• Journal of Microbiology and Biotechnology
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• v.31 no.3
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• pp.387-397
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• 2021

There is growing interest in the production of microalgae-based, high-value by-products as an emerging green biotechnology. However, a cultivation platform for Oocystis sp. has yet to be established. We therefore examined the effects of bacterial culture additions on the growth and production of valuable compounds of the microalgal strain Oocystis sp. KNUA044, isolated from a locally adapted region in Korea. The strain grew only in the presence of a clear supernatant of Sphingomonas sp. KNU100 culture solution and generated 28.57 mg/l/d of biomass productivity. Protein content (43.9 wt%) was approximately two-fold higher than carbohydrate content (29.4 wt%) and lipid content (13.9 wt%). Oocystis sp. KNUA044 produced the monosaccharide fucose (33 ㎍/mg and 0.94 mg/l/d), reported here for the first time. Fatty acid profiling showed high accumulation (over 60%) of polyunsaturated fatty acids (PUFAs) compared to saturated (29.4%) and monounsaturated fatty acids (9.9%) under the same culture conditions. Of these PUFAs, the algal strain produced the highest concentration of linolenic acid (C18:3 ω3; 40.2%) in the omega-3 family and generated eicosapentaenoic acid (C20:5 ω3; 6.0%), also known as EPA. Based on these results, we suggest that the application of Sphingomonas sp. KNU100 for strain-dependent cultivation of Oocystis sp. KNUA044 holds future promise as a bioprocess capable of increasing algal biomass and high-value bioactive by-products, including fucose and PUFAs such as linolenic acid and EPA.

• Journal of the Korea Society for Simulation
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• v.31 no.4
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• pp.11-22
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• 2022

Unlike a short-range, a long-range underwater acoustic communication(UWAC) uses low frequency signal and deep sound channel to minimize propagation loss. In this case, even though communication signals are modulated using a covert transmission technique such as spread spectrum, it is hard to conceal the existence of the signals. The unconcealed communication signal can be utilized as active sonar signal by enemy and presence of underwater vehicles may be exposed to the interceptor. Since it is very important to maintain stealthiness for underwater vehicles, the detection probability of friendly underwater vehicles should be considered when interceptor utilizes our long-range UWAC signal. In this paper, we modeled a long-range UWAC environment for analyzing the detection performance of underwater vehicles and proposed the region of interest(ROI) setup method and the measurement of detection performance. By computer simulations, we yielded parameters, analyzed the detection probability and the detection performance in ROI. The analysis results showed that the proposed detection performance analysis method for underwater vehicles could play an important role in the operation of long-range UWAC equipment.

• Korean Journal of Organic Agriculture
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• v.30 no.4
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• pp.451-470
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• 2022

Recently, the environment has been recognized as an important factor in increasing competitiveness in the industry. In agriculture and rural areas, the environment is becoming important in terms of the competitive advantage of agricultural products and continued regional development. This study intended to provide farmers with basic data for the continuous development of local agriculture through exploratory studies of environmental behaviors and regional development. In this study, 107 questionnaires were used for analysis of farmers in Jinan County to analyze the impact of farmers' environmental consciousness on regional development, and the research model was verified using a structural equation model. As a result of the analysis, it was analyzed that among the components of the environmental consciousness of farmers, environmental health has a statistically significant positive effect on environmental behaviors, while environmental interest and soil environment do not have an impact. The environmental behaviors of farmers have not been shown to be statistically significant to regional development. As a result of the analysis of this research, first, it is necessary to foster at the local level by establishing a customized fostering system for each village and region, such as education and technical support to vitalize the participation of young farmers and small and medium-sized farmers through the establishment of an Eco-friendly agricultural organization support system. It is necessary to raise public awareness of the public good function of agriculture and expand opportunities for sharing the value of Eco-friendly agriculture.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.39-46
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• 2022

As the link between traffic accidents and social and economic losses has been confirmed, there is a growing interest in developing safety policies based on crash data and a need for countermeasures to reduce severe crash outcomes such as severe injuries and fatalities. In this study, we select Daejeon city where the relative proportion of fatal crashes is high, as a case study region and focus on the severity of pedestrian crashes. After a series of data manipulation process, we run machine learning algorithms for the optimal model selection and variable identification. Of nine algorithms applied, AdaBoost and Random Forest (ensemble based ones) outperform others in terms of performance metrics. Based on the results, we identify major influential factors (i.e., the age of pedestrian as 70s or 20s, pedestrian crossing) on pedestrian crashes in Daejeon, and suggest them as measures for reducing severe outcomes.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.1-13
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• 2023

Predicting earthquakes is difficult due to the complexity of the systems underlying tectonic phenomena and incomplete understanding of the interactions among tectonic settings, tectonic stress, and crustal components. The Korean Peninsula is located in a stable intraplate region with a low average seismicity of M 2.3. As public interest in the earthquake grows, we analyzed earthquakes on the Korean Peninsula by attempting to predict spatio-temporal earthquake patterns and magnitudes using Facebook's Prophet model based on deep learning, and here we discuss seismic distribution zones using DBSCAN, a cluster analysis method. The Prophet model predicts future earthquakes in Chungcheongbuk-do, Gyeonggi-do, Seoul, and Gyeongsangbuk-do.

• Smart Structures and Systems
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• v.31 no.4
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• pp.421-436
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• 2023

This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.120-120
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• 2023

본 연구에서는 CCTV 영상 내 빗줄기의 특성을 바탕으로 강우강도를 산정하기 위한 합성곱 신경망(CNNs, Convolutional Neural Networks) 기반 강우강도 산정 모형을 제안하였다. 중앙대학교 및 한국건설생활환경시험연구원 내 대형기후환경시험실에서 얻은 CCTV 영상들을 대상으로 연구를 수행하고, 우적계 등과 같은 지상 관측자료와 강우강도 산정 결과를 비교·검증하였다. 먼저, CCTV 영상 내 빗줄기의 미세한 변동 특성을 반영하기 위해 데이터 전처리 작업을 진행하였다. 이는 원본 영상으로부터 빗줄기 층을 분리해내는 과정, 빗줄기 층에서 빗물 입자를 분리해내는 과정, 그리고 빗물 입자를 인식하는 과정 등 총 세 단계로 구분된다. 합성곱 신경망 기반 강우강도 산정 모형 구축을 위해 영상 전처리가 완료된 데이터들을 입력값으로 설정하고, 촬영 시점에 대응되는 지상관측 자료를 출력값으로 고려하여 강우강도 산정모형을 훈련시켰다. CCTV 원자료 내 특정 영역에 편향되어 강우강도를 산정하는 과적합 현상의 발생을 방지하기 위해 원자료 내 5개의 관심 영역(ROI, Region of Interest)을 설정하였다. 추가로, CCTV의 해상도를 총 4개(2560×1440, 1920×1080, 1280×720, 720×480)로 구분함으로써 해상도 변화에 따른 학습 결과의 차이를 분석·평가하였다. 이는 기존 사례들과 비교했을 때, CCTV 영상을 기반으로 빗줄기의 거동 특성과 같은 물리적인 현상을 직간접적으로 고려하여 강우강도를 산정했다는 점과 더불어 머신러닝을 적용하여 강우 이미지가 갖는 본질적인 특징들을 파악했다는 측면에서, 추후 본 연구에서 제안한 모형의 활용 가치가 극대화될 수 있을 것으로 판단된다.

• Health Policy and Management
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• v.33 no.3
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• pp.273-294
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• 2023

Background: Most developed countries are working to improve their universal health coverage systems. This study investigates regional disparities in unmet healthcare needs and their causes in South Korea. Additionally, it compares the unmet healthcare needs rate in South Korea with that of 33 European countries. Methods: The analysis incorporates information from 13,359 adults aged 19 or older, using data from the Korea Health Panel. The dependent variables encompass the experience of unmet healthcare needs and the three causes of occurrence: "burden of medical expenses," "time constraints," and "lack of care." The primary variable of interest is the region of residence, while control variables encompass 14 socio-demographic, health, and functional characteristics. Multivariable binary logistic regression analysis, accounting for the sampling design, is conducted. Results: The rate of unmet healthcare needs in Korea is 11.7% (95% confidence interval [CI], 11.0%-13.3%), which is approximately 30 times higher than that of Austria (0.4%). The causes of unmet healthcare needs, ranked in descending order, are "lack of care," "time constraints," and "burden of medical expenses." Predictive probabilities for experiencing unmet healthcare needs and each cause differ significantly between regions. For instance, the probability of experiencing unmet healthcare needs due to "lack of care" is approximately 10 times higher in Gangwon-do (13.5%; 95% CI, 13.0%-14.1%) than in Busan (1.3%; 95% CI, 1.3%-1.4%). The probability due to "burden of medical expenses" is approximately 14 times higher in Seoul (4.1%; 95% CI, 3.6%-4.6%) compared to Jeollanam-do (0.3%; 95% CI, 0.2%-0.4%). Conclusion: Amid rapid sociodemographic transitions, South Korea must make significant efforts to alleviate unmet healthcare needs and the associated regional disparities. To effectively achieve this, it is recommended that South Korea involves the National Assembly in healthcare policy-making, while maintaining a centralized financing model and delegating healthcare planning and implementation to regional authorities for their local residents-similar to the approaches of the United Kingdom and France.

• Journal of radiological science and technology
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• v.46 no.2
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• pp.151-157
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• 2023

The purpose of this study was to develop an assist device that could correct and support patient position during biopsy on computed tomography (CT) using 3D printing technology. The development method was conducted in the order of 3D design, 3D output, intermediate evaluation for product, final assist device evaluation. The 3D design method was conducted in the order of prior research data survey, measurement, primary modeling, 3D printing, output evaluation, and supplementary modeling. The 3D output was the 3D printer (3DWOX 2X, Sindoh, Korea) with additive manufacturing technology and the polylactic acid (PLA) materials. At this time, the optimal strength was evaluated to infill degree of product as the 3D printing factors into 20%, 40%, 60%, and 80%. The intermediate evaluation and supplementation was measured noise in the region of interest (ROI) around the beam hardening artifact on the CT images. We used 128-channel MDCT (Discovery 75 HD, GE, USA) to scan with a slice thickness of 100 kVp, 150 mA, and 2.5 mm on the 3D printing product. We compared the surrounding noise of the final 3D printing product with the beginning of it. and then the strength of it according to the degree of infill was evaluated. As a result, the surrounding noise of the final and the early devices were measured at an average of 3.3 ± 0.5 HU and 7.1 ± 0.1 HU, respectively, which significantly reduced the noise of the final 3D printing product (p<0.001). We found that the percentage of infill according to the optimal strength was found to be 60%. Finally, development of assist devices for CT biopsy will be able to minimize artifacts and provide convenience to medical staff and patients.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.247-257
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• 2023

Precise counting of cell number stands in important position within clinical and research laboratories. Conventional methods such as hemocytometer, migration/invasion assay, or automated cell counters have limited in analytical time, cost, and accuracy., which needs an alternative way with time-efficient in-situ approach to broaden the application avenue. Here, we present simple coding-based cell counting method using image analysis tool, freely available image software (ImageJ). Firstly, we encapsulated RFP-expressing bacteria in a droplet using microfluidic device and automatically performed fluorescence image-based analysis for the quantification of cell numbers. Also, time-lapse images were captured for tracking the change of cell numbers in a droplet containing different concentrations of antibiotics. This study confirms that our approach is approximately 15 times faster and provides more accurate number of cells in a droplet than the external analysis program method. We envision that it can be used to the development of high-throughput image-based cell counting analysis.