• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.205-209
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• 2019

The exquisite structure and attractive biological properties of biominerals have great potential and increased interest for use in a wide range of medical and industrial applications. Calcium carbonate biomineralization, mainly controlled by shell matrix proteins, has been used as a representative model to understand the biomineralization mechanism. In this study, in vitro calcium carbonate crystallization was carried out under room temperature and atmospheric pressure using recombinant shell matrix protein GRP_BA and artificial shell matrix protein GG1234. Both proteins inhibited the growth of typical rhombohedral calcite crystals in the calcium carbonate crystallization using $CaCl_2$ solution and $(NH_4)_2CO_3$ vapor, and spherulitic calcite crystals with rosette-like structures were synthesized in both the presence of GRP_BA and GG1234. These results might be caused by the properties of block-like domain structure and intrinsically disordered proteins. We expect that this study can contribute to enhance understanding of the calcium carbonate biomineralization controlled by shell matrix proteins.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.8-17
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• 2018

A large urban region in Bangkok, Thailand is often inundated due to shallow water floods along the paved roads that have poor drainage facilities, and that can cause urban flooding. Existing methods, including using sand bags are not effective to prevent flooding in urban areas where the amount of sand is not sufficient. Thus, it is necessary to install artificial flood defense structures. However flooding and overflow defense equipment, which was developed in some advanced nations in Europe and in the USA, is highly expensive and complex construction methods are needed, therefore they are not suitable to be used in Southeast Asia. Thus, it is necessary to develop a flood rapid defense system(FRDS), which is inexpensive and simple to build, but is also highly functional. Thus, this study developed an FRDS that can be applied to Southeast Asia through the careful study of FRDS overviews, an analysis on the development trends in Korea and overseas, and the proposal of development needs and directions of the region. For the system developed, Korean Standards(KS) performance evaluations on leakage ratio deformation tests and impact resistance tests were conducted at the Outdoor Demonstration Test Center(Seosan) in the Korea Conformity Laboratories(KCL) and the system satisfied the standards of KS F 2639(leakage and deformation test) and KS F 2236(impact resistance test). The present study results can not only be applied to urban floods in Southeast Asian nations to cope with flood-related disasters, but also be utilized in flood prone regions and for major facilities in Korea. They can also induce scientific and pro-active responses from major local governments and facility management organizations in relation to urban floods.

• Journal of Life Science
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• v.29 no.5
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• pp.580-587
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• 2019

Benthic macroinvertebrates were analyzed in March, June, September, and December 2018 to evaluate water quality in the Songji River in Sacheon-ci, Korea. The identified benthic macroinvertebrates included 447 individuals belonging to 20 species, 18 families, 12 orders, 5 classes, and 3 phyla. Various ecological parameters were estimated for evaluation of the river status. The total ecological score of benthic macroinvertebrate community (TESB) varied from 17 (Station D) to 41 (Station A). The saprobic index and ecological score of benthic macroinvertebrate community (ESB) for the evaluation of river status revealed a water quality evaluation at Station A of II (oligosaprobic), indicating some satisfactory water protection. The benthic macroinvertebrate index (BMI) varied from 25.207 (Site C) to 39.348 (Station A). The evaluation of the river status at Stations C and D was polysaprobic, and sensitive taxa were absent. The mean Shannon-Weaver index (H') of diversity varied from 1.288 (Station D) to 2.250 (Station A). The classification of saprobity based on H' was ${\beta}$-mesosaprobic at Station A and ${\alpha}$-mesosaprobic at the other stations. The value of geometric density was varied from 1.229 (Station A) to 2.071 (Station D), with a mean of 1.582. An artificial load is being added to this river. One of load is the rectal river construction which flows straight through the river physics. Thus, the environment of living organisms deteriorates due to insufficient water. In order to secure the quality of the Songji River and a good environmental habitat, several low-height stepped-beam structures are required.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.674-681
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• 2021

Cyber attacks targeting critical infrastructure are on the rise. Critical infrastructure is defined as core infrastructures within a country with a high degree of interdependence between the different structures; therefore, it is difficult to sufficiently protect it using outdated cybersecurity techniques. In particular, the distinction between the physical and logical risks of critical infrastructure is becoming ambiguous; therefore, risk management from a comprehensive perspective must be implemented. Accordingly, as a means of further actively protecting critical infrastructure, major countries have begun to apply their security and cybersecurity systems by design, as a more expanded concept is now being considered. This proactive security approach (CSbD, Cybersecurity by Design) includes not only securing the stability of software (SW) safety design and management, but also physical politics and device (HW) safety, precautionary and blocking measures, and overall resilience. It involves a comprehensive security system. Therefore, this study compares and analyzes security by design measures towards critical infrastructure that are leading the way in the US, Europe, and Singapore. It reflects the results of an analysis of optimal cybersecurity solutions for critical infrastructure. I would like to present a plan for applying by Design.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.25-34
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• 2020

In this paper, we empirically compare the effectiveness of training models to recognize beauty-related skin disease using supervised deep learning algorithms. Recently, deep learning algorithms are being actively applied for various fields such as industry, education, and medical. For instance, in the medical field, the ability to diagnose cutaneous cancer using deep learning based artificial intelligence has improved to the experts level. However, there are still insufficient cases applied to disease related to skin beauty. This study experimentally compares the effectiveness of identifying beauty-related skin disease by applying deep learning algorithms, considering CNN, ResNet, and SE-ResNet. The experimental results using these training models show that the accuracy of CNN is 71.5% on average, ResNet is 90.6% on average, and SE-ResNet is 95.3% on average. In particular, the SE-ResNet-50 model, which is a SE-ResNet algorithm with 50 hierarchical structures, showed the most effective result for identifying beauty-related skin diseases with an average accuracy of 96.2%. The purpose of this paper is to study effective training and methods of deep learning algorithms in consideration of the identification for beauty-related skin disease. Thus, it will be able to contribute to the development of services used to treat and easy the skin disease.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.187-193
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• 2022

In the Yeongdong region of Gangwon-do, coastal areas are important resources in terms of cultural, social and economic aspects. However, the coast of Gangwon-do is experiencing severe erosion, and it is concerned that its adverse effects will gradually increase. In this study, coastline changes of Yangyang and Gangneung in Gangwon-do were tracked and analyzed over a long period of time. In order to build time series image data, aerial photos from the 1940s to the present were mainly used, and data from CORONA satellite, which operated from the 1960s to the early 1970s, were collected and used together. Using 51cm resolution ortho image and 2m resolution Digital Elevation Model(DEM) as reference, ground control points were selected to perform geometric correction on the aerial photos and CORONA images. Subsequently, Canny edge detector applied to these images to extract the coastlines. As a result of analyzing the extracted and vectorized coastlines by overlaying them in chronological order, erosion and deposition occurring around the artificial structures and on the nearby beaches were observed. In this study, the effect of seasonal variation, tide, and various coastal management including the beach filling were not considered. Because coastal erosion is greatly affected by geographic factors, each local government must find its own solution. Continuous research and local data accumulation are required.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1777-1788
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• 2022

The reservoir is a major water supply source in the domestic agricultural environment, and the monitoring of water storage of reservoirs is important for the utilization and management of agricultural water resource. Remote sensing via satellite imagery can be an effective method for regular monitoring of widely distributed objects such as reservoirs, and in this study, image classification and image segmentation algorithms are applied to Sentinel-1 Synthetic Aperture Radar (SAR) imagery for water body detection in 53 reservoirs in South Korea. Six algorithms are used: Neural Network (NN), Support Vector Machine (SVM), Random Forest (RF), Otsu, Watershed (WS), and Chan-Vese (CV), and the results of water body detection are evaluated with in-situ images taken by drones. The correlations between the in-situ water surface area and detected water surface area from each algorithm are NN 0.9941, SVM 0.9942, RF 0.9940, Otsu 0.9922, WS 0.9709, and CV 0.9736, and the larger the scale of reservoir, the higher the linear correlation was. WS showed low recall due to the undetected water bodies, and NN, SVM, and RF showed low precision due to over-detection. For water body detection through SAR imagery, we found that aquatic plants and artificial structures can be the error factors causing undetection of water body.

• Fisheries and Aquatic Sciences
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• v.25 no.9
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• pp.473-488
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• 2022

To have a better understanding of the impact of the PETRONAS oil and gas platform on commercial fisheries activities, Universiti Malaysia Terengganu (UMT) examined two approaches which are data collection from satellite and data collection from fishermen and anglers. By profiling the anglers who utilize reefed oil and gas structures for fishing, it can determine if the design and location of the reef platforms will benefit or negatively impacts those anglers and fisherman. Furthermore, this assessment will be contributing to the knowledge regarding the value of offshore oil and gas platforms as fisheries resources. Collectively, the apparent fishing activity data included, combined with the findings in the reefing viability index will help to inform PETRONAS's future decommissioning decisions and may help determine if the design and proposed locations for future rigs-to-reefs candidates would benefit commercial fishing groups, further qualifying them as appropriate artificial reef candidates. The method applied in this study is approaching by using a data satellite known as Google's Global Fishing Watch technology, which is one of the applications to measure commercial fishing efforts around the globe. The apparent commercial fishing effort around the selected twelve PETRONAS platforms was analyzed from January 2012 to December 2018. Using the data collection from fishermen which is the total estimation of commercial fish value cost (in Malaysia ringgit, MYR [RM]) in Peninsular Malaysia Asset, Sabah Asset, and Sarawak Operation region. The data were extracted every month from 2016 to 2018 from the National Oceanic and Atmospheric Administration database. Most of the selected platforms that show a high frequency of vessels around the year are platform KP-A, platform BG-A and platform PL-B. The estimated values of commercial fishes varied between platforms, with ranged from RM 10,209.92 to RM 89,023.78. Thus, platforms with high commercial fish value are selected for reefing in-situ and will serve multi-purposes and benefit the locals as well as the country. The current study has successfully assessed the potential reefing area of the Malaysian offshore environment with greater representativeness and this paper focused on its potential as a new fishing ground.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.619-630
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• 2022

The concrete mix design and compressive strength evaluation are used as basic data for the durability of sustainable structures. However, the recent diversification of mixing factors has created difficulties in calculating the correct mixing factor or setting the reference value concrete mixing design. The purpose of this study is to design a predictive model of bidirectional analysis that calculates the mixing elements of ternary concrete using deep learning, one of the artificial intelligence techniques. For the DNN-based predictive model for calculating the concrete mixing factor, performance evaluation and comparison were performed using a total of 8 models with the number of layers and the number of hidden neurons as variables. The combination calculation result was output. As a result of the model's performance evaluation, an average error rate of about 1.423% for the concrete compressive strength factor was achieved. and an average MAPE error of 8.22% for the prediction of the ternary concrete mixing factor was satisfied. Through comparing the performance evaluation for each structure of the DNN model, the DNN5L-2048 model showed the highest performance for all compounding factors. Using the learned DNN model, the prediction of the ternary concrete formulation table with the required compressive strength of 30 and 50 MPa was carried out. The verification process through the expansion of the data set for learning and a comparison between the actual concrete mix table and the DNN model output concrete mix table is necessary.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.107-118
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• 2022

The social need for stable hydrogen storage technologies that respond to the increasing demand for hydrogen energy is increasing. Among them, underground hydrogen storage is recognized as the most economical and reasonable storage method because of its vast hydrogen storage capacity. In Korea, low-depth hydrogen storage using artificial protective structures is being considered. Further, establishing corresponding safety standards and ground stability evaluation is becoming essential. This study evaluated the hydro-mechanical behavior of the ground during a hydrogen gas leak from a low-depth underground hydrogen storage facility through the HM coupled analysis model. The predictive reliability of the simulation model was verified through benchmark experiments. A parameter study was performed using a metamodel to analyze the sensitivity of factors affecting the surface uplift caused by the upward infiltration of high-pressure hydrogen gas. Accordingly, it was confirmed that the elastic modulus of the ground was the largest. The simulation results are considered to be valuable primary data for evaluating the complex analysis of hydrogen gas explosions as well as hydrogen gas leaks in the future.