• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Journal of Welding and Joining
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• v.16 no.6
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• pp.86-96
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• 1998

This study proposes the analysis method of time series ultrasonic signal using the chaotic feature extraction for degradation extent evaluation. Features extracted from time series data using the chaotic time series signal analyze quantitatively degradation extent. For this purpose, analysis objective in this study is fractal dimension, lyapunov exponent, strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical system. In experiment, fractal correlation) dimensions, lyapunov exponents, energy variation showed values of 2.217∼2.411, 0.097∼ 0.146, 1.601∼1.476 voltage according to degardation extent. The proposed chaotic feature extraction in this study can enhances precision ate of degradation extent evaluation from degradation extent results of the degraded materials (SA508 CL.3)

• Korean Institute of Interior Design Journal
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• no.25
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• pp.176-183
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• 2000

The purpose of this study is to show the implications of the term "digital architecture," which are realized in the current architecture. To do this, I first observe its theoretical background and then analyze the works of Marcos Novak, Kas Oosterhuis, and Lars Spuybroek, all of whom are called the typical digital architects. In particular, this study tries to show that the digital architects are introducing the non-Euclidean multi-dimensions and the cyberspace and applying the notions of liquid architecture, transarchitecture, body-building, and body-building, and body-motorized system into their works. Finally, I conclude that the digital architecture anticipates the direction of the future architecture, in which the virtual world is merged with the real world, the digital space is realized in the real space, and the human is completely harmonized with nature.th nature.

• Proceedings of the KSPS conference
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• 1996.10a
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• pp.399-403
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• 1996

This paper addresses issues of perceptual constancy in speech perception through the use of a spatial metaphor for speech sound identity as opposed to a more conventional characterisation with multiple interacting acoustic cues. This spatial representation leads to a correlation between phonetic, acoustic and auditory analyses of speech sounds which can serve as the basis for a model of speech perception based on the general auditory characteristics of sounds. The correlations between the phonetic, perceptual and auditory spaces of the set of English voiceless fricatives /f $\theta$ s $\int$ h / are investigated. The results show that the perception of fricative segments may be explained in terms of 2-dimensional auditory space in which each segment occupies a region. The dimensions of the space were found to be the frequency of the main spectral peak and the 'peakiness' of spectra. These results support the view that perception of a segment is based on its occupancy of a multi-dimensional parameter space. In this way, final perceptual decisions on segments can be postponed until higher level constraints can also be met.

• Journal of Families and Better Life
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• v.21 no.3
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• pp.1-13
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• 2003

The purpose of this study is to understand the importance of exterior environments and to identify the design guidelines for the therapeutic garden for cognitively impaired seniors with Alzheimer's disease and related dementias. The data was collected from 4 Adult Day Care Centers, 2 Nursing Homes, & 1 Assisted living in the U.S.A. from 2001 to 2002 by interview and the floor plan about the outdoor space. Although some may believe that patients with Alzheimer's disease and related disorders are unresponsive to environment, evidence shows that environments especially designed for cognitively impaired seniors can maintain or increase their level of functioning. The use of specially designed exterior environments nay have in reducing incidents of aggressive behavior, and contributing significantly to a wanderer management program. The checklist includes 6 dimensions： safety environment, various sensual stimulations, social interactions, wandering, privacy, and support orientation and reality. The results indicated that the exterior environment have to support wandering behavior, orientation and reality.

• Korean Journal of Computational Design and Engineering
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• v.14 no.4
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• pp.217-224
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• 2009

Most divide-and-conquer implementations for Delaunay triangulation utilize quad-edge or winged-edge data structure since triangles are frequently deleted and created during the merge process. How-ever, the proposed divide-and-conquer algorithm utilizes the array based data structure that is much simpler than the quad-edge data structure and requires less memory allocation. The proposed algorithm has two important features. Firstly, the information of space partitioning is represented as a permutation vector sequence in a vertices array, thus no additional data is required for the space partitioning. The permutation vector represents adaptively divided regions in two dimensions. The two-dimensional partitioning of the space is more efficient than one-dimensional partitioning in the merge process. Secondly, there is no deletion of edge in merge process and thus no bookkeeping of complex intermediate state for topology change is necessary. The algorithm is described in a compact manner with the proposed data structures and operators so that it can be easily implemented with computational efficiency.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.3
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• pp.159-164
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• 2000

This paper treats the optimization of rotor construction in the permanent magnet synchronous motor (PMSM) for electric vehicle (EV). While the field system of PMSM has generally one magnet per pole, we replace the magnet into plural sub-magnets. The dimensions of each sub-magnet are determined by the concept of pulse width modulation (PWM). By adopting the proposed rotor construction, we can not only reduce the space harmonics of the air-gap field but also provide space for rotor bars (i.e., damper windings) around the direct-axis. From the investigation by hybrid EE-BE (coupled finite element and boundary element) method coupled with both electric circuit and motion equation, we verify that the construction is effective for practical use.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.11
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• pp.1398-1406
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• 2004

The nonlinear signals from an impedance meter for the area average void fraction in two-phase flow have been analyzed to construct a phase space trajectory. The pseudo phase space was constructed with the time delay and proper dimensions. The time delay and the embedding dimension were chosen by the average mutual information and by the false nearest neighborhood, respectively. The attractor-density-map of projected states was used to produce the two dimensional probability distribution functions (2D-PDF). Since the developed 2D-PDF showed clear distinction of the flow patterns, the flow regime identification was made with three rules and with the 2D-PDF. Also, the transition criteria of Mishima-Ishii agree well with the present results.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.40.2-40.2
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• 2018

NGC 5024 and NGC 5053 are among the most metal-poor globular clusters in the Milky Way. Both globular clusters are considered to be accreted from dwarf galaxies (like Sagittarius dwarf galaxy or Magellanic clouds), and common stellar envelope and tidal tails between globular clusters are also detected. We present a search for extra-tidal cluster member candidates around these globular clusters from APOGEE survey data. Using 20 chemical elements (e.g., Fe, C, Mg, Al) and radial velocities, t-distributed stochastic neighbour embedding (t-SNE), which identifies an optimal mapping of a high-dimensional space into fewer dimensions, was explored, and we find that globular cluster stars are well separated from the field stars in 2-dimensional map from t-SNE. We also find that some stars selected in t-SNE map are placed outside of the tidal radius of the clusters. The proper motion of stars outside tidal radius is also comparable to that of globular clusters, which suggest that these stars are tidally decoupled from the globular clusters. We manually measure chemical abundances for the clusters and extra-tidal stars, and discuss the association of extra-tidal stars with the clusters.

• Smart Media Journal
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• v.10 no.3
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• pp.9-22
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• 2021

Basically, machine learning models use input data to produce results. Sometimes, the input data is too complicated for the models to learn useful patterns. Therefore, feature engineering is a crucial data preprocessing step for constructing a proper feature set to improve the performance of such models. One of the most efficient methods for automating feature engineering is the autoencoder, which transforms the data from its original space into a latent space. However certain factors, including the datasets, the machine learning models, and the number of dimensions of the latent space (denoted by k), should be carefully considered when using the autoencoder. In this study, we design a framework to compare two data preprocessing approaches: with and without autoencoder and to observe the impact of these factors on autoencoder. We then conduct experiments using autoencoders with classifiers on popular datasets. The empirical results provide a perspective regarding the best suited autoencoder for these factors.