• Wind and Structures
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• v.30 no.4
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• pp.405-421
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• 2020

Quayside container cranes are important delivery machineries located in the most frontiers of container terminals, where strong wind attacks happen occasionally. Since the previous researches on quayside container cranes mainly focused on the mean wind load and static response characteristics, the fluctuating wind load and dynamic response characteristics require further investigations. In the present study, the aerodynamic wind loads on quayside container cranes were obtained from wind tunnel tests. The probabilistic and spectral models of the fluctuating aerodynamic loads were established. Then the joint probabilistic distributions of dynamic wind-induced responses were derived theoretically based on a series of Gaussian and independent assumption of resonant components. Finally, the results were validated by time domain analysis using wind tunnel data. It is concluded that the assumptions are acceptable. And the presented approach can estimate peak dynamic sliding force, overturning moments and leg uplifts of quayside container cranes effectively and efficiently.

• ETRI Journal
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• v.33 no.2
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• pp.219-229
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• 2011

In this paper, we propose a transformation scheme used to analyze online gaming traffic properties and develop a traffic model. We analyze the packet size and the inter departure time distributions of a popular first-person shooter game (Left 4 Dead) and a massively multiplayer online role-playing game (World of Warcraft) in order to compare them to the existing scheme. Recent online gaming traffic is erratically distributed, so it is very difficult to analyze. Therefore, our research focuses on a transformation scheme to obtain new smooth patterns from a messy dataset. It extracts relatively heavy-weighted density data and then transforms them into a corresponding dataset domain to obtain a simplified graph. We compare the analytical model histogram, the chi-square statistic, and the quantile-quantile plot of the proposed scheme to an existing scheme. The results show that the proposed scheme demonstrates a good fit in all parts. The chi-square statistic of our scheme for the Left 4 Dead packet size distribution is less than one ninth of the existing one when dealing with erratic traffic.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.11 no.2
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• pp.95-106
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• 1999

A numerical model is represented to calculate the wave fields such as the reflected waves, the transmitted waves and the depth-averaged velocities over submerged breakwaters for the normally incident wave trains of nonlinear mono-chromatic wave and solitary wave. The finite amplitude shallow water equations with the effects of bottom friction are solved numerically in time domain using an explicit dissipative Lax-Wendroff finite difference method. The numerical model is verified by comparisons with the other numerical results and the measured data. It is found that the submerged breakwater may be more useful for protecting the energies of monochromatic waves rather than solitary waves. Finally, the armor stability on submerged breakwater is indirectly analyzed using the hydrodynamic characteristics of flow fields.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.6
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• pp.516-527
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• 2011

This paper considers a numerical analysis of ship maneuvering performance in the high amplitude incident waves by adopting linear and nonlinear ship motion analysis. A time-domain ship motion program is developed to solve the wave-body interaction problem with the ship slip speed and rotation, and it is coupled with a modular type 4-DOF maneuvering problem. Nonlinear Froude-Krylov and restoring forces are included to consider weakly nonlinear ship motion. The developed method is applied to observe the nonlinear ship motion and planar trajectories in maneuvering test in the presence of incident waves. The comparisons are made for S-175 containership with existing experimental data. The nonlinear computation results show a fair agreement of overall tendency in maneuvering performance. In addition, maneuvering performances with respect to wave slope is predicted and reasonable results are observed.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.92-95
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• 2020

In this paper, the new architecture of seizure prediction using CNN and LSTM and DWT was presented. In the proposed architecture, EEG data was labeled into a preictal and interictal section, and DWT was adopted to the preprocessing process to apply the characteristics of the time and frequency domain of the processed EEG signal. Also, CNN was applied to extract the spatial characteristics of each electrode used for EEG measurement, and LSTM neural network was applied to verify the logical order of the preictal section. The learning of the proposed architecture utilizes the CHB-MIT Scalp EEG dataset, and the sliding window technique is applied to balance the dataset between the number of interictal sections and the number of preictal sections. As a result of the simulation of the proposed architecture, a sensitivity of 81.22% and an FPR of 0.174 were obtained.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.10a
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• pp.161-166
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• 2002

As offshore oil fields move towards the deep ocean, the oil production systems such as FPSO are being built these days. Generally, the FPSO is moored by turret mooring lines to keep the position of FPSO. Thus nonlinear motion analysis of moored FPSO must be carried out in the initial design stage because sea environments affect motion of it. In this paper the mathematical model is based on the slow motion maneuvering equations in the horizontal plane considering wave, current and wind forces. The direct integration method is employed to estimate wave loads. The current forces are calculated by using mathematical model of MMG. The turret mooring forces are quasi-statically evaluated by using the catenary equation. The coefficients of a model for wind forces are calculated from Isherwood's experimental data and the variation of wind speed is estimated by wind spectrum according to the guidelines of API-RP2A. The nonlinear motions of FPSO are simulated under external forces due to wave, current, wind including mooring forces in time domain.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.319-323
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• 2003

In this paper, we propose a hybrid transceiver for underwater acoustic communication, which allows the system to reduce complexity and increase robustness in time variant underwater channel environments. It is designed in the digital domain except for amplifiers and implemented by using a multiple digital signal processors (DSPs) system. The digital modulation technique is quadrature phase shift keying (QPSK) and frame synchronization is an energy (non-coherent) detection scheme based on the quadrature receiver structure. DSP implementation is based on block data parallel architecture (BDPA). We shaw experimental results in th? underwater anechoic basin at KRISO. The results indicate that the frame synchronization is performed without PLL. Also, we shaw that the adaptive equalizer can compensate frame synchronization error and the correction capability is dependent on the length of equalizer.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.49-63
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• 2003

This paper proposes and implements a tool for the development of efficient and reliable expert system. In the expert system the inference is executed, based on the knowledges stored in the knowledge base of specific domain. To acquire the reliable results of inference, the expert system requires the facilities which can access the various kinds of knowledge and maintain the consistency and accuracy of knowledge. In this context this paper implemented the knowledge management system which maintains the consistency and accuracy of knowledge, adding selectively the knowledges without error to the knowledge base by verifying their error before the knowledges are added to the knowledge base. At the same time this paper made the expert system call and use the procedural knowledge and the declarative knowledge in the data base so that it might use the various kinds of knowledge in the process of inference.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.474-484
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• 2017

This paper studies the applicability of an efficient numerical model based on artificial neural networks (ANNs) to predict the dynamic responses of the wing structure of an airplane due to atmospheric turbulence in the time domain. The turbulence velocity is given in the form of a stationary Gaussian random process with the von Karman power spectral density. The wing structure is modeled by a classical beam considering bending and torsional deformations. An unsteady vortex-lattice method is applied to estimate the aerodynamic pressure distribution on the wing surface. Initially, the trim condition is obtained, then structural dynamic responses are computed. The numerical solution of the wing structure's responses to a random turbulence profile is used as a training data for the ANN. The current ANN is a three-layer network with the output fed back to the input layer through delays. The results from this study have validated the proposed low-cost ANN model for the predictions of dynamic responses of wing structures due to atmospheric turbulence. The accuracy of the predicted results by the ANN was discussed. The paper indicated that predictions for the bending moments are more accurate than those for the torsional moments of the wing structure.

• Journal of Biomedical Engineering Research
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• v.27 no.5
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• pp.237-244
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• 2006

This study proposes an approach to the performance improvement of EMG(Electromyogram) pattern recognition. MFCC(Mel-Frequency Cepstral Coefficients)'s approach is molded after the characteristics of the human hearing organ. While it supplies the most typical feature in frequency domain, it should be reorganized to detect the features in EMG signal. And the dynamic aspects of EMG are important for a task, such as a continuous prosthetic control or various time length EMG signal recognition, which have not been successfully mastered by the most approaches. Thus, this paper proposes reorganized MFCC and HMM-GMM, which is adaptable for the dynamic features of the signal. Moreover, it requires an analysis on the most suitable system setting fur EMG pattern recognition. To meet the requirement, this study balanced the recognition-rate against the error-rates produced by the various settings when loaming based on the EMG data for each motion.