• Restorative Dentistry and Endodontics
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• v.18 no.2
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• pp.483-496
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• 1993

Dentin hypersensitivity medicaments such as Gluma, Scotchbond 2, All-Bond 2, which are resin adhesives, were used to compare the sealing effects of dentinal tubule under mechanical stress. Topical application of above medicaments on the dentin surfaces of extracted teeth followed by artificial tooth brushing for 6 weeks was performed for the comparison. The following conclusions on the degree of dentinal tubule exposure versus time by were reached by using polyvinyl siloxane impression material for taking the impression, epoxy resin for the duplication and SEM for observing the surface. 1. SEM was used to compare the accuracy of the duplicated surface, but no differences were found when teeth samples and the duplicated surfaces were observed. 2. After comparing the degree of dentinal tubules exposure with varnish applied contrast group, resin adhesive materials showed much less exposure as time went by. 3. The results indicated that AU-Bond 2 adhesive, under mechanical stress, showed lesser exposure of dentinal tubules comparing with Gluma and Scotchbond 2 adhesives After the results were put together, it was demonstrated that resin replica method is an useful way to evaluate the treatment effects of the dentinal tubule hypersensitivity medicaments. Also, it was noticed that under mechanical stress, All-Bond 2, classified as fourth generation, illustrated the best dentinal tubules sealing effects.

• Journal of the Ergonomics Society of Korea
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• v.18 no.1
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• pp.133-147
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• 1999

Traffic signs without a cognitive consideration in their design may cause information-processing problem that could result in a mental confusion among drivers often lead to a serious traffic accident. Therefore, in this study, several traffic signs currently used in Seoul Metropolitan area have been sampled and analyzed to identify design problems that usually caused by neglecting drivers cognitive ability. To classify the practical design problems, five major information-processing problems have been suggested: indistinguishable information, information conflict, missing information, sign-load mismatch, and information overload. In order to solve these cognitive problems, new traffic signs have been suggested in this study. An experiment was also performed to validate the new traffic sign. Twenty-four healthy subjects participated in the experiment. They were asked to answer the Question after observing the traffic signs continuously displayed on computer screen. The result indicated that subjects improved the accuracy in understanding the signs by 1.4 times when they used the suggested traffic sign compared to the old one. Based upon the results, a cognitive guideline was suggested for correct and speedy reading of traffic signs by improving information processing and reducing of human error. In conclusion, the traffic sign may well be applied to design an intelligent traffic sign system to increase the safety and comfort of drivers, especially in complex load condition.

• Proceedings of the Materials Research Society of Korea Conference
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• 2009.05a
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• pp.15.2-15.2
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• 2009

Manufacturing of printed electronics using printing technology has begun to get into the hot issue in many ways due to the low cost effectiveness to existing semi-conductor process. This technology with both low cost and high productivity, can be applied in the production of organic thin film transistor (OTFT), solar cell, radio frequency identification (RFID) tag, printed battery, E-paper, touch screen panel, black matrix for liquid crystal display (LCD), flexible display, and so forth. The emerging technology to manufacture the products in mass production is roll-to-roll printing technology which is a manufacturing method by printings of multi-layered patterns composed of semi-conductive, dielectric and conductive layers. In contrary to the conventional printing machines in which printing precision is about $50~100{\mu}m$, the printing machines for printed electronics should have a precision under $30{\mu}m$. In general, in order to implement printed electronics, narrow width and gap printing, register of multi-layer printing by several printing units, and printing accuracy of under $30{\mu}m$ are all required. We developed the roll-to-roll printing equipment used for printed electronics, which is composed of un-winder, re-winder, tension measurement system, feeding units, dancer systems, guide unit, printing unit, vision system, dryer units, and various auxiliary devices. The equipment is designed based on cantilever type in which all rollers except printing ones have cantilever types, which could give more accurate machine precision as well as convenience for changing rollers and observing the process.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.42-53
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• 1999

Two dimensional flame temperature and KL value distribution from the luminous flame containing soot in a DI diesel engine were measured by the tow-color method using tow different wavelengths of the flame image. The combustion chamber of a DI diesel engine was visualized by elongating the piston and cylinder and the flame in the combustion chamber was photographed on a nega-color film using a high speed camera. In this study, color CCD camera was used to digitize the three color density of the film exposed to the flame and standard lamp . The accuracy of the measuring method depends on the calibration line of film made from a high temperature standard tungsten lamp. The formation and oxidization of soot in the diesel engine were studied by observing measured time history of KL factor and flame temperature . Also , effects of various shapes of combustion chamber and fuel injection on flame temperature. Also, effects of various shapes of combustion chamber and fuel injection on flame temperature and KL value distribution were examined.

• Journal of the Korea Convergence Society
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• v.9 no.3
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• pp.15-21
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• 2018

The ocean drifter is a device for observing the ocean weather by floating off the sea surface. The data observed through the drifter is utilized in the ocean weather prediction and oil spill. Observed data may contain incorrect or missing data at the time of observation, and accuracy may be lowered when we use the data. In this paper, we propose a data correction model using recurrent neural networks. We corrected data collected from 7 drifters in 2015 and 8 drifters in 2016, and conducted experiments of drifter moving prediction to reflect the correction results. Experimental results showed that observed data are corrected by 13.9% and improved the performance of the prediction model by 1.4%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3851-3866
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• 2015

The dynamic nature of opportunistic networks results in long delays, low rates of success for deliveries, etc. As such user experience is limited, and the further development of opportunistic networks is constrained. This paper proposes a prediction-based routing method for opportunistic networks (PB-OppNet). Firstly, using an ARIMA model, PB-OppNet describes the historical contact information between a node pair as a time series to predict the average encounter time interval of the node pair. Secondly, using an optimal stopping rule, PB-OppNet obtains a threshold for encounter time intervals as forwarding utility. Based on this threshold, a node can easily make decisions of stopping observing, or delivering messages when potential forwarding nodes enter its communication range. It can also report different encounter time intervals to the destination node. With the threshold, PB-OppNet can achieve a better compromise of forwarding utility and waiting delay, so that delivery delay is minimized. The simulation experiment result presented here shows that PB-OppNet is better than existing methods in prediction accuracy for links, delivery delays, delivery success rates, etc.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.199-209
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• 2006

The Global Land Cover 2000 (GLC 200) project, as a most recent issue, is to provide for the year 2000 a harmonized land cover database over the whole globe. The classifications were performed according to continental or regional scales by corresponding organization using the data of VEGETATION sensor onboard the SPOT4 Satellite. Even if the global land cover classification for Asia provided by Chiba University showed a good accuracy in whole Asian area, some problems were detected in Korean region. Therefore, the construction of new land cover database over Korea is strongly required using more recent data set. The present study focuses on the development of a new upgraded land cover map at 1 km resolution over Korea considering the widely used K-means clustering, which is one of unsupervised classification technique using distance function for land surface pattern classification, and the principal components transformation. It is based on data sets from the Earth observing system SPOT4/VEGETATION. Newly classified land cover was compared with GLC 2000 for Korean peninsula to access how well classification performed using confusion matrix.

• Journal of the Korean Wood Science and Technology
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• v.49 no.5
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• pp.491-503
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• 2021

Wood identification is regularly performed by observing the wood anatomy, such as colour, texture, fibre direction, and other characteristics. The manual process, however, could be time consuming, especially when identification work is required at high quantity. Considering this condition, a convolutional neural networks (CNN)-based program is applied to improve the image classification results. The research focuses on the algorithm accuracy and efficiency in dealing with the dataset limitations. For this, it is proposed to do the sample selection process or only take a small portion of the existing image. Still, it can be expected to represent the overall picture to maintain and improve the generalisation capabilities of the CNN method in the classification stages. The experiments yielded an incredible F1 score average up to 93.4% for medium sample area sizes (200 × 200 pixels) on each CNN architecture (VGG16, ResNet50, MobileNet, DenseNet121, and Xception based). Whereas DenseNet121-based architecture was found to be the best architecture in maintaining the generalisation of its model for each sample area size (100, 200, and 300 pixels). The experimental results showed that the proposed algorithm can be an accurate and reliable solution.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.85-96
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• 2023

The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

• Analytical Science and Technology
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• v.36 no.2
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• pp.80-88
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• 2023

Fingerprints play a crucial role in the identification of potential suspects in criminal cases. However, determining the actual time, i.e., the time at which the fingermark was deposited, is challenging. Herein, we investigated the persistence and aging of fingerprints over time by observing the time evolution of latent fingerprints on a polystyrene box stored in a dark room. Fingerprint samples that were stored for up to two years could be detected with maximum accuracy using a black iron-oxide-based emulsion (black emulsion). To estimate the time of fingerprint deposition, fingerprint aging was studied by analyzing the lipid components of the fingerprints after their development. Cholesterol and squalene were selected as indicators of fingerprint aging, and their ratio was estimated to assess aging. In the case of fingerprint samples stored in a dark room for up to one month after deposition, the cholesterol/squalene ratio was approximately 0.01; it increased gradually to ≥ 0.1 over six months. A substantial reduction in the levels of cholesterol and squalene from the initial levels was also noted. Cholesterol and squalene were not detected after one year of storage. Thus, the extent of aging could be determined by analyzing the aging indicators for up to six months. Two cases that could cause error in the estimation of the fingerprint deposition time, namely, heating of the fingerprint sample before development and storage of the developed fingerprints in a dark room, were also investigated.