• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.54-63
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• 2014

It is general that the field plant is too large to be monitored by human works. So it is crucial to prepare one automated monitoring system to prevent unexpected accidents in advance. However, most of previous monitoring systems were to be implemented by human programmer independently, so the total developing cost of a set of similar monitoring systems is so high. In order to overcome this disadvantage, we propose a new specification language for meta-description of monitoring system. Also we propose a generation tool for monitoring system with the input meta-description files. Using these meta-description files, we show it is so fast and effective to get a new monitoring system for a specific field plant. In experiment we have shown that our generation system work successfully in newly developing a monitoring system for the water-vessel plant.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.395-402
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• 2018

This study aims to analyze the film "Never Let Me" by human value which is to be realized in the social structure suppressed by the power of life and the power of discipline in Foucault 's power theory. After 18century having changed monarch power holding the power of life-and-death that enforced corporal punishment, bio-power that corrected body and granted ability suitable discipline to people makes people worked like machine. In control of the bio-power, human achieved safe desire that cure disease and prolong life-span and worked as producer goods. School controls body and make people internalized rule using discipline for working bio-power efficiently. There is differentiation between this movie and the other about human clone. The clones adapt role as organ donator without resistance and there is no conflict between original and copy. Instead of preexistence novel and movie that is set in future, it is a form of past retrospect from the 1970s to 1990s. having emotions, They find independence ego and realize value of life in finite living by depending relation or undergoing loss.

• The Journal of the Korea Contents Association
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• v.6 no.11
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• pp.302-309
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• 2006

This paper propose a practical algorithm to reuse and expand the objects. This algorithm is based on the Motion Path Modification rules. We focus on reusing of the existing motions for synthesizing new motions for the objects. Both the linear and the nonlinear curve-fitting algorithm are applied to modify an animation by keyframe interpolation and to make the motion appear realistic. We also proposes a framework of the scenario-based 3D image synthesizing system that allows common users, who envision a scenario in their minds, to realize it into segments of a cool animation. The framework is useful in building a 3D animation in game programming with a limited set of 3D objects.

• Journal of KIISE:Software and Applications
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• v.33 no.8
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• pp.692-702
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• 2006

In this study, a weighted fuzzy min-max (WFMM) neural network model for pattern classification is proposed. The model has a modified structure of FMM neural network in which the weight concept is added to represent the frequency factor of feature values in a learning data set. First we present in this paper a new activation function of the network which is defined as a hyperbox membership function. Then we introduce a new learning algorithm for the model that consists of three kinds of processes: hyperbox creation/expansion, hyperbox overlap test, and hyperbox contraction. A weight adaptation rule considering the frequency factors is defined for the learning process. Finally we describe a feature analysis technique using the proposed model. Four kinds of relevance factors among feature values, feature types, hyperboxes and patterns classes are proposed to analyze relative importance of each feature in a given problem. Two types of practical applications, Fisher's Iris data and Cleveland medical data, have been used for the experiments. Through the experimental results, the effectiveness of the proposed method is discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.56-64
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• 2018

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.

• Speech Sciences
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• v.10 no.4
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• pp.201-219
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• 2003

Background: The perceptual assessment is generally performed by the voice specialist. The objective evaluation is performed in a voice laboratory. Research in voice laboratories has generated a variety of different objective tests and parameters. The perceptual evaluation is one of the most controversial topics in voice research. Review of literature reveals a wide variety of rating scales and reliability data fluctuating from study to study. Unfortunately, there is no widely accepted valid method for classifying voice disorders and assessing outcome after voice treatment. Objectives: The goals of this research were to identify important objective acoustic parameters of vocal quality, and to establish an objective and quantitative correlate of the perceived vocal quality. Materials and Methods : We evaluated the voice analyzed data from 122 dysphonic patients and 20 normal volunteers. A computerized speech lab. 4300B(CSL) was used to carry out the analysis of each voice sample. Results: Three dysphonia severity indices(DSI) were created using discriminant analysis. DSI is based on the weighted combination of the following selected set of acoustic parameters: absolute jitter(Jita in us), smoothed pitch period perturbation (sPPQ in %), amplitude perturbation quotient(APQ in %), soft phonation index(SPI), average fundamental frequency(Fo in Hz), lowest fundamental frequency(Flo in Hz), and smoothed amplitude perturbation quotient(sAPQ in %). The DSI, being the discriminating rule calculated by the logistic regression, consists of three equation based on statistically significant acoustic parameters. Three DSI were created to reflects best the degree of hoarseness as expressed by G from the GRBAS scale. The more positive this DSI is for a patient, the worse the vocal quality. The more it is negative, the better it is. The effect of sex is included implicitly in the DSI-1 and DSI-2, so that a separate DSI-1 and DSI-2 for males and females need not be used. The DSI is objective because no perceptual input is required for its calculation. Conculsion : This research demonstrates that the voice function values calculated from three different multivariate objective dysphonia severity indices are significantly associated with subjective voice assessments. These multivariate objective dysphonia severity indices may be appropriate for use in clinical trials and outcomes research on treatment effectiveness for voice disorders.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.212-217
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• 2009

There are rule-based learning method and statistic based learning method and so on which represent learning method for hierarchy relation between domain term. In this paper, we propose to leveling and similarity measure using the extended AHP of fuzzy term in Information system. In the proposed method, we extract fuzzy term in document and categorize ontology structure about it and level priority of fuzzy term using the extended AHP for specificity of fuzzy term. the extended AHP integrates multiple decision-maker for weighted value and relative importance of fuzzy term. and compute semantic similarity of fuzzy term using min operation of fuzzy set, dice's coefficient and Min+dice's coefficient method. and determine final alternative fuzzy term. after that compare with three similarity measure. we can see the fact that the proposed method is more definite than classification performance of the conventional methods and will apply in Natural language processing field.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.205-206
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• 2017

Casual games are often have simple rule and easy to play. Like Angry birds, players can sling a bird as a bomb to destroy target. But the film adaption encounters numerous questions. games in pursuit of strong sensed presence, pay attention to experience; film stress the integrity of the story, attaches great importance to plot. However, casual games don't have story and plot. This paper take angry birds as example, analyzes the difficulties and method of adaptation from leisure mobile games to films, summarizes the key successful elements of adaption, such as subdivided the target group, chose an appropriate genre, write a script follow the basic logic and frame of film, set contradiction, complicated the character and still contain key elements of the game, in order to provide new ideas in the future development of integration of game and movie industry.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.625-632
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• 2001

The electronic stores have realized that they need to understand their customers and to quickly response their wants and needs. To be successful in increasingly competitive Internet marketplace, recommender systems are adapting data mining techniques. One of most successful recommender technologies is collaborative filtering (CF) algorithm which recommends products to a target customer based on the information of other customers and employ statistical techniques to find a set of customers known as neighbors. However, the application of the systems, however, is not very suitable for seasonal products which are sensitive to time or season such as refrigerator or seasonal clothes. In this paper, we propose a new adjusted item-based recommendation generation algorithms called the exponentially weighted collaborative filtering recommendation (EWCFR) one that computes item-item similarities regarding seasonal products. Finally, we suggest the recommendation system with relatively high quality computing time on main memory database (MMDB) in XML since the collaborative filtering systems are needed that can quickly produce high quality recommendations with very large-scale problems.

• KDI Journal of Economic Policy
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• v.33 no.4
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• pp.143-177
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• 2011

Upon selecting preferred bidder in Public-Private Partnership projects, multi-dimensional procurement auction, where price factor and non-price factor are evaluated, is used. This paper tries to analyze bidding data in BTO road projects. It is shown that a winner tends to get higher score in bidding evaluation, which is partly due to increase in base score as well as fiercer competition among bidders. It turns out that score margin in non-price factor was determinant in selecting winner. Also, there was no competition when the level of bonus point was set too high. For price factor, it costs 730 million KRW per score in construction subsidy by government, while it costs 2.43 billion KRW per score in toll revenue. For non-price factor, it was estimated to cost 2.30 billion KRW. Based on the results, it was suggested that we should have appropriate level of bonus point for first initiator, change in scoring rule in construction subsidy part, adjustment of base score in evaluation.