• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1A
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• pp.125-133
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• 2008

According to longer and longer span, dynamic instability of stay cable should be prevented. Dynamic instability occurs mainly symmetric 1st mode and antisymmetric 1st mode in stay cable. Especially symmetric 1st mode has a lot of influence on sag. Therefore fundamental frequency of stay cable is different from that of taut sting. Irvine, Triantafyllou, Ahn etc. analyzed dynamic behavior of taut cable with sag through analytical technical and their researches give important results for large bounds of Irvine parameter. But each research shows mutually different values out of characteristic (cross-over or mode-coupled) point and each solution of frequency equations of all researchers can be very difficultly found because of their very high non-linearity. Presented study focuses on fundamental frequency of stay cable. Generalized mechanical energy with symmetric 1st mode vibration shape satisfied boundary conditions is evolved by Rayleigh-Ritz method. It is possible to give linear analytic solution within characteristic point. Error by this approach shows only below 3% at characteristic point against existing researches. And taut cable don't exceed characteristic point. I.e. high accuracy, easy solving techniques, and a little bit limitations. Therefore presented study can be announced that it is good study ergonomically.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6D
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• pp.761-770
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• 2009

The energy efficiency and environment-friendly aspect of the railway system would be superior to other on-land ransportation systems. In a preliminary feasibility study stage and selection of optimal railway route, the energy efficiency and problems related to environment are usually considered. For the selection of optimal railway route, geographical features and facility of management are generally considered. Environment effect factors for the selection of environment-friendly railway router are focused and studied in this paper. In this study, various analysis of opinion of specialists (railway, environment, transport, urban planning, survey) and the guideline for construction of environment-friendly railway were accomplished. From these results of various analysis, 7 major categories (topography/geology, flora and fauna, Nature Property, air quality, water quality, noise/vibration, visual impact/cultural assets) were extracted. To select environment friendly railway route, many alternatives should be compared optimal route must be selected by a comprehensive assessment considering these 7 categories. To solve this problem, the selected method was AHP which simplifies the complex problems utilizing hierarchy, quantifying qualitative problems through 1:1 comparison, and extracting objective conclusions by maintaining consistency. As a result, a GUIbased program was developed which provides basic values of weighted parameters of each category defined by specialists, and a quantification of detailed assessment guidelines to ensures consistency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2D
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• pp.299-309
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• 2006

Railway noise and vibration has been recognized as major problems with the speed-up of rolling stock. As a kind of solution to these problems, the decrease of stiffness of track pad have been tried. However, in this case, overturning of rail due to lateral force should be considered because it can have effect on the safety of running train. Therefore, above two things - decrease of stiffness of track pad and overturning of rail due to lateral force - should be considered simultaneously for the appropriate determination of spring coefficient of track pad. With this viewpoint, minimum spring coefficient of track pad is estimated through the comparison between the theoretical relationship about the overturning of rail and 3-dimensional FE analysis result. Two kinds of Lateral force and wheel load are used as input loads. Extracted values from the conventional estimation formula and the Shinkansen design loads are used. It is found that the overturning of rail changes corresponding to the change of the stiffness of track pad and the ratio of lateral force to wheel load. Moreover, it is found that the analysis model can have influence on the results. Through these procedure, minimum spring coefficient of track pad is estimated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4A
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• pp.707-717
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• 2006

As an alternative to conventional prestressed concrete (PSC) girders, various types of PSC girders are either under development or have already been applied in bridge structures. Incrementally prestressed concrete girder is one of these newly developed girders. According to the design concept, these new types of PSC girders have the advantages of requiring less self-weight while having the capability of longer spans. However, the dynamic interaction between bridge superstructures and passing trains is one of the critical issues concerning these railway bridges designed with more flexibility. Therefore, it is very important to evaluate modal parameters of newly designed bridges before doing dynamic analyses. In the present paper, a 25 meters long full scale PSC girder was fabricated as a test specimen and modal testing was carried out to evaluate modal parameters including natural frequencies and modal damping ratios at every prestressing stage. During the modal testing, a digitally controlled vibration exciter as well as an impact hammer is applied, in order to obtain precise frequency response functions and the modal parameters are evaluated varying with construction stages. Prestressed force effects on changes of modal parameters are analyzed at every incremental prestressing stage. With the application of reliable properties from modal experiments, estimation of dynamic performances of PSC girder railway bridges can be obtained from various parametric studies on dynamic behavior under the passage of moving train. Dynamic displacements, impact factor, acceleration of the slab, end rotation of the girder, and other important dynamic performance parameters are checked with various speeds of the train.

• Journal of Dental Anesthesia and Pain Medicine
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• v.23 no.6
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• pp.317-325
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• 2023

Background: Local anesthetic injections may induce pain in children, leading to fear and anxiety during subsequent visits. Among the various approaches recommended to reduce pain, one is the use of a Buzzy Bee^TM device that operates on the concept of gate control theory and distraction. The literature regarding its effectiveness during the deposition of local anesthesia remains limited; hence, the aim of the present study was to determine the efficacy of extraoral cold and vibrating devices in reducing pain perception during the deposition of local anesthesia. Methods: A split-mouth crossover study in which 40 children aged 3-12 years requiring maxillary infiltration or inferior alveolar nerve block for extractions or pulp therapy in the maxillary or mandibular posterior teeth were included. The control intervention involved the application of topical anesthetic gel for one minute (5% lignocaine gel), followed by the administration of local anesthetic (2% lignocaine with 1:80,000 adrenaline) at a rate of 1 ml/ minute. Along with the control protocol, the test intervention involved using the Buzzy Bee^TM device for 2 minutes before and during the deposition of the local anesthetic injection. The heart rate and face, legs, arms, cry, and consolability revised (FLACC-R) scale scores were recorded by the dentist to assess the child's pain perception. Results: The mean age of the participants in Group A and Group B was 7.050 ± 3.12 years and 7.9 ± 2.65 years respectively. A reduction in the mean heart rate and FLACC-R score was observed during the deposition of local anesthetic solution in the tissues when the Buzzy Bee^TM was used in both groups at different visits in the same subjects (P < 0.05) The Buzzy Bee^TM device was effective in reducing the heart rate and FLACC-R scores when used during maxillary infiltration and inferior alveolar nerve block local anesthesia techniques (P < 0.05). Conclusion: The use of extraoral cold and vibrating devices significantly reduces pain perception during local anesthetic deposition in pediatric patients. Considering the results of this study, the device may be incorporated as an adjunct in routine dental practice while administering local anesthesia in children.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.594-602
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• 2023

To date, research on heavy floor impact noise has mainly been conducted. The reason is that in the case of lightweight floor impact noise, sufficient performance could be secured with only the floating floor structure and floor finishing materials. In the case of heavy floor impact noise in a floating floor structure, the reduction performance can be predicted to some extent by measuring the dynamic elasticity of the floor cushioning material. However, with the recent introduction of the post-measurement system, various floor structures are being developed. In particular, many non-floating floor structures that do not use cushioning materials are being developed. In floor structures where cushioning materials are not used, the finishing material will have a significant impact on lightweight floor impact noise. However, research on floor finishing materials is currently lacking. In this study, as a basic research on the development of various floor finishing materials for effective reduction of lightweight floor impact noise, various materials used as floor finishing materials for apartment complexes were selected, the sound insulation performance of lightweight floor impact noise was measured in an actual laboratory, and vibration characteristics were identified through simple experiments. The purpose was to confirm the predictability of light floor impact noise.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.171-180
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• 2023

Hydrogen energy technology is gaining importance in the era of the Fourth Industrial Revolution, offering military advantages when applied to military vehicles due to its characteristics such as reduced greenhouse gas emissions, noise, and low vibration. Korea's military has initiated the Army Tiger 4.0 plan, focusing on hydrogen application, downsizing, and AI-based smart features. The Ministry of National Defense plans to collaborate with the Ministry of Environment to expand hydrogen charging stations nationwide, anticipating increased deployment of military hydrogen vehicles. However, considering the Jet Fire and VCE(Vapor Cloud Explosion) nature of hydrogen, ensuring safety during installation is crucial. Current military guidelines specify a minimum safety distance of 2m from adjacent buildings for charging stations. Scientific methods have been employed to quantitatively assess the accident damage range of hydrogen, proposing a minimum safety distance beyond the affected area.

• 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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.61-68
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• 2024

The majority of high-speed railway bridges along the domestic Gyeongbu and Honam lines feature a PSC-box type structure with a span length ranging from 35 to 40m, which typically exhibits a first bending natural frequency of approximately 4 to 5Hz. When KTX high-speed trains transverse these bridges at speeds ranging from 290 to 310km/h, the vibration induced by the trains approaches the first bending natural frequency of the bridge. Furthermore, with the upcoming operation of a EMU-320 high-speed train and the anticipated increase in the speeds of these high-speed trains, there is a need to analyze the dynamic response of high-speed railway bridges. For this, based on measured responses from actual railway bridges, a numerical model was constructed using a numerical model updating technique. The dynamic response of the updated numerical model exhibited a strong agreement with the measured response from the actual railway bridges. Subsequently, this updated model was utilized to analyze the dynamic response characteristics of the bridges when KTX and EMU-320 trains operate at increased speeds. The maximum vertical displacement and acceleration at the mid-span of the bridges were also compared to those specified in the railway design standard with the increasing speed of KTX and EMU-320.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.