• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.61-70
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• 2004

It is difficult to find an appropriate web site because exponentially growing web contains millions of web documents. Personalization of web search can be realized by recommending proper web sites using user profile but more efficient method is needed for estimating preference because user's evaluation on web contents presents many aspects of his characteristics. As user profile has a property of non-linearity, estimation by classifier is needed and combination of classifiers is necessary to anticipate diverse properties. Structure adaptive self-organizing map (SASOM) that is suitable for Pattern classification and visualization is an enhanced model of SOM and might be useful for web mining. Fuzzy integral is a combination method using classifiers' relevance that is defined subjectively. In this paper, estimation of user profile is conducted by using ensemble of SASOM's teamed independently based on fuzzy integral and evaluated by Syskill ＆ Webert UCI benchmark data. Experimental results show that the proposed method performs better than previous naive Bayes classifier as well as voting of SASOM's.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.33-40
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• 2009

This paper presents the high performance control of interior permanent magnet synchronous motor(IPMSM) using space vector(SV) PWM method based on hybrid artificial intelligent(HAI) controller. The HAI controller combines the advantages between adaptive fuzzy control and neural network The SV PWM method is applied to a speed control system of motor in the industry field until now and is feasible to improve harmonic rate of output current, switching frequency and response characteristics. This HAI controller is used instead of conventional PI controller in order to solve problems happening when calculating a reference voltage. The HAI controller improves speed performance by hybrid combination of reference model-based adaptive mechanism method, fuzzy control and neural network. This paper analyzes response characteristics of parameter variation, steady-state and transient-state using proposed HAI controller and this controller compares with conventional fuzzy neural network(FNN) and PI controller. Also, this paper proves validity of HAI controller.

• The Journal of Industrial Distribution & Business
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• v.9 no.2
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• pp.65-72
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• 2018

Purpose - One of the biggest problems in the e-learning distribution process is the lack of quality content and learners' discredit in e-learning content. In order to respond to the various demands of the corporate education field appropriately, it is necessary to search for directions of new e-learning models that are out of traditional e-learning contents. The purpose of this study is to identify recent trend issues related to corporate e-learning and to suggest directions for development. Research design, data, and methodology - Based on the literature review, trend issues that should be considered important in corporate e-learning were derived. Online survey was conducted to evaluate the importance-feasibility of each issue to 13 experts on e-learning and corporate education. The contents of the questionnaire are as follows: 1) recognition of importance and feasibility of trend issues to be considered important in the future corporate education field; 2) factors to be considered in developing future e-learning contents. Results - Six trends derived from a comprehensive literature review. The most important e-learning trends for corporate education field were 'mobile learning', 'micro learning', 'blended learning', 'social learning', 'adaptive learning', 'engaged learning'. As a result of evaluating the importance and feasibility of each issue, experts point out that 'mobile learning' and 'micro learning' should be actively considered for introduction and utilization at present. In addition, 'social learning' and 'blended learning' need to be actively considered in the near future. On the other hand, experts recognized that 'adaptive learning' and 'engaged learning' need to be prepared from a long-term perspective. Conclusions - There are two main reasons for this result. First, in corporate e-learning, it is important to 1) be able to update on time, 2) the connection with the workplace is important. Second, it requires realistic verification of the expected performance of the learning model. To be considered part of the future are as follows: First, the value and effectiveness of the new e-learning type should be studied. Seconds, e-learning contents should be developed through adopting SAM or Agile methodology. Through this process, we would be able to enhance the quality in e-learning content.

• Journal of Microbiology and Biotechnology
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• v.18 no.2
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• pp.270-282
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• 2008

The yeast Saccharomyces cerevisiae has defense mechanisms identical to higher eukaryotes. It offers the potential for genome-wide experimental approaches owing to its smaller genome size and the availability of the complete sequence. It therefore represents an ideal eukaryotic model for studying cellular redox control and oxidative stress responses. S. cerevisiae Yap1 is a well-known transcription factor that is required for $H_2O_2$-dependent stress responses. Yap1 is involved in various signaling pathways in an oxidative stress response. The Gpx3 (Orp1/PHGpx3) protein is one of the factors related to these signaling pathways. It plays the role of a transducer that transfers the hydroperoxide signal to Yap1. In this study, using extensive proteomic and bioinformatics analyses, the function of the Gpx3 protein in an adaptive response against oxidative stress was investigated in wild-type, gpx3-deletion mutant, and gpx3-deletion mutant overexpressing Gpx3 protein strains. We identified 30 proteins that are related to the Gpx3-dependent oxidative stress responses and 17 proteins that are changed in a Gpx3-dependent manner regardless of oxidative stress. As expected, $H_2O_2$-responsive Gpx3-dependent proteins include a number of antioxidants related with cell rescue and defense. In addition, they contain a variety of proteins related to energy and carbohydrate metabolism, transcription, and protein fate. Based upon the experimental results, it is suggested that Gpx3-dependent stress adaptive response includes the regulation of genes related to the capacity to detoxify oxidants and repair oxidative stress-induced damages affected by Yap1 as well as metabolism and protein fate independent from Yap1.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.398-407
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• 2012

We propose a tree modeling method of expressing realistically and efficiently numerous trees distributed on a broad terrain. This method combines and simplifies the recursive hierarchy of tree branch and branch generation process through self-organizing from buds, allowing users to generate trees that can be used more intuitively and efficiently. With the generation process the leveled structure and the appearance such as branch length, distribution and direction can be controlled interactively by user. In addition, we introduce an environment-adaptive model that allows to grow a number of trees variously by controlling at the same time and we propose an efficient application method of growing environment. For the real-time rendering of the complex tree models distributed on a broad terrain, the rendering process, the LOD(level of detail) for the branch surfaces, and shader instancing are introduced through the GPU(Graphics Processing Unit). Whether the numerous trees are expressed realistically and efficiently on wide terrain by proposed models are confirmed through simulation.

• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.123-140
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• 2009

Fuzzy neural network is an integrated model of artificial neural network and fuzzy system and it has been successfully applied in control and forecasting area. Recently ANFIS(Adaptive Network-based Fuzzy Inference System) has been noticed widely among various fuzzy neural network models because of outstanding performance of control and forecasting accuracy. ANFIS has capability to refine its fuzzy rules interactively with human expert. In particular, when we use initial rule structure for machine learning which is generated from human expert, it is highly probable to reach global optimum solution as well as shorten time to convergence. We propose metrics to evaluate interpretability of generated rules as a means of acquiring domain knowledge and compare level of interpretability of ANFIS fuzzy rules to those of C5.0 classification rules. The proposed metrics also can be used to evaluate capability of rule generation for the various machine learning methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3B
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• pp.114-129
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• 2005

In this paper, we examine Interleaved Polling with Adaptive Cycle Time (IPACT) algorithm which was proposed to control upstream traffic for Gigabit Ethernet-PONs, and we analyze the performance of the gated service and the limited service of the IPACT mathematically. For the mathematical performance analysis, we model IPACT algorithm as a polling system and use mean-value analysis. We divide arrival rate λ value into three regions and analyze each region accordingly. We obtain average packet delay, average queue size and average cycle time of both the gated and the limited service. We compare analytical results with simulation to verify the accuracy of the mathematical analysis. Upon now, simulation analysis have been used to evaluate the performance of EPONs, which require much time sud effort. Mathematical analysis can be widely used in the design of EPON systems since system designers can obtain various performance results rapidly.

• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.315-323
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• 2011

This paper proposes two methods of estimating prior distribution to improve the performance of rapid speaker adaptation based on maximum a posteriori linear regression (MAPLR). In general, prior distribution of the transformation matrix used in MAPLR adaptation is estimated from all of the training speakers who are employed to construct the speaker-independent model, and it is applied identically to all new speakers. In this paper, we propose a method in which prior distribution is estimated from a group of reference speakers, selected using adaptation data, so that the acoustic characteristics of the selected reference speakers may be similar to that of the new speaker. Additionally, in MAPLR adaptation with block-diagonal transformation matrix, we propose a method in which the mean matrix and covariance matrix of prior distribution are estimated from two groups of transformation matrices obtained from the same training speakers, respectively. To evaluate the performance of the proposed methods, we examine word accuracy according to the number of adaptation words in the isolated word recognition task. Experimental results show that, for very limited adaptation data, statistically significant performance improvement is obtained in comparison with the conventional MAPLR adaptation.

• IMMUNE NETWORK
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• v.5 no.3
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• pp.137-143
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• 2005

Background: Millions of people in the world are suffering from atopic dermatitis (AD), which is a chronic inflammatory skin disease triggered by Th2 immune responses. The NC/Nga mouse is the most extensively studied animal model of AD. Like human AD, NC/Nga mice demonstrate increased levels of IgE, a hallmark of Th2 immune responses. Adaptive immunity cannot be generated without help of innate immunity. Especially natural killer T (NKT) cells and marginal zone B (MZB) cells have been known to play important roles in linking innate immunity to adaptive immunity. Methods: Through flow cytometric analysis and ELISA assay, we investigated whether these lymphocytes might be altered in number in NC/Nga mice. Results: Our data demonstrated that the number of NKT cells was reduced in NC/Nga mice and IFN${\gamma}$ production by NKT cells upon ${\alpha}-GalCer$ stimulation decreased to the levels of CD1d KO mice lacking in NKT cells. However, reduction of NKT cells in NC/Nga mice was not due to CD1d expression, which was normal in the thymus. Interestingly, there was a significant increase of $CD1d^{high}B220^+$ cells in the spleen of NC/Nga mice. Further, we confirmed that $CD1d^{high}B220^+$ cells are B cells, not dendritic cells. These $CD1d^{high}B220^+$ B cells show $IgM^{high}CD21^{high}CD23^{low}$, a characteristic phenotype of MZB cells. Conclusion: We provide the evidence that there are decreased activities of NKT cells and increased number of MZB cells in the NC/Nga mice. Our findings may thus explain why NC/Nga mice are susceptible to AD.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.253-260
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• 2004

This paper proposes a novel algorithm for hybrid lossless audio coding, which employs an integer wavelet transform and a linear prediction model. The proposed algorithm divides the input signal into flames of a proper length, decorrelates the framed data using the integer wavelet transform and linear prediction and finally entropy-codes the frame data. In particular, the adaptive Golomb-Rice coding method used for the entropy coding selects an optimal option which gives the best compression efficiency. Since the proposed algorithm uses integer operations, it significantly improves the computation speed in comparison with an algorithm using real or floating-point operations. When the coding algorithm is implemented in hardware, the system complexity as well as the power consumption is remarkably reduced. Finally, because each frame is independently coded and is byte-aligned with respect to the frame header, it is convenient to move, search, and edit the coded, compressed data.