• The Korean Journal of Food And Nutrition
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• v.29 no.1
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• pp.79-86
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• 2016

This study was analyzed to provide fundamental data of food safety education way on the recognition, knowledge and purchase attitude of GMO foods. Data was collected from 270 University students in the Gyeong-gi region through a self-administered questionnaire. According to the results of the reliability and factor analysis, the knowledge and purchase attitude of GMO foods showed 0.742 and 0.832 in Cronbach alpha coefficient, 0.791 and 0.831 in KMO. There were significant differences in the recognition and intake possibility and purchase will, safety and absorption to a GMO foods between the specialty person and non-specialist (p<0.05). By the kind of GMO foods it appeared highly by the order corn (70.0%), tomato (67.5%), beans (63.3%) and potato (51.3%). There were significant differences in the general knowledge of GMO foods (p<0.05), whereas no significant differences in question 'There were no genes in ordinary beans' by a presence of a specialty (p>0.05). After the purchase attitude difference to the GMO foods was analyzed by a presence of a specialty, I appeared most highly in the question to which I say 'I think a GMO foods is ethical.' by a negative question and 'I think a GMO foods is mass-produced, and it's possible to make a food problem decrease.' by an affirmative question. Therefore, the purchase attitude of GMO foods showed a significant differences of University students according to their major (p<0.05). Based on this study, it is considered that provision of detailed and continuous education must be accomplished by raising the recognition of GMO foods and its acceptance level, allowing a proper understanding of GMO foods to be conveyed and assisting subjects from receiving the information they desire effectively by various education mediums.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.235-240
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• 2004

In this paper, we propose a framework for ontological knowledge-based image understanding systems. Ontology composed of concepts can be used as a guide for describing objects from a specific domain of interest and describing relations between objects from different domains The proposed framework consists of four main subparts ⅰ) ontological knowledge bases, ⅱ) primitive feature detectors, ⅲ) concept inference engine, and ⅳ) semantic inference engine. Using ontological knowledge bases on various domains and features extracted from the detectors, concept inference engine infers concepts on regions of interest in an image and semantic inference engine reasons semantic situations between concepts from different domains. We present a outline for ontological knowledge-based image understanding systems and application examples within specific domains such as text recognition and human recognition in order to show the validity of the proposed system.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.125-138
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• 2010

The purpose of this research is to enhance document recognition system which is essential for developing full-text retrieval system of the document image data stored in the digital library of a public institution. To achieve this purpose, the main tasks of this research are: 1) analyzing the document image data and then developing its image preprocessing technology and document structure analysis one, 2) building its specialized knowledge base consisting of document layout and property, character model and word dictionary, respectively. In addition, developing the management tool of this knowledge base, the document recognition system is able to handle the various types of the document image data. Currently, we developed the prototype system of document recognition which is combined with the specialized knowledge base and the library of document structure analysis, respectively, adapted for the document image data housed in National Archives of Korea. With the results of this research, we plan to build up the test-bed and estimate the performance of document recognition system to maximize the utilization of full-text retrieval system.

• Journal of the Korean Society of Safety
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• v.34 no.4
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• pp.49-58
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• 2019

There was a difference in recognition of chemical substances according to cognitive level of GHS, knowledge level of organic solvents and each department of workers. they were showed higher recognition of chemical substances by research group, partially group and good group. To identify the relationship between types of job classification(group of department, group of GHS cognitive level and group of organic solvents knowledge level) and the levels of recognition of chemical substances, a total of 153 workers in a small and medium business workplace. Descriptive statistics(SAS ver 9.2)was performed. the results of recognition of chemical substances were analyzed the mean and standard deviation by t-test, and anova, (P=0.05). These results In general, small- and medium-sized workplaces have low levels of GHS awareness and organic solvents knowledge. The perception of chemical substances according to the departments. In general, the demand for chemical substances education was highly suggested regardless of the job type. There was a significant difference in the perception of health, safety and practice according to the level of GHS cognitive, and a high perception in the incomplete group. There was not much difference in average awareness of health, safety and practice according to organic solvents knowledge level, but there was a high perception in good group. It is very important to regularly check the worker's perception of the workplace and identify problems with the work environment and improve the work environment. In addition, each department presents appropriate safety and health education such as chemical process safety, toxicity of chemical substances and human exposure. We also propose a chemical substances assessment and management plan that integrates safety and health.

• The Journal of the Acoustical Society of Korea
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• v.23 no.4E
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• pp.112-119
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• 2004

This paper presents a method for the automatic recognition of pitch accents with no prior knowledge about the phonetic content of the signal (no knowledge of word or phoneme boundaries or of phoneme labels). The recognition algorithm used in this paper is a time-delay recurrent neural network (TDRNN). A TDRNN is a neural network classier with two different representations of dynamic context: delayed input nodes allow the representation of an explicit trajectory F0(t), while recurrent nodes provide long-term context information that can be used to normalize the input F0 trajectory. Performance of the TDRNN is compared to the performance of a MLP (multi-layer perceptron) and an HMM (Hidden Markov Model) on the same task. The TDRNN shows the correct recognition of $91.9{\%}\;of\;pitch\;events\;and\;91.0{\%}$ of pitch non-events, for an average accuracy of $91.5{\%}$ over both pitch events and non-events. The MLP with contextual input exhibits $85.8{\%},\;85.5{\%},\;and\;85.6{\%}$ recognition accuracy respectively, while the HMM shows the correct recognition of $36.8{\%}\;of\;pitch\;events\;and\;87.3{\%}$ of pitch non-events, for an average accuracy of $62.2{\%}$ over both pitch events and non-events. These results suggest that the TDRNN architecture is useful for the automatic recognition of pitch accents.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.04a
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• pp.314-320
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• 1998

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

• Tribology and Lubricants
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• v.15 no.2
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• pp.206-211
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• 1999

Wear debris morphology is closely related to the wear mode and mechanism occured. Image recognition of wear debris is, therefore, a powerful tool in wear monitoring. But it has usually required expert's experience and the results could be too subjective. Development of automatic tools for wear debris recognition is needed to solve this problem. In this work, an algorithm for automatic wear debris recognition was suggested and implemented by PC base software. The presented method defined a characteristic 3-dimensional feature space where typical types of wear debris were separately located by the knowledge-based system and compared the similarity of object wear debris concerned. The 3-dimensional feature space was obtained from multiple feature vectors by using a multi-dimensional scaling technique. The results showed that the presented automatic wear debris recognition was satisfactory in many cases application.

• Proceedings of the CALSEC Conference
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• 2005.03a
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• pp.55-61
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• 2005

We will introduce a new web-based knowledge management system in progress, in which XML-based web information extraction and our structuring knowledge technologies are combined using ontology-based natural language processing. Our aim is to provide efficient access to heterogeneous information on the web, enabling users to use a wide range of textual and non textual resources, such as newspapers and databases, effortlessly to accelerate knowledge acquisition from such knowledge sources. In order to achieve the efficient knowledge management, we propose at first an XML-based Web information extraction which contains a sophisticated control language to extract data from Web pages. With using standard XML Technologies in the system, our approach can make extracting information easy because of a) detaching rules from processing, b) restricting target for processing, c) Interactive operations for developing extracting rules. Then we propose a structuring knowledge system which includes, 1) automatic term recognition, 2) domain oriented automatic term clustering, 3) similarity-based document retrieval, 4) real-time document clustering, and 5) visualization. The system supports integrating different types of databases (textual and non textual) and retrieving different types of information simultaneously. Through further explanation to the specification and the implementation technique of the system, we will demonstrate how the system can accelerate knowledge acquisition on the Web even for novice users of the field.

• Journal of the Korean Home Economics Association
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• v.37 no.8
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• pp.55-72
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• 1999

The purpose of this study is to identify the levels of informationized life of individual, consumers knowledge and attitudes to informationized society, and the recognition of consumer problems in informationized society, and to investigate the related variables. Data were collected from 693.consumers living in Seoul using the constructed questionnaires by the authors. Frequency, Percentage and Multiple Regression Analysis were applied for the analysis. The level of informationized life of consumers was lower than the mid-point of the scale, the level of the consumers knowledge about informationized society was sightly higher than mid-point of the scale, and the consumer attitudes to informationized society appeared to be positive. The level of the recognition of consumer problems in informationized society was higher than the mid-point of the scale,and was influenced by job, age of consumers, and the level of consumers knowledge about informationized society.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.80-83
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• 2005

A binocular robot vision system having an autonomously moving active viewpoint is proposed. By using this active viewpoint, the system constructs a correspondence between the images of a feature points on the right and left retinas and calculates the spatial coordinates of the feature points. The system incorporates a function of detecting straight lines in an image. To detect lines the system uses Hough transform. The system searches a region surrounded by 4 straight lines. Then the system recognizes the region as a quadrangle. The system constructs a correspondence between the quadrangles in the right and left images. By the use of the result of the constructed correspondence, the system calculates the spatial coordinates of an object. An experiment shows the effect of the line detection using Hough transform, the recognition of the surface of the object and the calculation of the spatial coordinates of the object.