• Restorative Dentistry and Endodontics
• /
• v.44 no.1
• /
• pp.5.1-5.9
• /
• 2019

Objectives: The aim of this in vitro study was to evaluate the push-out bond strength of a novel calcium silicate-based root repair material-BIOfactor MTA to root canal dentin in comparison with white MTA-Angelus (Angelus) and Biodentine (Septodont). Materials and Methods: The coronal parts of 12 central incisors were removed and the roots were embedded in acrylic resin blocks. Midroot dentin of each sample was horizontally sectioned into 1.1 mm slices and 3 slices were obtained from each root. Three canal-like standardized holes having 1 mm in diameter were created parallel to the root canal on each dentin slice with a diamond bur. The holes were filled with MTA-Angelus, Biodentine, or BIOfactor MTA. Wet gauze was placed over the specimens and samples were stored in an incubator at $37^{\circ}C$ for 7 days to allow complete setting. Then samples were subjected to the push-out test method using a universal test machine with the loading speed of 1 mm/min. Data was statistically analyzed using Friedman test and post hoc Wilcoxon signed rank test with Bonferroni correction. Results: There were no significant differences among the push-out bond strength values of MTA-Angelus, Biodentine, and BIOfactor MTA (p > 0.017). Most of the specimens exhibited cohesive failure in all groups, with the highest rate found in Biodentine group. Conclusions: Based on the results of this study, MTA-Angelus, Biodentine, and BIOfactor MTA showed similar resistances to the push-out testing.

• Journal of the Korea Convergence Society
• /
• v.10 no.5
• /
• pp.35-42
• /
• 2019

Recently, as the Internet and various wearable devices have appeared, Internet technology has contributed to obtaining more convenient information and doing business. However, as the internet is used in various parts, the attack surface points that are exposed to attacks are increasing, Attempts to invade networks aimed at taking unfair advantage, such as cyber terrorism, are also increasing. In this paper, we propose a feature selection method to improve the classification performance of the class to classify the abnormal behavior in the network traffic. The UNSW-NB15 dataset has a rare class imbalance problem with relatively few instances compared to other classes, and an undersampling method is used to eliminate it. We use the SVM, k-NN, and decision tree algorithms and extract a subset of combinations with superior detection accuracy and RMSE through training and verification. The subset has recall values of more than 98% through the wrapper based experiments and the DT_PSO showed the best performance.

• The Journal of Sustainable Design and Educational Environment Research
• /
• v.18 no.1
• /
• pp.38-48
• /
• 2019

The purpose of this study is to present a more effective daily checklist than the formal routine check before the experiment to prevent accidents in the university laboratory. To do this, we reconstructed the current daily checklist and previous research data and conducted a second Delphi survey. As a result, there were four general safeties such as arranging the laboratory, three mechanical safeties such as abnormal condition of machine and tool tightening parts, three electric safeties such as prohibition of loading around the electric distribution panel, six chemical safeties such as handling and managing harmful factors, three items of fire safety such as fire extinguisher inspection, five cases of gas safety gas container inspection, one item of biological safety such as the state of hand sterilizer management and one other item, which were provided in the daily checklist as twenty six categories in total. According to the opinions of related experts, it is necessary to have an easy and simplified daily checklist for actual daily checkups.

• Korean Journal of Agricultural Science
• /
• v.47 no.4
• /
• pp.717-726
• /
• 2020

The physical characteristics of the major varieties of perilla were analyzed to use as basic data for the design of a high-quality, high-efficiency perilla cleaner and stone separator. Because the size, thousand-grain weight, angle of repose, angle of friction, bulk density and terminal velocity of perilla have significant differences according to the perilla variety, the different of characteristics by variety should be considered for performance improvement of a perilla cleaner and stone separator. Therefore the cleaner and stone separator using a sieve could be improved by the application of a detachable sieve or by using equipment such as a 2 - 3 stage sieve and regulating the slope. Moreover, because differences in the terminal velocity occur due to the differences in the size and thousand-grain weight according to the perilla variety, a blower with an adjustable fan speed was considered for the design of the improved cleaner. Additionally, it was shown that the length of perilla has the greatest correlation based on a comparison of the coefficients of the other characteristics. Accordingly, the length of perilla could be used as a major factor for the fine adjustment and parts replacement of the device. These results can be used as basic data for a high-quality, high-efficiency perilla cleaner and stone separator. In the future, the development of the machine and follow-up studies based on the basic data are needed to determine the optimized operating conditions and mechanism of action.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.2
• /
• pp.1-9
• /
• 2021

In this paper, we extend a generic library framework based on the state monad to exploit deterministic parallelism in a purely functional language Haskell and provide benchmarks for the extended features on a multicore machine. Although purely functional programs are known to be well-suited to exploit parallelism, unintended squential data dependencies could prohibit effective parallelism. Symbolic execution programs usually implement fresh name generation in order to prevent confusion between variables in different scope with the same name. Such implementations are often based on squential state management, working against parallelism. We provide reusable primitives to help developing parallel symbolic execution programs with unbound-genercis, a generic name-binding library for Haskell, avoiding sequential dependencies in fresh name generation. Our parallel extension does not modify the internal implementation of the unbound-generics library, having zero possibility of degrading existing serial implementations of symbolic execution based on unbound-genecrics. Therefore, our extension can be applied only to the parts of source code that need parallel speedup.

• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.257-261
• /
• 2022

Diseases of agricultural plants in recent years have spread greatly across the regions of the Kyrgyz Republic and pose a serious threat to the yield of many crops. The consequences of it can greatly affect the food security for an entire country. Due to force majeure, abnormal cases in climatic conditions, the annual incomes of many farmers and agricultural producers can be destroyed locally. Along with this, the rapid detection of plant diseases also remains difficult in many parts of the regions due to the lack of necessary infrastructure. In this case, it is possible to pave the way for the diagnosis of diseases with the help of the latest achievements due to the possibilities of feedback from the farmer - developer in the formation and updating of the database of sick and healthy plants with the help of advances in computer vision, developing on the basis of machine and deep learning. Currently, model training is increasingly used already on publicly available datasets, i.e. it has become popular to build new models already on trained models. The latter is called as transfer training and is developing very quickly. Using a publicly available data set from PlantVillage, which consists of 54,306 or NewPlantVillage with a data volumed with 87,356 images of sick and healthy plant leaves collected under controlled conditions, it is possible to build a deep convolutional neural network to identify 14 types of crops and 26 diseases. At the same time, the trained model can achieve an accuracy of more than 99% on a specially selected test set.

• Transactions of Materials Processing
• /
• v.31 no.1
• /
• pp.17-22
• /
• 2022

Hot stamping is widely used to manufacture structural parts to satisfy requirements of eco-friendly vehicles. Recently, hot forming technology using uncoated steel sheet is being studied to reduce cost and solve patent problems. In particular, research is focused on process technology capable of suppressing the generation of an oxide layer. To evaluate the oxide layer in the hot stamping process, Gleeble testing machine can be used to evaluate the oxide layer by controlling the temperature history and the atmosphere condition. At this time, since cooling by gas injection is impossible to protect the oxide layer on the surface of a specimen, research on a method for securing a quenching speed through natural cooling is required. This paper proposes a specimen shape design method to secure a target quenching speed through natural cooling when evaluating the oxide layer of an un-coated boron steel sheet by Gleeble test. For the evaluation of the oxide layer of the un-coated steel sheet through the Gleeble test, dog-bone and rectangular type specimens were used. In consideration of the hot stamping process, the temperature control conditions for the Gleeble test were set and the quenching speed according to the specimen shape design was measured. Finally, the quenching speed sensitivity according to shape parameter was analyzed through regression analysis. A quenching speed prediction equation was then constructed according to the shape of the specimen. The constructed quenching speed prediction equation can be used as a specimen design guideline to secure a target quenching speed when evaluating the oxide layer of an un-coated boron steel sheet by the Gleeble test.

• Journal of the Korean Society of Industry Convergence
• /
• v.25 no.6_2
• /
• pp.1111-1117
• /
• 2022

Recently, interest in the circular economy has emerged in the industry. As a result, interest in Re-manufacturing, which makes old equipment similar to new products, is growing. In the machine tool industry with many aging equipment, the Re-manufacturing industry is essential, and among them, research on the performance improvement of gear type oil pumps was conducted. The purpose was to achieve the target performance of flow rate and volume efficiency by changing the shape of the gear pump housing clearance and inlet/outlet, and Computational Fluid Analysis and Central Composite Design were conducted using ANSYS CFX 2022 R2 and MINITAB®. The level of each determined factor was determined. 20 design points were derived, and the Flow Rate at each design point was calculated, and the Theoretical Flow Rate was calculated to obtain Volumetric Efficiency. The optimal design point was obtained when the Flow Rate was 140 lpm and the Volumetric Efficiency was maximum, the optimal design point was obtained when both were maximum, and the Surface Plot for each factor was obtained to identify the tendency.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.11
• /
• pp.107-114
• /
• 2022

In this paper, proposes a delivery robot that can be autonomous driving learning. The proposed robot is designed to be used in park-type apartments without ground parking facilities. Compared to the existing apartments with complex ground and underground routes, park-type apartments have a standardized movement path, allowing the robot to run stably, making it suitable for students' initial education environment. The delivery robot is configured to enable delivery of parcels through machine learning technology for route learning and autonomous driving using cameras and LiDAR sensors. In addition, the control MCU was designed by separating it into three parts to enable learning by level, and it was confirmed that it can be used as a delivery robot for learning through operation tests such as autonomous driving and obstacle recognition. In the future, we plan to develop it into an educational delivery robot for various delivery services by linking with the precision indoor location information recognition technology and the public technology platform of the apartment.

• Journal of Korean Dental Hygiene Science
• /
• v.5 no.1
• /
• pp.13-19
• /
• 2022

Background: In this study, zirconia copings were fabricated by setting clinically acceptable inner values for prostheses using computer-aided design/computer-aided manufacturing (CAD/CAM). The processed copings were evaluated for the marginal and internal fit of each abutment shape with a CAD program using the silicone replica technique. Methods A total of 20 copings was produced by selecting models commonly used in clinical practice. After injecting the sample, the minimum thickness, internal adhesion interval, and distance to the margin line were set to 0.5, 0.05, and 1.00 mm using a dental CAD program, respectively. It was measured using a 2D section function in a three-way program of the silicon replication technology. Although the positions and number of measurements of the anterior and posterior regions differed, nine parts of each pre-tube were designated and measured by referring to a previous study to compare the two samples. Results As a result, the average margin of the mesial, distal, and buccal (labial) surfaces was 59.90 ㎛ in the anterior region and 60.40 ㎛ in the posterior region. The mean axial wall margin was 67.25 ㎛ in the anterior region and 69.25 ㎛ in the posterior region. In occlusion, the anterior teeth (77.70 ㎛), posterior teeth (77.60 ㎛), and both anterior and posterior regions were within the clinically acceptable range. Conclusion The edge and inner fit of zirconia coping manufactured using the CAD/CAM system showed clinically applicable results. To reduce errors and increase accuracy, materials and machine errors that affect the manufacture of prosthetics should be investigated. Based on our results, the completeness of prosthetics could increase if the inner value and characteristics of the material are adjusted when applied in clinical practice.