• The International Journal of Costume Culture
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• v.12 no.1
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• pp.26-37
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• 2009

This study has begun as to identify various forms of personified Hindu deitiesand its goal is to understand the symbols of Hindu which are the backgrounds of the modern Hindu culture and present the hairstyle images of ancient Indians through the Hindu deities of the era. Scope of the research has been determined to six major deitiesamong those from Hindu culture that affect the Indian society and the images of Hindu deitiesappeared in the Indian miniatures and sculptures were studied as times changed. The deities could be identified by symbols maintained in common by each divinity as the Hindu deities were diversified through the long history. Examining the transitions in hairstyles and headstyles of Hindu deities, hair shapes of spiraling curls were expressed in the ancient Hindu sculptures from $2^{nd}$ century to $6^{th}$ century due to the influence of early Indian Buddhism. In Hindu paintings from $15^{th}$ century to $19^{th}$ century, beards and sideburns were expressed in male deities due to the influence from Mugul arts, while feminine characters were emphasized in goddesses with long loose hair. Works are each presented encapsulating the results of the researches on Vishnu and Lakshmi from these Hindu deities. It is attempted to find Hindu image and present directions for developments of modern beauty by supplying motives to modern hair design by researching the hairstyles of Hindu deities.

• The Transactions of the Korea Information Processing Society
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• v.2 no.5
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• pp.746-756
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• 1995

This paper describes the intractive visual programming environment using multi-view which shows the tools of visualization for called and the visualizations for called member-function flow in C＋＋ language. This research defines new visual symbols for class and constructs interactive visual programming environment of various views by using visual symbols. Our proposed interactive multi-view visual programming environment can represent visualization for representation of class and execution relationships between objects in the object-oriented language, which is easy to understand the structure of object-oriented program, therefore our proposed interactive visual programming environment enables easy program development, and can use of education and trainning for beginner in useful.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.10
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• pp.843-850
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• 2005

FBA(flux balance analysis) with Boolean rules for representing regulatory events has correctly predicted cellular behaviors, such as optimal flux distribution, maximal growth rate, metabolic by-product, and substrate concentration changes, with various environmental conditions. However, until now, since FBA has not taken into account a hierarchical regulatory network, it has limited the representation of the whole transcriptional regulation mechanism and interactions between specific regulatory proteins and genes. In this paper, in order to solve these problems, we describe the construction of hierarchical regulatory network with defined symbols and the introduction of a weight for representing interactions between symbols. Finally, the whole cellular behaviors with time were simulated through the linkage of a hierarchical regulatory network module and dynamic simulation module including FBA. The central metabolic network of E. coli was chosen as the basic model to identify our suggested modeling method.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.149-156
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• 2015

In this paper, we propose a Korean sentence symbol preprocessor for a SSML (speech synthesis markup language) supported speech synthesis system in order to improve the quality of the synthesized result. After the analysis of Korean Wikipedia documents, we propose 8 categories for the meaning of sentence symbols and 11 regular expression for the classification of each category. After the development of a Korean sentence symbol preprocess system we archived 56% of precision and 71.45% of recall ratio for 63,000 sentences.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2A
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• pp.43-50
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• 2005

In this paper, we present an improved channel estimation method for orthogonal frequency division multipexing systems using pilot symbol assisted modulation(PSAM). Conventional linear minimum mean square error(LMMSE) channel estimation method uses only pilot symbols for channel estimation. So, as the fading channel varies rapidly, the system performance is degraded. The basic idea of the proposed scheme is that we firstly estimate channel coefficients at the middle point between two pilot symbols and then compute the channel attenuation by using LMMSE method. Superior performance achieved with the proposed method is illustrated by simulation experiments with the Doppler frequency of 36Hz and 185Hz in comparison with conventional LMMSE channel estimator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.1C
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• pp.55-64
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• 2010

In this paper, we propose a new compensation scheme for combined channel distortions and RF impairments based on the analysis of the impacts of IQ(In-phase/Quadrature) imbalance and phase noise on the OFDM(Orthogonal Frequency Division Multiplexing) system in the direct conversion transceiver and frequency selective fading channel distortion. The proposed scheme estimates the combined distortion by the use of training symbols and the residual distortion by pilot symbols and compensates the combined distortion, including IQ imbalance, phase noise and multipath fading at the same time. The simulation results show that the proposed scheme compensates the combined distortion of IQ imbalance, phase noise and multipath fading simultaneously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.995-1000
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• 2016

The maximum cross-correntropy (MCC) algorithm with a set of random symbols keeps its optimum weights undisturbed from impulsive noise unlike MSE-based algorithms and its main factor has been known to be the input magnitude controller (IMC) that adjusts the input intensity according to error power. In this paper, a normalization of the step size of the MCC algorithm by the power of IMC output is proposed. The IMC output power is tracked recursively through a single-pole low-pass filter. In the simulation under impulsive noise with two different multipath channels, the steady state MSE and convergence speed of the proposed algorithm is found to be enhanced by about 1 dB and 500 samples, respectively, compared to the conventional MCC algorithm.

• Journal of Korea Multimedia Society
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• v.11 no.12
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• pp.1625-1634
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• 2008

In this study, a modified Fuzzy C-Means algorithm with Gaussian weights (MFCM_GW) is presented for the problem of nonlinear blind channel equalization. The proposed algorithm searches for the optimal channel output states of a nonlinear channel based on received symbols. In contrast to conventional Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in this method. In the search procedure, all possible sets of desired channel states are constructed by considering the combinations of estimated channel output states. The set of desired states characterized by the maxima] value of the Bayesian fitness is selected and updated by using the Gaussian weights. After this procedure, the Bayesian equalizer with the final desired states is implemented to reconstruct transmitted symbols. The performance of the proposed method is compared with those of a simplex genetic algorithm (GA), a hybrid genetic algorithm (GA merged with simulated annealing (SA):GASA), and a previously developed version of MFCM. In particular, a relative]y high accuracy and a fast search speed have been observed.

• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.838-843
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• 2021

This paper presents an algorithm for effective retrieval of score information to an input score image. The originality of the proposed algorithm is that it is designed to be robust to recognition errors by an OMR (Optical Music Recognition), while existing methods such as pitch histogram requires error induced OMR result be corrected before retrieval process. This approach helps people to retrieve score without training on music score for error correction. OMR takes a score image as input, recognizes musical symbols, and produces structural symbolic notation of the score as output, for example, in MusicXML format. Among the musical symbols on a score, it is observed that filled noteheads are rarely detected with errors with its simple black filled round shape for OMR processing. Barlines that separate measures also strong to OMR errors with its long uniform length vertical line characteristic. The proposed algorithm consists of a descriptor for a score and a similarity measure between a query score and a reference score. The descriptor is based on note-count, the number of filled noteheads in a measure. Each part of a score is represented by a sequence of note-count numbers. The descriptor is an n-gram sequence of the note-count sequence. Simulation results show that the proposed algorithm works successfully to a certain degree in score image-based retrieval for an erroneous OMR output.