• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.230-239
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• 2003

This paper presents face recognition algorithm using projection vector reflecting local feature for the area in contour lines. The outline shape of a face has many difficulties to distinguish people because human has similar face shape. For 3 dimensional(3D) face images include depth information, we can extract different face shapes from the nose tip using some depth values for a face image. In this thesis deals with 3D face image, because the extraction of contour lines from 2 dimensional face images is hard work. After finding nose tip, we extract two areas in the contour lilies from some depth values from 3D face image which is obtained by 3D laser scanner. And we propose a method of projection vector to localize the characteristics of image and reduce the number of index data in database. Euclidean distance is used to compare of similarity between two images. Proposed algorithm can be made recognition rate of 94.3% for face shapes using depth information.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1372-1381
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• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.2
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• pp.315-320
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• 2008

Nowadays, a lot of related data obtained from these research could be given a new present meaning to accomplish the original purpose of the whole research as a human genome project. In such a thread, construction of gene expression analysis system and a basis rank analysis system is being watched newly. Recently, being identified fact that particular sub-class of tumor be related with particular chromosome, microarray started to be used in diagnosis field by doing cancer classification and predication based on gene expression information. In this thesis, we used cDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer, created system that can extract informative gene list through normalization separately and proposed combination method for selecting more significant genes. And possibility of proposed system and method is verified through experiment. That result is that PC-ED combination represent 98.74% accurate and 0.04% MSE, which show that it improve classification performance than case to experiment after generating gene list using single similarity scale.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.698-711
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• 2019

The purpose of this study was to investigate the effect of social servicescape on customer satisfaction, customer trust, and customer loyalty. Data were collected from 311 adults who lived in Daegu where they had used Japanese restaurants. For data analysis, frequency analysis, factor analysis, regression analysis and multiple regression analysis were used. Through the factor analysis, the social servicescape of Japanese restaurant was identified as two components of human service and customer similarity. As a result of the multiple regression analysis, two components of social servicescape have positive effects on customer satisfaction and customer trust, and have a partial positive effect on customer loyalty. The results of regression analysis showed that customer satisfaction had a positive effect on customer trust and customer loyalty. In addition, customer trust has a positive effect on customer loyalty. The results of this study confirmed the influence of social servicescape on Japanese specialty restaurants and suggested practical and theoretical implications.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.143-159
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• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.

• Parasites, Hosts and Diseases
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• v.57 no.2
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• pp.197-200
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• 2019

Cryptosporidium is a common intestinal protozoan that can lead to diarrhea in humans and dogs. The predominant species of infection are C. hominis and C. parvum in humans, and C. canis in dogs. However, C. canis can infect immunocompromised humans. Considering the close contact with humans, dogs have the potential to be reservoirs for human cryptosporidiosis. Breeding kennels are the major supply source of puppies for pet shops. The present study is to determine the molecular prevalence and characteristics of Cryptosporidium spp. found in breeding kennel dogs. A total of 314 fecal samples were collected from young and adult dogs kept in 5 breeding kennels. A polymerase chain reaction targeting the small subunit rRNA gene was employed for the detection of Cryptosporidium spp. To determine the species, the DNA sequences were compared to GenBank data. Overall, 21.0% of the fecal samples were positive for Cryptosporidium spp. infection. Cryptosporidium spp. was detected in all 5 facilities. A sequencing analysis demonstrated that all isolates shared 99-100% similarity with C. canis. The results suggest that Cryptosporidium spp. infection is present at a high-level in breeding kennel dogs. However, because dominant species in this survey was C. canis, the importance of breeding kennel dogs as reservoirs for Cryptosporidium spp. transmission to humans is likely to be low in Japan.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.172-178
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• 2020

In order to recommend contents, the company generally uses collaborative filtering that takes into account both user preferences and video (item) similarities. Such services are primarily intended to facilitate user convenience by leveraging personal preferences such as user search keywords and viewing time. It will also be ranked around the keywords specified in the video. However, there is a limit to analyzing video similarities using limited keywords. In such cases, the problem becomes serious if the specified keyword does not properly reflect the item. In this paper, I would like to propose a system that identifies the characteristics of a video as it is by the system without human intervention, and analyzes and recommends similarities between videos. The proposed system analyzes similarities by taking into account all words (keywords) that have different meanings from training videos, and in such cases, the methods handled by big data clusters are applied because of the large scale of data and operations.

• The Research Journal of the Costume Culture
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• v.29 no.3
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• pp.361-373
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• 2021

The purpose of this study is to contribute to the role of lines in creative design development by analyzing the expression types and aesthetic characteristics of modern fashion using geometric formativeness of symmography. A literature study was conducted of works since 2009 to examine the general consideration of lines together with analysis of the concept and characteristics of symmography in the formative arts field, and to analyze the expression types and aesthetic characteristics of modern fashion design using the formativeness of symmography. The infinite sense of formativeness and original expression of symmography are used in formative arts such as space design, installation art, and industrial design. Expression types of modern fashion design using geometric formativeness of symmography can be classified into the following three types: two-dimensional graphic pattern, relief surface, and three-dimensional spatial. First, the two-dimensional graphic pattern type forms an optical pattern, providing individuality and visual interest to the textile design. Second, the relief surface type expresses the plane in various ways, so that the thickness changes according to how lines overlap. Third, the three-dimensional spatial type expands the boundaries of clothing and creates a fantastic spatial beauty. Next, the aesthetic formativeness of fashion design using symmography can be classified into repetitive rhythmicity, geometric self-similarity, and optical spatiality. Symmography enables a myriad of geometric patterns to be developed depending on material, color, and the designer's imagination, and helps inspire a variety of designs in fashion that sculpt a three-dimensional human body.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.15-21
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• 2022

In the content-based video retrieval applications, the information on the movement of an object can be used as important in classifying the content. In particular, analyzing and classifying human movement can be used for various purposes as well as retrieval. In this paper, a method to improve the performance of the shape variation descriptor and shape sequence to describe and classify movement using shape information that changes according to the movement of an object is proposed. By selecting a shape descriptor to more efficiently describe the shape information of an object and comparing the distance function used to measure the similarity, the description and retrieval efficiency of movement information can be increased. Through experiments, it was shown that the proposed method can describe movement information more efficiently and increase the retrieval efficiency compared to the previous method.

• Journal of Microbiology and Biotechnology
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• v.32 no.9
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• pp.1195-1208
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• 2022

Silver nanoparticles (AgNPs) have potential applications in medicine, photocatalysis, agriculture, and cosmetic fields due to their unique physicochemical properties and strong antimicrobial activity. Here, AgNPs were synthesized using actinobacterial SL19 strain, isolated from acidic forest soil in Poland, and confirmed by UV-vis and FTIR spectroscopy, TEM, and zeta potential analysis. The AgNPs were polydispersed, stable, spherical, and small, with an average size of 23 nm. The FTIR study revealed the presence of bonds characteristic of proteins that cover nanoparticles. These proteins were then studied by using liquid chromatography with tandem mass spectrometry (LC-MS/MS) and identified with the highest similarity to hypothetical protein and porin with molecular masses equal to 41 and 38 kDa, respectively. Our AgNPs exhibited remarkable antibacterial activity against Escherichia coli and Pseudomonas aeruginosa. The combined, synergistic action of these synthesized AgNPs with commercial antibiotics (ampicillin, kanamycin, streptomycin, and tetracycline) enabled dose reductions in both components and increased their antimicrobial efficacy, especially in the case of streptomycin and tetracycline. Furthermore, the in vitro activity of the AgNPs on human cancer cell lines (MCF-7, A375, A549, and HepG2) showed cancer-specific sensitivity, while the genotoxic activity was evaluated by Ames assay, which revealed a lack of mutagenicity on the part of nanoparticles in Salmonella Typhimurium TA98 strain. We also studied the impact of the AgNPs on the catalytic and photocatalytic degradation of methyl orange (MO). The decomposition of MO was observed by a decrease in intensity of absorbance within time. The results of our study proved the easy, fast, and efficient synthesis of AgNPs using acidophilic actinomycete SL19 strain and demonstrated the remarkable potential of these AgNPs as anticancer and antibacterial agents. However, the properties and activity of such particles can vary by biosynthesized batch.