• Journal of Information Processing Systems
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• v.12 no.3
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• pp.358-380
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• 2016

In order to considerably reduce the ambiguity rate, we propose in this article a disambiguation approach that is based on the selection of the right diacritics at different analysis levels. This hybrid approach combines a linguistic approach with a multi-criteria decision one and could be considered as an alternative choice to solve the morpho-lexical ambiguity problem regardless of the diacritics rate of the processed text. As to its evaluation, we tried the disambiguation on the online Alkhalil morphological analyzer (the proposed approach can be used on any morphological analyzer of the Arabic language) and obtained encouraging results with an F-measure of more than 80%.

• Speech Sciences
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• v.3
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• pp.71-82
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• 1998

Five sets of nonsense acoustical stimuli {$[sp{\varepsilon},st{\varepsilon},sk{\varepsilon}],\;[p{\varepsilon},t{\varepsilon},k{\varepsilon}],\;[sb{\varepsilon},sd{\varepsilon},sg{\varepsilon}],\;[b{\varepsilon},d{\varepsilon},g{\varepsilon}],\;['{\varepsilon}b{\varepsilon},'{\varepsilon}d{\varepsilon},'{\varepsilon}g{\varepsilon}]$} were presented for identification of English stops to native speakers of English, Chinese, and Korean. The English speakers perceived stops after /s/ as /p, t, k/; in other contexts as /b, d, g/. In the languages where other distinctions exist, however, the evaluation was different. The results suggest that in English the cue for stops after /s/ was syllable structure constraint: After initial /s/ always /p, t, k/ follow; the cue for the initial stops was aspiration. On the basis of the results, it was concluded that in English we should classify the unaspirated voiceless stops in initial /s/-stop clusters into the phoneme where [$p^{h},t^{h},k^{h}$] are in, and that perception is not only language specific but also context specific.

• Journal of Sensor Science and Technology
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• v.21 no.5
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• pp.324-328
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• 2012

In the past a few decades, various kinds of cells have been examined in laboratories all over the world, and their interesting results have been expressed through various methods in journal publications. For a representative example, the increment or reduction of cell numbers during a bio-related experimental process has been demonstrated using the hazard ratio in survival analysis or in the form of a graph. In addition, the condition of cells such as their normality or abnormality would be indicated by the images of the cell nuclei or membranes treated with proper fluorescent labeling. However, the above methods seem to not be quantitative but rather qualitative assessments, which might be difficult to provide people with the eidetic understanding through parameters or numerical data. With adequate suggestions on any indices enabling the explanation for cell conditions, some analyses may be underestimated due to the lack of objectiveness caused by merely linguistic evaluation for the cell conditions, not numerally scientific interpretation. Therefore, in this study, we would suggest some indices enabling quantitative analysis on the cellular conditions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.267-270
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• 1997

In this paper, we proposed an optimazation method using Genetic Algorithm for nonlinear system modeling. Fuzzy Neural Network(FNNs) was used as basic model of nonlinear system. FNNs was fused of Fuzzy Inference which has linguistic property and Neural Network which has learning ability and high tolerence level. This paper, We used FNNs which was proposed by Yamakawa. The FNNs was composed Simple Inference and Error Back Propagation Algorithm. To obtain optimal model, parameter of membership function, learning rate and momentum coefficient of FNNs are tuned using genetic algorithm. And we used simplex algorithm additionaly to overcome limit of genetic algorithm. For the purpose of evaluation of proposed method, we applied proposed method to traffic choice process and waste water treatment process, and then obtained more precise model than other previous optimization methods and objective model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.29-41
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• 1990

An assessment of risk in industrial and urban environments is essential in the prevention of accident and in the analysis of situations which are hazardous to public health and safety. The risk imposed by a particular hazard increases with the likelihood of occurence of the event, the exposure and the possible consequence of that event. In a traditional approach, the calculation of a quantitative value of risk is usually based on an assignment of numerical values of each of the risk factors. Then the product of the values of likelihood, exposure and consequences called risk score is derived. However vagueness and imprecision in mathematical quantification of risk are equated with fuzziness rather than randomness. In this paper, a fuzzy set theoretic approach to risk analysis is proposed as an alternative to the techniques currently used in the area of systems safety. Then the concept of risk evaluation using linguistic representation of the likelihood, exposure and consequences is introduced. A risk assessment model using approximate reasoning technique based on fuzzy logic is presented to drive fuzzy values of risk and numerical example for risk analysis is also presented to illustrate the results.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.2
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• pp.67-72
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• 2005

This paper presents a method to select contingency ranking considering voltage security problems in power systems. Direct method which needs not the detailed knowledge of the post contingency voltage at each bus is used. Based on system operator's experience and knowledge, the membership functions for the MVAR mismatch and allowable voltage violation are justified describing linguistic representation with heuristic rules. Rule base is used for the computation of severity index for each contingency by fuzzy inference. Contingency ranking harmful to the system is formed by the index for security evaluation. Compared with 1P-1Q iteration, this algorithm using direct method and fuzzy inference shows higher computation speed and almost the same accuracy. The proposed method is applied to model system and KEPCO pratical system which consists of 311 buses and 609 lines to show its effectiveness.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.37-46
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• 1997

제품의 정성적 품질평가에서, 제품의 최종품질을 구성하는 다수의 특성에 대한 만족도가 언어로써 표현되어 소비자의 구매행동이란 의사결정으로 표출되는데, 이러한 주관적 평가에는 평가의 애매함(fuzziness)이 수반되므로 품질의 평가구조를 합리적으로 파악하기 위해서는 애매함의 존재를 고려에 넣지 않으면 안된다. 다수의 품질특성이 계층적(hierarchical)인 구조로 연결되어 최상위 품질특성으로 구성되며, 특성간의 중요도(relative importances)가 계층별로 결정되는 경우, 이들 개개의 특성에 대한 만족도의 평가로부터 어떤 구조적인 관계를 통해 그 제품에 대한 종합평가가 이루어지나, 개개의 특성에 대한 평가가 애매한 이상 최종 결과인 종합적 만족도도 애매한 것으로 된다. 즉, 평가모델의 구조도 평가의 패턴도 퍼지화되므로 이러한 평가에서 퍼지이론의 응용에 따른 효과를 가장 크게 기대할 수 있는 퍼지추론모델을 이용하여 계층간, 품질특성간의 퍼지관계와 특성의 중요도 및 언어변수(linguistic variables)의 형태로 주어지는 입력정보로써 품질구조를 명확히 하고, 패턴인식(pattern recognition)의 개념을 이용하여 평가자의 제품에 대한 평가결과를 언어로써 표현한다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.2
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• pp.233-240
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• 1999

Even though the recent construction safety disasters not only result in the loss inside construction sites but also become to a large public disasters, safety activities are managed in an irrational way and safety rules are ignored in the construction sites which leads to occur same type of disasters repeatedly. In this paper, a fuzzy set theoretic approach to risk analysis is proposed as an alternative to the techniques currently used in the general construction projects safety. Then the concept of risk evaluation using linguistic representation of the likelihood, exposure and consequences is introduced. A risk assessment model using approximate reasoning technique base on fuzzy logic is presented to drive fuzzy values of risk and numerical example for risk analysis is also presented to illustrate the results.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.4
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• pp.1-9
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• 2001

In this paper, we propose Fuzzy M/M/1/K queueing network model which has derived by appling the fuzzy set theory to M/M/l/K queueing network model in which has single server and system capacity K. When the arriving rate of input job and the servicing rate of a server arc represented as the linguistic attributes, the system analysis can be performed by using this model. The major evaluation measures of system such as the average number of jobs existing in the system, the average number of jobs into system, and the average spending time of job in system etc. are derived for the evaluation of system. Computer simulation was performed for verifying the effectiveness of these result equations. In which the various fuzzy arriving rates and fuzzy servicing rates according to varying the system capacity K were given for the system evaluation. We verified that the results of simulation are in accord with the expected evaluations in the proposed fuzzy model.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.