• Computers and Concrete
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• v.17 no.1
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• pp.141-156
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• 2016

The search for new structural systems capable of associating performance and safety requires deeper knowledge regarding the mechanical behavior of structures subject to different loading conditions. The Strut-and-Tie Model is commonly used to structurally designing some reinforced concrete elements and for the regions where geometrical modifications and stress concentrations are observed, called "regions D". This method allows a better structural behavior representation for strength mechanisms in the concrete structures. Nonetheless, the topological model choice depends on the designer's experience regarding compatibility between internal flux of loads, geometry and boundary/initial conditions. Thus, there is some difficulty in its applications, once the model conception presents some uncertainty. In this context, the present work aims to apply the Strut-and-Tie Model to nonlinear structural elements together with a topological optimization method. The topological optimization method adopted considers the progressive stiffness reduction of finite elements with low stress values. The analyses performed could help the structural designer to better understand structural conceptions, guaranteeing the safety and the reliability in the solution of complex problems involving structural concrete.

• The Journal of Korea Robotics Society
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• v.7 no.2
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• pp.92-100
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• 2012

A map of complex environment can be generated using a robot carrying sensors. However, representation of environments directly using the integration of sensor data tells only spatial existence. In order to execute high-level applications, robots need semantic knowledge of the environments. This research investigates the design of a system for recognizing objects in 3D point clouds of urban environments. The proposed system is decomposed into five steps: sequential LIDAR scan, point classification, ground detection and elimination, segmentation, and object classification. This method could classify the various objects in urban environment, such as cars, trees, buildings, posts, etc. The simple methods minimizing time-consuming process are developed to guarantee real-time performance and to perform data classification on-the-fly as data is being acquired. To evaluate performance of the proposed methods, computation time and recognition rate are analyzed. Experimental results demonstrate that the proposed algorithm has efficiency in fast understanding the semantic knowledge of a dynamic urban environment.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.789-794
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• 2005

LDA (Linear Discriminant Analysis) provides the projection that discriminates the data well, and shows a very good performance for face recognition. However, since LDA provides only one transformation matrix over whole data, it is not sufficient to discriminate the complex data consisting of many classes like honan faces. To overcome this weakness, we propose a new face recognition method, called LDA mixture model, that the set of alf classes are partitioned into several clusters and we get a transformation matrix for each cluster. This detailed representation will improve the classification performance greatly. In the simulation of face recognition, LDA mixture model outperforms PCA, LDA, and PCA mixture model in terms of classification performance.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.524-526
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• 1999

In the construction of successful fuzzy models and/or controllers for nonlinear systems, the identification of a good fuzzy inference system is an important yet difficult problem, which is traditionally accomplished by a time-consuming trial-and-error process. In this paper, we propose a systematic identification procedure for complex multi-input single-output nonlinear systems with DNA coding method. A DNA coding method is optimization algorithm based on biological DNA as conventional genetic algorithms(GAs) are. The strings in the DNA coding method are variable-length strings, while standard GAs work with a fixed-length coding scheme. the DNA coding method is well suited to learning because it allows a flexible representation of a fuzzy inference system. We also propose a new coding method fur applying the DNA coding method to the identification of fuzzy models. This coding scheme can effectively represent the zero-order Takagi-Sugeno(TS) fuzzy model. To acquire optimal TS fuzzy model with higher accuracy and economical size, we use the DNA coding method to optimize the parameters and the number of fuzzy inference system. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its application to a Duffing-forced oscillation system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.6
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• pp.211-216
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• 2017

XML is becoming a de facto standard for the representation and exchange of data, and XML itself is well structured to store and manage data, but it is difficult to understand the document structure at a glance due to its diverse and complex expressions. Thus, it is not appropriate to use it as a tool of conceptual model. In this paper, we propose a method to transform XML schema document structure into conceptual model. To do this, we describe CMXML as a conceptual modeling tool and present transformation rules and data structures for transforming an XML schema structure into CMXML diagram. In the transformation procedure, the XML schema document is input and the CMXML diagram is generated by applying the transformation rules.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.523-528
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• 2001

There are many difficult problems in analyzing the flow characteristics in a high voltage circuit breaker such as shock wave and complex geometries, which may be either static or in relative motion. Although a variety of mesh generation techniques are now available, the generation of meshes around complicated, multicomponent geometries like a gas circuit breaker is still a tedious and difficult task for the computational fluid dynamics. This paper presents the computational method for analyzing the compressible flow fields in a high voltage gas circuit breaker using the Cartesian cut-cell method based on the CFD-CAD integration, which can achieve the accurate representation of the geometry designed by a CAD tools. The technique is frequently satisfied, and it will be almost universally so in the future, as the CFD-CAD traffic increases.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.183-192
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• 2006

A CAD/CAM system has been developed for rapid prototyping (RP) of microfluidic devices based on excimer laser micromachining. The system comprises of two complementary softwares. One, the CAM tool, creates part programs from CAD models. The other, the Simulator Tool, uses a part program to generate the laser tool path and the 2D and 3D graphical representation of the machined microstructure. The CAM tool's algorithms use the 3D geometry of a microstructure, defined as an STL file exported from a CAD system, and process parameters (laser fluence, pulse repetition frequency, number of shots per area, wall angle), to automatically generate Numerical Control (NC) part programs for the machine controller. The performance of the system has been verified and demonstrated by machining a particle transportation device. The CAM tool simplifies part programming and replaces the tedious trial-and-error approach to creating programs. The simulator tool accepts manual or computer generated part programs, and displays the tool path and the machined structure. This enables error checking and editing of the program before machining, and development of programs for complex microstructures. Combined, the tools provide a user-friendly CAD/CAM system environment for rapid prototyping of microfluidic devices.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.553-561
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• 2018

To easily understand and systematically express the behaviors of the industrial systems, various system modeling techniques have been developed. Particularly, the importance of system modeling has been greatly emphasized in recent years since modern industrial systems have become larger and more complex. Multilevel flow modeling (MFM) is one of the qualitative modeling techniques, applied for the representation and reasoning of target system characteristics and phenomena. MFM can be applied to industrial systems without additional domain-specific assumptions or detailed knowledge, and qualitative reasoning regarding event causes and consequences can be conducted with high speed and fidelity. However, current MFM techniques have a limitation, i.e., the dynamic features of a target system are not considered because time-related concepts are not involved. The applicability of MFM has been restricted since time-related information is essential for the modeling of dynamic systems. Specifically, the results from the reasoning processes include relatively less information because they did not utilize time-related data. In this article, the concepts of time-to-detect and time-to-effect were adopted from the system failure model to incorporate time-related issues into MFM, and a methodology for enhancing MFM-based reasoning with time-series data was suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1189-1204
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• 2018

Detecting and capturing 3D human structures from the intensity-based image sequences is an inherently arguable problem, which attracted attention of several researchers especially in real-time activity recognition (Real-AR). These Real-AR systems have been significantly enhanced by using depth intensity sensors that gives maximum information, in spite of the fact that conventional Real-AR systems are using RGB video sensors. This study proposed a depth-based routine-logging Real-AR system to identify the daily human activity routines and to make these surroundings an intelligent living space. Our real-time routine-logging Real-AR system is categorized into two categories. The data collection with the use of a depth camera, feature extraction based on joint information and training/recognition of each activity. In-addition, the recognition mechanism locates, and pinpoints the learned activities and induces routine-logs. The evaluation applied on the depth datasets (self-annotated and MSRAction3D datasets) demonstrated that proposed system can achieve better recognition rates and robust as compare to state-of-the-art methods. Our Real-AR should be feasibly accessible and permanently used in behavior monitoring applications, humanoid-robot systems and e-medical therapy systems.

• Korean Journal of Child Studies
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• v.15 no.2
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• pp.97-116
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• 1994

This study investigated the effect of young children's interaction with a teacher and computer environments on their development of representational competence cf replay, the children's ability to construct and reconstruct actions. A pretest-posttest design with one experimental group and one control group was used; quantitative analyses, including interview assessments and coded observations of children's work in the context of educational interventions were supplemented by qualitative analyses of this work. Thirty-nine children (2-5 years of age) were randomly assigned to either an experimental or control group. The educational intervention provided to the experimental group involved a sequence of twenty sessions incorporating a series of three computer environments. A teaching strategy, based on Vygotsky's Zone of Proximal Development (ZPD) and Sigel's distancing theory, was used to mediate children's interaction with these computer environments. Results indicated that children's representational competence kept developing and reached a higher stage and the educational intervention fostered the development of representational competence, with strong evidence of near transfer but no evidence of far transfer. These results suggest that representational competence is a teachable concept and that a complex mediating structure allows children to reconstruct their previous experiences and apply them to problem situations.