• English Language & Literature Teaching
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• no.6
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• pp.89-111
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• 2000

Since speaking is correlated with time and time is metaphorically conceptualized in terms of space, it is natural for us to conceptualize language metaphorically in terms of space. For example, we think that the future is in front and the past is behind. Reddy(1979) suggested in his conduit metaphor that linguistic expressions are containers. According to him, the speaker puts his ideas(objects) into words{containers)and sends them along a conduit to a hearer who takes the idea(object) out of the word(container). As a result we are able to know that the larger linguistic expressions have more meaning in it. In other words the space of a linguistic form has close relationship with meaning. Moreover we are able to see that formal distance between arguments or elements of linguistic expressions shows semantic influences between them. If two elements keep close distance, a preceeding element has a strong, direct and whole influence upon the following element. Sometimes even the results of the influence can be brought out implicitly by the formal relation between two elements. Therefore, the purpose of this paper is to show that tins difference in meaning which is due to formal distance of sentence elements can be explained by the metaphorical concept presented by Lakoff and Johnson(1980).

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.37-44
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• 2008

Data entered into RFID tags are used for saving costs and enhancing competitiveness in the development of applications in various industrial areas. RFID readers perform the identification and search of hundreds of objects, which are tags. RFID technology that identifies objects on request of dynamic linking and tracking is composed of application components supporting information infrastructure. Despite their many advantages, existing applications, which do not consider elements related to real.time data communication among remote RFID devices, cannot support connections among heterogeneous devices effectively. As different network devices are installed in applications separately and go through different query analysis processes, there happen the delays of monitoring or errors in data conversion. The present study implements a RFID database handling system in semantic Web environment for integrated management of information extracted from RFID tags regardless of application. Users’ RFID tags are identified by a RFID reader mounted on an application, and the data are sent to the RFID database processing system, and then the process converts the information into a semantic Web language. Data transmitted on the standardized semantic Web base are translated by a smart browser and displayed on the screen. The use of a semantic Web language enables reasoning on meaningful relations and this, in turn, makes it easy to expand the functions by adding modules.

• Journal of the Korean Society for Library and Information Science
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• v.40 no.3
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• pp.175-190
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• 2006

For the recent several years, there has been much interest in lexical semantic network However it seems to be very difficult to evaluate the effectiveness and correctness of it and invent the methods for applying it into various problem domains. In order to offer the fundamental ideas about how to evaluate and utilize lexical semantic networks, we developed two automatic vol·d clustering systems, which are called system A and system B respectively. 68.455.856 words were used to learn both systems. We compared the clustering results of system A to those of system B which is extended by the lexical-semantic network. The system B is extended by reconstructing the feature vectors which are used the elements of the lexical-semantic network of 3.656 '-ha' verbs. The target data is the 'multilingual Word Net-CoroNet'. When we compared the accuracy of the system A and system B, we found that system B showed the accuracy of 46.6% which is better than that of system A. 45.3%.

• Journal of KIISE
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• v.43 no.1
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• pp.106-118
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• 2016

Recently, as the generation and sharing of web data have increased, the importance of a social semantic web that combines the semantic web and the social web has also been increasing. In this paper, we propose a trust evaluation scheme based on provenance by extending the PROV model in the social semantic web environment. The proposed scheme manages the provenance of web data and adds the necessary elements for trust evaluation in the PROV model of W3C. The extended PROV model supports data management and provenance tracing. The proposed trust evaluation scheme considers various parameters such as user trust, original data trust, and user evaluation. The evaluated trust is managed as provenance. When processing a query, the proposed scheme generates a result by considering the trust. Therefore, the proposed scheme can manage the provenance of web data and compute data trust correctly by using such various parameters. The evaluated trust becomes a criterion to determine whether the query result can be trusted or not. In order to show the validity of the proposed scheme, we verify its performance using SPARQL queries.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.325-332
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• 1998

In the context of total quality management, customer satisfaction is a key factor of success. Customer needs have been in the past described with rather vague words. In order to lead in the competitive market, product designers must be willing to interpret and reflect customer perceptions of a product on the design. The objective of this research is to develop a systematic process capable of linking customer preferences on a product to the design of product elements or specifications. The design process consists of multivariate statistical analyses, semantic differentials, and multidimensional scaling techniques under the framework of a methodology known as quality function deployment which is frequently used to construct a quality design process. The process being established is expected to serve as an effective means to communicate between the customer and the designer through proper representational schemes of design elements.

• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.3
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• pp.537-547
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• 2001

The purpose of this study was to develop the measurement of the fashion sensibility. The stimulus were 91 photos selected in fashion magazines and had dominant visual power under detail, color, texture and pattern in the elements of fashion design. The semantic differential scale was constructed bipolar 25 pairs. The obtained data were analyzed by cluster analysis, factor analysis, ANOVA and t-test. The results were as follows; 1. The hierarchical structure was combined a natural and interesting, sensitive and lovely fashion sensibility. 2. The constructing factors of fashion sensibility were found out as aesthetic value, maturity, character and femininity·masculinity.(total variance: 55.7%) 3. Fashion sensibility by elements of fashion design was significantly different regarding all factors. 4. Fashion sensibility by demographic variables sex, age, marriage, education, occupation and expenditure was significantly different regarding partial factors.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.142-153
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• 1999

In the context of total quality management, customer satisfaction is a key factor of success. Customer needs have been in the past described with rather vague words. In order to lead in the competitive market, product designers must be willing to interpret and reflect customer perceptions of a product on the design. The objective of this research is to develop a systematic process capable of linking customer preferences on a product to the design of product elements or specifications. The design process consists of multivariate statistical analyses, semantic differentials, and multidimensional scaling techniques under the framework of a methodology known as quality function deployment which is frequently used to construct a quality design process. The process being established is expected to serve as an effective means to communicate between the customer and the designer through proper representational schemes of design elements.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.508-514
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• 2007

In order to extract some important information of a person from text, an extracting model was proposed. The person's name is recognized based on the maximal entropy statistic model and the training corpus. The sentences surrounding the person's name are analyzed according to the conceptual knowledge base. The three main elements of events, domain, situation and background, are also extracted from the sentences to construct the structure of events about the person.

• Journal of Educational Research in Mathematics
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• v.17 no.3
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• pp.253-270
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• 2007

by A.C. Clairaut was written based on the historico-genetic principle such as his . In this paper, by analyzing his we can induce six principles that Clairaut adopted to teach algebra: necessity and curiosity as a motive of studying algebra, harmony of discovery and proof, complementarity of generalization and specialization, connection of knowledge to be learned with already known facts, semantic approaches to procedural knowledge of mathematics, reversible approach. These can be considered as strategies for teaching algebra accorded with beginner's mind. Some of them correspond with characteristics of , but the others are unique in the domain of algebra. And by comparing Clairaut's approaches with school algebra, we discuss about some mathematical subjects: setting equations in relation to problem situations, operations and signs of letters, rule of signs in multiplication, solving quadratic equations, and general relationship between roots and coefficients of equations.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.47-55
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• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.