• Asian Pacific Journal of Cancer Prevention
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• 제14권4호
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• pp.2151-2153
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• 2013

The history of the APOCP/APJCP goes back to 1999 when a number of interested scientists joined together to form the organization and to launch a new journal to support cancer prevention research in the Asian-Pacific area. Since the initial Founding Conference, some six General Assemblies (GAs) and ten Regional Conferences (RCs) and Special Study Sessions have been organized. Already the decisions have been made for two further GAs and at least three RCs. As of the April issue of 2013, a total of nearly 3,700 papers have already been published in regular issues of the APJCP or special supplements. With support of the Korean National Cancer Center, housing the Chief Editorial Office, the journal is now including approximately 100 papers a month. Although it experienced a set-back by reduction in the Impact Factor (IF) from 1.29 in 2010 to 0.67 in 2011, there are good grounds to expect an improvement in 2012. However, the future of the APOCP/APJCP will continue to depend on its membership, making continuous efforts to attend our conferences and submit good quality manuscripts. It is particularly important to cite papers in the APJCP wherever possible, if the wish is for an IF commensurate with our long term aims. In that sense it is up to all authors, since the journal will continue to have a very positive ploicy towards accepting papers from all countries within the Asian-Pacific, with continue to varied levels of resources. The editorial team looks forward to your considered support. The APOCP also hopes to see you in person at future meeetings, so that you have a more active voice in deciding the best way forward in our cooperative enterprise.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2000년도 봄 학술발표회 논문집
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• pp.101-108
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• 2000

In this study, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river, This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• 한국통신학회논문지
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• 제18권8호
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• pp.1083-1093
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• 1993

Recently, some applications require the multicast service that transmit messages to multiple destinations in computer communication network enviroment. Multicast service is to send messages to the group which consists of a number of processes. A multicast group is a collection of processes which are destinations of the transmitted messages and these processes may run on one or more hosts. Therefore, it is important to manage each member of process groups in order to provide efficient multicast services. In this paper, we design and implement group management system to support multicast services. Group Management System was designed with Process Group Management System(PGMS) and Host Group Management System(HGMS). We have implemented basic primitives of PGMS, HGMS. Also, membership tree management algorithm is designed and implemented. Membership tree provides the relation of the members of multicast groups and routing Informations.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제14권4호
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• pp.240-248
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• 2014

We present a robust speaker identification algorithm that uses novel features based on soft bag-of-word representation and a simple Naive Bayes classifier. The bag-of-words (BoW) based histogram feature descriptor is typically constructed by summarizing and identifying representative prototypes from low-level spectral features extracted from training data. In this paper, we define a generalization of the standard BoW. In particular, we define three types of BoW that are based on crisp voting, fuzzy memberships, and possibilistic memberships. We analyze our mapping with three common classifiers: Naive Bayes classifier (NB); K-nearest neighbor classifier (KNN); and support vector machines (SVM). The proposed algorithms are evaluated using large datasets that simulate medical crises. We show that the proposed soft bag-of-words feature representation approach achieves a significant improvement when compared to the state-of-art methods.

• 대한산업공학회지
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• 제29권1호
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• pp.32-40
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• 2003

In this study, we develop the Genetic Fuzzy System(GFS) to estimate the link traveling speed. Based on the genetic algorithm, we can get the fuzzy rules and membership functions that reflect more accurate correlation between traffic data and speed. From the fact that there exist missing links that lack traffic data, we added a Case Base Reasoning(CBR) to GFS to support estimating the speed of missing links. The case base stores the fuzzy rules and membership functions as its instances. As cases are accumulated, the case base comes to offer appropriate cases to missing links. Experiments show that the proposed GFS provides the more accurate estimation of link traveling speed than existing methods.

• 한국치위생학회지
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• 제23권6호
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• pp.493-499
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• 2023

Objectives: This study sought to identify dental hygiene students' adult attachment, interpersonal competence, self-respect, and sociable support, and to identify factors that affect interpersonal competence. Method: A self-administered survey was conducted on 180 students attending dental hygiene schools nationwide from 14 February to 30 May, 2023. Descriptive statistics, t-test, one-way ANOVAs, Pearson correlation coefficient, and stepwise multiple linear regression analys were used, as determined by the SPSS 26.0 program. Results: Dental hygiene students' interpersonal competence measured 3.61 points, adult attachment measured 3.44 points, self-respect measured 3.44 points, and sociable support measured 4.00 points. In terms of general characteristics, significant differences were found in satisfaction with college life and club membership. Interpersonal competence was positively correlated with adult attachment, self-respect, and sociable support. The factor that had the greatest impact on interpersonal competence of dental hygiene students was sociable support, with an explanatory power of 37.3%. Conclusions: In order to improve the sociable support for dental hygiene students, a social activity support network within and outside of school is needed.

• 한국지능시스템학회논문지
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• 제13권4호
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• pp.486-490
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• 2003

Software qualify models can predict the risk of faults in the software early enough for cost-effective prevention of problems. This paper introduces a least squares support vector machine (LS-SVM) as a fuzzy regression method for predicting fault ranges in the software under development. This LS-SVM deals with the fuzzy data with crisp inputs and fuzzy output. Predicting the exact number of bugs in software is often not necessary. This LS-SVM can predict the interval that the number of faults of the program at each session falls into with a certain possibility. A case study on software reliability problem is used to illustrate the usefulness of this LS -SVM.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.204-210
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• 2011

This paper proposes a fuzzy support vector machine ($FSVM_n$) pattern classifier to classify the arrhythmia patterns of an electrocardiograph (ECG). The $FSVM_n$ is a pattern classifier which combines n-dimensional fuzzy membership functions with a slack variable of SVM. To evaluate the performance of the proposed classifier, the MIT/BIH ECG database, which is a standard database for evaluating arrhythmia detection, was used. The pattern classification experiment showed that, when classifying ECG into four patterns - NSR, VT, VF, and NSR, VT, and VF classification rate resulted in 99.42%, 99.00%, and 99.79%, respectively. As a result, the $FSVM_n$ shows better pattern classification performance than the existing SVM and FSVM algorithms.

• 산업공학
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• 제12권4호
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• pp.506-513
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• 1999

We use a path analysis to identify influential latent variables on employees' anticipated commitment to a merged bank. Survey samples are taken from Hanvit bank which is a merged form of Hanil and Sangup. Latent variables used in the path analysis are perceptions of organizational support, contact conditions, organizational unity, employee threat and organizational commitment. We find an interesting pre-merger group membership effect as well as merger pattern perceived by employees on the path for the anticipated commitment to the merged bank.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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• pp.1171-1174
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• 1993

A promising approach to get the benefits of neural networks and fuzzy logic is to combine them into an integrated system to merge the computational power of neural networks and the representation and reasoning properties of fuzzy logic. In this context, this paper presents a fuzzy neural network which is able to code fuzzy knowledge in the form of it-then rules in its structure. The network also provides an efficient structure not only to code knowledge, but also to support fuzzy reasoning and information processing. A learning scheme is also derived for a class of membership functions.