• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1721-1737
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• 2020

Human apparent age estimation has become a popular research topic and attracted great attention in recent years due to its wide applications, such as personal security and law enforcement. To achieve the goal of age estimation, a large number of methods have been pro-posed, where the models derived through the cumulative attribute coding achieve promised performance by preserving the neighbor-similarity of ages. However, these methods afore-mentioned ignore the geometric structure of extracted facial features. Indeed, the geometric structure of data greatly affects the accuracy of prediction. To this end, we propose an age estimation algorithm through joint feature selection and manifold learning paradigms, so-called Feature-selected and Geometry-preserved Least Square Regression (FGLSR). Based on this, our proposed method, compared with the others, not only preserves the geometry structures within facial representations, but also selects the discriminative features. Moreover, a deep learning extension based FGLSR is proposed later, namely Feature selected and Geometry preserved Neural Network (FGNN). Finally, related experiments are conducted on Morph2 and FG-Net datasets for FGLSR and on Morph2 datasets for FGNN. Experimental results testify our method achieve the best performances.

• Journal of Korea Multimedia Society
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• v.15 no.1
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• pp.63-70
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• 2012

In this paper an extension to an original active shape model(ASM) for facial feature extraction is presented. The original ASM suffers from poor shape alignment by aligning the shape model to a new instant of the object in a given image using a simple similarity transformation. It exploits only informations such as scale, rotation and shift in horizontal and vertical directions, which does not cope effectively with the complex pose variation. To solve the problem, new shape alignment with 6 degrees of freedom is derived, which corresponds to an affine transformation. Another extension is to speed up the calculation of the Mahalanobis distance for 2-D profiles by trimming the profile covariance matrices. Extensive experiment is conducted with several images of varying poses to check the performance of the proposed method to segment the human faces.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.109-117
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• 2009

Identity recognition in real environment with a reliable mode is a key issue in human computer interaction (HCI). In this paper, we present a robust person identification system considering score-based optimal reliability measure of audio-visual modalities. We propose an extension of the modified reliability function by introducing optimizing parameters for both of audio and visual modalities. For degradation of visual signals, we have applied JPEG compression to test images. In addition, for creating mismatch in between enrollment and test session, acoustic Babble noises and artificial illumination have been added to test audio and visual signals, respectively. Local PCA has been used on both modalities to reduce the dimension of feature vector. We have applied a swarm intelligence algorithm, i.e., particle swarm optimization for optimizing the modified convection function's optimizing parameters. The overall person identification experiments are performed using VidTimit DB. Experimental results show that our proposed optimal reliability measures have effectively enhanced the identification accuracy of 7.73% and 8.18% at different illumination direction to visual signal and consequent Babble noises to audio signal, respectively, in comparison with the best classifier system in the fusion system and maintained the modality reliability statistics in terms of its performance; it thus verified the consistency of the proposed extension.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1493-1505
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• 1996

As Internet and its users grow dramatically multi-media data are getting common, many types of electronic mail applications are showing up. Internet s/w developers and users would like to electronic mail system for commercial purposes. They also would like to protect their electronic mail somehow. For these purpose, the security feature using cryptography is one of the essential functions. In this paper, we describe the library function development for handing MOSS(MIME Object Security Service), the security version of MINE(Multi -Purpose Internet Mail Extension). For these purpose, we explain the security features and structures of MOSS and defined the necessary function and we also discussed design issues for the MOSS implementation.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.261-274
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• 1997

Most of the data sets to which the conventional discriminant rules have been applied contain only those which belong to one and only one class among the classes of interest. However the extension of the bivalence to multivlaence like Fuzzy concepts strongly influence the traditional view that an object must belong to only class. Thus the goal of this paper is to develop new discriminant rules which can handle the data each object of which may belong to moer than two classes with certain degrees of belongings. A calibration model is used for the relationship between the feature vector of an object and the degree of belongings and a Bayesian inference is made with the Metropolis algorithm on the degree of belongings when a feature vector of an object whose membership is unknown is given. An evalution criterion is suggested for the rules developed in this paper and comparision study is carried using two training data sets.

• Journal of the Korean Society of Costume
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• v.56 no.7 s.106
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• pp.148-162
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• 2006

The purpose of this study is to examine the concept of convergence which is one of the trendy issues as a new digital paradigm of Integrative thinking in 21st century, to analyze the plastic feature and internal meaning of convergence expressed in fashion design, and to grasp the cultural symbolism through this aesthetic analysis. Because there have been considerable discussions on convergence, centering on industrial product area associated with media, I will proceed my study on the basis of them. For this, the documentary study and practical case study have been executed. This study will be helpful to find a direction of future fashion design trend. Convergence in digital stage can be defined as a phenomenon which different functions of product move towards one direction for greater efficiency, and not only as a technical integration between functions of product, but also an extension of area. Convergence can be classified by their use as (1) convergence for convenient daily life (2) convergence with intelligent scientific technology (3) convergence for entertainment on the basis of sensual experience. The plasticity of convergence designs feature as a open dynamic structure which potentiate transformation and their internal meaning can be inquired such qualities as integrative multiplicity, efficiency, mobility, intelligence. Specially convergence fashion design has protection qualify resulting from wearability on body. Ultimately convergence fashion design as a future digital paradigm can be thought as both eco-friendly design and human-centered design from positive technology-based viewpoint, because it is easy to transform according to our environment, convenient to reserve, and efficient to enhance spatial usibility.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1083-1096
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• 2008

This paper proposes an energy-aware path management scheme, so-called the TBP(Threshold based Back-Pressure) algorithm, which is designed for lifetime extension of the energy-constrained wireless sensor networks. With the goal of fair energy consumptions, we extensively utilize the available paths between the source and the sink nodes. The traffic distribution feature of the TBP algorithm operates in two scales; the local and the whole routing area. The threshold and the back-pressure signal are introduced for implementing those operations. It is noticeable that the TBP algorithm maintains the scalability by defining both the threshold and the back-pressure signal to have their meanings locally confined to one hop only. Throughout several experiments, we observe that the TBP algorithm enhances the network-wide energy distribution. which implies the extension of the network lifetime. Additionally, both the delay and the throughput outcomes show remarkable improvements. This shows that the energy-aware path control scheme holds the effects of the congestion control.

• Mycobiology
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• v.47 no.2
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• pp.200-206
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• 2019

Allelic differences in A and B mating-type loci are a prerequisite for the progression of mating in the genus Pleurotus eryngii; thus, the crossing is hampered by this biological barrier in inbreeding. Molecular markers linked to mating types of P. eryngii KNR2312 were investigated with randomly amplified polymorphic DNA to enhance crossing efficiency. An A4-linked sequence was identified and used to find the adjacent genomic region with the entire motif of the A locus from a contig sequenced by PacBio. The sequence-characterized amplified region marker $7-2_{299}$ distinguished A4 mating-type monokaryons from KNR2312 and other strains. A BLAST search of flanked sequences revealed that the A4 locus had a general feature consisting of the putative HD1 and HD2 genes. Both putative HD transcription factors contain a homeodomain sequence and a nuclear localization sequence; however, valid dimerization motifs were found only in the HD1 protein. The ACAAT motif, which was reported to have relevance to sex determination, was found in the intergenic region. The SCAR marker could be applicable in the classification of mating types in the P. eryngii breeding program, and the A4 locus could be the basis for a multi-allele detection marker.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.129-136
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• 2011

This paper presents the coding method that have multi-mode and efficiency of audio codecs using the feature of audio signal. Recently, the developed extension super-wideband codec based on G.718 wideband divides two mode between Generic and Sinusiodal. So codec efficently encode audio signal exist in super-wideband. But the codec is not as efficent coding for harmonic component of wind instrument and string instrument and individual-Line component of percussion instrument. The proposed method are modeling and encoding multiple pitch and individual-line feature using multi mode coding. For the performance evaluation, we used SNR in MDCT domain for objective test and MUSHRA test for subjective test. As a result, the performance of SNR and MUSHRA test of the proposed method have better performance than the G.718 super-wideband codec.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.375-380
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• 2014

Under controlled environment, such as fixed viewpoints or consistent illumination, the performance of face recognition is usually high enough to be acceptable nowadays. Face recognition is, however, a still challenging task in real world. SIFT(Scale Invariant Feature Transformation) algorithm is scale and rotation invariant, which is powerful only in the case of small viewpoint changes. However, it often fails when viewpoint of faces changes in wide range. In this paper, we use Affine SIFT (Scale Invariant Feature Transformation; ASIFT) to detect affine invariant local descriptors for face recognition under wide viewpoint changes. The ASIFT is an extension of SIFT algorithm to solve this weakness. In our scheme, ASIFT is applied only to gallery face, while SIFT algorithm is applied to probe face. ASIFT generates a series of different viewpoints using affine transformation. Therefore, the ASIFT allows viewpoint differences between gallery face and probe face. Experiment results showed our framework achieved higher recognition accuracy than the original SIFT algorithm on FERET database.