• International Journal of Oral Biology
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• v.34 no.1
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• pp.21-28
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• 2009

Mutations in DLX3 are associated with both autosomal dominant hypoplastic hypomaturation amelogenesis imperfecta (ADHHAI) and tricho-dento-osseous (TDO) syndrome. ADHHAI is caused by a c.561_562delCT (2bp-del DLX3) mutation whereas TDO syndrome is associated with a c.571_574delGGGG (4bp-del DLX3) mutation. However, although the causal relationships between DLX3 and an enamel phenotype have been established, the pathophysiological role of DLX3 mutations in enamel development has not yet been clarified. In our current study, we prepared expression vectors for wild type and deletion mutant DLX3 products (4bp-del DLX3, 2bp-del DLX3) and examined the effects of their overexpression on the expression of the enamel matrix proteins and proteases. Wild type DLX3 enhanced the expression of matrix metalloprotease 20 (MMP20) mRNA and protein in murine ameloblast-like cells. However, neither a 4bp-del nor 2bp-del DLX3 increased MMP20 expression. Wild type DLX3, but not the above DLX3 mutants, also increased the activity of reporters containing 1.5 kb or 0.5 kb of the MMP20 promoter. An examination of protein stability showed that the half-life of wild type DLX3 protein was less than 12 h whilst that of both deletion mutants was longer than 24 h. Endogenous Dlx3 was also found to be continuously expressed during ameloblast differentiation. Since inactivating mutations in the gene encoding MMP20 are associated with amelogenesis imperfecta, the inability of 4bp-del or 2bp-del DLX3 to induce MMP20 expression suggests a possible involvement of such mutations in the enamel phenotype associated with TDO syndrome or ADHHAI.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.851-858
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• 2016

This paper presents a new statistical voice activity detection (VAD) based on the probabilistic interpretation of nonnegative matrix factorization (NMF). The objective function of the NMF using Kullback-Leibler divergence coincides with the negative log likelihood function of the data if the distribution of the data given the basis and encoding matrices is modeled as Poisson distributions. Based on this probabilistic NMF, the VAD is constructed using the likelihood ratio test assuming that speech and noise follow Poisson distributions. Experimental results show that the proposed approach outperformed the conventional Gaussian model-based and NMF-based methods at 0-15 dB signal-to-noise ratio simulation conditions.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.303-309
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• 2016

This paper proposes a novel approach to the problem of audio signal clustering using a stacked autoencoder. The proposed stacked autoencoder learns an efficient representation for the input signal, enables clustering constituent signals with similar characteristics, and therefore the original sources can be separated based on the clustering results. STFT (Short-Time Fourier Transform) is performed to extract time-frequency spectrum, and rectangular windows at all the possible locations are used as input values to the autoencoder. The outputs at the middle, encoding layer, are used to cluster the rectangular windows and the original sources are separated by the Wiener filters derived from the clustering results. Source separation experiments were carried out in comparison to the conventional NMF (Non-negative Matrix Factorization), and the estimated sources by the proposed method well represent the characteristics of the orignal sources as shown in the time-frequency representation.

• Journal of Mechanical Science and Technology
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• v.19 no.5
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• pp.1072-1079
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• 2005

Conceptual design is the first step in the overall process of product design. Its intrinsic uncertainty, imprecision, and lack of information lead to the fact that current conceptual design activities in engineering have not been computerized and very few CAD systems are available to support conceptual design. In most of the current intelligent design systems, approach of principle synthesis, such as morphology matrix, bond graphic, or design catalogues, is usually adopted to deal with the concept generation, in which optional concepts are generally combined and enumerated through function analysis. However, as a large number of concepts are generated, it is difficult to evaluate and optimize these design candidates using regular algorithm. It is necessary to develop a new approach or a tool to solve the concept generation. Generally speaking, concept generation is a problem of concept synthesis. In substance, this process of developing design candidate is a combinatorial optimization process, viz., the process of concept generation can be regarded as a solution for a state-place composed of multi-concepts. In this paper, genetic algorithm is utilized as a feasible tool to solve the problem of combinatorial optimization in concept generation, in which the encoding method of morphology matrix based on function analysis is applied, and a sequence of optimal concepts are generated through the search and iterative process which is controlled by genetic operators, including selection, crossover, mutation, and reproduction in GA. Several crucial problems on GA are discussed in this paper, such as the calculation of fitness value and the criteria for heredity termination, which have a heavy effect on selection of better concepts. The feasibility and intellectualization of the proposed approach are demonstrated with an engineering case. In this work concept generation is implemented using GA, which can facilitate not only generating several better concepts, but also selecting the best concept. Thus optimal concepts can be conveniently developed and design efficiency can be greatly improved.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.758-765
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• 2021

Recently, various research on the application of deep learning to video encoding for enhancing coding efficiency are being actively studied. This paper proposes a deep learning based intra prediction which uses multiple models by extending Matrix-based Intra Prediction(MIP) that is a neural network-based technology adopted in VVC. It also presents an efficient learning method for the multi-model intra prediction. To evaluate the performance of the proposed method, we integrated the VVC MIP and the proposed fully connected layer based multi-model intra prediction into HEVC reference software, HM16.19 as an additional intra prediction mode. As a result of the experiments, the proposed method can obtain bit-saving coding gain up to 0.47% and 0.19% BD-rate, respectively, compared to HM16.19 and VVC MIP.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.362-368
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• 2024

In this paper, we investigated the performance of directional and omnidirectional precoding schemes when transmitting to improve downlink performance in massive MIMO. Omnidirectional precoding was used to broadcast a common signal, such as a synchronization or control signal, to all users. The main purpose of omnidirectional precoding is to design the precoding matrix so that the signal transmitted in the downlink is the same in all directions and emitted with maximum energy. We propose a flexible omnidirectional precoding method for full-dimensional massive MIMO that can set the spatial coverage range to less than 120 degrees. The constraints of omnidirectionality of all antennas, equal transmit power, and maximum transmit rate are used to design the encoding matrix of the proposed method. The performance was evaluated in terms of spatial coverage by considering changing the spatial coverage of the antenna array by changing the distance between neighboring antennas in the antenna array.

• KSBB Journal
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• v.26 no.3
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• pp.237-242
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• 2011

As a number of archaea are ubiquitously found in non-extreme habitats, elucidation of their functional roles becomes currently an emerging issue. However, most of them are unable to grow in pure culture and so it remains to be established. In order to find genes lacking in the genome of an ammonia-oxidizing archaeon (AOA), we here report on the comparative analyses of an AOA genome with those of experimentally or theoretically established minimal genomes for independent growth. We assessed the genes lacking in AOA using logic of clusters of orthologous groups (COG), remote homology, consensus sequence weight matrix, function-based motif or domain, and then further excluded genes encoding hypothetical orarchaea-specific proteins. The results of these combination analyses revealed 19 candidate genes lacking in the genome of an AOA. Thus, our results provide a possibility of inducing independent growth of AOA when supplemented with product (s) of the lacking gene (s), and also give a chance for finding new proteins with novel sequence or structure space even if the predicted lacking-genes will be found using another algorithms or biochemical studies.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.43-51
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• 2008

Evolutionary Algorithms (EAs) cover all the applications involving the use of Evolutionary Computation in electronic system design. It is largely applied to complex optimization problems. EAs introduce a new idea for automatic design of electronic systems; instead of imagine model, ions, and conventional techniques, it uses search algorithm to design a circuit. In this paper, a method for automatic optimization of the digital circuit design method has been introduced. This method is based on randomized search techniques mimicking natural genetic evolution. The proposed method is an iterative procedure that consists of a constant-size population of individuals, each one encoding a possible solution in a given problem space. The structure of the circuit is encoded into a one-dimensional genotype as represented by a finite string of bits. A number of bit strings is used to represent the wires connection between the level and 7 types of possible logic gates; XOR, XNOR, NAND, NOR, AND, OR, NOT 1, and NOT 2. The structure of gates are arranged in an $m{\times}n$ matrix form in which m is the number of input variables.

• Convergence Security Journal
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• v.11 no.6
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• pp.37-44
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• 2011

VANET(Vehicular Ad-hoc Network) is a kind of ad hoc networks consist of intelligence vehicular ad nodes, and has become a hot emerging research project in many field. It provide traffic safety, cooperative driving and etc. but has also some security problems that can be occurred in general ad hoc networks. Also, in VANET, vehicles shoul d be able to authenticate each other to securely communicate with network-based infrastructure, and their locations and identifiers should not be exposed from the communication messages. This paper proposes V2I(Vehicular to Infra structure) authentication protocol that anonymity and untraceability of vehicular using Error Correcting Code that ge nerate encoding certification using generation matrix. The proposed scheme based on ECC resolves overhead problems of vehicular secure key management of KDC.

• BMB Reports
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• v.41 no.4
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• pp.322-327
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• 2008

In this study, we compared the gene expression profiles of non-syndromic hyperplastic dental follicle (HDF) fibroblasts and normal dental follicle (NDF) fibroblasts using cDNA micro-arrays, quantitative PCR, and immunohistochemical staining. Microarray analysis showed that several collagens genes were upregulated in the HDF's, including collagen types I, IV, VIII, and XI and TIMP-1, -3, and -4 (fold ratio > 2.0). In contrast, the expression of MMP-1, -3, -10, and -16 together with IL-8 was more than two fold downregulated. The differential expression of the genes encoding alkaline phosphatase, MMP-1, -3, -8, and IL-8 was confirmed by quantitative RT-PCR, while that of 24 HDFs and 18 NDFs was confirmed by immunohistochemical analysis. However, HDFs showed stronger expression of MMP-3 than NDFs (P < 0.001). Collectively, these results indicate that defective regulation of MMPs mediating connective tissue remodeling may be responsible for abnormal tooth eruption.