• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.121-132
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• 2018

Weather is an important factor affecting roadway transportation in many aspects such as traffic flow, driver 's driving patterns, and crashes. This study focuses on the relationship between weather and road surface condition and develops a model to estimate the road surface condition using machine learning. A road surface sensor was attached to the probe vehicle to collect road surface condition classified into three categories as 'dry', 'moist' and 'wet'. Road geometry information (curvature, gradient), traffic information (link speed), weather information (rainfall, humidity, temperature, wind speed) are utilized as variables to estimate the road surface condition. A variety of machine learning algorithms examined for predicting the road surface condition, and a two - stage classification model based on 'Random forest' which has the highest accuracy was constructed. 14 days of data were used to train the model and 2 days of data were used to test the accuracy of the model. As a result, a road surface state prediction model with 81.74% accuracy was constructed. The result of this study shows the possibility of estimating the road surface condition using the existing weather and traffic information without installing new equipment or sensors.

• Korean Chemical Engineering Research
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• v.59 no.1
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• pp.94-99
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• 2021

It was found that mixing patterns suddenly changed at an impeller rotation speed in a dished bottom vessel with dual Rushton turbines. Two isolated mixing regions like doughnuts rings generated at a low rotational speed and three isolated mixing regions generated at a higher speed. This phenomenon was observed at the mixing condition in transition area, where the power number with baffle was the same as that without baffle. We found a phenomenon in which the flow state in a dish-bottom agitation tank equipped with a two-stage Rushton turbine blade changes at a certain rotational speed. In the laminar flow region, the isolated stable donut rings were formed even when the rotational speed was changed, and no specific variation in the mixing pattern was observed. In the transition region, the two isolated thick unmixed donut rings do not change even if the rotation speed is changed in the flat bottom vessel, whereas in the dished bottom vessel, when the rotation speed is 450 rpm, the two isolated thick unmixed donut rings are changed to three isolated thin donut rings and then improved mixing. In the dished bottom vessel, in the range of Re=138~178, the isolated ring-shaped unmixed region appeared in three places and the size was also large. But in the flat bottom vessel, the isolated thick ring-shaped unmixed region appeared in two places in Re=116~176 and the size was also small. It appeared in two places, and the size was also small. The condition in which this phenomenon is observed is a transition region, and it was found that when the baffle plate is attached, the power number starts to increase compared to when the baffle plate is not present. In addition, when the mixing Reynolds number exceeded 300 and a slight turbulence was mixed in the flow state, the disconnection of these flow pattern was resolved and the mixture was completely mixed.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.19-26
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• 2021

Cultural assets excavated in historical areas have their own characteristics based on the background of the times, and it can be seen that their patterns and characteristics change little by little according to the history and the flow of the spreading area. Cultural properties excavated in some areas represent the culture of the time and some maintain their intact appearance, but most of them are damaged/lost or divided into parts, and many experts are mobilized to research the composition and repair the damaged parts. The purpose of this research is to learn patterns and characteristics of the past through artificial intelligence neural networks for such restoration research, and to restore the lost parts of the excavated cultural assets based on Generative Adversarial Network(GAN)[1]. The research is a process in which the rest of the damaged/lost parts are restored based on some of the cultural assets excavated based on the GAN. To recover some parts of dammed of cultural asset, through training with the 2D image of a complete cultural asset. This research is focused on how much recovered not only damaged parts but also reproduce colors and materials. Finally, through adopted this trained neural network to real damaged cultural, confirmed area of recovered area and limitation.

• Korean Journal of Optics and Photonics
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• v.33 no.4
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• pp.146-158
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• 2022

The detector of a focal-plane-array mid-wave infrared (MWIR) camera has different response characteristics for each detector pixel, resulting in nonuniformity between detector pixels. In addition, image nonuniformity occurs due to heat generation inside the camera during operation. To solve this problem, in the process of camera manufacturing it is common to use a gain-and-offset table generated from a blackbody to correct the difference between detector pixels. One method of correcting nonuniformity due to internal heat generation during the operation of the camera generates a new offset value based on input frame images. This paper proposes a technique for dividing an input image into block image patches and generating offset values using only homogeneous patches, to correct the nonuniformity that occurs during camera operation. The proposed technique may not only generate a nonuniformity-correction offset that can prevent motion marks due to camera-gaze movement of the acquired image, but may also improve nonuniformity-correction performance with a small number of input images. Experimental results show that distortion such as flow marks does not occur, and good correction performance can be confirmed even with half the number of input images or fewer, compared to the traditional method.

• Clean Technology
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• v.28 no.4
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• pp.293-300
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• 2022

The remarkable mechanical, electrical, and thermal properties of graphene have recently sparked tremendous interest in various research fields. One of the most promising methods to produce large quantities of graphene dispersion is liquid-phase exfoliation (LPE) which utilizes ultrasonic waves or shear stresses to exfoliate bulk graphite into graphene flakes that are a few layers thick. Graphene dispersion produced via LPE can be transformed into graphene ink to further boost graphene's applications, but producing high-quality graphene more economically remains a challenge. To overcome this shortcoming, an advanced LPE process should be developed that uses relatively cheap natural graphite as a graphene source. In this study, a flow-LPE process was used to exfoliate natural graphite to produce graphene that was three times cheaper and seven times larger than synthetic graphite. The optimal exfoliation conditions in the flow-LPE process were determined in order to produce high-quality graphene flakes. In addition, the structural and electrical properties of the flakes were characterized. The electrical properties of the exfoliated graphene were investigated by carrying out an ink formulation process to prepare graphene ink suitable for inkjet printing, and fabricating a printed graphene pattern. By utilizing natural graphite, this study offers a potential protocol for graphene production, ink formulation, and printed graphene devices in a more industrial-comparable manner.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.4
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• pp.109-118
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• 2022

The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.65-79
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• 2020

As Programmable Logic Controllers (PLCs), popular components in industrial control systems (ICS), are incorporated with the technologies such as micro-controllers, real-time operating systems, and communication capabilities. As the latest PLCs have been connected to the Internet, they are becoming a main target of cyber threats. This paper proposes two sanitizers that improve the security of uC/OS-II based firmware for a PLC. That is, we devise BU sanitizer for detecting out-of-bounds accesses to buffers and UaF sanitizer for fixing use-after-free bugs in the firmware. They can sanitize the binary firmware image generated in a desktop PC before downloading it to the PLC. The BU sanitizer can also detect the violation of control flow integrity using both call graph and symbols of functions in the firmware image. We have implemented the proposed two sanitizers as a prototype system on a PLC running uC/OS-II and demonstrated the effectiveness of them by performing experiments as well as comparing them with the existing sanitizers. These findings can be used to detect and mitigate unintended vulnerabilities during the firmware development phase.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6B
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• pp.653-663
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• 2008

The purpose of this study is to establish a database of weather, hydrology, point source pollution management, reservoir release and tillage management for SWAT model evaluation of Anseongcheon watershed ($370.1km^2$, the upstream of Gongdo water level gauging station), and to use them for the following research of future climate and land use change impact on streamflow and stream water quality. It is expected that the database can achieve the practical analysis of current watershed hydrologic and environmental condition. The model calibration and validation were conducted using the constructed database. The model results showed that the tillage management affected the temporal shift of pollutant loads, and changed the flow pattern of pollutant transport through cultivation area. It was identified that the April and May irrigation water supply from the agricultural reservoir also affected the streamflow of downstream. The data application of pollutants treatment facilities and tillage management of cultivation area showed about 10% difference in the simulation results of stream water quality. The data establishment of agricultural reservoir operation, the tillage management of cultivated area within the watershed and the attributes inclusion of pollutants treatment facilities were proved to be important in SWAT model evaluation. The results of model setup in this study are expected for more reliable model application in the following research of future climate and land use change impact on hydrology and stream water quality of the study watershed.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.446-454
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• 2023

The impact of climate change on agriculture is substantial, especially as global warming is projected to lead to varying temperature and humidity patterns in the future. These changes pose a higher risk for both crops and livestock, exposing them to environmental stressors under altered climatic conditions. Specifically, as temperatures are expected to rise, the risk of heat stress is assessable through the Temperature-Humidity Index (THI), derived from temperature and relative humidity data. This study involved the comparison of THI collected from 10 Korea Meteorological Administration ASOS stations spanning a 60-year period from 1961 to 2020. Moreover, high-resolution temperature and humidity distribution data from 1981 to 2020 were employed to generate high-resolution TH I distributions, analyzing temporal changes. Additionally, the number of days characterized by heat stress, derived from TH I, was compared over different time periods. Generally, TH I showed an upward trend over the past, albeit with varying rates across different locations. As TH I increased, the frequency of heat stress days also rose, indicating potential future cost increases in the livestock industry due to heat-related challenges. The findings emphasize the feasibility of evaluating heat stress risk in livestock using THI and underscore the need for research analyzing THI under future climate change scenarios.