• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.441-453
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• 2021

Recently, the untact healthcare industry due to COVID-19 has been attracting attention, and the telemedicine industry based on medical information has become a field of the healthcare industry receiving attention. However, in Korea, due to obstacles in the legal system, telemedicine is still illegal between doctors and patients. In the case of neighboring China, the reality is the opposite of the recent rapid growth of the telemedicine industry under the leadership of the government. This study looks at this from the perspective of the industrial innovation system on the grounds that telemedicine is an industry and innovative technology needs to be changed to clarify the difference between domestic and Chinese telemedicine industries. As a result of analyzing China's telemedicine industry on the seven sub-divisions of demand conditions, innovators, networks et al., Such as seizing appropriate opportunities for demand driving effects and appropriate communication between economic actors were identified as major success factors. This researcher proposes the following suggestions. first, it conforms to the current digital New Deal policy flow, and conducts a demand survey on the change in demand for medical services in the 4th Industrial Revolution and the Untact Era. For the introduction, a plan to conduct a demand survey for the public and second, second, a plan to grow and intensively foster digital high-tech medical care as a new industry was suggested.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.2
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• pp.129-151
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• 2022

In the current work, a series of three-dimensional finite element analyses have been carried out to understand the behaviour of piles when the adjacent tunnelling passes underneath grouped piles with a reinforced pile cap. In the current study, the numerical analysis studied the computed results regarding the ground reinforcement condition between the tunnel and pile foundation. In addition, several key issues, such as the pile settlements, the axial pile forces, the shear stresses and the relative displacements have been thoroughly analysed, and the IoT platform based preliminary design guidelines were also presented. The pile head settlements of the nearest pile from the tunnel without the ground reinforcement increased by about 70% compared to the farthest pile from the tunnel with the maximum level of reinforcement. The quality management factor data of the piles were provided as API (Application Programming Interface) of various forms by the collection and refinement. Hence it has been shown that it would be important to provide the appropriate API by defining the each of data flow process when the data were created. The behaviour of the grouped piles with the pile cap, depending on the amount of ground reinforcement, has been extensively analysed, and the IoT platform regarding the quality management of piles has been suggested.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.59-72
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• 2022

This study employed a 3-D numerical analysis based on the distinct element method to estimate the strength and deformability of a Cretaceous biotite granitic rock mass at Gijang, Busan, Korea. A workflow was proposed to evaluate the scale effect and the representative elementary volume (REV) of mechanical properties for fractured rock masses. Directional strength and deformability parameters such as block strength, deformation modulus, shear modulus, and bulk modulus were estimated for a discrete fracture network (DFN) in a cubic block the size of the REV. The size of the mechanical REV for fractured rock masses in the study area was determined to be a 15 m cube. The mean block strength and mean deformation modulus of the DFN cube block were found to be 52.8% and 57.7% of the intact rock's strength and Young's modulus, respectively. A constitutive model was derived for the study area that describes the linear-elastic and orthotropic mechanical behavior of the rock mass. The model is expected to help evaluate the stability of tunnels and underground spaces through equivalent continuum analysis.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.41-57
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• 2022

A workflow is presented to estimate the size of a representative elementary volume and 3-D hydraulic conductivity tensor based on fluid flow analysis for a discrete fracture network (DFN). A case study is considered for a Cretaceous granitic rock mass at Gijang in Busan, Korea. The intensity and size of joints were calibrated using the first invariant of the fracture tensor for the 2-D DFN of the study area. Effective hydraulic apertures were obtained by analyzing the results of field packer tests. The representative elementary volume of the 2-D DFN was determined to be 20 m square by investigating the variations in the directional hydraulic conductivity for blocks of different sizes. The directional hydraulic conductivities calculated from the 2-D DFN exhibited strong anisotropy related to the hydraulic behavior of the study area. The 3-D hydraulic conductivity tensor for the fractured rock mass of the study area was estimated from the directional block conductivities of the 2-D DFN blocks generated for various directions in 3-D. The orientations of the principal components of the 3-D hydraulic conductivity tensor were found to be identical to those of delineated joint sets in the study area.

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.4
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• pp.289-298
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• 2023

In this study, the development of a self-healing concrete waterproofing agent was examined, focusing on its manufacturing and waterproofing properties. The optimal ratio using microcapsules for the concrete waterproofing agent was determined through assessments of flow, compressive strength, and permeability conducted during the mortar stage. These findings aimed to provide fundamental data for evaluating the self-healing properties of the concrete waterproofing agent designed for use in concrete structures. The self-healing concrete waterproofing agent was comprised of three types of inorganic materials commonly used for repair purposes. From experimental results, a composition ratio with a high potassium silicate content, referred to as SIM-2, was found suitable. A surfactant mixing ratio of 0.03 % was identified to enhance the dispersibility of the concrete waterproofing agent, while a mixing ratio of 0.2 % distilled water was deemed suitable for viscosity adjustment. For the magnetic self-healing concrete waterproofing agent's healing agent, using microcapsules in the range of 0.5 % to 0.7 % met the KS F 4949 and KS F 4926 standards.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2002.06a
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• pp.148-155
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• 2002

Multithreaded models improve the efficiency of parallel systems by combining inner parallelism, asynchronous data availability and the locality of von Neumann model. This model executes thread code which is generated by compiler and of which quality is given by the method of generation. But multithreaded models have the demerit that execution model is restricted to a specific platform. On the contrary, Java has the platform independency, so if we can translate from threads code to Java bytecode, we can use the advantages of multithreaded models in many platforms. Java executes Java bytecode which is intermediate language format for Java virtual machine. Java bytecode plays a role of an intermediate language in translator and Java virtual machine work as back-end in translator. But, Java bytecode which is translated from multithreaded models have the demerit that it is not secure. This paper, multhithread code whose feature of platform independent can execute in java virtual machine. We design and implement translator which translate from thread code of multithreaded code to Java bytecode and which check secure problems from Java bytecode.