• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.25-33
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• 2009

Recently, the TS fuzzy models that include the linear equations in the consequent part are widely used for time series forecasting, and the prediction performance of them is somewhat dependent on the characteristics of time series such as stationariness. Thus, a new prediction method is suggested in this paper which is especially effective to nonstationary time series prediction. First, data preprocessing is introduced to extract the patterns and regularities of time series well, and then multiple model TS fuzzy predictors are constructed. Next, an appropriate model is chosen for each input data by an adaptive model selection mechanism based on rough sets, and the prediction is going. Finally, the error compensation procedure is added to improve the performance by decreasing the prediction error. Computer simulations are performed on typical cases to verify the effectiveness of the proposed method. It may be very useful for the prediction of time series with uncertainty and/or nonstationariness because it handles and reflects better the characteristics of data.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.526-537
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• 1999

In the paper. we propose an evaluation model based the adaptive fuzzy systems, which can transform the physical features of a color pattern to the emotional features. The model is motivated by the Soen's psychological experiments, in which he found the physical features such as average hue, saturation, intensity and the dynamic components of the color patterns affects to the emotional features represented by a pair of adjective words having the opposite meanings. Our proposed model consists of two adaptive fuzzy rule-bases and the y-model, a l i r ~ r ys et operator, to fuze the evaluation values produced by them. The model shows con~parablep erformances to the neural network for the approximation of the nonlinear transforms, and it has the advantage to obtain the linbwistic interpretation from the trained results. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

• The Journal of the Korea Contents Association
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• v.14 no.6
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• pp.529-538
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• 2014

This study was conducted as an need analysis through close and open semi-structured surveys, in order to identify the adaptive elements of the adaptive e-learning system. The study was conducted on students majoring computer education in teacher's college. In terms of the process of the need analysis, Rossett Model was applied. For the research method, responses on the open questionnaire were analyzed. In terms of the analysis method, coding was used to extract the theme of the content, and through the constant comparison method, categorizing took place. As the element that offers adaption in the adaptive learning system, it escapes from the existing learning style, and recognized the importance of providing adaptability for different elements such as the learner's level, learning objectives, and learning contents. Especially, An instructional model was identified as an important element that helps reach rationality as well as efficiently conduct the learning objectives.

• Korean Journal of Social Welfare Studies
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• v.44 no.2
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• pp.113-140
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• 2013

This study aimed to empirically test the causal model of stress-coping-adaptation for unwed mothers, which was built upon the Lazarus and Folkman's(1984) "Stress-Coping-Adaptation" model. In doing so researchers endeavored to provide practice implications as well as theoretical ones which would be helpful both to alleviate the unwed mothers' stress level, and to facilitate social adaptation of the unwed mothers. In order to fulfill research purpose data were collected from the national sample of 423 unwed mothers in Korea. The results showed that the overall goodness of the fit of the proposed causal model was excellent. Most of the path coefficients between social support, stress, coping, and adaption turned out to be statistically significant. The moderating effects of "pursuit of social support" between stress and adaption was not significant statistically, though. Implications and suggestions were provided to reduce the level of stress of the unwed mothers, and to facilitate the adaptation of the unwed mothers.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.511-518
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• 2018

This paper deals with improving speech intelligibility by applying binary mask to time-frequency units of speech in noise. The binary mask is set to "0" or "1" according to whether speech is dominant or noise is dominant by comparing signal-to-noise ratio with pre-defined threshold. Bayesian classifier trained with Gaussian mixture model is used to estimate the binary mask of each time-frequency signal. The binary mask based noise suppressor improves speech intelligibility only in noise condition which is included in the training data. In this paper, speaker adaptation techniques for speech recognition are applied to adapt the Gaussian mixture model to a new noise environment. Experiments with noise-corrupted speech are conducted to demonstrate the improvement of speech intelligibility by employing adaption techniques in a new noise environment.

• Journal of Convergence for Information Technology
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• v.10 no.5
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• pp.1-7
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• 2020

This paper proposes a link adaptation method for Underwater Internet of Things (IoT), which reduces power consumption of sensor nodes and improves the throughput of network in underwater IoT network. Adaptive Modulation and Coding (AMC) technique is one of link adaptation methods. AMC uses the strong correlation between Signal Noise Rate (SNR) and Bit Error Rate (BER), but it is difficult to apply in underwater IoT as it is. Therefore, we propose the machine learning based AMC technique for underwater environments. The proposed Modulation Coding and Scheme (MCS) prediction model predicts transmission method to achieve target BER value in underwater channel environment. It is realistically difficult to apply the predicted transmission method in real underwater communication in reality. Thus, this paper uses the high accuracy BER prediction model to measure the performance of MCS prediction model. Consequently, the proposed AMC technique confirmed the applicability of machine learning by increase the probability of communication success.

• The Journal of the Acoustical Society of Korea
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• v.21 no.5
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• pp.455-461
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• 2002

This paper presents a method that improves the performance of the personal voice dialling system in which speaker independent phoneme HMM's are used. Since the speaker independent phoneme HMM based voice dialing system uses only the phone transcription of the input sentence, the storage space could be reduced greatly. However, the performance of the system is worse than that of the system which uses the speaker dependent models due to the phone recognition errors generated when the speaker independent models are used. In order to solve this problem, a new method that jointly estimates transformation vectors for the speaker adaptation and transcriptions from training utterances is presented. The biases and transcriptions are estimated iteratively from the training data of each user with maximum likelihood approach to the stochastic matching using speaker-independent phone models. Experimental result shows that the proposed method is superior to the conventional method which used transcriptions only.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.349-351
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• 2005

자가 적응 시스템을 무인 시스템(UWS: Unmanned Weapon Systems)에 적용하기 위한 다양한 연구가 이루어지고 있다. 자가 적응 시스템은 임무중인 시스템이 다양한 주변 환경 및 시스템의 변화에 따라 능동적으로 시스템 또는 임무수행을 위한 전략을 주정해 항상 최상의 성능을 발휘할 수 있도록 하는 능력을 갖춘 시스템을 말한다. 자가 적응 시스템에서 능동적으로 변화시킨 시스템의 아키텍처나 임무수행 전략이 유효한 것인지에 관한 검증을 수행한 후 시스템에 적용해야 한다. 기존의 대부분의 자가 적응 시스템에 대한 연구결과에서는 능동적으로 변화된 시스템이 임무수행에 적합한지에 대한 검증 방법을 제시해 주고 있지 않다. 본 연구에서는 UWS의 자가 적응 시스템이 임무수행 중 변화 되었을 때 미래의 발생할 사건에 대해 적절하게 적용 가능한지를 검증하기 위하여 시간적인 사건의 완전성을 검증하기에 적합한 Computation Tree Logic(CTL) 모델체킹(Model Checking)을 적용하여 자가 적응 시스템의 적응결과를 검증하는 방법을 제시하였다.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.212-214
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• 1999

최근 인터넷 기반의 분산 멀티미디어 환경에서 가장 활성화되고 있는 기술로 스트림 서비스와 분산 객체 기술을 들 수 있다. 특히, 분산 객체 기반의 스트림 서비스의 연구가 진행되면서, 다양한 프로토콜과 관리 모델들이 소개되고 있다. 이러한 연구를 바탕으로, 본 논문에서는 스트림 서비스의 품질을 보장하기 위해 분산 객체기술의 표준안인 CORBA를 이용한 QoS 관리 모델을 제안한다. 이를 위해, 사용자 제어 모듈과 QoS 관리 모듈을 설계하였으며, 이들은 협약(Negotiation)과 적응(Adaptation) 기법을 통하여 상호작용함으로써 스트림을 송수신하는 두 시스템간에 QoS를 보장한다. 제안된 QoS 관리 모델은 기존의 화상회의, VOD, 인터넷 방송 등의 서비스에 응용 가능하도록 설계하였다. 마지막으로 설계한 객체 모듈들을 사용하여 CORBA 기반의 스트림 서비스가 가능한 QoS 관리 모델의 프로토타입을 제안한다.

• Journal of Digital Convergence
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• v.10 no.11
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• pp.377-382
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• 2012

In this paper, the echo noise robust CHMM learning model using echo cancellation average estimator LMS algorithm is proposed. To be able to adapt to the changing echo noise. For improving the performance of a continuous speech recognition, CHMM models were constructed using echo noise cancellation average estimator LMS algorithm. As a results, SNR of speech obtained by removing Changing environment noise is improved as average 1.93dB, recognition rate improved as 2.1%.