• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.19-21
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• 2004

In many cases, human's visual recognition depends on contextual information. We need to use effective feature information for performing vigorous place recognition to illumination, noise, etc. In the existing cases that use edge and color, etc., visual recognition doesn't cope effectively with real environment. To solve this problem, using natural marker, we improve the efficiency of place recognition.

• Journal of Environmental Health Sciences
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• v.41 no.6
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• pp.380-388
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• 2015

Objectives: Poisonous substances experts engage in policymaking regarding poisonous substances, whereas poisonous substances managers perform legal duties related to poisonous substances management systems at worksites. To understand and improve poisonous substances designation systems, it is necessary to distinguish the roles of these experts and managers. We further aimed to identify problems with poisonous substances appointment systems and provide basic data for their improvement by investigating the knowledge and recognition of the need for system improvement among managers and experts. Methods: To determine the $subjects^{\circ}{\emptyset}$ awareness of poisonous substances designation systems, a selfadministered questionnaire comprised of items on general characteristics and knowledge and recognition of the need for system improvement was issued. Data were analyzed via t-tests and ANOVA using SPSS v 16.0 Results: Regarding system comprehension, managers (n=213; mean 3.28, SD 0.63) significantly differed from experts (n=35; mean 4.08, SD 0.59) (P<0.001). No differences were found in recognition of need for improvement between managers (mean 3.11, SD 0.34) and experts (mean 3.24, SD 0.31). Significant differences in comprehension were found among managers by education level (P<0.05) and company size (P<0.05). Regarding industry type, comprehension was greater in the electrical/electronic and chemical/environmental industries compared to in other industries (P = 0.066). Comprehension was higher among those with five years or more of experience compared to those with less than five years. Regarding recognition of need for improvement, managers showed significant differences by company size (P<0.05). $Experts^{\circ}{\emptyset}$ comprehension showed no differences by general characteristics, while need for improvement differed according to work experience (P<0.001). Conclusion: The study found that the bigger the company size, the higher the level of comprehension by managers and the experts. In the case of both groups, where a higher comprehension of the poisonous substances designation system was evident, they recognized the necessity of its improvement.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.3
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• pp.205-225
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• 2023

The Study is to investigate information resources recognition of collection development policy that is a key element of Gwangju representative library. 68 Librarians, 98 library users and 20 libraries responded the questions of information resources. The fields of the questions are media, subjects and levels of information resources. The results of the research are as follows. First, the correlation coefficients between librarian group's preference and need is lower than that of the user group. Second, information resources for the knowledge-disadvantaged has low preference and need but the actual usage rate was high. Third, Librarians need to transfer historical paper and books, historical objects, technical reports and journal articles to the representative library. Fourth, information resources about philosophy have middle preference, low need and the resources have low need for transfer to representative library. Fifth, local historical resources and administrative policy resources has low usage rate high need for transfer to representative library. Sixth, the level of public library in Gwangju is 1.837 and the expectative level of Gwangju representative library is 3.325.

• Journal of the East Asian Society of Dietary Life
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• v.11 no.4
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• pp.247-258
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• 2001

This study focused on the recognition and information need for GMO(Genetically Modified Organism). The data were collected from 350 adults living in Daegu and Busan by means of a self-administered questionnaire. Frequencies and chi-square tests were conducted by SPSS Windows. The results of the survey were as follows: (1) the concerns about GMO were high but recognition was low. (2) many respondents were worried about the safety of GMO. (3) many people desired the labelling of GMO, and (4) the need for information about GMO was high and most respondents wanted to be informed about safety of GMO. This study suggests that the consumer education about GMO should be conducted through mass media and consumer protection organizations.

• Fashion & Textile Research Journal
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• v.19 no.1
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• pp.19-29
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• 2017

This study identified the purchase decision-making process of outdoor wear consumers and examined the hypothesis that consumer satisfaction mediates the relationship between purchase decision-making process and repurchase intention. Data were acquired from a survey and analyzed with descriptive, factor analysis, reliability analysis and multiple regression analysis. Respondents were 454 adults who have purchased outdoor wear. The results are as follows. First, the purchase decision-making processes of outdoor wear consumers consisted of a series of steps: need recognition & passive information search, active information search, evaluation of alternatives with practical attributes, evaluation of alternatives with unpractical attributes, purchase decision, and post-purchase evaluation. Second, four purchase decision-making processes (except for need recognition & passive information search and active information search) had significantly positive effects on consumer satisfaction. Third, the need recognition & passive information search, the evaluation of alternatives with unpractical attributes and post-purchase evaluation had significantly positive effects on repurchase intention. Lastly, the partial mediation of consumer satisfaction in the relationship between two purchase decision-making processes (evaluation of alternatives with unpractical attributes and post-purchase evaluation) and repurchase intention were indicated. This academic study will help to understand the purchase decision-making processes of outdoor wear and allow companies to obtain information (from the industrial aspect) about which process to invest in and how to manage the process.

• Journal of the Korean Society of Food Culture
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• v.16 no.4
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• pp.296-309
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• 2001

This study was conducted to investigate the consumers' recognition and information need for food safety, especially focused on pesticide residues, foodborne illness, and food additives. The data were collected from 350 adults living in Taegu and Pusan by the self-administered questionnaire. Frequencies and chi-square tests were conducted by SPSS. The results of the survey were as follows: (1) the consumers' concerns about food safety were high, (2) many respondents worried about eating vegetables, fruits and grains in turn because of pesticide residues, and did not trust the results from food-safety tests, (3) the major factor for foodborne illness was regarded as unfreshed or contaminated food stuffs, (4) many consumers concerned highly about preservatives among food additives, and tried to consume food containing less food additives, and (5) many respondents wanted to get the information about harmfulness of pesticide residues in foods, method to choose fresh food, and safety of food additives.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.284-288
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• Journal of Korea Multimedia Society
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• v.24 no.5
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• pp.701-708
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• 2021

As one of the most widely used technology in the world right now, Face recognition has already received widespread attention by all the researcher and institutes. It has been used in many fields such as safety protection, surveillance system, crime control and even in our ordinary life such as home security and so on. This technology with today's technology has advantages such as high connectivity and real time transformation. But we still need to improve its recognition rate, reaction time and also reduce impact of different environmental status to the whole system. So in this paper we proposed a face recognition system model with improved CNN which combining the characteristics of flat network and residual network, integrated learning, simplify network structure and enhance portability and also improve the recognition accuracy. We also used AR and ORL database to do the experiment and result shows higher recognition rate, efficiency and robustness for different image conditions.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.2
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• pp.135-145
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• 2023

Recently, as deep learning technology has developed, various deep learning technologies have been introduced in handwritten recognition, greatly contributing to performance improvement. The recognition accuracy of handwritten Hangeul recognition has also improved significantly, but prior research has focused on recognizing 520 Hangul characters or 2,350 Hangul characters using SERI95 data or PE92 data. In the past, most of the expressions were possible with 2,350 Hangul characters, but as globalization progresses and information and communication technology develops, there are many cases where various foreign words need to be expressed in Hangul. In this paper, we propose a model that recognizes and combines the consonants, medial vowels, and final consonants of a Korean syllable using a multi-label classification model, and achieves a high recognition accuracy of 98.38% as a result of learning with the public data of Korean handwritten characters, PE92. In addition, this model learned only 2,350 Hangul characters, but can recognize the characters which is not included in the 2,350 Hangul characters

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.150-154
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.