• Honam Mathematical Journal
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• v.26 no.1
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• pp.87-103
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• 2004

A practical estimation method for groundwater contaminant concentration is introduced. Using geostatistical techniques and symmetry, experimental variograms show significant improved correlation compared with those from conventional techniques. Numrical experiments are performed using a field data set.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.209-240
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• 2001

Computer-based simulation and analysis is used extensively in engineering for a variety of tasks. Despite the steady and continuing growth of computing power and speed, the computational cost of complex high-fidelity engineering analyses and simulations limit their use in important areas like design optimization and reliability analysis. Statistical approximation techniques such as design of experiments and response surface methodology are becoming widely used in engineering to minimize the computational expense of running such computer analyses and circumvent many of these limitations. In this paper, we compare and contrast five experimental design types and four approximation model types in terms of their capability to generate accurate approximations for two engineering applications with typical engineering behaviors and a wide range of nonlinearity. The first example involves the analysis of a two-member frame that has three input variables and three responses of interest. The second example simulates the roll-over potential of a semi-tractor-trailer for different combinations of input variables and braking and steering levels. Detailed error analysis reveals that uniform designs provide good sampling for generating accurate approximations using different sample sizes while kriging models provide accurate approximations that are robust for use with a variety of experimental designs and sample sizes.

• Journal of Navigation and Port Research
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• v.32 no.9
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• pp.723-727
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• 2008

Sensing performances of evanescent field absorption (EFA) hetero-core fiber sensor has been presented based on EFA by changing the length and the core diameter of the single mode fiber. Experimental results have demonstrated a good feature in their relationship between the length and the core diameter of the single mode fiber. The sensor consists of 2 fiber optics which have the same cladding diameter of $125{\mu}m$ However one fiber optic used is single mode and has varying core diameter ranging from 3.3 to $5.6{\mu}m$. The other fiber is multimode type and has a thicker fixed core diameter of $62.5{\mu}m$. The 2 fiber optics are thermally spliced together. Experiments conducted to measure the resonance wavelength were carried out over a range of refractive index, to find the optimum sensing length Experiments show that core diameter of the single mode fiber and sensing length offects the linearity and sensitivity.

• Journal of the Ergonomics Society of Korea
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• v.17 no.3
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• pp.103-115
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• 1998

Although applying experimental data of ergonomics to a industrial design seems to be a difficult task, making every effort to the application of ergonomics to the industrial design process is still attempted. Sometimes, it is easy to use experimental data, yet, it is very hard to take that data and implement it into the design process. The essence of industrial design depends on human sensitivity, thus we can call the sense of design the software and the experimental data of ergonomics the hardware. The harmony of this hard & software is very important for the process and development of design. New products always demand new forms. Accordingly, it is easy for designers to neglect applying experiments and ergonomic data to products for public users. However, the study of ergonomics data continuously helps to be applied to more products year after year. This paper explores, how to improve the design of the tilting angle related to the shape of knobs on a front panel of a computer monitor. The results of experiments show that a tilted angle is more efficient than that of straight-type when placed on the front panel of a computer monitor with a power button.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.864-870
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• 2003

In recent engineering, the designer has become more and more dependent on the computer simulations such as FEM(Finite Element Method) and BEM(Boundary Element Method). In order to optimize such implicit models more efficiently and reliably, the meta -modeling technique has been developed for solving such a complex problems combined with the DACE(Design and Analysis of Computer Experiments). It is widely used for exploring the engineer's design space and for building approximation models in order to facilitate an effective solution of multi-objective and multi-disciplinary optimization problems. Optimization of a train suspension is performed according to the minimization of forty -six responses that represent ten ride comforts, twelve derailment quotients, twelve unloading ratios, and twelve stabilities by using the Kriging model of a train suspension. After each Kriging model is constructed, multi -objective optimal solutions are achieved by using a nonlinear programming method called SQP(Sequential Quadratic Programming).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.62-69
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• 2014

In this paper, WBAN(Wireless Body Area Network) On-body system using the surface-oriented antenna about the impact of human internal organs were analyzed through experiments. The received signal strength is measured for effect of human using the human model and the phantom of torso. Experiments are performed in anechoic chamber without moving and measured by Vector Network Analyzer. This paper confirms the effect of human body by comparing the human model and the phantom of torso. And also know the human internal organs effect on the antennas loss of received signal strength by measured data.

• Smart Structures and Systems
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• v.16 no.3
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• pp.521-535
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• 2015

Vibration-based monitoring is one approach used to perform structural condition assessment. By measuring structural response, such as displacement, dynamic characteristics of a structure may be estimated. Often, the primary dynamic responses in civil structures are below 5 Hz, making accurate low frequency measurement critical for successful dynamic characterization. In addition, static deflection measurements are useful for structural capacity and load rating assessments. This paper presents a DC coupled continuous wave radar to accurately detect both dynamic and static displacement. This low-cost radar sensor provides displacement measurements within a compact, wireless unit appropriate for a range of structural monitoring applications. The hardware components and operating mechanism of the radar are introduced and a series of laboratory experiments are presented to assess the performance characteristics of the radar. The laboratory and field experiments investigate the effect of factors such as target distance, motion amplitude, and motion frequency on the radar's measurement accuracy. The results demonstrate that the radar is capable of both static and dynamic displacement measurements with sub-millimeter accuracy, making it a promising technology for structural health monitoring.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.389-398
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• 2012

Texture is an important visual feature for image analysis. Many approaches have been proposed to model and analyze texture features. Although these approaches significantly contribute to various image-based applications, most of these methods are sensitive to the changes in the scale and orientation of the texture pattern. Because textures vary in scale and orientations frequently, this easily leads to pattern mismatching if the features are compared to each other without considering the scale and/or orientation of textures. This paper suggests an Orientation Matching Scheme (OMS) to ease the problem of mismatching rotated patterns. In OMS, a pair of texture features will be compared to each other at various orientations to identify the best matched direction for comparison. A database including rotated texture images was generated for experiments. A synthetic retrieving experiment was conducted on the generated database to examine the performance of the proposed scheme. We also applied OMS to the similarity computation in a K-means clustering algorithm. The purpose of using K-means is to examine the scheme exhaustively in unpromising conditions, where initialized seeds are randomly selected and algorithms work heuristically. Results from both types of experiments show that the proposed OMS can help improve the performance when dealing with rotated patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.249-268
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• 2014

Relevance feedback is an effective tool to bridge the gap between superficial image contents and medically-relevant sense in content-based medical image retrieval. In this paper, we propose an interactive medical image search framework based on pairwise constraint propagation. The basic idea is to obtain pairwise constraints from user feedback and propagate them to the entire image set to reconstruct the similarity matrix, and then rank medical images on this new manifold. In contrast to most of the algorithms that only concern manifold structure, the proposed method integrates pairwise constraint information in a feedback procedure and resolves the small sample size and the asymmetrical training typically in relevance feedback. We also introduce a long-term feedback strategy for our retrieval tasks. Experiments on two medical image datasets indicate the proposed approach can significantly improve the performance of medical image retrieval. The experiments also indicate that the proposed approach outperforms previous relevance feedback models.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.305-314
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• 2017

Clustering is a method that collects data objects into groups based on their similary. Performance of the state-of-the-art clustering methods is different according to the data characteristics. There have been numerous studies that performed experiments to compare the accuracy of the state-of-the-art clustering methods by applying various kinds of datasets. A common problem of these studies is that they only consider clustering algorithms that yield the most accurate results for a particular dataset. They do not consider what factors affect the execution time of each clustering method and how they are affected. Nevertheless, execution time is an important factor in clustering performance if there is no significant difference in accuracy. In order to solve the problems of the existing research, through a series of experiments using various types of datasets, we compare the accuracy of four representative clustering methods. In addition, we perform practical clustering performance comparisons by deriving time complexity and identifying factors that influences to its performance.