• Restorative Dentistry and Endodontics
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• v.39 no.3
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• pp.155-163
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• 2014

Objectives: Light-curing of resin-based materials (RBMs) increases the pulp chamber temperature, with detrimental effects on the vital pulp. This in vitro study compared the temperature rise under demineralized human tooth dentin during light-curing and the degrees of conversion (DCs) of three different RBMs using quartz tungsten halogen (QTH) and light-emitting diode (LED) units (LCUs). Materials and Methods: Demineralized and non-demineralized dentin disks were prepared from 120 extracted human mandibular molars. The temperature rise under the dentin disks (n = 12) during the light-curing of three RBMs, i.e. an Ormocer-based composite resin (Ceram. X, Dentsply DeTrey), a low-shrinkage silorane-based composite (Filtek P90, 3M ESPE), and a giomer (Beautifil II, Shofu GmbH), was measured with a K-type thermocouple wire. The DCs of the materials were investigated using Fourier transform infrared spectroscopy. Results: The temperature rise under the demineralized dentin disks was higher than that under the non-demineralized dentin disks during the polymerization of all restorative materials (p < 0.05). Filtek P90 induced higher temperature rise during polymerization than Ceram.X and Beautifil II under demineralized dentin (p < 0.05). The temperature rise under demineralized dentin during Filtek P90 polymerization exceeded the threshold value ($5.5^{\circ}C$), with no significant differences between the DCs of the test materials (p > 0.05). Conclusions: Although there were no significant differences in the DCs, the temperature rise under demineralized dentin disks for the silorane-based composite was higher than that for dimethacrylate-based restorative materials, particularly with QTH LCU.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1267-1267
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• 2001

The existing fruit sorter has the method of tilting tray and extracting fruits by the action of solenoid or springs. In peaches, the most sort processing is supported by man because the sorter make fatal damage to peaches. In order to sustain commodity and quality of peach non-destructive, non-contact and real time based sorter was needed. This study was performed to develop peach sorter using near-infrared spectroscopy in real time and nondestructively. The prototype was developed to decrease internal and external damage of peach caused by the sorter, which had a way of extracting tray with it. To decrease positioning error of measuring sugar contents in peaches, fiber optic with two direction diverged was developed and attached to the prototype. The program for sorting and operating the prototype was developed using visual basic 6.0 language to measure several quality index such as chlorophyll, some defect, sugar contents. The all sorting result was saved to return farmers for being index of good quality production. Using the prototype, program and MLR(multiple linear regression) model, it was possible to estimate sugar content of peaches with the determination coefficient of 0.71 and SEC of 0.42bx using 16 wavelengths. The developed MLR model had determination coefficient of 0.69, and SEP of 0.49bx, it was better result than single point measurement of 1999's. The peach sweetness grading system based on NIR reflectance method, which consists of photodiode-array sensor, quartz-halogen lamp and fiber optic diverged two bundles for transmitting the light and detecting the reflected light, was developed and evaluated. It was possible to predict the soluble solid contents of peaches in real time and nondestructively using the system which had the accuracy of 91 percentage and the capacity of 7,200 peaches per an hour for grading 2 classes by sugar contents. Draining is one of important factors for production peaches having good qualities. The reason why one farm's product belows others could be estimated for bad draining, over-much nitrogen fertilizer, soil characteristics, etc. After this, the report saved by the peach grading system will have to be good materials to farmers for production high quality peaches. They could share the result or compare with others and diagnose their cultural practice.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.2
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• pp.127-133
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• 2011

A LabVIEW program has been developed together with simple infrared thermography(IRT) system to control the lock-in conditions of the system efficiently. The IR imaging software was designed to operate both of infrared camera and halogen lamp by synchronizing them with periodic sine signal based on thyristor(SCR) circuits. LabVIEW software was programmed to provide users with screen-menu functions by which it can change the period and energy of heat source, operate the camera to acquire image, and monitor the state of the system on the computer screen. In experiment, lock-in IR image for a specimen with artificial hole defects was obtained by the developed IRT system and compared with optical image.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1614-1614
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• 2001

The sweetness (。Bix) of fruit is the main quality factor contributing to the fruit taste. The brix of the apple fruit can be measured non-destructively by near infrared (NIR) spectroscopy, allowing the sweetness grading of individual apple fruit. However, the fruit quality is influenced by various factors such as growing location, producing year, variety and harvest time etc., accordingly the robust NIR calibration is required. In this experimental results are presented the influence of two variations such as growing location and producing year of apple fruit in establishing of calibrations for sweetness, and developed a stable and highly accurate calibration. Apple fruit (Fuji) was collected every year from 1995 to 1997 in 3 different growing locations (Andong, Youngchun and Chungsong) of Kyungpook in Korea. NIR reflectance spectra of apple fruit were scanned in wavelength range of 1100∼2500nm using an InfraAlyzer 500C (Bran+Luebbe) with halogen lamp and PbS detector. The multiple linear regression and stepwise was carried out between the NIR raw spectra and the brix measured by refractometer to select the best regression equations. The calibration models by each growing district were well predicted to dependent sample set, but poorly predicted to independent sample set. Combined calibration model using data of three growing districts predicted reasonable well to a population set drawn from all growing districts(SEP = 0.69%, Bias=-0.075). The calibration models by each harvest year were not transferable across harvest year, however a combined calibration model using data of three harvest years was sufficiently robust to predict each sample sets(SEP = 0.53%, Bias = 0.004).

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1528-1528
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• 2001

Ginseng cultivated in different country or growing condition has generally different components such as saponin and protein, and it relates to efficacy and action. Protein content assumes by nitrogen content in ginseng radix. Nitrogen content could be determined by chemical analysis such as kjeldahl or extraction methods. However, these methods require long analysis time and result environmental pollution and sample damage. In this work we investigated possibility of non-destructive determination of nitrogen content in ginseng radix using near-infrared spectroscopy. Ginseng radix, root of Panax ginseng C. A. Meyer, was studied. Total 120 samples were used in this study and it was consisted of 6 sample sets, 4, 5 and 6-year-old Korea ginseng and 7, 8 and 9-year-old China ginseng, respectively. Each sample set has 20 sample. Nigrogen content was measured by electronic analysis. NIR reflectance spectra were collected over the 1100 to 2500 nm spectral region with a InfraAlyzer 500C (Bran+Luebbe, Germany) equipped with a halogen lapmp and PbS detector and data were collected every 2 nm data point intervals. The calibration models were carried out by multiple linear regression (MLR) and partial least squares (PLS) analysis using IDAS and SESAME software. Result of electronic analysis, Korean ginseng were different mean value in nitrogen content of China ginseng. Ginseng tend to generally decrease the nitrogen content according as cultivation year is over 6 years. The MLR calibration model with 8 wavelengths using IDAS software accurately predicted nitrogen contents with correlation coefficient (R) and standard error of prediction of 0.985 and 0.855%, respectively. In case of SESAME software, the MLR calibration with 9 wavelength was selected the best calibration, R and SEP were 0.972 and 0.596%, respectively. The PLSR calibration model result in 0.969 of R and 0.630 of RMSEP. This study shows the NIR spectroscopy could be applied to determine the nitrogen content in ginseng radix with high accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1354-1358
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• 2008

Environmental-friendly nontocxic flame retardant paint which can overcomes the restriction of harmful materials for human body and environments such as Pb, Hg, Cd, $C^{+6}$, PBB/PBDE by EU and domestic Ministry of Environment was developed. Developed paint is the water-soluble organic inorganic hybrid material that VOC(volatility organic compound) discharge is low, and that human riskiness and environmental pollution is minimized not using the kinds of halogen materials. $Mg(OH)_2$, $Sb_{2}O_{3}$, and Zinc borate were used as flame retardant materials, 2% Micell and water were used as binder and solvent, respectively. Results showed the optimum activity was obtained when the ratio of those frame retardant agents($Mg(OH)_2$, $Sb_{2}O_{3}$, Zinc borate made by 1: 2: 2), binder(2% Micell) and water was 1: 0.5: 0.5.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.87-94
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• 2018

Purpose: In this study, the defect quantification of thin metal plate was evaluated by using lock-in infrared thermography. Methods: A STS304 standard specimens, which had the artificial-defects of different size, were used. The focal distance between the infrared camera and the specimen was set to 500mm, and the distance between the lump and the specimen was set to 200mm. One halogen lamp with a maximum capacity of 1kW was used, and phase-lock infrared thermal images with a frequency of 1Hz were captured and analyzed. Result: Objectively quantified data values were obtained by analyzing the contrast ratio and signal-to-noise ratio. Conclusion: The possibility of defect diagnosis for thin metal plate was confirmed by using the lock-in infrared thermography technique.

• Transactions of the Korean hydrogen and new energy society
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• v.22 no.4
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• pp.451-457
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• 2011

Purple non-sulfur (PNS) bacterium $Rhodobacter$ $sphaeroides$ KD131 was studied with the aim of achieving maximum hydrogen production using various carbon and nitrogen sources at different pH conditions. Cells grew well and produced hydrogen using $(NH_4){_2}SO_4$ or glutamate as a nitrogen source in combination with a carbon substrate, succinate or malate. During 48h of photo-heterotrophic fermentation under 110$W/m^2$ illumination using a halogen lamp at $30^{\circ}C$, 67% of 30mM succinate added was degraded and the hydrogen yield was estimated as 3.29mol $H^2$/mol-succinate. However, less than 30% of formate was consumed and hydrogen was not produced due to a lack of genes coding for the formate-hydrogen lyase complex of strain KD131. Initial cell concentrations of more than 0.6g dry cell weight/L-culture broth were not favorable for hydrogen evolution by cell aggregation, thus leading to substrate and light unavailability. In a modified Sistrom's medium containing 30mM succinate with a carbon to nitrogen ratio of 12.85 (w/w), glutamate produced 1.40-fold more hydrogen compared to ammonium sulfate during the first 48h. However, ammonium sulfate was 1.78-fold more effective for extended cultivation of 96h. An initial pH range from 6.0 to 9.0 influenced cell growth and hydrogen production, and maintenance of pH 7.5 during photofermentation led to the increased hydrogen yield.

• Elastomers and Composites
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• v.38 no.1
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• pp.72-80
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• 2003

Phosphoric ester compound was employed as thermal resistant and flame retardant for chlorinated polyethylene(CPE) rubber material which is used to prepare automotive oil cooler hose. Cure characteristics, physical properties, thermal resistance, and flame retardation of CPE rubber compounds were investigated. CPE rubber which has excellent properties such as cold resistance and chemical corrosion resistance, and is inexpensive in price than existing ethyleneacrylate rubber(EAR) was used to prepare a rubber compound useful for hose. A non-halogen flame retarding agent N,N'-bis- (diphenylphosphoro) diaminohexane(BDPDH), which is condensed phosphoric ester, was synthesized and it was mixed to CPE rubber material with the range of $0{\sim}30 phr$. From the test results, rheological properties, heat resistance, and flame retardance of CPE rubber compounds were found out to be much increased. The optimum content of BDPDH to rubber which gives maximum effect on thermal resistance and flame retardation, within the range of tolerable specification for rubber materials, was determined to be 20 phr.

• Smart Structures and Systems
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• v.33 no.1
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• pp.55-64
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• 2024

This paper proposes a fusion imaging-based coating-defect classification method for steel structures that uses zero-shot learning. In the proposed method, a halogen lamp generates heat energy on the coating surface of a steel structure, and the resulting heat responses are measured by an infrared (IR) camera, while photos of the coating surface are captured by a charge-coupled device (CCD) camera. The measured heat responses and visual images are then analyzed using zero-shot learning to classify the coating defects, and the estimated coating defects are visualized throughout the inspection surface of the steel structure. In contrast to older approaches to coating-defect classification that relied on visual inspection and were limited to surface defects, and older artificial neural network (ANN)-based methods that required large amounts of data for training and validation, the proposed method accurately classifies both internal and external defects and can classify coating defects for unobserved classes that are not included in the training. Additionally, the proposed model easily learns about additional classifying conditions, making it simple to add classes for problems of interest and field application. Based on the results of validation via field testing, the defect-type classification performance is improved 22.7% of accuracy by fusing visual and thermal imaging compared to using only a visual dataset. Furthermore, the classification accuracy of the proposed method on a test dataset with only trained classes is validated to be 100%. With word-embedding vectors for the labels of untrained classes, the classification accuracy of the proposed method is 86.4%.