• Korean Journal of Construction Engineering and Management
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• v.20 no.6
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• pp.34-43
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• 2019

The maintenance cost for road pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance preventive maintenance requires the establishment of a strategic plan through accurate prediction of road pavement. Hence, In this study, the deep neural network(DNN) and the recurrent neural network(RNN) were used in order to develop the expressway pavement damage prediction model. A superior model among these two network models was then suggested by comparing and analyzing their performance. In order to solve the RNN's vanishing gradient problem, the LSTM (Long short-term memory) circuits which are a more complicated form of the RNN structure were used. The learning result showed that the RMSE value of the RNN-LSTM model was 0.102 which was lower than the RMSE value of the DNN model, indicating that the performance of the RNN-LSTM model was superior. In addition, high accuracy of the RNN-LSTM model was verified through the comparison between the estimated average road pavement condition and the actually measured road pavement condition of the target section over time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.681-687
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• 2013

This study examined whether the combination of the indoor temperature on the learning environment and the colors of the learning materials affect the learning performance. To do this, the condition of indoor temperature was divided into three conditions: the neutral condition which is the appropriate temperature condition of the learning activities ($22.5{\sim}24^{\circ}C$), the high-temperature condition (> $24^{\circ}C$), and the low-temperature condition (< $22.5^{\circ}C$). In addition, colors of red, blue, black, and green were used as the warm, cold, and neutral colors, and the verbal-working memory task was used as the learning task. As a result, it was not significant differences in the response time of the learning task, whereas, in the accuracy rate of the learning task, the performance was more accurate in red- and black-color conditions. These results could be interpreted as the saliency and color-temperature of the red color, and the familiarity and specificity of the black color.

• Fashion & Textile Research Journal
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• v.2 no.3
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• pp.220-226
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• 2000

This study was to determine the characteristics of vapor-permeable waterproof finished fabric by the coating method. 4 different kinds of coating fabrics (A : wet, porous, polyurethane, B : dry, no porous, polyurethane, C : shape memory polyurethane and D : dry, porous polyurethane) were used, which were developed recently With this sample, moisture transport rate ($40^{\circ}C$, 45%RH & $40^{\circ}C$, 95%RH), changes of coating side's shape by washing times, water repellency rate, contracted length, qmax, heat conductivity, heat keeping rate, heat keeping rate with cotton, heat keeping rate on humidity temperature and humidity within clothing etc. were checked. And it was done in a climate chamber under $20{\pm}2^{\circ}C$, $65{\pm}5%RH$. The results of this study were as follow; In the moisture vapor transmission of sample B and C increased on high temperature and high humidity while sample A and D decreased, on this condition. Qmax rate had high relation with ground fabric's surface properties and the order was A>C>D>B. Heat conductivity had high relation with thickness and surface properties. Heat keeping rates on sweat condition showed around half percents of heat keeping rates on normal condition, but had no relation with moisture vapor transport rate. Changes of the fabric's properties by washing times were different in accordance with the construction of fabrics and the coating resin. Sample C had tow heat keeping rate on the high temperature and humidity and high heat keeping rate on the low temperature and humidity Moisture transport rate of vapor-permeable waterproof finished fabrics had high relation with the properties of ground fabrics on low humidity condition, but on the high humidity condition, it was highly related with the properties of coating resin.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.77-87
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• 2023

Wind turbines playing a critical role in renewable energy generation, accurately assessing their operational status is crucial for maximizing energy production and minimizing downtime. This study conducts a comparative analysis of different neural network models for wind turbine condition diagnosis, evaluating their effectiveness using a dataset containing sensor measurements and historical turbine data. The study utilized supervisory control and data acquisition data, collected from 2 MW doubly-fed induction generator-based wind turbine system (Model HQ2000), for the analysis. Various neural network models such as artificial neural network, long short-term memory, and recurrent neural network were built, considering factors like activation function and hidden layers. Symmetric mean absolute percentage error were used to evaluate the performance of the models. Based on the evaluation, conclusions were drawn regarding the relative effectiveness of the neural network models for wind turbine condition diagnosis. The research results guide model selection for wind turbine condition diagnosis, contributing to improved reliability and efficiency through advanced neural network-based techniques and identifying future research directions for further advancements.

• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.153-160
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• 2008

Seismic modeling is used to simulate wave propagation in the earth. Although the earth's subsurface is usually semi-infinite, we cannot handle the semi-infinite model in seismic modeling because of limited computational resources. For this reason, we usually assume a finite-sized model in seismic modeling. In that case, we need to eliminate the edge reflections arising from the artificial boundaries introducing a proper boundary condition. In this study, we changed three kinds of boundary conditions (sponge boundary condition, Clayton and Engquist's absorbing boundary condition, and Higdon's transparent boundary condition) so that they can be applied in elastic wave modeling for anisotropic media. We then apply them to several models whose Poisson's ratios are different. Clayton and Engquist's absorbing boundary condition is unstable in both isotropic and anisotropic media, when Poisson's ratio is large. This indicates that the absorbing boundary condition can be applied in anisotropic media restrictively. Although the sponge boundary condition yields good results for both isotropic and anisotropic media, it requires too much computational memory and time. On the other hand, Higdon's transparent boundary condition is not only inexpensive, but also reduce reflections over a wide range of incident angles. We think that Higdon's transparent boundary condition can be a method of choice for anisotropic media, where Poisson's ratio is large.

• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.59-65
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• 2016

The result of analyzing the cognitive reaction due to the color environment has been applied to various filed especially in medical field. Moreover, the study about the identification of patient's condition and examination the brain activity by collecting the bio-signal based on the color environment is being actively conducted. Even though, there were a variety of experiments by convention the color environment using a light or LED color, it still has a problem that affects the psychological information. Therefore, our proposed system using a HMD (Head Mounting display) to provide a completed color environment condition. This system uses the BMS(Biomedical System) to collect the biometric information which responds to the specific color condition and the human body response information can be measured by the development the Memory and Attention test on Mobile phone. The collection of Biometric information includes electro cardiogram(ECG), respiration, oxygen saturation (Sp02), Bio-impedance, blood pressure will store in the database. In addition, we can verify the result of the human body reaction in the color environment by Memory and Attention application. By utilizing the reaction of the human body information that is collected thought the proposed system, we can analyze the correlation between the physiological information and the color environment. And we also expect that this system can apply to the medical diagnosis and treatment. For future work, we will expand the system for prediction and treatment of Alzheimer disease by analyzing the visualization data through the proposed system. We will also do evaluation on the effectiveness of the system for using in the rehabilitation program.

• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.425-434
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• 2011

In the present study was to examine the influence of cold stress conditions on memory function in relation with 5-hydroxytryptamine(serotonin, 5-HT), trptophanhydroxylase(TPH) expression and cell proliferation in the hippocampus. For this study, male Sprague-Dawley rats weighing $250{\pm}10g$ (7 weeks in age) were used. The rats were randomly divided into three groups(n = 10 in each group): the $22^{\circ}C$-control group, the $4^{\circ}C$-3 days group, the $4^{\circ}C$-5 weeks group. The environmental temperature at $22^{\circ}C$ set as the normal conditions, $4^{\circ}C$ was as the cold stress conditions. The present results showed that cold stress conditions shorten latency, representing cold stress disturbed memory function. 5-HT and TPH expressions in the dorsal raphe were increased cold stress. Neurogenesis in the dentate gyrus was increased under cold conditions. The present study revealed that cold stress exerted deteriorative memory function. However, through increasing of 5-HT, TPH and BrdU expression under cold stress conditions did not show memory enhancing effect.

• Science of Emotion and Sensibility
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• v.21 no.3
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• pp.151-164
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• 2018

The appropriate interpretation of social cues is a crucial ability for everyday life. While processing socially relevant information, beyond the low-level physical features of the stimuli to emotional information is known to influence human cognition in various stages, from early perception to later high-level cognition, such as working memory (WM). However, it remains unclear how the influence of each type of emotional information on cognitive processes changes in response to what has occurred in the processing stage. Past studies have largely adopted face stimuli to address this type of research question, but we used a unique class of socially relevant motion stimuli, called biological motion (BM), which depicts various human actions and emotions with moving dots to exhibit the effects of anger, happiness, and neutral emotion on task performance in perceptual and working memory. In this study, participants determined whether two BM stimuli, sequentially presented with a delay between them (WM task) or one immediately after the other (perceptual task), were identical. The perceptual task showed that discrimination accuracies for emotional stimuli (i.e., angry and happy) were lower than those for neutral stimuli, implying that emotional information has a negative impact on early perceptual processes. Alternatively, the results of the WM task showed that the accuracy drop as the interstimulus interval increased was actually lower in emotional BM conditions than in the neutral condition, which suggests that emotional information benefited maintenance. Moreover, anger and happiness had distinct impacts on the performance of perception and WM. Our findings have significance as we provide evidence for the interaction of type of emotion and information-processing stage.

• Science of Emotion and Sensibility
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• v.18 no.2
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• pp.85-100
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• 2015

This study aimed at examining if the original memory remains after a misinformation is presented, using Event-Related Potential based Concealed Information Test (ERP-based CIT). In the first stage of the study, the participant was presented with either the original information or a misleading information after experiencing an event (Post-information). The second stage was to measure brain wave and reaction time on the original, misleading, and irrelevant information (CIT-Stimulus). P300 amplitude, P300 area, P300 latency, and reaction time were used as dependant variables. In the result, a significant Post-information ${\times}$ CIT-Stimulus interaction effect was found on the P300 area measured at Cz, Pz, and Oz area. This interaction effect implied the possibility that the original information could be partially impaired in memory by misleading information presented afterward. P300 amplitude at Pz area did not differ between the accurate and the misleading stimuli in the condition in which a misleading information was presented. This result can be explained by source monitoring error. In discussion, the limitations of this study and directions of future studies were discussed.

• Progress in Medical Physics
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• v.26 no.2
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• pp.72-78
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• 2015

Organic solvents are known toxic effects like vertigo, behavioral obstacle, distracting, and peripheral neuropathy in neuron areas. However, there have been few studies how neurotoxic solvents-exposed workers are affected by the cognitive load of preceding working memory tasks. Therefore, we used fMRI as to measure the neural correlates of working memory impairment in occupational workers who had from chronic exposure to organic solvent. Twenty-nine solvent-exposed workers were included in this study. Each participant concluded the verbal N-back tasks (1- and 2-back) during the fMRI acquisition. Within-group analyses showed fronto-parietal networks were active in each condition. Direct comparisons between 1- and 2-back showed higher activation during the 2-back than 1-back. We found that increased activation of these regions at lower task demand is associated with increased cost of implementing.