• Steel and Composite Structures
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• v.45 no.2
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• pp.159-173
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• 2022

This paper proposes a hybrid machine-learning model, which is called DANN-IP, that combines a deep artificial neural network (DANN) and an interior-point (IP) algorithm in order to improve the prediction capacity on the patch loading resistance of steel plate girders. For this purpose, 394 steel plate girders that were subjected to patch loading were tested in order to construct the DANN-IP model. Firstly, several DANN models were developed in order to establish the relationship between the patch loading resistance and the web panel length, the web height, the web thickness, the flange width, the flange thickness, the applied load length, the web yield strength, and the flange yield strength of steel plate girders. Accordingly, the best DANN model was chosen based on three performance indices, which included the R^2, RMSE, and a20-index. The IP algorithm was then adopted to optimize the weights and biases of the DANN model in order to establish the hybrid DANN-IP model. The results obtained from the proposed DANN-IP model were compared with of the results from the DANN model and the existing empirical formulas. The comparison showed that the proposed DANN-IP model achieved the best accuracy with an R^2 of 0.996, an RMSE of 23.260 kN, and an a20-index of 0.891. Finally, a Graphical User Interface (GUI) tool was developed in order to effectively use the proposed DANN-IP model for practical applications.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.1038-1044
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• 2013

A research on thermal analysis method is conducted for the characterization of heat generation during operation of Interior Permanent Magnet Synchronous Motor(IPMSM) for Light Railway Transits(LRT) in this paper. Efficient cooling of the heat generated in the IPMSM is important because the excessive heat generated from the winding, core and permanent magnet makes it harder for a long time continuous operation of IPMSM. Therefore, in order to analyze the heat generation characteristics of the 110kW-class IPMSM as advanced research for application the IPMSM to the cooling device, the heat transfer coefficients for each component of the 110 kW-class IPMSM were derived and the thermal equivalent network was configured to perform the thermal analysis in this study. Finally, the 110kW-class IPMSM prototype is made and a comparative verification between the test data and the thermal analysis results through its various performance tests are carried out.

• Korean Institute of Interior Design Journal
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• v.19 no.5
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• pp.173-181
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• 2010

Opened on November 2008, as the public exhibition center of a telecommunication company, T.um is dedicated for delivering the future ubiquitous technologies and business vision of the company leading domestic mobile communication business to the global expected clients and business partners. Since the public opening, not only over 18,000 audiences in 112 nations have been visiting T.um, but also the public media have been releasing news regarding the ubiquitous museum constantly. By the reasons, T.um is regarded as a successful case for public exhibition centers. The most distinguished quality of the museum is established by the Location Based Service technology in the initial construction stage. A visitor in anyplace of T.um can be detected by digital devices equipped GPS systems. The LBS system in T.um allows visitors to get the information of relevant technologies as well as the process of how to operating each content at his own spots by smart phone of which wireless network systems make it possible. This study is focusing on analyzing and defining the T.um special qualities in terms of technologies to provide the basic data for following exhibition space projects based on LBS. The special method of experiencing contents can be designed by utilizing the network system applied to T.um in the planning stage.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2005.05a
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• pp.88-92
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• 2005

The Ubiquitous life is not a life style that exists in a science fiction or in a far distance future anymore. The Combination of electronic and physical space, this new type of space was created by the ubiquitous network system, and this system will offer us new life style. Also the pattern of our living will be changed by the information that has obtained from this ubiquitous network system. By offering a new way of communication from the ubiquitous surrounding, our life style such as shopping, medical treatment, banking, and working conditions and a notion such as the preference in a job title would have shifted. This study have arrived at the development of the high technology, in other words Ubiquitous age , I have considered the notion of home-network that have observed by the preceding investigators as well as the theoretical consideration of residential space in ubiquitous surrounding. After I look into the usages and examples of residential space in ubiquitous surrounding of today's society, I hope that this would be helpful for the design that strives for the comfortable living in this ubiquitous age.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1183-1188
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• 2004

The inverse heat conduction problem (IHCP) is a problem of estimating boundary condition from temperature measurement at one or more interior points. Neural networks are general information processing systems inspired by the connectionist theory of human brain. By properly training the network by the learning rule, the neural network method can handle many non-linear or other complex problems. In this work, neural network is applied to complicated inverse heat conduction problems. Efficiency of the procedure is enhanced by incorporating the radial basis functions (RBF). The RBF is trained faster than other neural network and can find smooth solution. In order to demonstrate the effectiveness of the current scheme, a typical one-dimensional IHCP is considered. At one surface, the temperature as well as the heat flux is known. The unknown temperature of interest is estimated on the other side of the slab. The results from the proposed method based on RBF neural network are compared with the conventional method.

• Korean Institute of Interior Design Journal
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• no.21
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• pp.69-75
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• 1999

The extensive coverage and high speed of communication network, which is a basic structure of the information society, enables the provision of various forms of informatiov. especially, such services as cyber medicine, cyber education, home office, home banking, and home shopping will be common; and, now, no one can deny that the information society starts to be part of our life. Regarding home office, John Navigate predicted home office through the electronic house in New Mecca Trend and Alvin Toffler asserted in The third Wave that people could do their work anywhere including living room in their hoses with the development of communication technology and other related appliances. Such predictions are realized with the development of information communicatiov. Therefore, housing space should be changed according to the realization of home office and the direction of housing plan need to be set for home office.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2008.05a
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• pp.46-49
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• 2008

This research does Complexity form, Interior epidermis cell re-organization, Object discovery that have correct numerical value concept by purpose. Research applied by Grid re-organization in form generation, Parameter variation of cell unit (morphor, tweener), Symbol, pattern of variation, self-organization cell substitution order. Representation through 3d digital modeler of polygon, Nurbs and street-sheet program(x,y,z coordinates & Network way of points) etc. of main work. Investigator specified numbers of U profiles*30, V point-20 that is 600 Paramaters individual in volume, and define circle radius of lighting in object, Projection size variously and tried difference. Transposition cell to point and Heightened brightness of color using pointillism of painting. Led lighting cell object is expressed being decoded by digital code.

• Structural Engineering and Mechanics
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• v.64 no.4
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• pp.437-447
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• 2017

Explicit expressions for rapid prediction of inelastic design quantities (considering cracking of concrete) from corresponding elastic quantities, are presented for multi-storey composite frames (with steel columns and steel-concrete composite beams) subjected to service load. These expressions have been developed from weights and biases of the trained neural networks considering concrete stress, relative stiffness of beams and columns including effects of cracking in the floors below and above. Large amount of data sets required for training of neural networks have been generated using an analytical-numerical procedure developed by the authors. The neural networks have been developed for moments and deflections, for first floor, intermediate floors (second floor to ante-penultimate floor), penultimate floor and topmost floor. In the case of moments, expressions have been proposed for exterior end of exterior beam, interior end of exterior beam and both interior ends of interior beams, for each type of floor with a total of twelve expressions. Similarly, in the case of deflections, expressions have been proposed for exterior beam and interior beam of each type of floor with a total of eight expressions. The proposed expressions have been verified by comparison of the results with those obtained from the analytical-numerical procedure. This methodology helps to obtain the inelastic design quantities from the elastic quantities with simple calculations and thus would be very useful in preliminary design.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2804-2823
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• 2013

Wireless sensor network (WSN) is a promising technology for monitoring physical phenomena at fine-grained spatial and temporal resolution. However, the typical approach of sending each sensed measurement out of the network for detailed spatial analysis of transient physical phenomena may not be an efficient or scalable solution. This paper focuses on in-network physical phenomena detection schemes, particularly the distributed computation of the boundary of physical phenomena (i.e. event), to support energy efficient spatial analysis in wireless sensor networks. In-network processing approach reduces the amount of network traffic and thus achieves network scalability and lifetime longevity. This study investigates the recent advances in distributed event detection based on in-network processing and includes a concise comparison of various existing schemes. These boundary detection schemes identify not only those sensor nodes that lie on the boundary of the physical phenomena but also the interior nodes. This constitutes an event geometry which is a basic building block of many spatial queries. In this paper, we introduce the challenges and opportunities for research in the field of in-network distributed event geometry boundary detection as well as illustrate the current status of research in this field. We also present new areas where the event geometry boundary detection can be of significant importance.