• Smart Structures and Systems
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• v.29 no.5
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• pp.747-755
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• 2022

Hierarchical structure parameters, proposed in She-Leveque model, are investigated for velocity components obtained from different flow types over a large range of Reynolds numbers 255 < Re_𝜆 < 720. The values of intermittency parameter 𝛽, with respect to a fixed velocity component, are observed nearly same for all four types of turbulence. The parameter 𝛾, for streamwise velocity components is nearly the same but significantly different for vertical components in different flows. It is also observed that for both parameters, an obvious relation between the longitudinal and transverse components 𝛽_T < 𝛽_L (and 𝛾_T < 𝛾_L) always holds. However, the difference between 𝛽_L and 𝛽_T is found very small in all types of turbulent flows, we studied here. It is evidenced that at low Reynolds numbers, the deviations from K41 scaling are mainly due to the most intense structures and slightly because of more heterogeneous hierarchy of fluctuation structures. However, at higher Reynolds numbers the deviations seem as a consequence of the most intense structures only. Over all, the study suggests that the hierarchy parameter 𝛽 may be consider as a universal constant.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.171-181
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• 2012

In the new video coding standard, called high efficiency video coding (HEVC), the coding unit (CU) is adopted as a basic unit of a coded block structure. Therefore, the rate control (RC) methods of H.264/AVC, whose basic unit is a macroblock, cannot be applied directly to HEVC. This paper proposes the largest CU (LCU) level RC method for hierarchical video coding in a HEVC. In the proposed method, the effective bit allocation is performed first based on the hierarchical structure, and the quantization parameters (QP) are then determined using the Cauchy density based rate-quantization (RQ) model. A novel method based on the linear rate model is introduced to estimate the parameters of the Cauchy density based RQ model precisely. The experimental results show that the proposed RC method not only controls the bitrate accurately, but also generates a constant number of bits per second with less degradation of the decoded picture quality than with the fixed QP coding and latest RC method for HEVC.

• Journal of the Korean Statistical Society
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• v.30 no.2
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• pp.179-192
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• 2001

When a statistical model has a hierarchical structure such as multilayer perceptrons in neural networks or Gaussian mixture density representation, the model includes distribution with unidentifiable parameters when the structure becomes redundant. Since the exact structure is unknown, we need to carry out statistical estimation or learning of parameters in such a model. From the geometrical point of view, distributions specified by unidentifiable parameters become a singular point in the parameter space. The problem has been remarked in many statistical models, and strange behaviors of the likelihood ratio statistics, when the null hypothesis is at a singular point, have been analyzed so far. The present paper studies asymptotic behaviors of the maximum likelihood estimator and the Bayesian predictive estimator, by using a simple cone model, and show that they are completely different from regular statistical models where the Cramer-Rao paradigm holds. At singularities, the Fisher information metric degenerates, implying that the cramer-Rao paradigm does no more hold, and that he classical model selection theory such as AIC and MDL cannot be applied. This paper is a first step to establish a new theory for analyzing the accuracy of estimation or learning at around singularities.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.403.2-403.2
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• 2016

Porous materials play a significant role in energy storage and conversion applications such as catalyst support for polymer electrolyte membrane fuel cell. In particular, hierarchical porous materials with both micropores (poresize, ${\delta}$ < 2 nm) and regularly arranged mesopores (2 nm < ${\delta}$ < 50 nm) are known to greatly enhance the efficiency of catalytic reactions by providing enormous surface area as well as fast mass transport channels for both reactants and products from/to active sites. Although it is generally agreed that the microscopic structure of the porous materials directly affects the performance of these catalytic reactions, neither detailed mechanisms nor fundamental understanding are available at hand. In this study, we propose an atomistic model of hierarchical nanostructured porous carbons (HNPCs) in molecular dynamics simulations. By performing a systematic study, we found that structural features of the HNPC can be independently altered by tuning specific synthesis parameters, while remaining other structures unchanged. In addition, we show some structure-property relations including mechanical and gas transport properties.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.3
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• pp.163-175
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• 1996

This paper invetigates estimation methods of mapping parameters in object-oriented coding. In this paper, we propose a fast parameter estimation method with its performance similar to that of the conventional methods. We employ hierarchical structure in difference images to redcue the computational complexity and also combine conventional six- and eight-mapping parameter estimation methods to compensate for the performance degradation caused by employment of hierarchical structure. Computer simulation shows that the proposed mehtod gives results similar to conventional methods with greatly reduced computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1614-1632
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• 2017

Bag of visual words is a popular model in human action recognition, but usually suffers from loss of spatial and temporal configuration information of local features, and large quantization error in its feature coding procedure. In this paper, to overcome the two deficiencies, we combine sparse coding with spatio-temporal pyramid for human action recognition, and regard this method as the baseline. More importantly, which is also the focus of this paper, we find that there is a hierarchical structure in feature vector constructed by the baseline method. To exploit the hierarchical structure information for better recognition accuracy, we propose a tree regularized classifier to convey the hierarchical structure information. The main contributions of this paper can be summarized as: first, we introduce a tree regularized classifier to encode the hierarchical structure information in feature vector for human action recognition. Second, we present an optimization algorithm to learn the parameters of the proposed classifier. Third, the performance of the proposed classifier is evaluated on YouTube, Hollywood2, and UCF50 datasets, the experimental results show that the proposed tree regularized classifier obtains better performance than SVM and other popular classifiers, and achieves promising results on the three datasets.

• Korean Journal of Materials Research
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• v.23 no.11
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• pp.655-660
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• 2013

Photoelectrochemical cells have been used in photolysis of water to generate hydrogen as a clean energy source. A high efficiency electrode for photoelectrochemical cell systems was realized using a ZnO hierarchical nanostructure. A ZnO nanofiber mat structure was fabricated by electrospinning of Zn solution on the substrate, followed by oxidation; on this substrate, hydrothermal synthesis of ZnO nanorods on the ZnO nanofibers was carried out to form a ZnO hierarchical structure. The thickness of the nanofiber mat and the thermal annealing temperature were determined as the parameters for optimization. The morphology of the structures was examined by field-emission scanning electron microscopy, transmission electron microscopy, and X-ray diffraction. The performance of the ZnO nanofiber mat and the potential of the ZnO hierarchical structures as photoelectrochemical cell electrodes were evaluated by measurement of the photoelectron conversion efficiencies under UV light. The highest photoconversion efficiency observed was 63 % with a ZnO hierarchical structure annealed at $400^{\circ}C$ in air. The morphology and the crystalline quality of the electrode materials greatly influenced the electrode performance. Therefore, the combination of the two fabrication methods, electrospinning and hydrothermal synthesis, was successfully applied to fabricate a high performance photoelectrochemical cell electrode.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.405-410
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• 2002

In this paper, fuzzy system modeling using new hierarchical structure is suggested for the complex and uncertain system. The proposed modeling technique Is to decompose the fuzzy rule base structure into the above-rule base and the sub-rule base. By applying hierarchical fuzzy rules, they can be used efficiently and logically. Also, hieratical fuzzy rules can improve the accuracy and the transparency of structure in the fuzzy system. The genetic algorithm is applied for optimization of the parameters and the structure of the fuzzy rules. To show the effectiveness of the proposed method, fuzzy modeling of the complex nonlinear system is provided.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.453-458
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• 1998

In this paper, a new approach to modeling of nonlinear systems using fuzzy theory is presented. So as to handle a variety of nonlinearity and reflect the degree of confidence in the informations about system, we combine multiple model method with hierarchical prioritized structure. The mountain clustering technique is used in partition of system, and TSK rule structure is adopted to form the fuzzy rules. Back propagation algorithm is used for learning parameters in the rules. Computer simulations are performed to verify the effectiveness of the proposed method. It is useful for the treatment fo the nonlinear system of which the quantitative math-approach is difficult.

• Advances in concrete construction
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• v.11 no.1
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• pp.1-9
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• 2021

This article discusses the issue of optimizing controller design issues, in which the artificial intelligence (AI) evolutionary bat (EB) optimization algorithm is combined with the fuzzy controller in the practical application of the building. The controller of the system design includes different sub-parts such as system initial condition parameters, EB optimal algorithm, fuzzy controller, stability analysis and sensor actuator. The advantage of the design is that for continuous systems with polytypic uncertainties, the integrated H2/H∞ robust output strategy with modified criterion is derived by asymptotically adjusting design parameters. Numerical verification of the time domain and the frequency domain shows that the novel system design provides precise prediction and control of the structural displacement response, which is necessary for the active control structure in the fuzzy model. Due to genetic algorithm (GA), we use a hierarchical conditions of the Hurwitz matrix test technique and the limits of average performance, Hierarchical Fitness Function Structure (HFFS). The dynamic fuzzy controller proposed in this paper is used to find the optimal control force required for active nonlinear control of building structures. This method has achieved successful results in closed system design from the example.