The objectives of this study was to evaluate the durability of 4 resin cements by means of microtensile bond strength test combined with thermocycling method and fractographic FE-SEM analysis. Experimental groups were prepared according to thermocycling (0, 1,000, 5,000) and the kind of resin cements, those were Variolink II, Multilink, Panavia F 2.0, Rely X Unicem. Flat dentin surfaces were created on mid-coronal dentin of extracted third molars. Then fresh dentin surface was grounded with 320-grit silicon carbide abrasive papers to create uniform smear layers. Indirect composite block (Tescera, Bisco Inc., Schaumburg, IL, USA) was fabricated ($12\;{\times}\;12\;{\times}\;6\;mm^3$). It's surface for bonding to tooth was grounded with silicon carbide abrasive papers from 180- to 600-grit serially, then sandblasted witk $20\;-\;50\;{\mu}m$ alumina oxide. According to each manufacturer's instruction, dentin surface was treated and indirect composite block was luted on it using each resin cement. For Rely X Unicem, dentin surface was not treated. The bonded tooth-resin block were stored in distilled water at $37^{\circ}C$ for 24 hours. After thermocycling, the bonded tooth-resin block was sectioned occluso-gingivally to 1.0 mm thick serial slabs using all Isomet slow-speed saw (Isomet, Buehler Ltd, Lake Bluff, IL, USA). These sectioned slabs were further sectioned to $1.0\;{\times}\;1.0\;mm^2$ composite-dentin beams. The specimens were tested with universal testing machine (EZ-Test, Shimadzu, Japan) at a crosshead speed of 1.0 mm/min with maximum load of 500 N. The data was analyzed using one-way ANOVA and Duncan's multiple comparison test at $p\;{\leq}\;0.05$ level. Within the limited results, we conclude as follows; 1. The bond strength of Variolink II was evaluated the highest among experimental groups and was significantly decreased after 1,000 thermocycling (p < 0.05). 2. The bond strength of Multilink was more affected by thermocycling than the other experimental groups and significantly decreased after 1,000 thermocycling (p < 0.05). 3. Panavia F 2.0 and Rely X Unicem showed the gradually decreased tendency of microtensile bond strength according to thermocycling but there was no significant difference (p > 0.05). 4. Adhesive based-resin cements showed lower bond strength with or without thermocycling than composite based-resin cements. 5. Variolink II & Multilink showed high bond strength and mixed failure, which was occurred with a thin layer of luting resin cement before thermocycling and gradually increased adhesive failure along the dentin surface after thermocycling. The bonding performance of resin cement can be affected by application procedure and chemical composition. Composite based-resin cement showed higher bond strength and durability than adhesive based-resin cement.
Background: Effective cardiopulmonary resuscitation (CPR) should provide acceptable hemodynamics for the vital organs during cardiac arrest and early restoration of spontaneous circulation that guarantees long-term, neurologically intact survival. CPR using heart-lung bypass has been suggested as an option for that use. This study was designed to determine the effectiveness of standard CPR techniques, closed-vs. open-chest CPR, which could be used in the future study verifying the role of heart-lung bypass CPR. Material and Method: By using adult mongrel dogs, closed-chest CPR (CCCPR, n=4) and open-chest CPR (OCCPR, n=5) were compared with respects to hemodynamics, restoration of spontaneous circulation(ROSC), and survival. Ventricular fibrillation-cardiac arrest (VF-CA) was induced by electrical shock in all animals. After 4 minutes of cardiac arrest, basic life support (BLS) was applied for 15 minutes and followed by advanced life support (ALS). ALS was maintained until achi ving ROSC but not longer than 30 minutes regardless of the recovery. Resuscitation procedures in either group were standardized by adopting the protocol of American Heart Association. Result: Prearrest baseline hemodynamic data was not different between two groups. During resuscitation, substantially higher systolic pressure was maintained in OCCPR group than in CCCPR group (45$\pm$15 vs. 33$\pm$11 mmHg during BLS, 83$\pm$36 vs. 44$\pm$15 mmHg during ALS; p=NS). Mean pulmonary arterial pressure went up to the level of mean systemic arterial pressures in CCCPR group and to half of that in OCCPR group, and had kept higher in CCCPR group throughout CPR (32$\pm$10 vs. 22$\pm$4 mmHg during BLS and 32$\pm$15 vs. 24$\pm$10 mmHg during ALS; p=NS). ROSC was obtained in 4 of 5 dogs receiving open-chest CPR and 2 of 4 closed-chest CPR. Prolonged survival was noted in all dogs in OCCPR group (6 to 1440 hours) but not in CCPR group (p<.05). Conclusion: These findings indicate that open-chest CPR can be more effective t maintain hemodynamics during cardiac arrest and to obtain restoration of spontaneous circulation and survival. Further experiment will be designed to compare heart-lung bypass CPR with open-chest CPR.
Purpose As medical radiation exposures on patients are being social issues an interest in a relief of radiation exposures on patients is increasing. Further, there are many cases where some patients among who are getting PET/CT tests choose to get implanted with metal artifacts in their bodies. This study is to find out effects of presence or absence of metal artifacts when dose change or CT attenuation correction for the relief of radiation exposures are applied using phantoms through changes in standard uptake value (SUV). Materials and Methods GE company's Discovery 710 machine was used for PET/CT test equipments. We used NEMA IEC body phantoms. We also used screw and mesh cage made of titanium which are used in real clinical processes for the metal artifacts. Two experiments were conducted: One is to test and measure repeatedly about SUV about differences in CT attenuation corrections according to dose changes and another is to do the same procedure for SUV about the presence and absence of the metal artifacts. We injected $^{18}F-FDG$ into NEMA IEC body phantoms with a TBR ratio of 4:1 and then put the metal material into the transformation phantoms. Once a scanning for the metal artifacts was done we eliminated the metal artifacts and went on non-metal artifacts. For the each two experiments, we scanned repeatedly with CT kVp (140, 120, 100, 80) and mA (120, 80, 40, 20, 10) for an experimental condition. For PET, we reconstructed each with standard AC (STD) technique and quantitation achieved cnsistently QAC) technique among CT attenuation correction methods. We conducted a comparative analysis on measured average values and variations which were measured through repeated measure of SUV of region 1, 2, 3 spheres for each conditions of non-metal /metal scan. Results For each kVp, 120, 80, 40 (mA) of non/metal (screw, mesh cage) showed low frequency of fluctuation rates of above 2%. In 20, 10 mA above 2% of fluctuation rates appeared in high frequency. Also, when we compared the fluctuation rates of STD and QAC techniques in non/metal (screw, mesh cage) tests QAC technique showed about 1-10% of differences for each conditions compared to STD technique. In addition, metal types did not have significant effects on fluctuation rates. Conclusion We confirmed that SUV fluctuation rates for both STD and QAC techniques increase as dosage is lower. We also found that the SUV of PET data was maintained steadily in a low dosage for QAC technique when compared with STD technique. Hence, when the low dosage is used for the relief of radiation exposures on patients QAC technique may be exploited helpfully and this could be applied in the same way for patients with metal artifacts implanted in their bodies.
The purpose of this study is to investigate the effect of number of times dipped in coloring liquid and sintering temperature on the flexural strength of zirconia ceramic. In this study, using a zirconia block having improved transparency, specimens with size of $25mm{\times}2mm{\times}1.5mm$ were fabricated. The zirconia ceramic specimens were divided into three groups according to the number of times dipped in coloring liquid by 0, 2 and 4 times, and dyed in the coloring liquid to give color to each specimen. Then, after sintering them at the final temperature of $1,450^{\circ}C$ and $1,600^{\circ}C$, flexural strength was measured using a universal testing machine (total 6 group, n=10 for each group). Also, a scanning electron microscopy (SEM) was performed to observe its microstructure, and the data obtained through the experiment were analyzed with two-way ANOVA. The results of the flexural strength analysis show that the highest value was measured $762.3{\pm}42.3MPa$ in EKL2 group, while the lowest value was $516.4{\pm}77.1MPa$ in EKH4 group. According to the results of the two-way ANOVAs, flexural strength was not related with interaction between sintering temperature and number of times dipped in coloring liquid ($R^2=0.737$). However, there were statistically significant differences in flexural strength depending on sintering temperature (P<0.001). The flexural strength of zirconia ceramics having improved transparency was dependent on sintering temperature. The number of times dipped in the coloring liquid did not affect flexural strength of the zirconia ceramic having improved transparency.
Journal of Korea Society of Industrial Information Systems
/
v.24
no.1
/
pp.45-63
/
2019
The number of domestic construction company is expanding every year while the construction workers' exposure to disaster risk is increasing due to technological advancements and popularity of high-rise buildings. In particular, the industry faces greater fatalities and severe large scale accidents because of construction industry characteristics including influx of foreign workers with different language and culture, large number of aged workers, outsourcing, high place work, heavy machine construction. The construction industry is labor-intensive, which is to be completed under given timeline and consists of unique working environment with a lot of night shifts. In addition, when a fixed construction budget is not secured, there is less investment in safety management resulting in poor risk management at the construction site. Taking account that the construction industry has higher accident risk rate and fatality rate, risky and unique working environment, and various labor pool from foreign to aged workers, preemptive safety management through risk factor identification is a mandatory requirement for the construction industry and site. The study analyzes about 8,500 cases of construction accidents that occurred over the past 10 years and identified risk factor by construction industry sector to secure a systematic insight for risk management. Based on interrelation analysis between accident types, work types, original cause materials and assailing materials, there is correlation between each analysis factor and work industry. Especially for work types, there is great correlation between work tasks and industry type. For reinforced concrete and earthwork are among the most frequent types of accidents, and they are not only high in frequency of accidents, but also have a high risk in categories of occurrence.
The paper investigates the minimal pair of Korean phonemes quantitatively. To achieve this goal, I calculated the number of consonant minimal pairs in the syllable-initial position as both raw counts and relative counts, and analyzed the part of speech relations of the two words in the minimal pair. "Urimalsaem" was chosen as the object of this study because it was judged that the minimal pair analysis should be done through a dictionary and it is the largest among Korean dictionaries. The results of the study are summarized as follows. First, there were 153 types of minimal pairs out of 337,135 examples. The ranking of phoneme pairs from highest to lowest was 'ㅅ-ㅈ, ㄱ-ㅅ, ㄱ-ㅈ, ㄱ-ㅂ, ㄱ-ㅎ, ${\ldots}$, ㅆ-ㅋ, ㄸ-ㅋ, ㅉ-ㅋ, ㄹ-ㅃ, ㅃ-ㅋ'. The phonemes that played a major role in the formation of the minimal pair were /ㄱ, ㅅ, ㅈ, ㅂ, ㅊ/, in that order, which showed a high proportion of palatals. The correlation between the raw count of minimal pairs and the relative count of minimal pairs was found to be quite high r=0.937. Second, 87.91% of the minimal pairs shared the part of speech (same syntactic category). The most frequently observed type has been 'noun-noun' pair (70.25%), and 'vowel-vowel' pair (14.77%) was the next ranking. It can be indicated that the minimal pair could be grouped into similar categories in terms of semantics. The results of this study can be useful for various research in Korean linguistics, speech-language pathology, language education, language acquisition, speech synthesis, and artificial intelligence-machine learning as basic data related to Korean phonemes.
Purpose: The aim of this study was to evaluate the effects of four surface treatment methods to improve zirconia roughness and three types of resin cement on the shear bond strength (SBS). Materials and methods: A total of 120 zirconia blocks were randomly divided into four surface treatments: non-treatment (Control), airborne-particle abrasion (APA) with 50 ㎛ Al2O3 (APA50), APA with 125 ㎛ Al2O3 (APA125), and ZrO2 slurry (ZA). Three resin cements (Panavia F 2.0, Superbond C&B, and Variolink N) were applied to the surface-treated zirconia specimens. All specimens were subjected to SBS testing using a universal testing machine. The surface of the representative specimens of each group was observed by scanning electron microscope (SEM). SBS data were analyzed with oneway ANOVA, two-way ANOVA test and post-hoc Tukey HSD Test (α=.05). Results: In the surface treatment method, APA125, APA50, ZA, and Control showed high shear bond strength in order, but there was no significant difference between APA125 and APA50 (P>.05). Also, ZA showed significantly higher shear bond strength than Control (P<.05). In the resin cement type, Panavia F 2.0, Superbond C&B, and Variolink N showed significantly higher shear bond strength in order (P<.05). In SEM images, the zirconia surfaces of the APA50 and APA125 showed quite rough and irregular shapes, and the zirconia surface of the ZA was observed small irregular porosity and rough surfaces. Conclusion: APA and ZrO2 slurry were enhanced the surface roughness of zirconia, and Panavia F 2.0 containing MDP showed the highest shear bond strength with zirconia.
Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.
Kim, Donggyu;Lee, Dongwook;Park, Jangwon;Oh, Sungwoo;Kwon, Sungjun;Lee, Inyong;Choi, Dongwon
Journal of Intelligence and Information Systems
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v.28
no.2
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pp.191-206
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2022
Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.
Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.
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