Choo, Tai Ho;Ok, Chi Youl;Kim, Jin Won;Maeng, Seung Jin
KSCE Journal of Civil and Environmental Engineering Research
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v.29
no.4B
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pp.357-363
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2009
When yields the mean velocity of the closed conduit which is used generally, it is available to use Darcy Weisbach Friction Loss Head equation. But, it is inconvenient very because Friction Loss coefficient f is the function of Reynolds Number and Relative roughness (${\varepsilon}$/d). So, it is demanded more convenient equation to estimate. In order to prove the reliability and an accuracy of Chiu's velocity equation from the research which sees hereupon, proved agreement very well about measured velocity measurement data by using Laser velocimeter which is a non-insertion velocity measuring equipment from the closed conduit (Laser Doppler Velocimeter: LDV) and an insertion velocity measuring equipment and the Pitot tube which is a supersonic flow meter (Transit-Time Flowmeters). By proving theoretical linear-relation between maximum velocity and mean velocity in laboratory flume without increase and decrease of discharge, the equilibrium state of velocity in the closed conduit which reachs to equilibrium state corresponding to entropy parameter M value has a trend maintaining consistently this state. If entropy M value which is representing one section is determinated, mean velocity can be gotten only by measuring the velocity in the point appearing the maximum velocity. So, it has been proved to estimate simply discharge and it indicates that this method can be a theoretical way, which is the most important in the future, when designing, managing and operating the closed conduit.
KSCE Journal of Civil and Environmental Engineering Research
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v.29
no.2A
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pp.119-130
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2009
Seismic fragility curves of a structure represent the probability of exceeding the prescribed structural damage state for a given various levels of ground motion intensity such as peak ground acceleration (PGA), spectral acceleration ($S_a$) and spectral displacement ($S_d$). So those are very essential to evaluate the structural seismic performance and seismic risk. The purpose of this paper is to develop seismic fragility curves for PSC box girder bridges. In order to construct numerical fragility curve of bridge structure using nonlinear time history analysis, a set of ground motions corresponding to design spectrum are artificially generated. Assuming a lognormal distribution, the fragility curve is estimated by using the methodology proposed by Shinozuka et al. PGA is simple and generally used parameter in fragility curve as ground motion intensity. However, the PGA has not good relationship with the inelastic structural behavior. So, $S_a$ and $S_d$ with more direct relationship for structural damage are used in fragility analysis as more useful intensity measures instead of PGA. The numerical fragility curves based on nonlinear time history analysis are compared with those obtained from simple method suggested in HAZUS program.
Journal of the Korea Society of Computer and Information
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v.28
no.10
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pp.1-8
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2023
If there is a defect in the wheel bearing, which is a major part of the car, it can cause problems such as traffic accidents. In order to solve this problem, big data is collected and monitoring is conducted to provide early information on the presence or absence of wheel bearing failure and type of failure through predictive diagnosis and management technology. System development is needed. In this paper, to implement such an intelligent wheel hub bearing maintenance system, we develop an embedded system equipped with sensors for monitoring reliability and soundness and algorithms for predictive diagnosis. The algorithm used acquires vibration signals from acceleration sensors installed in wheel bearings and can predict and diagnose failures through big data technology through signal processing techniques, fault frequency analysis, and health characteristic parameter definition. The implemented algorithm applies a stable signal extraction algorithm that can minimize vibration frequency components and maximize vibration components occurring in wheel bearings. In noise removal using a filter, an artificial intelligence-based soundness extraction algorithm is applied, and FFT is applied. The fault frequency was analyzed and the fault was diagnosed by extracting fault characteristic factors. The performance target of this system was over 12,800 ODR, and the target was met through test results.
Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.
Journal of the Institute of Convergence Signal Processing
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v.24
no.2
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pp.119-125
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2023
In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.
The plane wave reflection coefficient is an acoustic property containing all the information concerning the ocean bottom and can be used as an input parameter to various acoustic propagation models. In this paper, we measure the plane wave reflection coefficient, the sound speed, thd the attenuation for saturated granular medium in the water tank. Three kinds of glass beads and natural sand are used as the granular medium. The reflection experiment is performed with the sinusoidal tone bursts of 100 kHz at incident angles from 28 to 53 degrees, and the sound speed and attenuation experiment are performed also with the same signal. From the measured reflection signal, the reflection coefficient is calculated with the self calibration method and the experimental uncertainties are discussed. The sound speed and the attenuation measurements are used for the estimation of the porosity and permeability, the main Biot parameters. The estimated values are compared to the directly measured values and used as input values to the Biot theory in order to calculate the theoretical reflection coefficient. Finally, the reflection coefficient predicted by Biot theory is compared to the measured reflection coefficient and their characteristics are discussed.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.15
no.4
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pp.135-149
/
2020
As youth employment has become a social issue every year, the government is pushing for policies to support youth start-ups to create jobs voluntarily as a way to enhance the youth employment rate. In the case of young people in Gangwon Province, the number of people moving to other regions is increasing. This research is intended to empirically analyze the actual achievements of youth start-ups through the 'Youth Start-up Project' in Gangwon-do. It was divided into four categories: participation in government support, education completion, intellectual property right retention, and certification retention, which are characteristics of start-up companies, and hypotheses that they will have a positive impact on start-up performance (sales amount, duration of existence, or whether they are retained or not). Age and geographical factors (Yeongdong and Yeongseo) were injected as control variables to see how they affect them. Furthermore, empirical analysis was conducted by setting up a hypothesis that the characteristics of start-up companies and subsequent support between start-up performance would have a positive intermediary effect. The research results showed that the remaining characteristics, except for education completion, had a positive impact on sales, and that the more participation in government projects, the longer the duration of the company's existence. In addition, the level of participation in government support projects was significant in the direction of the government. The analysis results of the parameter, follow-up support, had a positive impact on the start-up performance, and the subsequent support mediating effect showed the mediating effect of the start-up performance, except for geographical factors. The results of this study suggest the need for customized support suitable for the characteristics of youth start-ups in order to enhance the performance of young start-ups. Support agencies need to refer to corporate characteristics for smooth management and selection. In the Gangwon-do area, the government should seek to provide timely and organic support for start-up companies in order to produce successful start-up cases.
Osteoporosis is a clinical condition in which the amount of bone tissue is reduced and the likelihood of fracture is increased. It is known that the electrical property of the bone is related to its density, and, in particular, the electrical resistance of the bone decreases as the bone loss increases. This implies that the electrical property of bone may be an useful parameter to diagnose osteoporosis, provided that it can be readily measured. The study attempted to evaluate the electrical conductivity of bone using a technique of electrical impedance tomography (EIT). It nay not be easy in general to get an EIT for the bone due to the big difference (an order of 2) of electrical properties between the bone and the surrounding soft tissue. In the present study, we took an adaptive mesh regeneration technique originally developed for the detection of two phase boundaries and modified it to be able to reconstruct the electrical conductivity inside the boundary provided that the geometry of the boundary was given. Numerical simulation was carried out for a tibia phantom, circular cylindrical phantom (radius of 40 mm) inside of which there is an ellipsoidal homeogenous tibia bone (short and long radius are 17 mm and 15 mm, respectively) surrounded by the soft tissue. The bone was located in the 15 mm above from the center of the circular cross section of the phantom. The electrical conductivity of the soft tissue was set to be 4 mS/cm and varies from 0.01 to 1 ms/cm for the bone. The simulation considered measurement errors in order to look into its effects. The simulated results showed that, if the measurement error was maintained less than 5 %, the reconstructed electrical conductivity of the bone was within 10 % errors. The accuracy increased with the electrical conductivity of the bone, as expected. This indicates that the present technique provides more accurate information for osteoporotic bones. It should be noted that tile simulation is based on a simple two phase image for the bone and the surrounding soft tissue when its anatomical information is provided. Nevertheless, the study indicates the possibility that the EIT technique may be used as a new means to detect the bone loss leading to osteoporotic fractures.
Shin, Sung-Kyun;Noh, Youngmin;Lee, Kwonho;Shin, Dongho;Kim, KwanChul;Kim, Young J.
Korean Journal of Remote Sensing
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v.30
no.2
/
pp.241-249
/
2014
The continuous observations for atmospheric aerosol were carried out during 3 years (2009-2011) by using a multi-wavelength Raman lidar at the Gwangju Institute of Science and Technology (GIST), Korea ($35.11^{\circ}N$, $126.54^{\circ}E$). The particle depolarization ratios were retrieved from the observations in order to distinguish the Asian dust layer. The vertical information of Asian dust layers were used as input parameter for the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model for analysis of its backward trajectories. The source regions and transport pathways of the Asian dust layer were identified. The most frequent source region of Asian dust in Korea was Gobi desert during observation period in this study. The statistical analysis on the particle depolarization ratio of Asian dust was conducted according to their transport route in order to retrieve the variation of optical properties of Asian dust during long-range transport. The transport routes were classified into the Asian dust which was transported to observation site directly from the source regions, and the Asian dust which was passed over pollution regions of China. The particle depolarization ratios of Asian dust which were transported via industrial regions of China was ranged 0.07-0.1, whereas, the particle depolarization ratio of Asian dust which was transported directly from the source regions to observation site were comparably higher and ranged 0.11-0.15. It is considered that the pure Asian dust particle from source regions were mixed with pollution particles, which is likely to spherical particle, during transportation so that the values of particle depolarization of Asian dust mixed with pollution was decreased.
This study was conducted to identify the parameter better representing the nitrogen supply capacity of soils for the vegetable crops growing in vinylhouse. All the parameters showed significant positive correlation with the yield of chinese cabbage. The correlation coefficients were in the order of $NO{_3}^--N+NH{_4}^+-N(2M\;KCl)$ > $NO{_3}^--N(2M\;KCl)$ > OM > T-N > 0.01M $NaHCO_3$ > 0.01M $CaCl_2$ > $NH{_4}^+-N(2M\;KCl)$ > 6N HCl. Between the soil N and N absorbed by plant, the correlation coefficients were in the order of $NO{_3}^--N+NH{_4}^+-N(2M\;KCl)$ > $NO{_3}^--N(2M\;KCl)$ > 0.01M $NaHCO_3$ > $NH{_4}^+-N(2M\;KCl)$ > 0.01M $CaCl_2$ > OM > T-N > 6N HCl. The results of this study suggest that 2M KCl extractable inorganic N. 2M KCl extractable $NO{_3}^--N$ are recommendable parameters for the estimation of N supply capacity of the vinylhouse soils. The sum of soil $NO{_3}^--N$ and fertilizer nitrogen showed highly significant positive correlation with the yields of chinese cabbage and nitrogen absorbed by the plant, while negative correlation with the nitrogen use efficiency.
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