• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.288-290
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• 2022

As part of the SOC digitization for smart water management and flood prevention, the government reported that automatic and remote control system for drainage facilities (180 billion won) to 57% of national rivers and established a real-time monitoring system (30 billion won). In addition, they were also planning to establish a smart dam safety management system (15 billion won) based on big data at 11 regions. Therefore, research is needed for smart water management and flood prevention system that can accurately calculate the flow rate through real-time flow rate measurement of rivers. In particular, the most important thing to improve the system implementation and accuracy is to ensure the accuracy of real-time flow rate measurements. To this end, radar sensors for measuring the flow rate of electromagnetic waves in the United States and Europe have been introduced and applied to the system in Korea, but demand for improvement of the system continues due to high price range and performance. Consequently, we would like to propose an improved flow rate measurement and flood forecast system by developing a radar sensor for measuring the electromagnetic surface current meter for real-time flow rate measurement.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.1-7
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• 2023

An artificial intelligence (AI) method based on image deep learning is proposed to predict the entire displacement shape of a structure using the feature of partial displacements. The performance of the method was investigated through a structural test of a steel frame. An image-to-image regression (I2IR) training method was developed based on the U-Net layer for image recognition. In the I2IR method, the U-Net is modified to generate images of entire displacement shapes when images of partial displacement shapes of structures are input to the AI network. Furthermore, the training of displacements combined with the location feature was developed so that nodal displacement values with corresponding nodal coordinates could be used in AI training. The proposed training methods can consider correlations between nodal displacements in 3D space, and the accuracy of displacement predictions is improved compared with artificial neural network training methods. Displacements of the steel frame were predicted during the structural tests using the proposed methods and compared with 3D scanning data of displacement shapes. The results show that the proposed AI prediction properly follows the measured displacements using 3D scanning.

• Journal of the Korean Geotechnical Society
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• v.23 no.3
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• pp.5-13
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• 2007

The performance of innovative prestressed support (IPS) earth retention system applied in soft clay was investigated and presented. The IPS wale system provides a high flexural stiffness to resist the bending by lateral earth pressure, and transfers lateral earth pressure to strut supports. The IPS wale system provides a larger spacing of support than conventional braced and anchored systems. The IPS earth retention system was selected for temporary earth support in a building construction in North Busan area. The excavation was made 28.8 m wide, 52.0 m long, and 16.1 m deep through loose fill to soft clay. The IPS system consists of 650 mm thick slurry walls, and five levels of IPS wales and struts. Field monitoring data were collected including wall deflections at six locations, ground water levels at four locations, IPS wale deflections at thirty locations, and axial loads on struts at twenty locations, during construction. The IPS earth retention system applied in soft clay performed successfully within a designed criterion. Field measurements were compared with design assumptions of the IPS earth retention system. The applicability and stability of the IPS earth retention system in soft clay were investigated and evaluated.

• Journal of the Korean Geotechnical Society
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• v.22 no.8
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• pp.107-118
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• 2006

Among a variety of influencing components, time-variant seepage and long-term underground motion are important to understand the abnormal behavior of tunnels. Excessiveness of these two components could be the direct cause of severe damage on tunnels, however, it is not easy to quantify the effect of these on the behavior of tunnels. These parameters can be estimated by using inverse methods once the appropriate relationship between inputs and results is clarified. Various inverse methods or parameter estimation techniques such as artificial neural network and least square method can be used depending on the characteristics of given problems. Numerical analyses, experiments, or monitoring results are frequently used to prepare a set of inputs and results to establish the back analysis models. In this study, a back analysis method has been developed to estimate geotechnically hard-to-known parameters such as permeability of tunnel filter, underground water table, long-term rock mass load, size of damaged zone associated with seepage and long-term underground motion. The artificial neural network technique is adopted and the numerical models developed in the first part are used to prepare a set of data for learning process. Tunnel behavior, especially the displacements of the lining, has been exclusively investigated for the back analysis.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.1
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• pp.41-47
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• 2022

In this study, rainfall water outlet water quality monitoring was performed on the C industrial complex to evaluate the characteristics of non-point pollutant runoff from the industrial complex during rainfall and to use it as basic data for calculating the load and unit of non-point pollutant. As a result of calculating EMC according to the outflow amount by rainfall event, the 1st rainfall showed EMCs ranges of BOD, COD_Mn, SS, T-N, and T-P of 1.32~48.76, 3.32~43.75, 2.89~199.43, 2.76~8.93, 0.08~068, and the 2nd rainfall was 0.5~2.9, 2.71~7.13, 2.82~174.94, 1.33~4.03, 0.01~1.28 mg/L, respectively. As a result of calculating the ratio of cumulative outflow and cumulative pollution load, most of the pollution load was less than the rainfall outflow, but over time, the initial washing phenomenon occurred as the ratio of cumulative rainfall outflow and cumulative pollution load increased to more than 1.

• Journal of Marine Life Science
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• v.3 no.2
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• pp.81-86
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• 2018

The purpose of this study is to determine the effects of vibration on primary (e.g. plasma cortisol), secondary (e.g. plasma glucose, aspartate aminotransferase (AST), alanine aminotransferase (ALT), Na⁺, K⁺ and Cl^- and tertiary (e.g. mortality) stress responses in cultured eel, Anguilla japonica. For this purpose, three groups (including one control group and two stress groups) were set up. The control group was made exposed to vibration corresponding to 48 decibel (dB, V) (produced using electric vibrators) for 15 minutes per hour every day, and the two stress groups was made exposed to vibration corresponding to 58 and 68 dB (V) (produced using the same electric vibrators), equally, for 15 minutes per hour every day. Blood was sampled at day 0 (before starting vibration stress tests, BS), and days 1, 3, 5, 7, 9 and 11 (after starting vibration stress tests). As a result, plasma cortisol showed trend to continuously rise by consecutive stress from 4.1±0.1 ng/ml in BS. In 48 dB group (control), cortisol showed the highest level with 7.6±0.9 ng/ml after 7 days (p<0.05), but at 9 and 11 days was not significantly compared with BS level. In 58 dB group, the cortisol showed the highest level with 43.1±4.8 ng/ml after 1st day. Cortisol of 68 dB group increased significantly during the experimental period (14.4±2.3~32.0±5.7 ng/ml) (p<0.05). In 58, and 68 dB groups during the experimental period differed significantly compared to 48 group (p<0.05). Glucose in 48 dB were increased from 42.0 ±5.7 (BS) to 52.5±2.1 (1 day), the level was not significantly from 1 to 11 days. Glucose in 58 and 68 dB groups was increased significantly than BS during experimental period (p<0.05). K⁺ in 68 dB increased significantly (p<0.05) from 2.3±0.2 mE/ql (BS) to 3.3±0.5 mE/ql at 5 days. In 48 and 58 dB groups during the experimental period differed significantly (p<0.05). Na⁺ and Cl^- levels were not differed significantly during the experimental period. AST and ALT in 58 and 68 dB groups showed trend to continuously rise by consecutive stress. At 7 and 9 days in AST, between 48, 58 and 68 dB groups differed significantly (p<0.05). In 48, 58 and 68 dB groups at 1 day, blood hematocrit increased significantly higher than BS. The 11 days after vibration stress, the mortality in 48, 58 and 68 dB groups was 1.1, 5.1 and 5.8%, respectively. The present results have shown that A. japonica exhibited ''typical'' physiological responses when exposed to chronic vibration stress. These data suggested that chronic vibration stress caused substantial stress in the fish; especially the persisting elevated plasma AST and ALT levels observed would be expected to adverse effect. In conclusion, chronic vibration stress could greatly affects the hematological characteristics in A. japonica.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.7-15
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• 2023

The electric submersible pump (ESP) has been operating in production wells around the world because of its high applicability and operational efficiency among artificial lift techniques. When operating an ESP in a reservoir, variables such as temperature, pressure, gas/oil ratio, and flow rate are factors that affect ESP performance. In particular, free gas in the production fluid is a major factor that reduces the life and operational efficiency of ESP. This study presents the flow loop system which can implement the performance and damage tests of ESP considering field operating conditions to quantitatively analyze the variables that affect ESP performance. The developed apparatus in an integrated system that can diagnose the failure and causes of ESP, and detect leak of tubing by linking ESP and tubing as one system. In this study, the flow conditions for stable operation of ESP were identified through single phase and two phase flow experiments related to evaluation for the performance of ESP. The results provide the basic data to develop the failure prediction and diagnosis program of ESP, and are expected to be used for real-time monitoring for optimal operating conditions and failure diagnosis for ESP operation.

• Korean Journal of Artificial Intelligence
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• v.11 no.2
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• pp.39-44
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• 2023

The creativity of thesis is that the significance of cyber security challenges in blockchain. The variety of enterprises, including those in the medical market, are the targets of cyberattacks. Hospitals and clinics are only two examples of medical facilities that are easy targets for cybercriminals, along with IoT-based medical devices like pacemakers. Cyberattacks in the medical field not only put patients' lives in danger but also have the potential to expose private and sensitive information. Reviewing and looking at the present and historical flaws and vulnerabilities in the blockchain-based IoT and medical institutions' equipment is crucial as they are sensitive, relevant, and of a medical character. This study aims to investigate recent and current weaknesses in medical equipment, of blockchain-based IoT, and institutions. Medical security systems are becoming increasingly crucial in blockchain-based IoT medical devices and digital adoption more broadly. It is gaining importance as a standalone medical device. Currently the use of software in medical market is growing exponentially and many countries have already set guidelines for quality control. The achievements of the thesis are medical equipment of blockchain-based IoT no longer exist in a vacuum, thanks to technical improvements and the emergence of electronic health records (EHRs). Increased EHR use among providers, as well as the demand for integration and connection technologies to improve clinical workflow, patient care solutions, and overall hospital operations, will fuel significant growth in the blockchain-based IoT market for linked medical devices. The need for blockchain technology and IoT-based medical device to enhance their health IT infrastructure and design and development techniques will only get louder in the future. Blockchain technology will be essential in the future of cybersecurity, because blockchain technology can be significantly improved with the cybersecurity adoption of IoT devices, i.e., via remote monitoring, reducing waiting time for emergency rooms, track assets, etc. This paper sheds the light on the benefits of the blockchain-based IoT market.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.2
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• pp.71-81
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• 2023

This study examined the transition process of clinical laboratory technologists' national examination and job definition in Korea and compared the differences in the national examination between Korea and neighboring countries, such as Japan and Taiwan. In Korea, the number of questions made for it was 200 (1965), 200 (1977), 300 (1982), 250 (1992), 330 (2006), and 280 (2015). The practice of clinical physiology is important for real-time monitoring, given the characteristics of physiological testing. On the other hand, there are conflicts between other occupations in the working area. Clinical molecular biology needs to be established as a new major subject considering the diagnostic importance of molecular biological tests and the speed of science and technology development. Clinical laboratory operations provide policy and guidance recommendations to technologist staff. The proposed clinical laboratory technologists' national examination comprises major subjects: clinical biochemistry, clinical hematology, clinical transfusionology, clinical immunology, clinical microbiology, clinical molecular biology, clinical histology, clinical cytology, clinical physiology, and clinical laboratory operations. In addition, this study proposes the job definition of clinical laboratory technologists, revising various chemical or physiological testing to biomedical or physiological testing required for medical practice.