• Tunnel and Underground Space
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• v.17 no.2 s.67
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• pp.102-108
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• 2007

Generally, the method used most widely for rock mass classification is considering the rock strength and development of joint frequency. However, if rock bed has micro-crack and long joint, this method is not rational. Therefore, the difficulties of excavation in the rock bed with complicated geological condition are decided by combining joint frequency. indoor tests (uniaxiall compressive strength, point load test, indoor elastic wave velocity, etc.) and field seismic refraction survey, and the rock mass classification should be implemented by considering their interrelationship.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.394-396
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• 2021

Additional pathological tests using imaging equipment are essential before diagnosing cancer cells. Recently, in order to reduce the need for time and human resources in these fields, research related to the establishment of a system capable of automatic classification of cancer cells using artificial intelligence is being actively conducted. However, in both previous studies, there were relatively limited deep learning algorithms and cell types, and limitations existed with low accuracy at the same time. In this study, a method of performing 4class Classification on four types of cancer cells through the Convolution Neral Network, a type of in-depth learning. EfficientNet, ResNet, and Inception were used, and finally Resnet was used to obtain an accuracy of 96.11 on average for k-fold.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.15-22
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• 2023

In this study, We conduct a comparative study of deep learning-based classification of agricultural field attributes using Tagged Image File (TIF) and Enhanced Compression Wavelet (ECW) images. The goal is to interpret and classify the attributes of agricultural fields by analyzing the differences between these two image formats. "FarmMap," initiated by the Ministry of Agriculture, Food and Rural Affairs in 2014, serves as the first digital map of agricultural land in South Korea. It comprises attributes such as paddy, field, orchard, agricultural facility and ginseng cultivation areas. For the purpose of comparing deep learning-based agricultural attribute classification, we consider the location and class information of objects, as well as the attribute information of FarmMap. We utilize the ResNet-50 instance segmentation model, which is suitable for this task, to conduct simulated experiments. The comparison of agricultural attribute classification between the two images is measured in terms of accuracy. The experimental results indicate that the accuracy of TIF images is 90.44%, while that of ECW images is 91.72%. The ECW image model demonstrates approximately 1.28% higher accuracy. However, statistical validation, specifically Wilcoxon rank-sum tests, did not reveal a significant difference in accuracy between the two images.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.213-219
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• 2023

In recent years, popularity of deep learning (DL) is increased due to its ability to extract features from Hyperspectral images. A lack of discrimination power in the features produced by traditional machine learning algorithms has resulted in poor classification results. It's also a study topic to find out how to get excellent classification results with limited samples without getting overfitting issues in hyperspectral images (HSIs). These issues can be addressed by utilising a new learning network structure developed in this study.EfficientNet-B4-Based Convolutional network (EN-B4), which is why it is critical to maintain a constant ratio between the dimensions of network resolution, width, and depth in order to achieve a balance. The weight of the proposed model is optimized by Search and Rescue Operations (SRO), which is inspired by the explorations carried out by humans during search and rescue processes. Tests were conducted on two datasets to verify the efficacy of EN-B4, with Indian Pines (IP) and the University of Pavia (UP) dataset. Experiments show that EN-B4 outperforms other state-of-the-art approaches in terms of classification accuracy.

• Tunnel and Underground Space
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• v.3 no.2
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• pp.167-174
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• 1993

Index tests are useful because they are rapid and cheap-and if bias is known the fundamental property can be estimated, as when estimating the compressive strength or the tensile sterngth from the rock test hammer value. Index tests which have proved to be very useful are the rock test hammer, the point load test and sonic velocity test. These can provide index values in their owing right or be used to estimate the compressive strength, the tensile strength and elastic modulus. Because of the heterogeneous and fractured nature of rock, many index tests have been developed for a variety of purposes, e.g.for use in rock mass classification schemes.

• Journal of Korean Association for Spatial Structures
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• v.16 no.2
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• pp.55-60
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• 2016

The Membrane structure has a number of problems in the application of a fireproof code based on general buildings codes. Thus, the fireproof code of membrane structure is necessary to activate the construction of the membrane structure. Because it requires a systematic classification of fire retardant and flame proof performance of membrane material. Fire retardant and flame proof tests are conducted on membrane materials mostly used in current construction to propose the fire and flame retardant performance criteria of membrane materials. Fire and flame retardant tests results, PTFE membrane material with the glass fiber fabric have a limit-combustible performance. PVDF membrane material with the polyester fabric does not ensure the fire retardant performance, but this membrane material has the flame retardant performance of a thick fabric. Also, ETFE does not ensure the fire retardant performance, but this membrane material has the flame retardant of a thin fabric.

• East Asian Economic Review
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• v.20 no.4
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• pp.493-517
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• 2016

This paper examines the persistent properties of 12 sectoral relative prices between Korea and Japan obtained following the Classification of Individual Consumption according to Purpose (COICOP) over the period of 1985-2016. Applying a new econometric method developed by Pesaran which controls for the cross-section dependence in a panel, we are not able to reject the hypothesis that the sectoral real exchange rates contain a common stochastic trend. On the other hand, the well-known panel unit root tests such as the IPS and LLC tests widely used by previous studies strongly reject the unit root hypothesis. Since the error term of the regression for our panel exhibits significant cross-section dependence, these opposite results justify that the use of the new econometric method is appropriate.

• Journal of the Korean GEO-environmental Society
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• v.23 no.1
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• pp.15-23
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• 2022

This paper presents the results of full-scale load tests performed frictional anchors to various lengths at several sites in Korea. Various rock types were tested, ranging from highly weathered shale to sound gneiss. In many tests, rock failure was reached and the ultimate loads were recorded along with observations of the shape and extent of the failure surface. Laboratory tests were also conducted to investigate the influence of the corrosion protection sheath on the bond strength. Based on test results, the main parameters governing the uplift capacity of the rock anchor system were determined. By evaluation of the ultimate uplift capacity of anchor foundations in a wide range of in situ rock masses, rock classification suitable for structural foundation was developed. Finally, a very simple and economical design procedure is proposed for rock anchor foundations subjected to uplift tensile loads.

• Communications of Mathematical Education
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• v.36 no.3
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• pp.355-372
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• 2022

The purpose of this study was to find out whether the Grit test is valid as a test tool for Identification of mathematically gifted elementary students. For this study, we conducted Grit tests, Mathematical Problem Solving Aability Tests, Mathematical Creative Ability Tests, and Mathematically Gifted Behavior Characteristic Tests on 39 ordinary students at Seoul public elementary school and 20 mathematically gifted students at the Education Center for Gifted Education, and analyzed correlation with each test. In addition, we conducted a discriminant analysis to find out how the Grit test can accurately determine the members of the mathematically gifted student group and the ordinary student group. As a result of Pearson's correlation analysis, the Grit test was .521 with the Mathematical Problem Solving Ability Tests, .440 with the Mathematical Creative Ability Tests, and .601 with the Mathematically Gifted Behavior Characteristic Tests, according to significant positive correlation at p<.01. Through this, it can be confirmed that the Grit test has a high official validity as a tool for determining mathematically gifted students. As a result of conducting a discriminant analysis to confirm the classification discrimination ability of the elementary mathematically gifted student group and ordinary student group of the Grit test, Wilk's λ was .799(p<.001). We confirm that the Grit test is a significant variable in determining the mathematically gifted student group and ordinary student group. In addition, 64.4% of the entire group was accurately classified as a result of group classification through discriminant analysis. This shows that the Grit test can be actually used as a test tool to determine mathematically gifted elementary students.

• Progress in Medical Physics
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• v.28 no.4
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• pp.197-206
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• 2017

We develop guidelines for the quality assurance of radiation treatment planning systems (TPS) by comparing and reviewing recommendations from major countries and organizations, as well as by analyzing the AAPM, ESTRO, and IAEA TPS quality assurance guidelines. We establish quality assurance items for acceptance testing, commissioning, periodic testing, system management, and security, and propose methods to perform each item within acceptable standards. Acceptance includes tests of hardware and network environments, data transmission, software, and benchmarking as specified by the system supplier, and apply the IAEA classification criteria. Commissioning includes dosimetric and non-dosimetric items for assessing TPS performance by applying the AAPM classification criteria and the latest technical items from the IAEA. Periodic quality assurance tests include daily, weekly, monthly, yearly, and occasional items by applying the AAPM classification criteria. System management and security items include the state and network connectivity of TPS, periodic data backup, and data access security. The guidelines for TPS quality assurance proposed in this study will help to improve the safety and quality of radiotherapy by preventing incidents related to radiotherapy.