• Journal of the Korean Institute of Gas
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• v.4 no.3 s.11
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• pp.59-64
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• 2000

The real time monitoring system is developed to detect third party damage imposed on natural gas pipeline and to estimate a damage position in section of pipeline in need of monitoring the third party damage. The monitoring system uses wireless data communication in order to build up data communication network. The availability of monitoring system was evaluated through full scale field damage test at Masan's submarine gas pipeline. It was turned out that the estimation error was one percentage of the propagation speed of damage sound in the gas pipeline.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.5
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• pp.83-99
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• 2021

With the advent of the fourth industrial revolution, studies on driving management and driving strategies of autonomous vehicles are emerging. While obtaining microscopic traffic data on vehicles is essential for such research, we also see that conventional traffic data collection methods cannot collect the driving behavior of individual vehicles. In this study, UAV videos were used to collect traffic data from the viewpoint of the aerial base that is microscopic. To overcome the limitations of the related research in the literature, the micro-traffic data were estimated using the multiple object tracking of deep learning and an image registration technique. As a result, the speed obtained error rates of MAE 3.49 km/h, RMSE 4.43 km/h, and MAPE 5.18 km/h, and the traffic obtained a precision of 98.07% and a recall of 97.86%.

• Atmosphere
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• v.32 no.2
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• pp.163-178
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• 2022

This study aims to evaluate the accuracy of retrieved horizontal winds with different quality control methods from three Doppler lidars deployed over the complex terrain during the PyeongChang 2018 Olympic and Paralympic games. To retrieve the accurate wind profile, this study also proposes two quality control methods to distinguish between meteorological signals and noises in the Doppler velocity field, which can be broadly applied to different Doppler lidars. We evaluated the accuracy of retrieved winds with the wind measurements from the nearby or collocated rawinsondes. The retrieved wind speed and direction show a good agreement with rawinsonde with a correlation coefficient larger than 0.9. This study minimized the sampling error in the wind evaluation and estimation, and found that the accuracy of retrieved winds can reach ~0.6 m s^-1 and 3° in the quasi-homogeneous wind condition. We expect that the retrieved horizontal winds can be used in the high-resolution analysis of the horizontal winds and provide an accurate wind profile for model evaluation or data assimilation purposes.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.1-8
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• 2023

An Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication system has drawn wide attention for its high transmission rate and high spectrum efficiency in not only radio but also Underwater Acoustic (UWA) applications. Because of the narrow sub-carrier spacing of OFDM, orthogonality between sub-carriers is easily affected by Doppler effect caused by the movement of transmitter or receiver. Previously, Doppler compensation signal processing algorithm for Desired propagation path was proposed. However, other Doppler shifts caused by delayed Undesired signal arriving from different directions cannot be perfectly compensated. Then Receiver Bit Error Rate (BER) is degraded by Inter-Carrier-Interference (ICI) caused in the case of Multi-path Doppler channel. To mitigate the ICI effect, a modified Delay and Doppler Profiler (mDDP), which estimates not only attenuation, relative delay and Doppler shift but also sampling clock shift of each multi-path component, is proposed. Based on the outputs of mDDP, an ICI canceling multi-tap equalizer is also proposed. Computer simulated performances of one-tap equalizer with the conventional Time domain linear interpolated Channel Transfer Function (CTF) estimator, multi-tap equalizer based on mDDP are compared. According to the simulation results, BER improvement has been observed. Especially, in the condition of 16QAM modulation, transmitting vessel speed of 6m/s, two-path multipath channel with direct path and ocean surface reflection path; more than one order of magnitude BER reduction has been observed at CNR=30dB.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.313-322
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• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• Wind and Structures
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• v.37 no.4
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• pp.289-302
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• 2023

Insulating glass units (IGUs) have been widely used in buildings in recent years due to their superior thermal insulation performance. However, because of the panel reciprocating motion and fatigue deterioration of sealants under long-term wind loads, many IGUs have the problem of early failure of watertight properties in real usage. This study aimed to propose a statistical method for wind-induced deflection of IGU panels during the whole life service period, for further precise analysis of the accumulated fatigue damage at the sealed part of the edge bond. By the estimation of the wind occurrence regularity based on wind pressure return period, the events of each wind speed interval during the whole life were obtained for the IGUs at 50m height in Beijing, which are in good agreement with the measured data. Also, the wind-induced deflection analysis method of IGUs based on the formula of airspace coefficient was proposed and verified as an improvement of the original stiffness distribution method with the average relative error compared to the test being about 3% or less. Combining the two methods above, the deformation of the outer and inner panes under wind loads during 30 years was precisely calculated, and the deflection and stress state at selected locations were obtained finally. The results show that the compression displacement at the secondary sealant under the maximum wind pressure is close to 0.3mm (strain 2.5%), and the IGUs are in tens of thousands of times the low amplitude tensile-compression cycle and several times to dozens of times the relatively high amplitude tensile-compression cycle environment. The approach proposed in this paper provides a basis for subsequent studies on the durability of IGUs and the wind-resistant behaviors of curtain wall structures.

• Journal of Radiation Protection and Research
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• v.48 no.4
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• pp.175-183
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• 2023

Background: Recently, biological adsorbents have been developed for removing radionuclides from radioactive liquid waste due to their high selectivity, eco-friendliness, and renewability. However, since they can be damaged by radiation in radioactive waste, a method for estimating the bio-adsorbent performance as a time should consider the radiation damages in terms of their renewability. This paper aims to develop a simulation method that applies a deep learning technique to rapidly and accurately estimate the adsorption performance of bio-adsorbents when inserted into liquid radioactive waste. Materials and Methods: A model that describes various interactions between a bio-adsorbent and liquid has been constructed using numerical methods to estimate the adsorption capacity of the bio-adsorbent. To generate datasets for machine learning, Monte Carlo N-Particle (MCNP) simulations were conducted while considering radioactive concentrations in the adsorbent column. Results and Discussion: Compared with the result of the conventional method, the proposed method indicates that the accuracy is in good agreement, within 0.99% and 0.06% for the R² score and mean absolute percentage error, respectively. Furthermore, the estimation speed is improved by over 30 times. Conclusion: Note that an artificial neural network can rapidly and accurately estimate the survival rate of a bio-adsorbent from radiation ionization compared with the MCNP simulation and can determine if the bio-adsorbents are reusable.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.151-162
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• 2020

This paper presents an acoustic inversion method for estimating the bubble size distribution. The estimation error of the attenuation coefficient represented by a Fredholm integral equation of the first kind is defined as an objective function, and an optimal solution is found by applying the Levenberg-Marquardt (LM) method. In order to validate the effectiveness of the inversion method, numerical simulations using two types of bubble distribution are performed. In addition, a series of experiments are carried out in a water tank (1.0 m × 0.54 m × 0.6 m), using bubbles generated by three different generators. Images of the distributed bubbles are obtained by a high-speed camera, and the insertion losses of the bubble layer are measured using a source and a hydrophone. The image is post-processed to glance a distribution characteristics of each bubble generator. Finally, the size distribution of bubbles is estimated by applying the inversion method to the measured insertion loss. From the inversion results, it was observed that the number of bubbles increases exponentially as the bubble size decreases, and then increases again after the local peak at 70 ㎛ - 120 ㎛.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.13 no.3
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• pp.78-88
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• 2014

Now, UTIS collects and provides traffic information by building RSE 1,150(unit) and OBE about 51,000(vehicle). it's inevitable to enlarge traffic information sources which use to improve quality of UTIS traffic information for Stabilizing UTIS's service. but there are missing data sections. And, In this study as a way to overcome these problems, based on BIS(Bus information system) installed and operating in the capital area to develop normal vehicle's link transit time estimation model which is used realtime collecting BMS data, we'll utilize the model to provide missing data section's information. For these problem, we selected partial section of suwon-city, anyang-city followed by drive only way or not and conducted model estimating and verification each of BMS data and UTIS traffic information. Consequently, Case2,4,6,8 presented highly credibility between UTIS communication data and estimated value but In the Case 3,5 we determined to replace communication data of UTIS' missing data section too hard for large error. So we need to apply high credibility model formula adjusting road managing condition and the situation of object section.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.1
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• pp.85-93
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• 2015

Previous studies have estimated crash prediction models with the fixed effect model which assumes the fixed value of coefficients without considering characteristics of each intersections. However the fixed effect model would estimate under estimation of the standard error resulted in over estimation of t-value. In order to overcome these shortcomings, the random effect model can be used with considering heterogeneity of AADT, geometric information and unobserved factors. In this study, data collections from 89 intersections in Daejeon and estimates of crash prediction models were conducted using the random and fixed effect negative binomial regression model for comparison and analysis of two models. As a result of model estimates, AADT, speed limits, number of lanes, exclusive right turn pockets and front traffic signal were found to be significant. For comparing statistical significance of two models, the random effect model could be better statistical significance with -1537.802 of log-likelihood at convergence comparing with -1691.327 for the fixed effect model. Also likelihood ration value was computed as 0.279 for the random effect model and 0.207 for the fixed effect model. This mean that the random effect model can be improved for statistical significance of models comparing with the fixed effect model.