• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.84-93
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• 1999

Determination of grain size of heat-treated stainless steel based fm digital ultrasonic signal processing technique is presented. This techniques consist in evidence accumulation with multiple feature parameters, difference absolute mean value(DAMV), variance(VAR), mean frequency (MEANF), auto regressive model coefficient(ARC) and linear cepstrum coefficient(LCC). Feature parameters were extracted from ultrasonic echo signal of heat-treated metals. It was found that a few parameters might not be sufficient to exactly evaluate the grain size of heat-treated metals. The determination of grain size of heat-treated metals was carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is designed to transform the distances for the application of the evidence accumulation method. In the work presented, heat-treated stainless steel samples with various grain sizes are examined. The processed experimental results supports the feasibility of the grain size determination technique presented.

• The Journal of the Acoustical Society of Korea
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• v.23 no.5
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• pp.400-409
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• 2004

In this paper. a voice personality transformation method is proposed. which makes one person's voice sound like another person's voice. To transform the voice personality. vocal tract transfer function is used as a transformation parameter. Comparing with previous methods. the proposed method makes transformed speech closer to target speaker's voice in both subjective and objective points of view. Conversion between vocal tract transfer functions is implemented by classification of entire vector space followed by linear transformation for each cluster. LPC cepstrum is used as a feature parameter. A joint classification and transformation method is proposed, where optimum clusters and transformation matrices are simultaneously estimated in the sense of a minimum mean square error criterion. To evaluate the performance of the proposed method. transformation rules are generated from 150 sentences uttered by three male and on female speakers. These rules are then applied to another 150 sentences uttered by the same speakers. and objective evaluation and subjective listening tests are performed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.1-6
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• 2016

Image rotation is one of main pre-processing step in image processing or image pattern recognition. It is implemented with rotation matrix multiplication. However it requires lots of floating point arithmetic operations and trigonometric function calculations, so it takes long execution time. We propose a new high speed image rotation algorithm without two major time-consuming operations. It use just 2 shear translation operations, so it is very fast. In addition, we apply a parallel computing technique with CUDA. CUDA is a massively parallel computing architecture using prevailed GPU recently. As GPU is a dedicated graphic processor, it is exellent for parallel processing of pixels. We compare the proposed algorithm with the conventional rotation one with various size images. Experimental results show that the proposed algorithm is superior to the conventional rotation ones.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.1
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• pp.49-58
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• 1999

This paper describes an integrated low pass filter fabricated by using $0.8{\mu}m$ single poly CMOS ASIC technology. The filter has been designed for a 5th-order elliptic switched capacitor filter with cutoff frequency of 5khz, 0.1dB passband ripple. The filter consists of MOS swiches poly capacitors and five CMOS op-amps. For the realization of the SC filter, continuous time transfer function H(s) is obtained from LC passive type, and transfered as discrete time transfer H(z) through bilinear-z transform. Another filter has been designed by capacitor scaling for reduced chip area, considering dynamic range of the op-amp. The test results of two fabricated filters are cutoff frequency of 4.96~4.98khz, 35~38dB gain attenuation and 0.72~0.81dB passband ripple with the ${\pm}2.5V$power supply clock of 50KHz.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.3
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• pp.10-19
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• 2009

In this paper, an efficient optical watermark method using multiple phase wrapping and real-valued decoding key is proposed. In the embedding process, two zero-padded original images placed in two quadrants on input plane are multiplied with two statistically independent random phase patterns and are Fourier transformed, respectively. Two encoded images are obtained by taking the real-valued data from these Fourier transformed images. And then two phase-encoded patterns, used as a hidden image and a decoding key, are generated by the use of multiple phase wrapping from each of the encoded images. A transmitted image is made from the linear superposition of the weighted hidden images and a cover image. In reconstruction process, the mirror reconstructed images can be obtained at all quadrants by the inverse-Fourier transform of the product of the transmitted image and the decoding key. Computer simulation and optical experiment are demonstrated in order to confirm the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.5-12
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• 2004

The data transformation between XML and Relation Database is made through the Principle of mapping bewtween them. There are two ways to access SQL Server, one is to assign SQL query to URL and the other is to use template file. MS-SQL server takes advantage of OpenXML function to transform the results of executing SQL query into XML documents. That is, OpenXML first makes node tree and then transforms row set data of XML documents into XML data of relation type. In order to insert XML data into database data. data is extracted from parsing XML documents using sp_xml_preparedocument procedure, and then the document structure is mapped into tree structure and stored in a table of database. Consequently, Data transformation between XML and Relation Database is made through mapping bewtween them. This article proposes the principle of mapping between XML and Relation Database and then shows the implementation of transformation between them so that it introduces the possibilty of bringing the extension and efficiency of data and various effects.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.7
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• pp.7-15
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• 2020

Recently, the fourth industrial revolution has been presented as a new paradigm and additive manufacturing (AM) has become one of the most important topics. For this reason, process monitoring for each cross-sectional layer of additive metal manufacturing is important. Particularly, deep learning can train a machine to analyze, optimize, and repair defects. In this paper, image classification is proposed by learning images of defects in the metal cross sections using the convolution neural network (CNN) image labeling algorithm. Defects were classified into three categories: crack, porosity, and hole. To overcome a lack-of-data problem, the amount of learning data was augmented using a data augmentation algorithm. This augmentation algorithm can transform an image to 180 images, increasing the learning accuracy. The number of training and validation images was 25,920 (80 %) and 6,480 (20 %), respectively. An optimized case with a combination of fully connected layers, an optimizer, and a loss function, showed that the model accuracy was 99.7 % and had a success rate of 97.8 % for 180 test images. In conclusion, image labeling was successfully performed and it is expected to be applied to automated AM process inspection and repair systems in the future.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2
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• pp.40-48
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• 1996

In this paper, a 40 dimensional segment vector with 4 frame and 7 frame width in every monosyllable interval was compressed into a 10, 14, 20 dimensional vector using K-L expansion and neural networks, and these was used to speech recognition feature parameter for CHMM. And we also compared them with CHMM added as feature parameter to the discrete duration time, the regression coefficients and the mixture distribution. In recognition test at 100 monosyllable, recognition rates of CHMM +${\bigtriangleup}$MCEP, CHMM +MIX and CHMM +DD respectively improve 1.4%, 2.36% and 2.78% over 85.19% of CHMM. And those using vector compressed by K-L expansion are less than MCEP + ${\bigtriangleup}$MCEP but those using K-L + MCEP, K-L + ${\bigtriangleup}$MCEP are almost same. Neural networks reflect more the speech dynamic variety than K-L expansion because they use the sigmoid function for the non-linear transform. Recognition rates using vector compressed by neural networks are higher than those using of K-L expansion and other methods.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1310-1323
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• 2008

Recently, many studies on automated generation of composite Web services have been done. Most of these works compose Web services by chaining their inputs and outputs, but do not consider the functional semantics. Therefore, they may construct unsatisfied composite services against users' intention. Futhermore, they have high time-complexity since every possible combinations of available services should be considered. To resolve these problems, this paper proposes a sophisticated composition method that explicitly specifies and uses the functional semantics of Web services. Specifically, A graph model is constructed to represent the functional semantics of Web services as well as the dependency among inputs and outputs. On the graph, we search core services which provide the requested function ality and additional services which transform between I/O types of the user request and the core services. Then, composite services are built from combinations of the discovered services. The proposed method improves the semantic correctness of composite services by the functional semantics of Web services, and reduces the time complexity by combinations of functionally related services.

• Polymer(Korea)
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• v.29 no.4
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• pp.369-374
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• 2005

In this work, the calcium alginate microcapsules containing lemon oil were prepared by emulsification-internal gelation and their potential use as aromatherapy was examined by the controlled release system. The lemon oil encapsulated in the alginate was successfully observed by Fourier transform (FT-IR) spectroscopy and differential scanning calorimeter (DSC) measurements. Analysis of the diameters and shapes of microcapsules was conducted by scanning electron microscopy (SEM). The mean diameters ranging from 4 to 7 um and encapsulation yield ranging from 50 to $85\%$ were obtained. The controlled release of the lemon oil at $37^{circ}$ was demonstrated by the infrared moisture determination (IMDB). It was found that the amount of released lemon oil decreased with increasing concentrations of alginate and $CaCl_2$ due to the higher the cross-linking density of the capsules prepared. The oil release from the capsule was measured as a function of physical force. We confirmed that the external factor could control the collapse of capsule wall and the release rate.