• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.501-506
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• 2015

This study seeks to analyze ships traffic characteristics according to water time in order to provide the necessary data for efficient traffic management development. To analyze maritime traffic volume according to water time, 1 year amount of solar calendar data were converted into lunar calendar, and then applied the traditional water time system of West Sea by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. As a result, it was found herein that the number of outbound ships was larger on the $2^{nd}-3^{nd}$ water times than the $7^{th}$ water times by 23-24 %. And the number of inbound ships was higher on the $12^{th}-13^{th}$ water times than the $9^{th}$ water time by 29-33 %. The hourly variation index of inbound and outbound ships according to time, in particular, was found to change in the form of sine function model. This study is expected to serve as a necessary basic material for development of maritime traffic management according to water time.

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.25-31
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• 2009

Widely used color information recognition methods based on the RGB color model with static fuzzy inference rules have limitations due to the model itself-the detachment of human vision and applicability of limited environment. In this paper, we propose a method that is based on HSI model with new inference process that resembles human vision recognition process. Also, a user can add, delete, update the inference rules in this system. In our method, we design membership intervals with sine, cosine function in H channel and with functions in trigonometric style in S and I channel. The membership degree is computed via interval merging process. Then, the inference rules are applied to the result in order to infer the color information. Our method is proven to be more intuitive and efficient compared with RGB model in experiment.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.952-959
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• 2018

Clustering is one of the most fundamental algorithms in machine learning. The performance of clustering is affected by the distribution of data, and when there are more data or more dimensions, the performance is degraded. For this reason, we use a stacked auto encoder, one of the deep learning algorithms, to reduce the dimension of data which generate a feature vector that best represents the input data. We use k-means, which is a famous algorithm, as a clustering. Sine the feature vector which reduced dimensions are also multi dimensional, we use the Euclidean distance as well as the cosine similarity to increase the performance which calculating the similarity between the center of the cluster and the data as a vector. A deep clustering networks combining a stacked auto encoder and k-means re-trains the networks when the k-means result changes. When re-training the networks, the loss function of the stacked auto encoder and the loss function of the k-means are combined to improve the performance and the stability of the network. Experiments of benchmark image ad document dataset empirically validated the power of the proposed algorithm.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.565-572
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• 2001

Analyzing functions with small values of the product of position and frequency uncertainties have many advantages in image processing and data compression. Until now, this values has been computed based on the uncertainty principle, but the computed frequency uncertainty is not practical the human visual filters which have on-zero peak response frequencies. A new metric for the frequency uncertainty is used to calculate a deviation about the frequency which has maximum response. The joint effective widths for various functions are derived. As the result of analysis, the joint uncertainty for many functions converges to 0.5 as the joint parameter increases. Furthermore. Gabor cosine function shows an excellent performance among the mentioned functions.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.61-64
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• 1996

To improve the performance of a recognition system, namely the recognition rate, we propose a hew implementation of perceptual distance using LPC cepstrum(perceptual cepstrum, PLC). The PLC is caculated by convolution of a usual LPC cepstrum and a perceptual lifter(PL). To caculate PL, we define a new weighting function in the linear frequency domain considering the frequency scale(Bark-scale) characteristics. The PL is the inverse Fourier transform of the exponents of the weighting function. We verified our method through the speech recognition experiments. The performance of PLC was compared with that of the rasied sine liftering method.

• Advances in nano research
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• v.9 no.3
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• pp.147-156
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• 2020

This research is related to nonlinear stability analysis of advanced microbeams reinforced by Graphene Platelets (GPLs) considering generic geometrical imperfections and thermal loading effect. Uniform, linear and nonlinear distributions of GPLs in transverse direction have been considered. Imperfection sensitivity of post-bucking behaviors of the microbeam to different kinds of geometric imperfections have been examined. Geometric imperfection is first considered to be identical as the first buckling mode, then a generic function is employed to consider sine-type, local-type and global-type imperfectness. Modified couple stress theory is adopted to incorporate size-dependent behaviors of the beam at micro scale. The post-buckling problem is solved analytically to derive load-amplitude curves. It is shown that post-buckling behavior of microbeam is dependent on the type geometric imperfection and its magnitude. Also, post-buckling load can be enhanced by adding more GPLs or selecting a suitable distribution for GPLs.

• Journal of Mechanical Science and Technology
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• v.20 no.12
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• pp.2043-2051
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• 2006

This paper considered identification of vibration characteristics of flexible structure with vector channel periodic lattice filter. We present an algorithm for AR coefficients for the vector-channel lattice filters, and characteristic equation and transfer function are derived from these coefficients. Vibration lattice filter is then constructed from the vector channel lattice filter, and performance of this vibration filter is tested with a test signal which is a combination of many sine waves to compare the performance of scalar and vector channel lattice. Also it is applied to the cantilever data to identify properties of the system, such as natural frequencies and damping ratios, to show its performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.718-721
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• 2007

The ionic-polymer-metal-composite actuators have the best merit for bio-mimetic locomotion because of their large bending performance. Especially, they have the advantage for mimicking a fish-like motion because IPMCs are useful to be actuated in water. So we have developed IPMC actuators with multiple electrodes for realization of biomimetic motion. This actuator is fabricated by combining electroless plating and electroplating techniques capable of patterning precisely and controlling a thickness of Pt electrode layer. The FRF analysis was conducted by a mechanical shaker and direct electrical excitation which is based on sweep sine wave function. From this result, the proper young‘s modulus of Platinum was investigated and applied on expecting the vibration characteristics of patterned IPMC actuator. The calculated maximum displacement of the patterned IPMC was 2.32mm under an applied 4mN/mm. The natural frequency was increased however displacement was decreased in according to increase a thickness of Pt.

• Transactions of Materials Processing
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• v.9 no.3
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• pp.304-312
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• 2000

An inverse finite element approach is employed to efficiently design the optimum blank shape and intermediate shapes from the desired final shape in multi-stage elliptic cup drawing processes. The multi-stage deep-drawing process is difficult to design with the conventional finite element analysis since the process is very complicate with the conventional finite element analysis since the process is very complicated with intermediate shapes and the numerical analysis undergoes the convergence problem even with tremendous computing time. The elliptic cup drawing process needs much effort to design sine it requires full three-dimensional analysis. The inverse analysis is able to omit all complicated and tedious analysis procedures for the optimum process design. In this paper, the finite element inverse analysis provides the thickness strain distribution of each intermediate shape through the multi-stage analysis. The multi-stage analysis deals with the convergence among intermediate shapes and the corresponding sliding constraint surfaces that are described by the analytic function of merged-arc type surfaces.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.950-955
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• 2001

For the development of an ultra-precision CNC polishing system including on-machine measurement system, we study a corrective polishing algorithm. We analyze and test the unit removal profiles for a ball type polishing tool. Using these results we calculate dwell time distributions and residual errors for a target removal shape. We use the polishing simulation method and feed rate calculation method for the dwell time calculation. We test corrective polishing algorithm with an optical glass. The target removal shape is a sine wave that has amplitude 0.3 micro meters. We find this polishing process has a machining resolution of nanometer order and is effective for sub-micrometer order machining. This result will be used for the software development of the CNC polishing system.