• Title/Summary/Keyword: Task structure

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A Study on the Effect of the Construction Conditions on a Thermal Crack of Mat Foundation (매트기초의 온도균열에 미치는 시공조건의 영향에 관한 연구)

  • Lee, Do-Bum;Kim, Hyo-Rak;Choi, Il-Ho
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2003.11a
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    • pp.1-4
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    • 2003
  • Recently, a structure has been larger and higher under the improvement of construction technique. So, a concrete constructions that a mat foundation thickness of structure is over 80cm have been many. Also, because of the reason high strength concrete, the matter of thermal crack have become an important task to be solved absolutely. In a cause a thermal crack occurrence, there used, mixture of concrete, construction and so forth. In this study, we executed temperature and stress analysis of mat foundation to know the effect the construction condition a thermal crack of mat foundation. And we evaluated quantitatively about the occurrence possibility of thermal crack using the hydration heat analysis program. By using of this analysis technique, will can control skilfully the quality of a mat foundation in advance.

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An Improvement on Estimation for Causal Models of Categorical Variables of Abilities and Task Performance

  • Kim, Sung-Ho
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.65-86
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    • 2000
  • The estimates from an EM when it is applied to a large causal model of 10 or more categorical variables are often subject to the initial values for the estimates. This phenomenon becomes more serious as the model structure becomes more serious as the model structure becomes more complicated involving more variables. In this regard Wu(1983) recommends among others that EMs are implemented several times with different sets of initial values to obtain more appropriate estimates. in this paper a new approach for initial values is proposed. The main idea is that we use initials that are calibrated to data. A simulation result strongly indicates that the calibrated initials give rise to the estimates that are far closer to the true values than the initials that are not calibrated.

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Reconstruction of Neural Circuits Using Serial Block-Face Scanning Electron Microscopy

  • Kim, Gyu Hyun;Lee, Sang-Hoon;Lee, Kea Joo
    • Applied Microscopy
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    • v.46 no.2
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    • pp.100-104
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    • 2016
  • Electron microscopy is currently the only available technique with a spatial resolution sufficient to identify fine neuronal processes and synaptic structures in densely packed neuropil. For large-scale volume reconstruction of neuronal connectivity, serial block-face scanning electron microscopy allows us to acquire thousands of serial images in an automated fashion and reconstruct neural circuits faster by reducing the alignment task. Here we introduce the whole reconstruction procedure of synaptic network in the rat hippocampal CA1 area and discuss technical issues to be resolved for improving image quality and segmentation. Compared to the serial section transmission electron microscopy, serial block-face scanning electron microscopy produced much reliable three-dimensional data sets and accelerated reconstruction by reducing the need of alignment and distortion adjustment. This approach will generate invaluable information on organizational features of our connectomes as well as diverse neurological disorders caused by synaptic impairments.

Distributed and Weighted Clustering based on d-Hop Dominating Set for Vehicular Networks

  • Shi, Yan;Xu, Xiang;Lu, Changkai;Chen, Shanzhi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1661-1678
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    • 2016
  • Clustering is one of the key technologies in vehicular networks. Constructing and maintaining stable clusters is a challenging task in high mobility environments. DWCM (Distributed and Weighted Clustering based on Mobility Metrics) is proposed in this paper based on the d-hop dominating set of the network. Each vehicle is assigned a priority that describes the cluster relationship. The cluster structure is determined according to the d-hop dominating set, where the vehicles in the d-hop dominating set act as the cluster head nodes. In addition, cluster maintenance handles the cluster structure changes caused by node mobility. The rationality of the proposed algorithm is proven. Simulation results in the NS-2 and VanetMobiSim integrated environment demonstrate the performance advantages.

A Study on the Effect of the Construction Conditions on a Thermal Crack of Mat Foundation (매트기초의 온도균열에 미치는 시공조건의 영향에 관한 연구)

  • 이도범;김효락;최일호
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2003.05a
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    • pp.1-4
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    • 2003
  • Recently, a structure has been larger and higher under the improvement of construction technique. So, a mass concrete constructions that a mat foundation thickness of structure is over 80cm have been many. Also, because of the reason of high strength of concrete, the matter of thermal crack have become an important task to be solved absolutely. tn a cause of a thermal crack occurrence, there are material used, mixture of concrete, construction condition and so forth. In this study, we executed temperature and stress analysis of mat foundation to know the effect of the construction condition on a thermal crack of mat foundation. And we evaluated quantitatively about the occurrence possibility of thermal crack using the hydration heat analysis program. By using of this analysis technique, we will can control skilfully the quality of a mat foundation in advance.

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GENIE : A learning intelligent system engine based on neural adaptation and genetic search (GENIE : 신경망 적응과 유전자 탐색 기반의 학습형 지능 시스템 엔진)

  • 장병탁
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1996.10a
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    • pp.27-34
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    • 1996
  • GENIE is a learning-based engine for building intelligent systems. Learning in GENIE proceeds by incrementally modeling its human or technical environment using a neural network and a genetic algorithm. The neural network is used to represent the knowledge for solving a given task and has the ability to grow its structure. The genetic algorithm provides the neural network with training examples by actively exploring the example space of the problem. Integrated into the training examples by actively exploring the example space of the problem. Integrated into the GENIE system architecture, the genetic algorithm and the neural network build a virtually self-teaching autonomous learning system. This paper describes the structure of GENIE and its learning components. The performance is demonstrated on a robot learning problem. We also discuss the lessons learned from experiments with GENIE and point out further possibilities of effectively hybridizing genetic algorithms with neural networks and other softcomputing techniques.

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PCA vs. ICA for Face Recognition

  • Lee, Oyoung;Park, Hyeyoung;Park, Seung-Jin
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.873-876
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    • 2000
  • The information-theoretic approach to face recognition is based on the compact coding where face images are decomposed into a small set of basis images. Most popular method for the compact coding may be the principal component analysis (PCA) which eigenface methods are based on. PCA based methods exploit only second-order statistical structure of the data, so higher- order statistical dependencies among pixels are not considered. Independent component analysis (ICA) is a signal processing technique whose goal is to express a set of random variables as linear combinations of statistically independent component variables. ICA exploits high-order statistical structure of the data that contains important information. In this paper we employ the ICA for the efficient feature extraction from face images and show that ICA outperforms the PCA in the task of face recognition. Experimental results using a simple nearest classifier and multi layer perceptron (MLP) are presented to illustrate the performance of the proposed method.

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Effective Techniques for Diagnosis and Test of Hard-to-Detect Faults in Analog Circuits (아날로그 회로의 난검출 고장을 위한 효과적인 진단 및 테스트 기법)

  • Lee, Jae-Min
    • IEMEK Journal of Embedded Systems and Applications
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    • v.4 no.1
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    • pp.23-28
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    • 2009
  • Testing of analog(and mixed-signal) circuits has been a difficult task for test engineers and effective test techniques to solve these problems are required. This paper develops a new technique which increases fault detection and diagnosis rates for analog circuits by using extended MTSS (Modified Time Slot Specification) technique based on MTSS proposed by the author. High performance current sensors with digital outputs are used as core components for these techniques. A fault diagnosis structure with minimal hardware overhead in ATE is also described.

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A study of the Snapping investigations of Seoul Southwest Baseball Dome (서울 서남권 돔 야구장의 Snapping 검토에 관한 연구)

  • Kim, Seung-Deog;Kim, Nam-Seok
    • Journal of Korean Association for Spatial Structures
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    • v.10 no.4
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    • pp.133-140
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    • 2010
  • This paper studies on the instability behaviour of the Seoul southwest baseball dome. The nonlinear Snapping phenomenon of the structure is investigated about the load mode by the design load of analysis structure and these combined loads. The initial imperfection obtains the buckling mode through the eigenvalue analysis of the tangential stiffness matrix and uses this for the nonlinear analysis. However, the buckling of members or the local buckling, and etc don't consider in the research range of this research task. Also it is limited the overall buckling phenomenon.

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Knowledge-Based Dynamic Structuring of Process Control Systems

  • de Silba, Clarence W.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1137-1140
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    • 1993
  • A dynamic-structure system is one that has the flexibility to change the system configuration automatically so as to operate in an optimal manner. A conceptural model for a dynamic-structure system is presented in this paper. In this model, the interchangeable components of the overall system are grouped together. Their activity levels are evaluated by an intelligent preprocessor that is associated with the group. A knowledge-based task distribution system evaluates the activity levels and makes decisions as to how the components operating below capacity should be shared with workcells that have similar components that are overloaded. Associated decision making can be effected through fuzzy logic and particularly the compositional rule of inference. A simulation example is given to illustrate the application of dynamic structuring.

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