knowledge. This proposed framework is based on ontology to accommodate a comprehensive range of knowledge and is represented with first-order logic to maintain a uniform representation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.378-382
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• 2001

The purpose of this study was to develop an expert system supporting the diagnosis of diffuse interstitial lung disease by high resolution computed tomography. CLIPS(C language integrated production system) with rule-based reasoning was used to develop the system. Development of expert system had three stages knowledge acquisition, knowledge representation, and reasoning. Knowledge was obtained and integrated, from tables and figure legends of a representative textbook in the domain of this expert system, High-Resolution CT of the Lung, by Webb WR, Mueller NL, and Naidich DP. The acquired knowledge was analyzed to form a knowledge base. Overlapping knowledge was eliminated, similar pieces of knowledge were combined and professional terms were defined. The most important knowledge of findings was then selected for each disease. After groupings of combined findings were made, disease groups were analyzed sequentially to determine final diagnoses. The system was based upon the input of 69 diseases, 185 findings, 73 conditions, 387 status, and 62 rules. The system was set up to determine the diagnoses of diseases from the combination of findings using forward reasoning. In an empirical trial, the system was applied to support the diagnosis of 40 cases of diffuse interstitial lung diseases. The performance of two doctors with support of the system was compared to that of another two doctors without support of the system. The two doctors with the support of the system made more accurate diagnoses than the doctors without the support of the system. The system is believed to be useful for the diagnosis of rare diseases and for cases with many possible differential diagnoses. In conclusion, an expert system supporting the high resolution computed tomographic diagnosis of diffuse interstitial lung disease was developed and the system is thought to be useful for medical practice.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3010-3022
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• 1997

Expert system is one of AI area which was came out at the end of 19705s. It simulates the human's way of thinking to give solutions of Problem in many applications. Most expert system consists of many components such as inference engine, knowledge base, and so on. Especially the performance of expert system depends on the control of enfficiency of inference engine. Inference engine has to get features; tirst, if possible to minimize restrictions when the knowledge base is constructed second, it has to serve various kinds of inferencing methods. In this paper, we design and implement the inference engine which is able to support the general functions to knowledge domain and inferencing method. For the purpose, forward chaining, backward chaining, and direct chaining was employed as an inferencing method in order to be able to be used by user request selectively. Also we not on1y selected production system which makes one ease staradization and modulation to obtain knowledges in target domain, but also constructed knowledge base by means of Extended Clause Bit Metrics (ECBM). Finally, the performance evaluation of inference engine between Rete pattern matching and ECBM has been done.

• The Journal of Korean Association of Computer Education
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• v.14 no.1
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• pp.45-54
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• 2011

Creativity is a fine ability among major values of human resource in knowledge-based society. The purpose of this study is to identify the components of the informatics creativity based on domain-specificity and confluence theory. To explore these components, a three-round, classical Delphi process was administered with an expert panel of 31 individuals. All members of the expert panel initially responded to open-ended questions, and the qualitative results were analyzed. The subsequent two rounds of the Delphi required quantitative responses in which the expert panel was asked to indicate the level of importance using a five point Likert scale associated with specific items. As a result of the Delphi survey, total of 32 items were selected as three core areas such as congnitive, affective and environmental components of informatics creativity.