• Journal of Korea Multimedia Society
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• v.2 no.1
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• pp.38-46
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• 1999

In this paper, the fractal image compression using the minimizing method of domain region is proposed. It is minimize to domain regions in the process of decoding. Since the conventional fractal decoding applies to IFS(iterative function system) for the total range blocks of the decoded image, its computational complexity is a vast amount. In order to improve this using the number of the referenced times to the domain blocks for the each range blocks, a classification method which divides necessary and unnecessary regions for IFS is suggested. If necessary regions for IFS are reduced, the computational complexity is reduced. The proposed method is to define the minimum domain region that a necessary region for IFS is minimized in the encoding algorithms. That is, a searched region of the domain is limited to the range regions that is similar with the domain regions. So, the domain region is more overlapped. Therefore, there is not influence on image quality or PSNR(peak signal-to-noise ratio). And it can be a fast decoding by reduce the computational complexity for IFS in fractal image decoding.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.2
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• pp.232-238
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• 2013

The vehicle system is a multi-domain system that requires many branches of science and engineering. Therefore the development of the vehicle system requires the use of design methodologies that utilize simulations, which have grown increasingly sophisticated in recent years. Our research group proposed a simulation modeling method based on the VHDL-AMS language. This paper describes how VHDL-AMS is used to model of vehicle fuel consumption simulation. The fuel consumption is shown using proposed simulation model on the Japanese 10-15 mode. We examine the influence of the vehicle system with electrical load and hill climb resistance in the vehicle running resistance.

• Smart Structures and Systems
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• v.16 no.3
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• pp.401-414
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• 2015

A developed hybrid method for crack identification of beams is presented. Based on the Euler-Bernouli beam theory and concepts of fracture mechanics, governing equation of the cracked beams is reformulated. Finite element (FE) method as a powerful numerical tool is used to discritize the equation in space domain. After transferring the equations from time domain to frequency domain, frequencies and mode shapes of the beam are obtained. Efficiency of the governed equation for free vibration analysis of the beams is shown by comparing the results with those available in literature and via ANSYS software. The used equation yields to move the influence of cracks from the stiffness matrix to the mass matrix. For crack identification measured data are produced by applying random error to the calculated frequencies and mode shapes. An objective function is prepared as root mean square error between measured and calculated data. To minimize the function, hybrid genetic algorithms (GAs) and particle swarm optimization (PSO) technique is introduced. Efficiency, Robustness, applicability and usefulness of the mixed optimization numerical tool in conjunction with the finite element method for identification of cracks locations and depths are shown via solving different examples.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.495-500
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• 2007

A Meshfree is a method used to establish algebraic equations of system for the whole problem domain without the use of a predefined mesh for the domain discretization. A point interpolation method is based on combining radial and polynomial basis functions. Involvement of radial basis functions overcomes possible singularity. Furthermore, the interpolation function passes through all scattered points in an influence domain and thus shape functions are of delta function property. This makes the implementation of essential boundary conditions much easier than the meshfree methods based on the moving least-squares approximation. This study aims to investigate a stress analysis of structural element between a meshfree method and the finite element method. Examples on cantilever type plate and stress concentration problems show that the accuracy and convergence rate of the meshfree methods are high.

• Smart Structures and Systems
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• v.31 no.2
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• pp.171-181
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• 2023

Using the most up-to-date system identification methods in both time and frequency domains, the dynamic monitoring data from the reinforced concrete Egebaekvej Bridge near Holte, Denmark, is examined in this investigation. The bridge was erected in the 1960s and was still standing during test campaign before demolishing. The ARTeMIS Modal was adopted to derive the modal parameters from ambient vibration data. Several Operational Modal Analysis (OMA) approaches were applied, including Enhanced Frequency Domain Decomposition (EFDD), Curve-fit Frequency Domain Decomposition (CFDD), and Frequency Domain Decomposition (FDD). Afterward, Principal Component (SSI-PC), Unweighted Principal Component (SSI-UPC) Stochastic Subspace Identification methods were utilized. Danish engineering consulting company, COWI with the allowance of the bridge contractor BARSLUND, allow the researcher for this experimental test to demonstrate the impact of OMA applications.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.209-219
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• 2022

Purpose : The purpose of this study was two-fold: to investigate the effects of uncertainty and depression on the quality of life (QoL) of elderly people with chronic diseases and to provide basic data on the physical, emotional, and psychological factors affecting their QoL in the field of physical therapy. Methods : A questionnaire covering uncertainty, depression, and QoL was distributed among 320 elderly people. Pearson's correlation analysis was performed to examine the correlation between uncertainty (ambiguity, complexity, inconsistency, and unpredictability), depression, and QoL (physical, psychological, social, and living environment domains) of the respondents; furthermore, multiple regression analysis was performed to identify the factors affecting the QoL of the respondents with a chronic disease. Results : The sub-factors of uncertainty and QoL-"complexity and social domain" (r=-.295, p<.001), "complexity and living environment domain" (r=-.302, p<.001), and "inconsistency and living environment domain" (r=-.360, p<.001)-showed a negative (-) correlation, as did depression and the sub-factors of QoL-"depression and physical domain" (r=-.782, p<.001), "depression and psychological domain" (r=-.876, p<.001), "depression and social domain" (r=-.668, p<.001), and "depression and living environment domain" (r=-.731, p<.001). The factors affecting QoL were complexity (𝛽=-.122, p<.001), inconsistency (𝛽=-.102, p=.002), unpredictability (𝛽=.112, p<.001), and depression (𝛽=-.850, p<.001). The relative influence of the independent variables was in the order of depression, complexity, unpredictability, and inconsistency, and the explanatory power was 77.1 % (F=215.853, p<.001). Conclusion : It is important to help the elderly with chronic diseases reduce the negative impact on their quality of life by helping them gain support from their families and medical professionals and by increasing their understanding through communication so that they can transition from negative emotions to positive emotions of opportunity.

• ETRI Journal
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• v.46 no.1
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• pp.59-70
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• 2024

We introduce a high-performance named entity recognition (NER) model for written and spoken language. To overcome challenges related to labeled data scarcity and domain shifts, we use transfer learning to leverage our previously developed KorBERT as the base model. We also adopt a meta-pseudo-label method using a teacher/student framework with labeled and unlabeled data. Our model presents two modifications. First, the student model is updated with an average loss from both human- and pseudo-labeled data. Second, the influence of noisy pseudo-labeled data is mitigated by considering feedback scores and updating the teacher model only when below a threshold (0.0005). We achieve the target NER performance in the spoken language domain and improve that in the written language domain by proposing a straightforward rollback method that reverts to the best model based on scarce human-labeled data. Further improvement is achieved by adjusting the label vector weights in the named entity dictionary.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.13-19
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• 2001

The conventional fractal decoding was required a vast amount computational complexity, since every range blocks was implemented to IFS(iterated function system). In order to improve this, it has been suggested that each range block was classified to iterated and non-iterated regions. Non-iterated regions is called data dependency region, and if data dependency region extended, IFS regions are contractive. In this paper, a searched region of the domain is limited to the range regions that is similar with the domain blocks, and the domain region is more overlapped. As a result, data dependency region has maximum region, that is IFS regions can be minimum region. The minimizing method of domain region is defined to minimum domain(MD) which is minimum IFS region. Using the minimizing method of domain region, there is not influence PSNR(peak signal-to-noise ratio). And it can be performed a fast decoding by reducing the computational complexity for IFS in fractal image decoding.

• Convergence Security Journal
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• v.22 no.4
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• pp.169-178
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• 2022

In general, organizations operating multi-domain networks find it difficult to represent and manage multiple domain net works on a single screen space. Instead, most of them are managed with multiple screens visualizing network topology by domain or partitioning one screen area into multiple domains. We propose an efficient method to visualize the topology using only minimal connection information between domain-agnostic nodes in this work. This method visualizes the topology by utilizing centrality indices representing the influence of nodes in the network. Furthermore, the method dynamically segments the entire node's display area using virtual Root nodes to auto-separate domains and weights of child nodes and placing nodes in 3D space. Thus, although it is a straightforward method, the multi-domain network topology can be visualized with only minimal connection information between nodes.

• Journal of Fashion Business
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• v.6 no.2
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• pp.110-123
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• 2002

This study investigated the influence of cultural and general trend of the times on fashion trends and the hybridization of these trends. The objectives of this study were to suggest new approach method of the fashion forecasting and to find out the cultural meanings and values of fashion. Key words that explains fashion trend from spring/summer of 1995 to fall/winter of 2002 were collected from professional fashion trend journals. These terms were analysed with domain analysis based on the semantic relationship. The frequency of their appearance in each season and the aspect of their appearance in each season were analysed. The hybrids of the fashion trends were analysed longitudinally and cross-sectionally as well by investigating the cover terms that were found as a result of domain analysis. The method used in this study can be applied to future study of fashion trend in that it offers an objective view of fashion trend and can allow researchers to study fashion trend in a concrete way.