• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.333-342
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• 2003

The objective of this paper is to present an algorithm to locate and size damage in a beam structure. The method uses the changes in the modal strain energy distribution. A damage index, utilized to identify possible location and corresponding severity of local damage, is formulated and expressed in terms of modal displacements that can be obtained from mode shapes of the undamaged and the damaged structures. The possible damage locations in the structure arc determined by the application of damage indicator according to previously developed decision rules. The robustness and effectiveness of the method arc demonstrated using numerical examples of beam structures with simulated damage.

• Journal of Construction Engineering and Project Management
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• v.3 no.3
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• pp.17-22
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• 2013

In many urban cities, super-tall buildings have been being constructed around New York and Chicago as the center since 1930 to improve the efficiency of land use and respond to new residential type. In terms of energy consumption, super-tall buildings are classified as a top energy consumption building. Also, as time passed, the degradation of energy performance occurs in super-tall buildings like general things so that these cannot show the initial performance planned in the design phase. Accordingly, building owners need to make a plan to apply energy saving measures to existing building during the operation phase. In order to select energy saving measures, calculus-based methods and enumerative schemes have been typically used. However, these methods are time-consuming and previous studies which used these methods have problems with not considering the initial construction cost. Consequently, this study proposes a model for selecting an optimal combination of energy saving measures which derives maximum energy saving within allowable cost using genetic algorithms. As a contribution of this research, it would be expected that a model is utilized as one of the decision-making tools during the planning stage for energy saving.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.1
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• pp.53-58
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• 2005

Water shortages are gradually accelerating because higher standards of living are required and water resources are more heavily utilized. Therefore, effective water treatment is necessary in order to retain the required qualify and amount of water. General treatment includes coagulation, flocculation, filtering, and disinfection. coagulation, flocculation, and disinfection are major components of water treatment processes. In this paper, a new automatic decision algorithm is proposed for coagulation. The proposed method shows how to determine the coagulant type and amount using data mining techniques.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.175-185
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• 2009

In this paper, performance of OFDM systems with turbo code is analyzed and simulated in a satellite broadcasting channel. The performance is evaluated in terms of bit error probability. The satellite channel is modeled as a combination of Rayleigh fading with shadowing and Rician fading channels. As turbo decoding algorithms, MAP (maximum a posteriori), Max-Log-MAP, and SOVA (soft decision Viterbi output) algorithms are chosen and their performances are compared. From simulation results, it is demonstrated that Max-Log-MAP algorithm is promising in terms of performance and complexity. It is shown that performance is substantially improved by increasing the number of iterations and interleaver length of a turbo encoder. The results in this paper can be applied to OFDM-based satellite broadcasting systems.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.957-963
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• 2014

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot end-point precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

• ETRI Journal
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• v.31 no.4
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• pp.438-447
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• 2009

In this paper, a novel image projection technique for face recognition application is proposed which is based on linear discriminant analysis (LDA) combined with the relevance-weighted (RW) method. The projection is performed through 2-directional and 2-dimensional LDA, or $(2D)^2$LDA, which simultaneously works in row and column directions to solve the small sample size problem. Moreover, a weighted discriminant hyperplane is used in the between-class scatter matrix, and an RW method is used in the within-class scatter matrix to weigh the information to resolve confusable data in these classes. This technique is called the relevance-weighted $(2D)^2$LDA, or RW$(2D)^2$LDA, which is used for a more accurate discriminant decision than that produced by the conventional LDA or 2DLDA. The proposed technique has been successfully tested on four face databases. Experimental results indicate that the proposed RW$(2D)^2$LDA algorithm is more computationally efficient than the conventional algorithms because it has fewer features and faster times. It can also improve performance and has a maximum recognition rate of over 97%.

• Journal of Mechanical Science and Technology
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• v.17 no.12
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• pp.1969-1976
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making for the product concepts, and the best alternative can be selected based on its estimated LCA and benefits. Both the lack of detailed information and time for a full LCA for a various range of design concepts need a new approach for the environmental analysis. This paper explores a new approximate LCA methodology for the product concepts by grouping products according to their environmental characteristics and by mapping product attributes into environmental impact driver (EID) index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then, a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for newly designed products. The training is generalized by using product attributes for an EID in a group as well as another product attributes for the other EIDs in other groups. The neural network model with back propagation algorithm is used, and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines for the design of environmentally conscious products in conceptual design phase.

• Journal of Information Technology Application
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• v.3 no.2
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• pp.1-24
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• 2001

This purpose of this study is to drive important criteria for improving customer relationship of R institute using data mining techniques. The focus of this research is to consider patterns and interactions of research variables from research management database of R institute, and to classify the outside organizations and the inside organizations for research contract organizations, and to decide the directions of customer relationship management through analyzing the research type and research cost of research topics. In order to drive criteria variables through pattern analysis of the research database, decision tree algorithm is employed. The results show that determinant variables of 17 input variables are research period, overhead cost, R ＆ D cost as variables to classify the outside and inside contract organization.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.53-62
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• 2008

Cross-lingual text retrieval(CLTR) is the information retrieval in which a user tries to search a set of documents written in one language for a query another language. This thesis proposes a CLTR system based on fuzzy multilingual thesaurus to handle a partial matching between terms of two different languages. The proposed CLTR system uses a fuzzy term matrix defined in our thesis to perform the information retrieval effectively. In the defined fuzzy term matrix, all relation degrees between terms are inferred from using the transitive closure algorithm to reflect all implicit links between terms into processing of the information retrieval. With this framework, the CLTR system proposed in our thesis enhances the retrieval effectiveness because it is able to emulate a human expert's decision making well in CLTR.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.53-63
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• 2013

To guide the decision making of the expert engineer specialized in power system operation and control; the practical OPF solution should take in consideration the critical situation due to severe loading conditions and fault in power system. Differential Evolution (DE) is one of the best Evolutionary Algorithms (EA) to solve real valued optimization problems. This paper presents simple Differential Evolution (DE) Optimization algorithm to solving multi objective optimal power flow (OPF) in the power system with shunt FACTS devices considering voltage deviation, power losses, and power flow branch. The proposed approach is examined and tested on the standard IEEE-30Bus power system test with different objective functions at critical situations. In addition, the non smooth cost function due to the effect of valve point has been considered within the second practical network test (13 generating units). The simulation results are compared with those by the other recent techniques. From the different case studies, it is observed that the results demonstrate the potential of the proposed approach and show clearly its effectiveness to solve practical OPF under contingent operation states.