• Title/Summary/Keyword: 성능 분석

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Preparation of Novel Natural Polymer-based Magnetic Hydrogels Reinforced with Hyperbranched Polyglycerol (HPG) Responsible for Enhanced Mechanical Properties (과분지 폴리글리세롤(HPG) 강화를 통해 기계적 물성이 향상된 새로운 천연 고분자 기반 자성 하이드로젤의 제조)

  • Eun-Hye Jang;Jisu Jang;Sehyun Kwon;Jeon-Hyun Park;Yujeong Jeong;Sungwook Chung
    • Clean Technology
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    • v.29 no.1
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    • pp.10-21
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    • 2023
  • Hydrogels that are made of natural polymer-based double networks have excellent biocompatibility, low cytotoxicity, and high water content, assuring that the material has the properties required for a variety of biomedical applications. However, hydrogels also have limitations due to their relatively weak mechanical properties. In this study, hydrogels based on an alginate di-aldehyde (ADA) and gelatin (Gel) double network that is reinforced with additional hydrogen bonds formed between the hydroxyl (-OH) groups of the hyperbranched polymer (HPG) and the functional groups present inside of the hydrogels were successfully synthesized. The enhanced mechanical properties of these synthesized hydrogels were evaluated by varying the amount of HPG added during the hydrogel synthesis from 0 to 25%. In addition, magnetite nanoparticles (Fe3O4 NPs) were synthesized within the hydrogels and the structures and the magnetic properties of the hydrogels were also characterized. The hydrogels that contained 15% HPG and Fe3O4 NPs exhibited superparamagnetic behaviors with a saturation magnetization value of 3.8 emu g-1. These particular hydrogels also had strengthened mechanical properties with a maximum compressive stress of 1.1 MPa at a strain of 67.4%. Magnetic hydrogels made with natural polymer-based double networks provide improved mechanical properties and have a significant potential for drug delivery and biomaterial application.

The Validity Test of Statistical Matching Simulation Using the Data of Korea Venture Firms and Korea Innovation Survey (벤처기업정밀실태조사와 한국기업혁신조사 데이터를 활용한 통계적 매칭의 타당성 검증)

  • An, Kyungmin;Lee, Young-Chan
    • Knowledge Management Research
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    • v.24 no.1
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    • pp.245-271
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    • 2023
  • The change to the data economy requires a new analysis beyond ordinary research in the management field. Data matching refers to a technique or processing method that combines data sets collected from different samples with the same population. In this study, statistical matching was performed using random hotdeck and Mahalanobis distance functions using 2020 Survey of Korea Venture Firms and 2020 Korea Innovation Survey datas. Among the variables used for statistical matching simulation, the industry and the number of workers were set to be completely consistent, and region, business power, listed market, and sales were set as common variables. Simulation verification was confirmed by mean test and kernel density. As a result of the analysis, it was confirmed that statistical matching was appropriate because there was a difference in the average test, but a similar pattern was shown in the kernel density. This result attempted to expand the spectrum of the research method by experimenting with a data matching research methodology that has not been sufficiently attempted in the management field, and suggests implications in terms of data utilization and diversity.

A User Participatory Study on the Development of Korean Road Racing Hand Cycle and Usability Assessment: Targeting on National Players (사용자 참여형 연구 기반의 한국형 경기용 핸드사이클 개발과 사용성평가 - 국가대표 대상으로 -)

  • Kim, Dong Wook;Kim, Jeong Hyun;Kim, Jong Bae
    • Korea Science and Art Forum
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    • v.28
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    • pp.23-32
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    • 2017
  • The purpose of this study is to contribute to the activation of sports for the disabled people in Korea through the localization of the road racing handcycles. Recently, there are no handcycles produced in Korea, and all the players are using products made in foreign countries. In the case of foreign products, it is made to fit the body shape of foreign athletes. Therefore, when domestic players are using them, they put additional parts to foreign products in order to fit their body shape. This not only adds to the cost burden, but also causes a decrease in the performance of the athletes. In order to overcome these problems, we developed the road racing handcycle in consideration of the body shape of the Koreans and conducted a comparative usability evaluation with the foreign products to evaluate the performance of the developed prototype. Therefore, we analyzed the quantitative and qualitative evaluation results of the prototype produced in the previous study, and developed the Korean road racing handcycle that can improve the competitiveness while considering the shape of domestic players. Based on the problems derived from the first prototype, this study additionally constructed a crank, an air intake part and a discharge part, and a rear anti-shake prevention device. In order to evaluate the usability, we conducted a comparative usability assessment with the foreign products used by the current standing handcycle athletes. The results were measured in the area of effectiveness, efficiency, and satisfaction, and the prototype developed through the research on efficiency and satisfaction excluding effectiveness was evaluated to be higher than those of foreign products. This study will contribute to the improvement of international competitiveness due to import substitution effects of foreign products and exports by lowering the handcycle cost of importing foreign handcycle.

Estimation for Ground Air Temperature Using GEO-KOMPSAT-2A and Deep Neural Network (심층신경망과 천리안위성 2A호를 활용한 지상기온 추정에 관한 연구)

  • Taeyoon Eom;Kwangnyun Kim;Yonghan Jo;Keunyong Song;Yunjeong Lee;Yun Gon Lee
    • Korean Journal of Remote Sensing
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    • v.39 no.2
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    • pp.207-221
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    • 2023
  • This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.

Verification of Multi-point Displacement Response Measurement Algorithm Using Image Processing Technique (영상처리기법을 이용한 다중 변위응답 측정 알고리즘의 검증)

  • Kim, Sung-Wan;Kim, Nam-Sik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.3A
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    • pp.297-307
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    • 2010
  • Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.

Behavior Analysis of Concrete Structure under Blast Loading : (I) Experiment Procedures (폭발하중을 받는 콘크리트 구조물의 실험적 거동분석 : (I) 실험수행절차)

  • Yi, Na Hyun;Kim, Sung Bae;Kim, Jang-Ho Jay;Choi, Jong Kwon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.5A
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    • pp.557-564
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    • 2009
  • In recent years, there have been numerous explosion-related accidents due to military and terrorist activities. Such incidents caused not only damages to structures but also human casualties, especially in urban areas. To protect structures and save human lives against explosion accidents, better understanding of the explosion effect on structures is needed. In an explosion, the blast overpressure is applied to concrete structures as an impulsive load of extremely short duration with very high pressure and heat. Generally, concrete is known to have a relatively high blast resistance compared to other construction materials. However, information and test results related to the blast experiment of internal and external have been limited due to military and national security reasons. Therefore, in this paper, to evaluate blast effect on reinforced have concrete structure and its protective performance, blast tests are carried out with $1.0m{\times}1.0m{\times}150mm$ reinforce concrete slab structure at the Agency for Defence Development. The standoff blast distance is 1.5 m and the preliminary tests consists with TNT 9 lbs and TNT 35 lbs and the main tests used ANFO 35 lbs. It is the first ever blast experiment for nonmilitary purposes domestically. In this paper, based on the basic experiment procedure and measurement details for acquiring structural behavior data, the blast experimental measurement system and procedure are established details. The procedure of blast experiments are based on the established measurement system which consists of sensor, signal conditioner, DAQ system, software. It can be used as basic research references for related research areas, which include protective design and effective behavior measurements of structure under blast loading.

Estimation of Chlorophyll-a Concentration in Nakdong River Using Machine Learning-Based Satellite Data and Water Quality, Hydrological, and Meteorological Factors (머신러닝 기반 위성영상과 수질·수문·기상 인자를 활용한 낙동강의 Chlorophyll-a 농도 추정)

  • Soryeon Park;Sanghun Son;Jaegu Bae;Doi Lee;Dongju Seo;Jinsoo Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.5_1
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    • pp.655-667
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    • 2023
  • Algal bloom outbreaks are frequently reported around the world, and serious water pollution problems arise every year in Korea. It is necessary to protect the aquatic ecosystem through continuous management and rapid response. Many studies using satellite images are being conducted to estimate the concentration of chlorophyll-a (Chl-a), an indicator of algal bloom occurrence. However, machine learning models have recently been used because it is difficult to accurately calculate Chl-a due to the spectral characteristics and atmospheric correction errors that change depending on the water system. It is necessary to consider the factors affecting algal bloom as well as the satellite spectral index. Therefore, this study constructed a dataset by considering water quality, hydrological and meteorological factors, and sentinel-2 images in combination. Representative ensemble models random forest and extreme gradient boosting (XGBoost) were used to predict the concentration of Chl-a in eight weirs located on the Nakdong river over the past five years. R-squared score (R2), root mean square errors (RMSE), and mean absolute errors (MAE) were used as model evaluation indicators, and it was confirmed that R2 of XGBoost was 0.80, RMSE was 6.612, and MAE was 4.457. Shapley additive expansion analysis showed that water quality factors, suspended solids, biochemical oxygen demand, dissolved oxygen, and the band ratio using red edge bands were of high importance in both models. Various input data were confirmed to help improve model performance, and it seems that it can be applied to domestic and international algal bloom detection.

Development of Seasonal Habitat Suitability Indices for the Todarodes Pacificus around South Korea Based on GOCI Data (GOCI 자료를 활용한 한국 연근해 살오징어의 계절별 서식적합지수 모델 개발)

  • Seonju Lee;Jong-Kuk Choi;Myung-Sook Park;Sang Woo Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1635-1650
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    • 2023
  • Under global warming, the steadily increasing sea surface temperature (SST) severely impacts marine ecosystems,such as the productivity decrease and change in marine species distribution. Recently, the catch of Todarodes Pacificus, one of South Korea's primary marine resources, has dramatically decreased. In this study, we analyze the marine environment that affects the formation of fishing grounds of Todarodes Pacificus and develop seasonal habitat suitability index (HSI) models based on various satellite data including Geostationary Ocean Color Imager (GOCI) data to continuously manage fisheries resources over Korean exclusive economic zone. About 83% of catches are found within the range of SST of 14.11-26.16℃,sea level height of 0.56-0.82 m, chlorophyll-a concentration of 0.31-1.52 mg m-3, and primary production of 580.96-1574.13 mg C m-2 day-1. The seasonal HSI models are developed using the Arithmetic Mean Model, which showed the best performance. Comparing the developed HSI value with the 2019 catch data, it is confirmed that the HSI model is valid because the fishing grounds are formed in different sea regions by season (East Sea in winter and Yellow Sea in summer) and the high HSI (> 0.6) concurrences to areas with the high catch. In addition, we identified the significant increasing trend in SST over study regions, which is highly related to the formation of fishing grounds of Todarodes Pacificus. We can expect the fishing grounds will be changed by accelerating ocean warming in the future. Continuous HSI monitoring is necessary to manage fisheries' spatial and temporal distribution.

Performance Evaluation of Monitoring System for Sargassum horneri Using GOCI-II: Focusing on the Results of Removing False Detection in the Yellow Sea and East China Sea (GOCI-II 기반 괭생이모자반 모니터링 시스템 성능 평가: 황해 및 동중국해 해역 오탐지 제거 결과를 중심으로)

  • Han-bit Lee;Ju-Eun Kim;Moon-Seon Kim;Dong-Su Kim;Seung-Hwan Min;Tae-Ho Kim
    • Korean Journal of Remote Sensing
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    • v.39 no.6_2
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    • pp.1615-1633
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    • 2023
  • Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

Preparation and Gas Permeation Performance of Pd-Ag-Cu Hydrogen Separation Membrane Using α-Al2O3 Support (α-Al2O3 지지체를 이용한 Pd-Ag-Cu 수소 분리막의 제조 및 기체투과 성능)

  • Sung Woo Han;Min Chang Shin;Xuelong Zhuang;Jae Yeon Hwang;Min Young Ko;Si Eun Kim;Chang Hoon Jung;Jung Hoon Park
    • Membrane Journal
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    • v.34 no.1
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    • pp.50-57
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    • 2024
  • In this experiment, Pd-Ag-Cu membrane was manufactured using electroless plating on an α-Al2O3 support. Pd, Ag and Cu were each coated on the surface of the support through electroless plating and heat treatment was performed for 18 h at 500℃ in H2 in the middle of electroless plating to form Pd alloy. The surface of the Pd-Ag-Cu membrane was observed through Scanning Electron Microscopy (SEM), and the thickness of the Pd membrane was measured to be 7.82 ㎛ and the thickness of the Pd-Ag-Cu membrane was measured to be 3.54 ㎛. Energy dispersive X-ray spectroscopy and X-ray diffraction analysis confirmed the formation of a Pd-Ag-Cu alloy with a composition of Pd-78wt%, Ag-8.81wt% and Cu-13.19wt%. The gas permeation experiment was conducted under the conditions of 350~450℃ and 1~4 bar in H2 single gas and H2/N2 mixed gas. The maximum H2 flux of the hydrogen separation membrane measured in H2 single gas is 74.16 ml/cm2·min at 450℃ and 4 bar for the Pd membrane and 113.64 ml/cm2·min at 450℃ and 4 bar for the Pd-Ag-Cu membrane. In the case of the separation factor measured in H2/N2 mixed gas, separation factors of 2437 and 11032 were measured at 450℃ and 4 bar.