• Fashion & Textile Research Journal
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• v.13 no.6
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• pp.827-837
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• 2011

The purpose of this study was to observe premium handbag users who are 20 to 30 year old of age, to determine purchase behavior and design preference of handbags by lifestyle and age variable to help market segmentation. A survey instrument was used. A sample was selected by quota sampling method from 20 to 30 aged Korean women, and reliable 538 data were analyzed by SPSS. Cluster type towards lifestyle and age were independent variable. There are two types of lifestyle clusters toward luxury handbags; Strongly favored and weakly favored group toward luxury handbags. Strongly favored group of luxury goods considered more brand, country of origin, and trend, while young people considered more new arrival of design in purchase of products. Preferred design type of hand bag was statistically associated with age variable. 20s consumers preferred shopper bag style and big size of handbags. Leather was preferred by the group of the strongly favored luxury goods. Through this research finding, we hope handbag brand market segmentation will be based on lifestyle and age variable to reflect customer's demand.

• Journal of Platform Technology
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• v.6 no.4
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• pp.26-33
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• 2018

In this paper, we propose an image retrieval algorithm for real-time processing and design it as hardware. The proposed method is based on the classification of BoWs(Bag of Words) algorithm and proposes an image search algorithm using bit stream. K-fold cross validation is used for the verification of the algorithm. Data is classified into seven classes, each class has seven images and a total of 49 images are tested. The test has two kinds of accuracy measurement and speed measurement. The accuracy of the image classification was 86.2% for the BoWs algorithm and 83.7% the proposed hardware-accelerated software implementation algorithm, and the BoWs algorithm was 2.5% higher. The image retrieval processing speed of BoWs is 7.89s and our algorithm is 1.55s. Our algorithm is 5.09 times faster than BoWs algorithm. The algorithm is largely divided into software and hardware parts. In the software structure, C-language is used. The Scale Invariant Feature Transform algorithm is used to extract feature points that are invariant to size and rotation from the image. Bit streams are generated from the extracted feature point. In the hardware architecture, the proposed image retrieval algorithm is written in Verilog HDL and designed and verified by FPGA and Design Compiler. The generated bit streams are stored, the clustering step is performed, and a searcher image databases or an input image databases are generated and matched. Using the proposed algorithm, we can improve convenience and satisfaction of the user in terms of speed if we search using database matching method which represents each object.

• The Journal of Society for e-Business Studies
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• v.19 no.3
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• pp.107-123
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• 2014

Current text mining techniques suffer from the problem that the conventional text representation models cannot express the semantic or conceptual information for the textual documents written with natural languages. The conventional text models represent the textual documents as bag of words, which include vector space model, Boolean model, statistical model, and tensor space model. These models express documents only with the term literals for indexing and the frequency-based weights for their corresponding terms; that is, they ignore semantical information, sequential order information, and structural information of terms. Most of the text mining techniques have been developed assuming that the given documents are represented as 'bag-of-words' based text models. However, currently, confronting the big data era, a new paradigm of text representation model is required which can analyse huge amounts of textual documents more precisely. Our text model regards the 'concept' as an independent space equated with the 'term' and 'document' spaces used in the vector space model, and it expresses the relatedness among the three spaces. To develop the concept space, we use Wikipedia data, each of which defines a single concept. Consequently, a document collection is represented as a 3-order tensor with semantic information, and then the proposed model is called text cuboid model in our paper. Through experiments using the popular 20NewsGroup document corpus, we prove the superiority of the proposed text model in terms of document clustering and concept clustering.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.1-9
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• 2019

In the recent marine sector, the development and standardization regarding S-100, which is the universal hydrographical data model standard for development of marine space information, was progressed, and for the effectiveness of marine chart production work and the multi-purpose use of water level data in S-100, S-102(Bathymetric Surface grid) standard development and various studies of BAG formats combined with water level and uncertainty, property information is being progressed. Since the water level information that is important in the operation of the ship is provided based on S-102, the calibration method of the location information when producing S-102 is an important factor in deciding the water level. In this study, the hydrographical surveying was conducted by piloting the standardized method for the production of S-102 in Korea, and have compared the accuracy of water level information according to the GNSS post treatment calibration method. As a result of comparing the water level in 2 places in the rocky terrain of the study area, the northern water level of Namu-do was shown as DL 0.79~0.83m, the eastern water level of Daeho-do was DL 12.63~12.91m, and the horizontal position errors of the intermittent sunshine water level were confirmed to be within 1m. As a result, the intermittent sunshine water level according to the location calibration method when producing the BAG was confirmed that it was in the available range for a ship's safe voyage. However, the accuracy verification for the location of the ship when conducting hydrographical surveying was judged that there is a need for a various additional study about regional characteristics and environment factor.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.41 no.4
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• pp.272-281
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• 2008

Seasonal and annual variation in the species composition of bag-net catch in the coastal waters of Incheon, Korea were examined from April 2000 to November 2004. To analyze seasonal variation of the fisheries data, we implemented a self-organizing map(SOM), an unsupervised artificial neural network, with the catch amount of 97 species. Over 5 years, we caught 68 species of fish, 23 species of crustaceans and six species of cephalopods. The total number of fish species were gradually increased during the study period. The number of species was higher during the spring than the autumn. The SOM identified four groups of the sampling months based on seasonal changes in communities. In the spring, the dominant species were Leptochela gracilis and Pholis fangi; whereas, in the autumn, Engraulis japonicus and Portunus trituberculatus were dominant species in bag-net catch. Our results will be used to estimate seasonal and annual variation in fisheries resources of Korean coastal waters.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.547-552
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• 2014

As social multimedia sites are getting popular such as Flickr and Facebook, the amount of image information has been increasing very fast. So there have been many studies for accurate social image retrieval. Some of them were web image classification using semantic relations of image tags and BoVW(Bag of Visual Words). In this paper, we propose a method to detect salient region in images using GBVS(Graph Based Visual Saliency) model which can eliminate less important region like a background. First, We construct BoVW based on SIFT algorithm from the database of the preliminary retrieved images with semantically related tags. Second, detect salient region in test images using GBVS model. The result of image classification showed higher accuracy than the previous research. Therefore we expect that our method can classify a variety of images more accurately.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.3
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• pp.281-290
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• 2011

In this study, a series of experiments were carried out to measure temporal stability of reduced sulfur compounds (RSCs) in Tedlar bag samples as a function of elapsed storage time. To this end, temporal variability of 4 RSC standard gases ($H_2S$, $CH_3SH$, DMS, DMDS) was measured up to 29 days. For the purpose of comparison, RSC samples were stored in both individual and mixed state. In the case of mixed standard, samples were also examined to allow comparison between light and dark condition. Then results of $CH_3SH$ data were the most stable with the least change in its concentrations through the end of exps (29 days). When compared with previous studies, the extent of stability appeared to be influenced by the initial concentration levels of samples. When the patterns were compared between individual and mixture samples, differences were not significant in the case of $H_2S$ and DMS. The effects of light conditions on temporal stability were seen to be fairly sensitive on most RSC other than $H_2S$. The results of our study confirm that the stability of RSC storage is affected by their involvement in photochemical reactions.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.8
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• pp.1179-1189
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• 2008

The purpose of this study is to investigate the satisfaction of the adolescents' school backpack bag and the important criteria when purchasing for developing comfort and functional backpack. The questionnaire was composed and surveyed with 245 middle school students and the data were analyzed through SPSS 13.0. Purchasing criteria were grouped into 5: practical, shop environment, comfort, aesthetic and maintenance. Satisfaction factors were function/comfort, fashion/aesthetic and durability/A.S. 50.2% of students recognized the inappropriate wearing backpack might cause the deformation of body shape. And the wrong habit of wearing bag was found to affect the body posture of students. Main symptoms caused by wearing it for long time are ‘sweating around shoulder and back' and ‘feeling stiff in shoulders and waist'. Needs arise to develop the bag which could prevent them and to educate students how to wear bags. According to the result from MDS of purchasing criteria, one axis is product vs. environment, and other is functional vs. psychological aspects. According to the result from MDS of bag satisfaction, one axis is function/durability vs. fashion/appearance, and other is gestalt quality vs. part quality. They wanted the improvement in the aspects of shape/design, material, maintenance, comfort and usability of the bags. Specially it is required that we research the adolescent customer-oriented way and develop the new materials or shapes pursuing both shoulder comfort and characteristics.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.79-82
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• 2015

Bag of visual words(BoVW) is one of the image classification and retrieval methods, using feature point that automatical sorting and searching system by image feature vector of data base. The existing method using feature point shall search or classify the image that user unwanted. To solve this weakness, when comprise the words, include not only feature point but color information that express overall mood of image or texture information that express repeated pattern. It makes various searching possible. At the test, you could see the result compared between classified image using the words that have only feature point and another image that added color and texture information. New method leads to accuracy of 80~90%.

• The Korean Journal of Emergency Medical Services
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• v.22 no.1
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• pp.49-59
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• 2018

Purpose: The purpose of this study was to develop an assistant device for the promotion of bag-valve-mask ventilation based on a non-equivalent control group pre-test and post-test design. Methods: The experimental tool was a mask assistance device developed by the researchers. Data were analyzed using SPSS 21.0 with the cardiopulmonary resuscitation (CPR) evaluation program from August 18 to 30, 2016. The research tools included general, hand-related, and ventilation-related characteristics. Results: Before and after using the mask assistance device, the tidal volume increased by 64 mL (p<.001) from 461.76 mL to 525.86 mL. The tidal volume for control was 477.86 mL, and there was a statistical difference (p<.05). The ventilation frequency in device users was 10 times per minute for a total of 20 ventilations with before 10.65 after 10 times, and that of the control group was before 10.36 times after 10 times; there was no difference in both groups(p>.05). The accuracy of the assistance device was $81.72{\pm}30.86%$, which was a very high value. However, the accuracy of ventilation in the control group with no assistance device was $18.97{\pm}32.44%$, which was a very low accuracy rate. Conclusion: This study's results suggested utilizing the newly-developed mask assistance device in CPR, and showed increases in tidal volume and accuracy of ventilation using the bag-valve-mask ventilation equipment. The general and hand-related characteristics did not have any effect, so the use of the device proved to increase the efficacy in all users.