• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.4
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• pp.283-292
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• 2013

The objective of this research is to evaluate of global and local damage for steel-concrete composite structures under highway bridge exposed to fire loading. To enhance the accuracy and efficiency of the numerical analysis, the proposed transient nonlinear thermal structure interaction(TSI) parallel fire analysis method is implemented in ANSYS. To validate the TSI parallel fire analysis method, a comparison is made with the standard fire test results. The proposed TSI parallel fire analysis method is applied to fire damage analysis and performance evaluation for Buchen highway bridge. The result of analysis, temperature of low flange and web are exceed the critical temperature. The deflection and deformation state show good agreement with the fire accident of buchen highway bridge.

• International Journal of High-Rise Buildings
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• v.3 no.1
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• pp.21-33
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• 2014

The tied braced frame (TBF) system was developed to achieve uniform seismic inelastic demand along the height of multi-storey eccentrically braced steel frames. A modular tied braced frame (M-TBF) configuration has been recently proposed to reach the same objective while reducing the large axial force demand imposed on the vertical tie members connecting the link beams together in TBFs. M-TBFs may however experience variations in storey drifts at levels where the ties have been removed to form the modules. In this paper, the possibility of reducing the discontinuity in displacement response of a 16-storey M-TBF structure by introducing energy dissipating (ED) devices between the modules is examined. Two M-TBF configurations are investigated: an M-TBF with two 8-storey modules and an M-TBF with four 4-storey modules. Three types of ED devices are studied: friction dampers (FD), buckling restrained bracing (BRB) members and self-centering energy dissipative (SCED) members. The ED devices were sized such that no additional force demand was imposed on the discontinuous tie members. Nonlinear response history analysis showed that all three ED systems can be used to reduce discontinuities in storey drifts of M-TBFs. The BRB members experienced the smallest peak deformations whereas minimum residual deformations were obtained with the SCED devices.

• Structural Engineering and Mechanics
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• v.18 no.5
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• pp.645-669
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• 2004

In seismic analysis of moment-resisting frames, beam-column connections are often modeled with rigid joint zones. However, it has been demonstrated that, in ductile reinforced concrete (RC) moment-resisting frames designed based on current codes (to say nothing of older non-ductile frames), the joint zones are in fact not rigid, but rather undergo significant shear deformations that contribute greatly to global drift. Therefore, the "rigid joint" assumption may result in misinterpretation of the global performance characteristics of frames and could consequently lead to miscalculation of strength and ductility demands on constituent frame members. The primary objective of this paper is to propose a rational method for estimating the hysteretic joint shear behavior of RC connections and for incorporating this behavior into frame analysis. The authors tested four RC edge beam-column-slab connection subassemblies subjected to earthquake-type lateral loading; hysteretic joint shear behavior is investigated based on these tests and other laboratory tests reported in the literature. An analytical scheme employing the modified compression field theory (MCFT) is developed to approximate joint shear stress vs. joint shear strain response. A connection model capable of explicitly considering hysteretic joint shear behavior is then formulated for nonlinear structural analysis. In the model, a joint is represented by rigid elements located along the joint edges and nonlinear rotational springs embedded in one of the four hinges linking adjacent rigid elements. The connection model is able to well represent the experimental hysteretic joint shear behavior and overall load-displacement response of connection subassemblies.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.12
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• pp.1337-1344
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• 2014

The objective of an echo canceller connected to any end of a communication line such as digital subscriber line (DSL) is to compensate the outgoing transmit signal in the receiving path that the hybrid circuit leaks. The echo canceller working in a full duplex environment is an adaptive system driven by the local signal. Conventional echo canceller that implement the least mean square (LMS) algorithm provides a low computational burden but poor convergence properties. The length of the echo canceller will directly affect both the degree of performance and the convergence speed of the adaptation process. To cancel long time-varying echoes, the number of tap coefficients of a conventional echo canceller must be large, which decreases the convergence speed of the adaptive filter. This paper proposes an alternative technique for the echo cancellation in a telecommunication channel. The new technique employs the bi-directional least mean square (LMS) algorithm for adaptively computing the optimal set of the coefficients of the echo canceller, which is composed of weighted combination of both feedforward and feedback algorithms. Finally, Simulation results as well as mathematical analysis demonstrates that the proposed echo canceller has faster convergence speed than the conventional LMS echo canceller with nearly equivalent complexity of computation.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.711-726
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• 2013

The purpose of this study was to investigate how congruently the learning objectives of Earth Science I textbooks match the 2009 revised Earth Science curriculum. For this purpose, we classified the learning objectives of curriculum and textbooks were into three factors including ability, cross-cutting concepts, and behavioral verbs. The text data were analyzed using the semantic network analysis method. The results are as follows. The learning objectives of textbooks with regard to ability factors mainly emphasized the cognitive and affective domain. In addition, the ability of inquiry performance was emphasized in the learning objective of the curriculum. The textbooks used various sub-frame of cross-cutting concepts in comparison with the curriculum. Both textbooks and curriculum used the term 'comprehension' the most as behavioral verbs. However, most behavioral verbs just remained at the level of cognitive system.

• KDI Journal of Economic Policy
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• v.25 no.2
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• pp.89-135
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• 2003

The paper tests the hypothesis that Internet banking reduces cost and ultimately enhances profitability for banks. Our analysis suggests that Internet banking does contribute to cost reduction but does not affect profitability. The implications are that the primary objective of Internet banking has been accomplished, but has not reached the stage in which the benefits overcome the burden of initial investment. The findings also offer the implication that Internet banking probably raises social welfare by passing on the benefit of cost reduction to customers rather than resulting in enhanced profits. In addition, we find that the banking customer's preference for face-to-face transactions may be very low in Korea, which supports the hypothesis that the cost in securing a customer base will be reduced significantly.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.517-524
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• 2004

The fuzzy set theory has been wide used in clustering of machine learning with data mining since fuzzy theory has been introduced in 1960s. In particular, fuzzy C-means algorithm is a popular fuzzy clustering algorithm up to date. An element is assigned to any cluster with each membership value using fuzzy C-means algorithm. This algorithm is affected from the location of initial cluster center and the proper cluster size like a general clustering algorithm as K-means algorithm. This setting up for initial clustering is subjective. So, we get improper results according to circumstances. In this paper, we propose a cluster merging using enhanced density based fuzzy C-means clustering algorithm for solving this problem. Our algorithm determines initial cluster size and center using the properties of training data. Proposed algorithm uses grid for deciding initial cluster center and size. For experiments, objective machine learning data are used for performance comparison between our algorithm and others.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.1
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• pp.53-62
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• 2010

This paper introduces a classification algorithm which can be applied to a learning problem with incomplete data sets, missing variable values or a class value. This algorithm uses a data expansion method which utilizes weighted values and probability techniques. It operates by extending a classifier which are considered to be in the optimal projection plane based on Fisher's formula. To do this, some equations are derived from the procedure to be applied to the data expansion. To evaluate the performance of the proposed algorithm, results of different measurements are iteratively compared by choosing one variable in the data set and then modifying the rate of missing and non-missing values in this selected variable. And objective evaluation of data sets can be achieved by comparing, the result of a data set with non-missing variable with that of C4.5 which is a known knowledge acquisition tool in machine learning.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1253-1261
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• 1996

The base station (BS) of CDMA mobile system (CMS) provides mobile call services by controlling call processing functions. The call Processing part of the BS is divided into two components; the base station transceiver subsystem (BTS) and the base station controller (BSC). In this paper, we present the call capacity estimation of the BS about control signals and traffic data of calls by the simulation, and find the bottleneck points and problems which may occur in the BS. In order to estimate the call capacity, first we extract the major parameters for the modeling the BS. Second, we suggest the simulation model for the BS. Third, we estimate the simulation results by finding major objective factors such that the call blocking probability, the utilization ratio and the delay time in the traffic channel elements (TCEs), the BTS interconnection network (BIN)-COMA interconnection network (CIN) trunks, the transcoding channels and the CIN packet router.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.618-626
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• 2004

In this paper, we describe a robot endeffector recognition system based on a Modular Neural Networks (MNN). The proposed recognition system can be used for vision system which track a given object using a sequence of images from a camera unit. The main objective to achieve with the designed MNN is to precisely recognize the given robot endeffector and to minimize the processing time. Since the robot endeffector can be viewed in many different shapes in 3- D space, a MNN structure, which contains a set of feedforwared neural networks, can be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training MNN patterns for a neural network share the similar characteristics so that they can be easily trained. The trained UM is les s sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14％ over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.