• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.9_10 s.146
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• pp.1274-1284
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• 2005

Effect of fixation methods and relaxation treatment on the dimensional stability and physical properties of MDPPA/HMM treated cotton knitted fabrics were studied. Combination of four different fixation methods - relaxation, swelling agent treatment, pad dry cure fixation, and wet fixation - were applied to flame retardant finish of 4 kinds of cotton knitted fabric with MDPPA/HMM. Then these fabrics were washed 10 times. As a result, In swelling treatment on 10G showed relatively higher value of length shrinkage than 14G. Length and width shrinkage were increased by initial washing treatment and no further change was shown after 6 washing cycles. After 10 washing cycles, length and width shrinkage decreased. The KES standardized basic value of B/W, 2HB/W and bursting strength of interlock were relatively larger than those of single jersey. The values of B/W and 2HB/W of cotton knitted fabrics were increased by relaxation and washing treatment but were decreased by swelling treatment. In addition, the bursting strength of the cotton knitted fabrics was decreased after fusing, washing and relaxation treatment.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.19 no.5
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• pp.215-222
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• 2009

Many concepts of external magnetic field applications in crystal growth processes have been developed to control melt convection, impurity content and growing interface shape. Especially, travelling magnetic fields (TMF) are of certain advantages. However, strong shielding effects appear when the TMF coils are placed outside the growth vessel. To achieve a solution of industrial relevance within the framework of the $KRISTMAG^{(R)}$ project inner heater-magnet modules(HMM) for simultaneous generation of temperature and magnetic field have been developed. At the same time, as the temperature is controlled as usual, e.g. by DC, the characteristics of the magnetic field can be adjusted via frequency, phase shift of the alternating current (AC) and by changing the amplitude via the AC/DC ratio. Global modelling and dummy measurements were used to optimize and validate the HMM configuration and process parameters. GaAs and Ge single crystals with improved parameters were grown in HMM-equipped industrial liquid encapsulated Czochralski (LEC) puller and commercial vertical gradient freeze (VGF) furnace, respectively. The vapour pressure controlled Czochralski (VCz) variant without boric oxide encapsulation was used to study the movement of floating particles by the TMF-driven vortices.

• The Journal of the Acoustical Society of Korea
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• v.10 no.1
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• pp.52-60
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• 1991

This paper describes the study on isolated word recognition by using DHMM(Dynamic Hidden Markov Model) which has dynamic feature of spectrum as a parameter. This paper discusses speech recognition experiment basedon HMM which can evaluate not only instantaneous spectral features but also dynamic spectral features. LPC cepstrum parameters is used as a static feature and LPC cepstrum's regression coefficient is used as a dynamic feature. These two features are quantized by each VQ codebook. DHMM is modeled by receiving static vector and dynamic vector by input. In the whole experiment, as recognition experiment using DHMM shows 92.7% of recognition rate while the experiment using conventional HMM shows 88.8% of recognition rate, DHMM proved to be a useful model.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.415-420
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• 2009

For the emergency detecting in general CCTV environment of our daily life, the monitoring by only images through CCTV information occurs some problems especially in cost as well as man power. Therefore, in this paper, for detecting emergency state dynamically through CCTV as well as resolving some problems, we propose our advanced speech recognition system. For the purpose of it, we adopt HMM(Hidden Markov Model) in our system to do a feature extraction. Also, we adopt Wiener filter technique for noise elimination in many information coming from on CCTV environment. In this paper, our system send only the emergency speech information to a manager to deal with emergency state effectively.

• The Journal of the Korea Contents Association
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• v.11 no.5
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• pp.138-147
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• 2011

While most Korean speech databases are developed for adults' speech, not for children's speech, there are various children's speech databases based on other languages. Because there are wide differences between children's and adults' speech in acoustic and linguistic characteristics, the children's speech database needs to be developed. In this paper, to find the differences between them in Korean, we built speech recognizers using HMM and tested them according to gender, age, and the presence of VTLN(Vocal Tract Length Normalization). This paper shows the speech recognizer made by children's speech has a much higher recognition rate than that made by adults' speech and using VTLN helps to improve the recognition rate in Korean.

• Smart Media Journal
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• v.1 no.4
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• pp.18-26
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• 2012

The increase of the number of smartphone applications has enforced the importance of new user interface emergence and has raised the interest of research in the convergence of multiple sensors. In this paper, we propose a method for the convergence of acceleration, magnetic and gyro sensors to recognize the gesture from motion of user smartphone. The proposed method first obtain the 3D orientation of smartphone and recognize the gesture of hand motion by using HMM(Hidden Markov Model). The proposed method for the representation for 3D orientation of smartphone in spherical coordinate was used for quantization of smartphone orientation to be more sensitive in rotation axis. The experimental result shows that the success rate of our method is 93%.

• Speech Sciences
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• v.12 no.4
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• pp.7-16
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• 2005

We investigate the effect of membership concentration on the performance of the speaker-independent recognition system by FVQ/HMM. For the membership function, we adopt the result obtained from the objective function approach by Bezdek. Membership concentration is done by varying the exponent in the membership function. The number of selected clusters is constrained to two for the sake of cheap computational cost. Experimental results showed that the recognition rate has its maximum value when the membership function was taken to be inversely proportional to the distance of the input vector from the cluster centroid. When the membership concentration was two weak or too strong, the performance was found to be relatively poor as expected. Except these extreme cases, the membership concentration was not shown to affect the recognition rate significantly. This is in accordance with the general observation that the fuzzy system is not much sensitive. to the detailed shape of the membership function as long as it is overlapped over multiple classes.

• ETRI Journal
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• v.33 no.4
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• pp.569-579
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• 2011

This paper presents a novel approach for human activity recognition (HAR) using the joint angles from a 3D model of a human body. Unlike conventional approaches in which the joint angles are computed from inverse kinematic analysis of the optical marker positions captured with multiple cameras, our approach utilizes the body joint angles estimated directly from time-series activity images acquired with a single stereo camera by co-registering a 3D body model to the stereo information. The estimated joint-angle features are then mapped into codewords to generate discrete symbols for a hidden Markov model (HMM) of each activity. With these symbols, each activity is trained through the HMM, and later, all the trained HMMs are used for activity recognition. The performance of our joint-angle-based HAR has been compared to that of a conventional binary and depth silhouette-based HAR, producing significantly better results in the recognition rate, especially for the activities that are not discernible with the conventional approaches.

• The Journal of the Acoustical Society of Korea
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• v.16 no.2
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• pp.49-57
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• 1997

In this paper, we propose the stochastic pronunciation lexicon model for large vocabulary continuous speech recognition system. We can regard stochastic lexicon as HMM. This HMM is a stochastic finite state automata consisting of a Markov chain of subword states and each subword state in the baseform has a probability distribution of subword units. In this method, an acoustic representation of a word can be derived automatically from sample sentence utterances and subword unit models. Additionally, the stochastic lexicon is further optimized to the subword model and recognizer. From the experimental result on 3000 word continuous speech recognition, the proposed method reduces word error rate by 23.6% and sentence error rate by 10% compare to methods based on standard phonetic representations of words.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.501-515
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• 2022

Despite the stylized statistical features of returns of financial returns such as fat-tailed distribution and leverage effect, no stochastic volatility models that can explicitly capture these features have been presented in the existing frequentist approach. we propose an approximate parameterization of stochastic volatility models that can explicitly capture the fat-tailed distribution and leverage effect of financial returns and a maximum likelihood estimation of the model using Langrock et al. (2012)'s hidden Markov model approximation in a frequentist approach. Through extensive simulation experiments and an empirical analysis, we present the statistical evidences validating the efficacy and accuracy of proposed parameterization.