• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.2
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• pp.115-124
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• 2003

In this paper, the effects of vehicle loads on flat slab system are investigated on the basis of the previous studies for beam-gilder parking structural system. The influence surfaces of flat slab for a typical design section are constructed lot the purpose of obtaining maximum member forces under vehicle loads. In addition, the equivalent vehicle load factors for flat slab parking structures are suggested using artificial neural network. The network responses we compared with the results obtained by numerical analyses to verify the validation of Levenberg-Marquardt algorithm adopted as training method in this Paper. Many parameter studies for the flat slab structural system show dominant vehicle load effects at the center positive moments in both column and middle strips, like the beam-girder parking structural system.

• Smart Structures and Systems
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• v.25 no.5
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• pp.605-617
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• 2020

The existence of damages in structures causes changes in the physical properties by reducing the modal parameters. In this paper, we develop a two-stages approach based on normalized Modal Strain Energy Damage Indicator (nMSEDI) for quick applications to predict the location of damage. A two-dimensional IsoGeometric Analysis (2D-IGA), Machine Learning Algorithm (MLA) and optimization techniques are combined to create a new tool. In the first stage, we introduce a modified damage identification technique based on frequencies using nMSEDI to locate the potential of damaged elements. In the second stage, after eliminating the healthy elements, the damage index values from nMSEDI are considered as input in the damage quantification algorithm. The hybrid of Teaching-Learning-Based Optimization (TLBO) with Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) are used along with nMSEDI. The objective of TLBO is to estimate the parameters of PSO-ANN to find a good training based on actual damage and estimated damage. The IGA model is updated using experimental results based on stiffness and mass matrix using the difference between calculated and measured frequencies as objective function. The feasibility and efficiency of nMSEDI-PSO-ANN after finding the best parameters by TLBO are demonstrated through the comparison with nMSEDI-IGA for different scenarios. The result of the analyses indicates that the proposed approach can be used to determine correctly the severity of damage in beam structures.

• Journal of the Optical Society of Korea
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• v.17 no.4
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• pp.289-295
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• 2013

Although low-level laser therapy (LLLT) has been a valuable therapeutic technology in the clinic, its efficacy may be reduced in deep tissue layers due to strong light scattering which limits the photon density. In order to enhance the photon density in deep tissue layers, this study developed an optical tissue clearing (OTC) laser probe (OTCLP) system which can utilize four different OTC methods: 1) tissue temperature control from 40 to $10^{\circ}C$; 2) laser pulse frequency from 5 to 30 Hz; 3) glycerol injection at a local region; and 4) a combination of the aforementioned three methods. The efficacy of the OTC methods was evaluated and compared by investigating laser beam profiles in ex-vivo porcine skin samples. Results demonstrated that total (peak) intensity at full width at half maximum of laser beam profile when compared to control data was increased: 1) 1.21(1.39)-fold at $10^{\circ}C$; 2) 1.22 (1.49)-fold at a laser pulse frequency of 5 Hz; 3) 1.64 (2.41)-fold with 95% glycerol injection; 4) 1.86 (3.4)-fold with the combination method. In conclusion, the OTCLP system successfully improved the laser photon density in deep tissue layers and may be utilized as a useful tool in LLLT by increasing laser photon density.

• Journal of ILASS-Korea
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• v.28 no.1
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• pp.1-9
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• 2023

In the cylinder of gasoline direct injection engines, the spray targeting from injectors is of great significance for fuel consumption and pollutant emissions. The automotive industry is putting a lot of effort into improving injector targeting accuracy. To improve the targeting accuracy of injectors, it is necessary to develop models that can predict the spray targeting positions. When developing spray targeting models, the most used technique is computational fluid dynamics (CFD). Recently, due to the superiority of machine learning in prediction accuracy, the application of machine learning in this field is also receiving constant attention. The purpose of this study is to build a machine learning model that can accurately predict spray targeting based on the design parameters of injectors. To achieve this goal, this study firstly used laser sheet beam visualization equipment to obtain many spray cross-sectional images of injectors with different parameters at different injection pressures and measurement planes. The spray images were processed by MATLAB code to get the targeting coordinates of sprays. A total of four models were used for the prediction of spray targeting coordinates, namely ANN, LSTM, Conv1D and Conv1D & LSTM. Features fed into the machine learning model include injector design parameters, injection conditions, and measurement planes. Labels to be output from the model are spray targeting coordinates. In addition, the spray data of 7 injectors were used for model training, and the spray data of the remaining one injector were used for model performance verification. Finally, the prediction performance of the model was evaluated by R² and RMSE. It is found that the Conv1D&LSTM model has the highest accuracy in predicting the spray targeting coordinates, which can reach 98%. In addition, the prediction bias of the model becomes larger as the distance from the injector tip increases.

• Journal of the Korean housing association
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• v.26 no.1
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• pp.1-10
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• 2015

In line with the recent public concern on the environmental issues in building industry, there has been a rise in demand for a healthy, sustainable housing environment in South Korea. In order to achieve a healthy environment in residential buildings, considerable efforts have been made in a wide range of sectors. Among others, the development of the certification schemes to promote environment-friendly planning and building construction is remarkable. In urban South Korea, recently built houses tend to be significantly high-rise, high-density buildings. Global warming has brought about drastic climate change and continued to increase the average annual temperature year by year. These changes should be well reflected on the government's implementation of the building environmental assessment system. For guidance, therefore, this study looks to the case of Hong Kong which is well known for high-density housing development and subtropical climate conditions. It compares the features of the green building certification schemes for newly developed multifamily housing in two regions, namely HK-BEAM in Hong Kong and G-SEED in South Korea. Based on the findings, it argues that the G-SEED implementor should have expanded roles in providing training programs and follow-up services in collaboration with the certification authorities. It is also argued that G-SEED professionals should be involved in the early stages of design processes, and training programs and licence systems to produce green building professionals should be developed. Finally, it points out that the assessment indicators should be more detailed and diversified.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.892-901
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• 2016

In the multi-user multiple-input multiple-output (MIMO) system, orthogonal random beamforming (ORBF) scheme is proposed to serve multiple users simultaneously in order to achieve the multi-user diversity gain. The opportunistic space-division multiple access system (OSDMA-S) scheme performs multiple weighting matrices during the training phase and chooses the best weighting matrix to be used to broadcast data during the transmitting phase. The OSDMA-S scheme works better than the original ORBF by decreasing the inter-user interference during the transmitting phase. To save more time in the training phase, a partly random multiple weighting matrices selection scheme is proposed in this paper. In our proposed scheme, the Base Station does not need to use several unitary matrices to broadcast pilot symbol. Actually, only one broadcasting operation is needed. Each subscriber generates several virtual equivalent channels with a set of pre-saved unitary matrices and the channel status information gained from the broadcasting operation. The signal-to-interference and noise ratio (SINR) of each beam in each virtual equivalent channel is calculated and fed back to the base station for the weighting matrix selection and multi-user scheduling. According to the theoretical analysis, the proposed scheme relatively expands the transmitting phase and reduces the interactive complexity between the Base Station and subscribers. The asymptotic analysis and the simulation results show that the proposed scheme improves the throughput performance of the multi-user MIMO system.

• Korean Journal of Applied Biomechanics
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• v.18 no.1
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• pp.137-146
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• 2008

The purpose of this study is to examine the causes of errors from EGR posture on the balance beam, which is bending flick-flack salto backward stretched national team players through kinematic analysis, and present training methods for them so as to provide scientifically useful information to coaches and athlete. Findings from this study are summarized below. The most important factors that affect the errors in boyd center position and speed change were the speed change of left and right body centers and the horizontal and vertical speed changes. The left and right acceleration changes were greater in failed posture than in successful posture. The horizontal and vertical accelerations in E3 and E5 were the key factors that affected the backward somersault and landing. The angular speed changes which varied between success and failure were notable in head and shoulder joints. In individual results. The section when the angular speeds of head and shoulder joint must be the greatest was E4. In this section, when the body is extending instantly in a bent posture, increasing the angular speeds of head, shoulder and hip joints can improve the duration of staying in the air and the rotation radius of a somersault.

• Journal of Engineering Education Research
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• v.10 no.4
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• pp.17-28
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• 2007

This paper aims to present the ways to maximize educational effects and facilitate a curriculum renovation through the Specified Track Curriculum Development, a joint lecture system among local universities which is implemented by Busan Educational Alliance of Mechanical Engineering (BEAM) as part of New University for Regional Innovation(NURI), a government-sponsored project to facilitate a balanced regional development of Korea. The Specified Track Curriculum is a unified governing body joined by 4 universities of mechanical engineering departments with an emphasis on their specified academic fields(advanced hightech, environmental, marine and foundational machinery sectors), And the universities mutually recognize academic credits. The track (Specified-Track Curriculum) was carried out three times from winter semester in 2005 to the present and 486 students took the track course for two years. As a result, the track laid out a foundation for the first local joint lecture system in korea with the performance-oriented and students-tailored education, meeting needs of the new era and training efficiency. The graduates' employment rose to 8.5%, compared with that of 2005. According to recent survey conducted on companies employing the graduates, the satisfaction with the graduates' performance marked 9.4% improvement. The track also contributed to expanding human networks, facilitating the educational exchange of local universities.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.530-536
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• 2021

Recently, due to the development of deep learning, end-to-end speech recognition, which directly maps graphemes to speech signals, shows good performance. Especially, among the end-to-end models, conformer shows the best performance. However end-to-end models only focuses on the probability of which grapheme will appear at the time. The decoding process uses a greedy search or beam search. This decoding method is easily affected by the final probability output by the model. In addition, the end-to-end models cannot use external pronunciation and language information due to structual problem. Therefore, in this paper conformer with lexicon transducer is proposed. We compare phoneme-based model with lexicon transducer and grapheme-based model with beam search. Test set is consist of words that do not appear in training data. The grapheme-based conformer with beam search shows 3.8 % of CER. The phoneme-based conformer with lexicon transducer shows 3.4 % of CER.

• Smart Structures and Systems
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• v.4 no.5
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• pp.583-603
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• 2008

In this study, a real-time damage detection method using output-only acceleration signals and artificial neural networks (ANN) is developed to monitor the occurrence of damage and the location of damage in structures. A theoretical approach of an ANN algorithm that uses acceleration signals to detect changes in structural parameters in real-time is newly designed. Cross-covariance functions of two acceleration responses measured before and after damage at two different sensor locations are selected as the features representing the structural conditions. By means of the acceleration features, multiple neural networks are trained for a series of potential loading patterns and damage scenarios of the target structure for which its actual loading history and structural conditions are unknown. The feasibility of the proposed method is evaluated using a numerical beam model under the effect of model uncertainty due to the variability of impulse excitation patterns used for training neural networks. The practicality of the method is also evaluated from laboratory-model tests on free-free beams for which acceleration responses were measured for several damage cases.