• Journal of Korean Society of Forest Science
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• v.12 no.1
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• pp.23-29
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• 1971

In order to see a possible strengthening of much injection of synthetic resin into timber by way of electric osmosis, Authors examined the change of the bending strength of the sample timber piece after being injected. 1. Three kinds of sample tree species, Pinus rigida, Magnolia and Populus were used and the size of the sample timber pieces was $30mm{\times}30mm{\times}330mm$. 2. Each of the electric osmosis was made with 250V of D. C. voltage and $0.01A/cm^2$ of the current for 2 hours and the experimenter hardened the injected resin by putting the sample in an oven of $120^{\circ}{\pm}2^{\circ}C$ temperature for 24 hours. 3. The size of the test sample piece for bending strength measurement was $20mm{\times}20mm{\times}320mm$ and Amsler type universal timber test machine was used for the measurement. 4. The strength difference between treated and untreated samples was as follows. Pinus rigida high sig. Magnolia None Sig. Populus Sig.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.1-11
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• 2021

Recently, in Korea, the risk of meteorological disasters is increasing due to climate change, and the damage caused by rainfall is being emphasized continuously. Although the current weather forecast provides quantitative rainfall, there are several difficulties in predicting the extent of damage. Therefore, in order to understand the impact of damage, the threshold rainfall for each watershed is required. The damage caused by rainfall occurs differently by region, and there are limitations in the analysis considering the characteristic factors of each watershed. In addition, whenever rainfall comes, the analysis of rainfall-runoff through the hydrological model consumes a lot of time and is often analyzed using only simple rainfall data. This study used GIS data and calculated the threshold rainfall from the threshold runoff causing flooding by coupling two hydrologic models. The calculation result was verified by comparing it with the actual case, and it was analyzed that damage occurred in the dangerous area in general. In the future, through this study, it will be possible to prepare for flood risk areas in advance, and it is expected that the accuracy will increase if machine learning analysis methods are added.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.29-39
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• 2021

As damages to individuals, private sectors, and businesses increase due to newly occurring cyber attacks, the underlying network security problem has emerged as a major problem in computer systems. Therefore, NIDS using machine learning and deep learning is being studied to improve the limitations that occur in the existing Network Intrusion Detection System. In this study, a deep learning-based NIDS model study is conducted using the Convolution Neural Network (CNN) algorithm. For the image classification-based CNN algorithm learning, a discrete algorithm for continuity variables was added in the preprocessing stage used previously, and the predicted variables were expressed in a linear relationship and converted into easy-to-interpret data. Finally, the network packet processed through the above process is mapped to a square matrix structure and converted into a pixel image. For the performance evaluation of the proposed model, NSL-KDD, a representative network packet data, was used, and accuracy, precision, recall, and f1-score were used as performance indicators. As a result of the experiment, the proposed model showed the highest performance with an accuracy of 85%, and the harmonic mean (F1-Score) of the R2L class with a small number of training samples was 71%, showing very good performance compared to other models.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.155-161
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• 2019

As composite is the light weight material whose durability and mechanical property are more superior than the existing general material. By taking notice of the composite with light weight, this study was about to investigate the static fracture characteristic of the bonded CFRP structure jointed with adhesive. Also, CFRP double cantilever beam with the variable of laminate angle was designed and the static fracture analysis was carried out. The laminate angles of CFRP double cantilever beam designed for this study were $30^{\circ}$, $45^{\circ}$ and $60^{\circ}$ individually. As the study result, the specimen with the laminate angle of $45^{\circ}$ was shown to have the durability better than those with the layer angles of $30^{\circ}$ and $45^{\circ}$. It was checked that the specimen with the laminate angle of $30^{\circ}$ had the weakest durability among all specimens. The damage data of the bonded CFRP structure by laminate angle could be secured through this study result. As the damage data of bonded interface obtained on the basis of this study result are utilized, the esthetic sense can be shown by being grafted onto the machine or structure at real life.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.175-180
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• 2018

In this study, CFRP was manufactured with the laminate angle of $45^{\circ}$. The specimen of TDCB bonded with the adhesive for structure was designed by CATIA and the analysis was progressed by using the finite element analysis program of ANSYS. This study model was designed on the basis of British industry and ISO standard and the configuration factor(m) was established with variable according to the angle of model configuration. As the study result of this paper, the maximum deformations at the specimens with the tapered angles of $4^{\circ}$ and $8^{\circ}$ become most as 12.628 mm and least as 12.352mm respectively. Also, the maximum equivalent stresses at the specimens with the tapered angles of $6^{\circ}$ and $8^{\circ}$ become most as 9210.3 MPa and least as 4800.5 MPa respectively. The damage data of TDCB structure with the laminate angle which was manufactured with CFRP could be secured through this study result. As the damage data of TDCB structure bonded with CFRP obtained on the basis of this study result are utilized, the esthetic sense can be shown by being grafted onto the machine or structure at real life.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.5
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• pp.689-699
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• 2022

Recently, high productivity capabilities have been improved due to the application of advanced technologies in various industries, but in the construction industry, productivity improvements have been relatively low. Research on advanced technology for the construction industry is being conducted quickly to overcome the current low productivity. Among advanced technologies, 3D scan technology is widely used for creating 3D digital terrain models at construction sites. In particular, the 3D digital terrain model provides basic data for construction automation processes, such as earthwork machine guidance and control. The quality of the 3D digital terrain model has a lot of influence not only on the performance and acquisition environment of the 3D scanner, but also on the denoising, registration and merging process, which is a preprocessing process for creating a 3D digital terrain model after acquiring terrain scan data. Therefore, it is necessary to improve the terrain scan data processing performance. This study seeks to solve the problem of density inhomogeneity in terrain scan data that arises during the pre-processing step. The study suggests a 'pixel-based point cloud comparison algorithm' and verifies the performance of the algorithm using terrain scan data obtained at an actual earthwork site.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.457-468
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• 2022

In aged society, it is important to prevent older people from being disability needing long-term care. The purpose of this study is to develop a prediction model to discover high-risk groups who are likely to be beneficiaries of Long-Term Care Insurance. This study is a retrospective study using database of National Health Insurance Service (NHIS) collected in the past of the study subjects. The study subjects are 7,724,101, the population over 65 years of age registered for medical insurance. To develop the prediction model, we used logistic regression, decision tree, random forest, and multi-layer perceptron neural network. Finally, random forest was selected as the prediction model based on the performances of models obtained through internal and external validation. Random forest could predict about 90% of the older people in need of long-term care using DB without any information from the assessment of eligibility for long-term care. The findings might be useful in evidencebased health management for prevention services and can contribute to preemptively discovering those who need preventive services in older people.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.71-82
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• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.

• Journal of the Korean Society of Safety
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• v.37 no.1
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• pp.64-69
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• 2022

The study measured a subway construction worker's Macpa stress by Heart Rate Variability measuring instrument and conducted a survey of Korean job stress from subway construction workers. Also, the study analyzed the relationship between Macpa stress index and Korean job stress result and suggested managing stress method for each item. According to National Statistical Office data, the first line subway in Seoul was started to open in 1974. The extended total length is 996 kilometers until 2019. Many aged workers are currently working at subway construction sites due to the avoidance of young workers since the past until now. It means that the elderly has a substantial portion among subway construction workers. The productivity has been adversely affected by health problems due to the aging of workers, job stress due to heavy work, and personal health problems. So, the regulation and policies on job stress health management are being strengthened. The data were measured Macpa stress by machine measuring heart rate variability and conducted Korean job stress survey(shortened) from Sa-sang to Ha-dan line Busan subway construction workers for analyzing the relationship. Independent variable were age, job duration, job position, employment type, working type in this study. Macpa's dependent variable was stress index and Korean job stress survey(shortened)'s dependent variables were job requirements, job autonomy, relationship conflict, job instability, organizational structure, inappropriate compensation, working place culture, and total score. SPSS 12.0 K Statistics Program was used for statistical analysis. Kruskal-wallis test, a nonparametric statistical analysis, was used because the data are difficult to be assumed as normal distribution. As a result, the paper indicated the significant correlation between Macpa stress index and Korean job stress(short version). The elderly workers presented higher Macpa index and higher job stress due to aging and heavy-duty work. The majority workers were daily workers who had unstable working condition and uncertainty about the future. The study suggested a manual that could reduce job stress for subway construction workers and future study deriving management tool through analyzing job stress factor is necessary.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.101-113
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• 2021

In this paper, we introduce a speaker overlap system and look at the process of converting the existed system on the specific framework of artificial intelligence. Speaker overlap is when two or more speakers speak at the same time during a conversation, and can lead to performance degradation in the fields of speech recognition or speaker recognition, and a lot of research is being conducted because it can prevent performance degradation. Recently, as application of artificial intelligence is increasing, there is a demand for switching between artificial intelligence frameworks. However, when switching frameworks, performance degradation is observed due to the unique characteristics of each framework, making it difficult to switch frameworks. In this paper, the process of converting the speaker overlap detection system based on the Keras framework to the pytorch-based system is explained and considers components. As a result of the framework switching, the pytorch-based system showed better performance than the existing Keras-based speaker overlap detection system, so it can be said that it is valuable as a fundamental study on systematic framework conversion.