• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.169-180
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• 2013

The modification of conditional Fuzzy C-Means (CFCM) with Gaussian weights (CFCM_GW) is accomplished for blind equalization of channels in this paper. The proposed CFCM_GW can deal with both of linear and nonlinear channels, because it searches for the optimal desired states of an unknown channel in a direct manner, which is not dependent on the type of channel structure. In the search procedure of CFCM_GW, the Bayesian likelihood fitness function, the Gaussian weighted partition matrix and the conditional constraint are exploited. Especially, in contrast to the common Euclidean distance in conventional Fuzzy C-Means(FCM), the Gaussian weighted partition matrix and the conditional constraint in the proposed CFCM_GW make it more robust to the heavy noise communication environment. The selected channel states by CFCM_GW are always close to the optimal set of a channel even when the additive white Gaussian noise (AWGN) is heavily corrupted. These given channel states are utilized as the input of the Bayesian equalizer to reconstruct transmitted symbols. The simulation studies demonstrate that the performance of the proposed method is relatively superior to those of the existing conventional FCM based approaches in terms of accuracy and speed.

• Smart Structures and Systems
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• v.25 no.3
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• pp.301-310
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• 2020

The laser ultrasonic technique is gaining popularity for nondestructive evaluation (NDE) applications because it is a noncontact and couplant-free method and can inspect a target from a remote distance. For the conventional laser ultrasonic techniques, a pulsed laser is often used to generate broadband ultrasonic waves in a target structure. However, for crack detection using nonlinear ultrasonic modulation, it is necessary to generate narrowband ultrasonic waves. In this study, a pulsed laser is shaped into dual-line arrays using a spatial mask and used to simultaneously excite narrowband ultrasonic waves in the target structure at two distinct frequencies. Nonlinear ultrasonic modulation will occur between the two input frequencies when they encounter a fatigue crack existing in the target structure. Then, a nonlinear damage index (DI) is defined as a function of the magnitude of the modulation components and computed over the target structure by taking advantage of laser scanning. Finally, the fatigue crack is detected and localized by visualizing the nonlinear DI over the target structure. Numerical simulations and experimental tests are performed to examine the possibility of generating narrowband ultrasonic waves using the spatial mask. The performance of the proposed fatigue crack localization technique is validated by conducting an experiment with aluminum plates containing real fatigue cracks.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.108-117
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• 2022

The recent development of information and communication technology has a great impact on the audio/video industry. In particular, IP-based AoIP transmission technology and AVB technology are making changes in the audio/video market. Video signal transmission technology has been introduced to the market through a network, but it has not replaced the video switcher function. Video signals in the conference room or classroom are still controlled by the switching device. In order to switch input/output video devices, a cable that is not limited by distance must be connected to the switcher. In addition, the control of the switching device must be performed by a person who has received professional training. In this paper, it is a technology that can be operated even by non-experts by replacing complex video cables (RGB, DVI, HDMI, DP) with LAN cables and enabling IP-based video switching and transmission (Video Mirroring over IP: VMoIP) to replace video switcher equipment. We are going to do this study, I/O videos were controlled in the form of matrix and high-definition videos were transmitted without distortion, and VMoIP is expected to become the standard for video switching systems in the future.

• Journal of Digital Convergence
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• v.17 no.5
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• pp.117-125
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• 2019

This study measured inefficiencies of Korean banks with weighted Russell directional distance function, WRDDM, for the years of 2004-2013. Checking contributions of inputs and outputs to these inefficiencies, we found that non-performing loan as undesirable output was the most influential factor. The annual average of inefficiencies of Korean banks was 0.3912, and it consisted of non-performing loan 0.1883, output factors 0.098 except non-performing loan, input factors 0.098. The annual average inefficiency went sharply up from 0.2995 to 0.4829 mainly due to the sharp increase of inefficiency of non-performing loan from 0.1088 to 0.2678 before and after 2007-2008 Global financial crisis. We empirically showed the non-performing loan needed to be considered since it was the most important factor among the influential factors of technical inefficiency such as manpower, total deposit, securities, and non-performing loan. This study had some limitation since we did not control financial environment factor in WRDDM.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• The KIPS Transactions:PartD
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• v.8D no.3
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• pp.295-304
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• 2001

The standards of a telephone Hangul keyboard should be decided in terms of objective factors : the number of strokes and fingers’moving distance. A number of designers will agree on them, because these factors can be calculated in an objective manner. So, We developed the model which can evaluate the efficiency of inputting Hangul on a telephone keyboard in terms of two factors. As compared with other models, the major features of this model are as follows : in order to evaluate the efficiency of Hangul input on a telephone keyboard, (1) this model calculated not a typing time but the number of strokes ; (2) concurrence frequency that had been counted on KOREA-1 Corpus was used directly ; (3) a total set of 67 consonants and vowels was used ; and (4) this model could evaluate a number of keyboards that use a kind of syllabic function key-the complete key, the null key and the final consonant key and also calculate a lot of keyboards that adopt no syllabic function key. However, there are many other factors to judge the efficiency of inputting Hangul on a telephone keyboard. If we want to make more accurate estimate of a telephone Hangul keyboard, we must consider both logical data and experimental data as well.

• Korean Journal of Optics and Photonics
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• v.14 no.6
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• pp.606-612
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• 2003

The self-imaging effect or lensless imaging effect of a phase line grating is theoretically analyzed by using Fresnel diffraction theory, then experimentally investigated. The self-imaging distance $z_{T,p}$, that is the imaging distance being perfectly copied from the phase distribution of the phase grating to its intensity distribution with the magnification of 1X, can be uniquely defined as the (4n-3) $z_{T,a}$/4(n=positive integers), where rte is the well-known self-imaging distance of an amplitude grating. When the coherent laser beam is illuminated at the phase grating, the self-imaged images were obtained at $z_{T,p}$= $z_{T,a}$/4 and $z_{T,p}$=5 $z_{T,a}$/4 without any optics. On the other side, the phase-reversed self-imaging was obviously observed at $z_{T,p}$ = 3 $z_{T,a}$/4. The visibility of self-imaged images of a phase line grating as a function of the number of slits of the input grating was measured by the FFT(Fast Fourier Transform) results of the self-imaging images. As a result a stationary maximum visibility of V = 0.10 can be obtained from a grating with more than 15 slit pairs.n 15 slit pairs.

• Design Convergence Study
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• v.15 no.1
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• pp.135-150
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• 2016

Due to the development of communication technology and expansion of Intelligent Transport System (ITS), the car is changing from a simple mechanical device to second living space which has comprehensive convenience function and is evolved into the platform which is playing as an interface for this role. As the interface area to provide various information to the passenger is being expanded, the research importance about smart car based user experience is rising. This study has a research objective to propose the guidelines regarding the smart car user experience elements. In order to conduct this study, smart car user experience elements were defined as function, interaction, and surface and through the discussions of UX/UI experts, 8 representative techniques, 14 representative techniques, and 8 locations of the glass windows were specified for each element. Following, the smart car users' priorities of the experience elements, which were defined through targeting 100 drivers, were analyzed in the form of questionnaire survey. The analysis showed that the users' priorities in applying the main techniques were in the order of safety, distance, and sensibility. The priorities of the production method were in the order of voice recognition, touch, gesture, physical button, and eye tracking. Furthermore, regarding the glass window locations, users prioritized the front of the driver's seat to the back. According to the demographic analysis on gender, there were no significant differences except for two functions. Therefore this showed that the guidelines of male and female can be commonly applied. Through user requirement analysis about individual elements, this study provides the guides about the requirement in each element to be applied to commercialized product with priority.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.301-306
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• 2012

We propose a method for accurate image acquisition in a machine vision system in the present study. The most important feature is required by the various lenses to implement real and of the same high quality image-forming optical role. The input of the machine vision system, however, is generated due to the aberration of the lens distortion. Transformation defines the relationship between the real-world coordinate system and the image coordinate system to solve these problems, a mapping function that matrix operations by calculating the distance between two coordinates to specify the exact location. Tolerance Focus Lens caused by the lens aberration correction processing to Galvanometer laser precision machining operations can be improved. Aberration of the aspheric lens has a two-dimensional shape of the curve, but the existing lens correction to linear time-consuming calibration methods by examining a large number of points the problem. How to apply the Bilinear interpolation is proposed in order to reduce the machining error that occurs due to the aberration of the lens processing equipment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.466-472
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• 2008

The paper concerns Fuzzy C-Means clustering based fuzzy neural networks (FCM-FNN) and the optimization of the network is carried out by means of hierarchal fair competition-based parallel genetic algorithm (HFCPGA). FCM-FNN is the extended architecture of Radial Basis Function Neural Network (RBFNN). FCM algorithm is used to determine centers and widths of RBFs. In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM-FNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Since the performance of FCM-FNN is affected by some parameters of FCM-FNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the HFCPGA which is a kind of multipopulation-based parallel genetic algorithms(PGA) is exploited to carry out the structural optimization of FCM-FNN. Moreover the HFCPGA is taken into consideration to avoid a premature convergence related to the optimization problems. The proposed model is demonstrated with the use of two representative numerical examples.