• Journal of Institute of Control, Robotics and Systems
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• v.6 no.12
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• pp.1113-1119
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• 2000

To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.251-257
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• 1998

Spherical space frame structure with triangular network pattern, which has the various characteristics for the mechanic property, a funtional property, an aesthetic property and so on, has often been used as one of the most efficient space structures. It is expected that this type will be used widely in large-span structural roofs. But because this structure is made of network by combination of line elements there me many nodes therefore, the structure behavior is very complicated and there can be an overall collapse of structure by buckling phenomenon if the external force reaches a limitation. This kind of buckling is due to geometric shape, network pattern, the number of layer and so on, of structure. Therefore spherical space frame with triangle network pattern have attracted many designers and researchers attention all over the world. The number of layer of space frame is divided in to the simgle, double, multi layer. That is important element which is considered deeply in the beginning of structural design. The buckling characteristics of single-layer model and double-layer model for the spherical space frame structure with triangular network pattern are evaluated and the buckling loads of these types are compared with investigation their structural efficiency in this study.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.477-482
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• 2004

Due to the traffic congestion of the city and public transportation-oriented policies, public transportation is receiving more attention and being used increasingly However, relatively less research on the design and distribution of public transportation network and limitations in quantitative approaches have made implementation and operation practically difficult. Over- or under-supply of transportation routes caused unbalanced connectivity among areas and differences in time, expenses and metal burden of users. On the other hand, the Space Syntax theory, designed to calculate the connectivity of urban or architectural space, helps generate quantitative connectivity of whole space simply based on the spacial structure. This study modified the original Space Syntax algorithm to fit the public transportation problem and showed how it is appied to a network by creating an artificial network using the GIS.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Journal of the Korean association of regional geographers
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• v.12 no.2
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• pp.245-264
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• 2006

According to many conceptual researches and discourses, development of information-communication technology(ICT) has made great influences upon activities on time and space. But some empirical studies have shown that its influence in the real world is not so great as we may expect In order to avoid these two oppositional views, this paper wants to put interests on socio-spatial relationships or networks, rather than individual phenomena or consciousness, which have been transformed under the influence of ICT. The development of ICT presupposes a creation of information network, and hence the term 'etwork social space' can be used to see its spatial influence, which would be further understood with the theory of actor-network. This paper also suggests that network social space has three strata, that is, 'nstant' 'unctional 'and 'aterial' and that network social space can be emphasized not only as newly emerging social space but also as reconstruction of subjects' identity through his/her participation into information network as its node.

• The Bulletin of The Korean Astronomical Society
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• v.34 no.1
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• pp.185.2-185.2
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• 2009

• Journal of Korea Game Society
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• v.10 no.6
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• pp.89-96
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• 2010

To identify characteristics of social network farm game based on smart phone platform, this study analyzed how social network play experience connects with the space of farm game. The play experience of social network farm game based on smart phone platform is mainly composed of three modules for cultivating, placing environment, extending space. This study categorized space for external perspective space, internal perspective space, symbolic design space according to space experience theory and researched play experience in these spaces. In farm game players perceive space by fixed point of view, and make their own space a standard unit for reinterpreting and rearranging modules. In this process the space played subjective role not only background to bring co-work play is essential in social network game.

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.75-96
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• 1996

This study is intended to compare the effectiveness of the neural network inductive learning model with a vector space model in information retrieval. As a result, searches responding to incomplete queries in the neural network inductive learning model produced a higher precision and recall as compared with searches responding to complete queries in the vector space model. The results show that the hybrid methodology of integrating an inductive learning technique with the neural network model can help solve information retrieval problems that are the results of inconsistent indexing and incomplete queries--problems that have plagued information retrieval effectiveness.

• Bulletin of the Korean Space Science Society
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• 2009.04a
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• pp.56.1-56.1
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• 2009

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.37.4-38
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• 2008

Recently, statement of Intent for ILN has been signed by 9 countries including Korea, initiated March of this year by NASA which invited countries having lunar exploration plans. Concept of ILN is placing several core set of instrumentation on the Moon, in order to maximize scientific return to all of the participants. Network measurements from various nodes on lunar surface is essential for understanding internal structure of the Moon and environment around the Moon. Currently, Core Instrument Working Group is discussing the scientific interests and instrumentation among participated countries. Korea also is looking over various ways to participate ILN. We will introduce the progress and possible lunar science of ILN and will discuss the science mission objectives.