• Title/Summary/Keyword: accuracy analysis

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Accuracy Analysis for Slope Movement Characterization by comparing the Data from Real-time Measurement Device and 3D Model Value with Drone based Photogrammetry (도로비탈면 상시계측 실측치와 드론 사진측량에 의한 3D 모델값의 정확도 비교분석)

  • CHO, Han-Kwang;CHANG, Ki-Tae;HONG, Seong-Jin;HONG, Goo-Pyo;KIM, Sang-Hwan;KWON, Se-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.23 no.4
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    • pp.234-252
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    • 2020
  • This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

Polyphenols in peanut shells and their antioxidant activity: optimal extraction conditions and the evaluation of anti-obesity effects (폴리페놀 함량과 항산화력에 따른 피땅콩 겉껍질의 최적 추출 조건 확립과 항비만 기능성 평가)

  • Gam, Da Hye;Hong, Ji Woo;Yeom, Suh Hee;Kim, Jin Woo
    • Journal of Nutrition and Health
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    • v.54 no.1
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    • pp.116-128
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    • 2021
  • Purpose: The extraction conditions for bioactive components from peanut shells, which is a byproduct of peanut processing, were optimized to enhance the total phenolic content (TPC, Y1), total flavonoid content (TFC, Y2), and 2,2-diphenyl-1-picrylhydrazyl radical scavenging activity (RSA, Y3). In addition, this study evaluated the anti-obesity effect of peanut shell extract. Methods: Optimization of ultrasonic-assisted extraction (UAE) was performed using a response surface methodology. The independent variables applied for extraction were time (X1: 5.0-55.0), temperature (X2: 26.0-94.0), and ethanol concentration (X3: 0.0%-99.5%). Quadratic regression models were derived based on the results of 17 experimental sets, and an analysis of the variance was performed to verify its accuracy and precision of the regression equations. Results: When evaluating the effects of independent variables on responses using statistically-based optimization, the independent variable with the most significant effect on the TPC, TFC, and RSA was the ethanol concentration (p = 0.0008). The optimal extraction conditions to satisfy all three responses were 35.8 minutes, 82.7℃, and 96.0% ethanol. Under these conditions, the inhibitory activities of α-glucosidase and pancreatic lipase by the extract were 86.4% and 78.5%, respectively. Conclusion: In this study, UAE showed superior extraction efficiency compared to conventional hot-water extraction in the extraction of polyphenols and bioactive materials. In addition, α-glucosidase and pancreatic lipase inhibitory effects were identified, suggesting that peanut shells can be used as effective antioxidants and anti-obesity agents in functional foods and medicines.

Deep Learning-Based Box Office Prediction Using the Image Characteristics of Advertising Posters in Performing Arts (공연예술에서 광고포스터의 이미지 특성을 활용한 딥러닝 기반 관객예측)

  • Cho, Yujung;Kang, Kyungpyo;Kwon, Ohbyung
    • The Journal of Society for e-Business Studies
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    • v.26 no.2
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    • pp.19-43
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    • 2021
  • The prediction of box office performance in performing arts institutions is an important issue in the performing arts industry and institutions. For this, traditional prediction methodology and data mining methodology using standardized data such as cast members, performance venues, and ticket prices have been proposed. However, although it is evident that audiences tend to seek out their intentions by the performance guide poster, few attempts were made to predict box office performance by analyzing poster images. Hence, the purpose of this study is to propose a deep learning application method that can predict box office success through performance-related poster images. Prediction was performed using deep learning algorithms such as Pure CNN, VGG-16, Inception-v3, and ResNet50 using poster images published on the KOPIS as learning data set. In addition, an ensemble with traditional regression analysis methodology was also attempted. As a result, it showed high discrimination performance exceeding 85% of box office prediction accuracy. This study is the first attempt to predict box office success using image data in the performing arts field, and the method proposed in this study can be applied to the areas of poster-based advertisements such as institutional promotions and corporate product advertisements.

Analysis of Debris Flow Hazard Zone by the Optimal Parameters Extraction of Random Walk Model - Case on Debris Flow Area of Bonghwa County in Gyeongbuk Province - (Random Walk Model의 최적 파라미터 추출에 의한 토석류 피해범위 분석 - 경북 봉화군 토석류 발생지를 대상으로 -)

  • Lee, Chang-Woo;Woo, Choongshik;Youn, Ho-Joong
    • Journal of Korean Society of Forest Science
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    • v.100 no.4
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    • pp.664-671
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    • 2011
  • Random Walk Model can predict the sediment areas of debris flow but it must be extracted three parameters fitted topographical environment. This study developed the method to extract the optimal values of three parameters - Once flowing volume, Stopping slope and Gravity weight - for Random Walk Model. And the extracted parameters were validated by aerial photographs of the debris flowed area. To extract the optimal parameters was randomly performed, limiting the range values of three parameters and developing an accuracy decision method that is called the rate of concordance. The set of the optimal parameters was decided on highest the rate of concordance and a consistency. As a result, the optimal parameters in Bonghwa county were showed that the once flowing volume is $1.0m^3$, the stopping slope is $4.2^{\circ}$ and the gravity weight is 2 when the rate of concordance is -0.2. The validating result of the optimal parameters showed closely that the rate of concordance is average -0.2.

Spatiotemporal Traffic Density Estimation Based on Low Frequency ADAS Probe Data on Freeway (표본 ADAS 차두거리 기반 연속류 시공간적 교통밀도 추정)

  • Lim, Donghyun;Ko, Eunjeong;Seo, Younghoon;Kim, Hyungjoo
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.6
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    • pp.208-221
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    • 2020
  • The objective of this study is to estimate and analyze the traffic density of continuous flow using the trajectory of individual vehicles and the headway of sample probe vehicles-front vehicles obtained from ADAS (Advanced Driver Assitance System) installed in sample probe vehicles. In the past, traffic density of continuous traffic flow was mainly estimated by processing data such as traffic volume, speed, and share collected from Vehicle Detection System, or by counting the number of vehicles directly using video information such as CCTV. This method showed the limitation of spatial limitations in estimating traffic density, and low reliability of estimation in the event of traffic congestion. To overcome the limitations of prior research, In this study, individual vehicle trajectory data and vehicle headway information collected from ADAS are used to detect the space on the road and to estimate the spatiotemporal traffic density using the Generalized Density formula. As a result, an analysis of the accuracy of the traffic density estimates according to the sampling rate of ADAS vehicles showed that the expected sampling rate of 30% was approximately 90% consistent with the actual traffic density. This study contribute to efficient traffic operation management by estimating reliable traffic density in road situations where ADAS and autonomous vehicles are mixed.

QTc Prolongation due to Psychotropic Drugs Intoxication and Its Risk Assessment (향정신성 약물 중독에 의한 QTc 연장과 그 위험성에 대한 고찰)

  • Park, Kwan Ho;Hong, Hoon Pyo;Lee, Jong Seok;Jeong, Ki Young;Ko, Seok Hun;Kim, Sung Kyu;Choi, Han Sung
    • Journal of The Korean Society of Clinical Toxicology
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    • v.18 no.2
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    • pp.66-77
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    • 2020
  • Purpose: The aims of the present study were twofold. First, the research investigated the effect of an individual's risk factors and the prevalence of psychotropic drugs on QTc prolongation, TdP (torsades de pointes), and death. Second, the study compared the risk scoring systems (the Mayo Pro-QT risk score and the Tisadale risk score) on QTc prolongation. Methods: The medical records of intoxicated patients who visited the emergency department between March 2010 and February 2019 were reviewed retrospectively. Among 733 patients, the present study included 426 psychotropic drug-intoxicated patients. The patients were categorized according to the QTc value. The known risk factors of QTc prolongation were examined, and the Mayo Pro-QT risk score and the Tisadale risk score were calculated. The analysis was performed using multiple logistic regression, Spearman correlation, and ROC (receiver operating characteristic). Results: The numbers in the mild to moderate group (male: 470≤QTc<500 ms, female: 480≤QTc<500 ms) and severe group (QTc≥500 ms or increase of QTc at least 60ms from baseline, both sex) were 68 and 95, respectively. TdP did not occur, and the only cause of death was aspiration pneumonia. The statically significant risk factors were multidrug intoxications of TCA (tricyclic antidepressant), atypical antipsychotics, an atypical antidepressant, panic disorder, and hypokalemia. The Tisadale risk score was larger than the Mayo Pro-QT risk score. Conclusion: Multiple psychotropic drugs intoxication (TCA, an atypical antidepressant, and atypical antipsychotics), panic disorder, and hypokalemia have been proven to be the main risk factors of QTc prolongation, which require enhanced attention. The present study showed that the Tisadale score had a stronger correlation and predictive accuracy for QTc prolongation than the Mayo Pro-QT score. As a result, the Tisadale risk score is a crucial assessment tool for psychotropic drug-intoxicated patients in a clinical setting.

An Empirical Formula of Bearing Capacity on Prebored and Precast Steel Piles (강관 매입말뚝의 지지력 공식 제안)

  • Park, Jong-Jeon;Kim, Do-Hyun;Jung, Gyung-Ja;Jeong, Sang-Seom
    • Journal of the Korean Geotechnical Society
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    • v.37 no.6
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    • pp.5-20
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    • 2021
  • In this study, a modified empirical formula for estimating the bearing capacity of the steel pipe prebored and precast pile was proposed by performing 20 cases of real-scale field pile loading tests. The proposed formula will be based on expanded SPT N-value in order to consider the realistic condition of the surrounding soil. The formula is proposed based on a statistic approach of the data points from the field pile loading test, in order to ensure safe engineering practice while finding a reliable formula. The statistical analysis of the data points from the loading test indicated that the existing formula has been underestimated the bearing capacity of the prebored and precast pile. The proposed formula estimates 15% and 20% higher pile End bearing capacity (qt=230Pdriven(kN/m2)) and the shaft resistance (fmax=3.0NsE(kN/m2)) compared to the existing formula. The accuracy and the stability of the proposed formula was verified by comparing the estimated results with additional field test data. The verification process showed that the proposed formula was estimated to be more accurate than the existing formula.

A Study on Improvement of Directional Errors for K-MLRS Launcher (천무 발사대 방향성 오류현상 개선에 관한 연구)

  • Kim, Hyeeun;Kim, Minchang;Yu, Hanjun;Bae, Gongmyeong;Oh, Eunbin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.705-713
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    • 2021
  • Because the cage assembly serves as the launch platform, an accurate aim is essential to ensure shooting accuracy for the target. On the other hand, the abnormal rotation of the cage due to the directional errors of the K-MLRS has continuously caused quality problems. The quality problem of weapon systems may have a negative impact on the military's power loss. In this study, improvement plans were derived by examining the defects and analyzing the directional errors of the K-MLRS launcher. In addition, all possible causes of directional errors were derived from the flow diagram for cage directionality. Based on the results, the defense design through the software program was intended to prevent the loss of direction. Through this study, the signal error of the resolver was improved by preventing unspecific signals in the data. Furthermore, the directional judgment method was improved to minimize the impact of data distortion. Lastly, directional storage and verification methods were improved so that data for the cage rotation direction would not be affected by errors. For the design improvement method, the reliability was verified through the system applicability. This study is expected to be a reference for failure analysis and design for similar weapon systems in the future.

Developing the District Unit Plan Simulation using Procedural Modeling (절차적 모델링을 활용한 지구단위계획 시뮬레이션 개발)

  • Jun, Jin Hwan;Kim, Chung Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.3
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    • pp.546-559
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    • 2021
  • This research aimed to develop the district unit plan simulation using procedural modeling based on shape grammar. For this, Esri's CityEngine 2020.0 was selected as a main development tool, and Inside Commercial Area in Bangi-dong, Songpa-gu, Seoul as the research site where about 25% of the total area was developed over the past five years. Specifically, the research developed the simulation through the following three phases of Data-Information-Knowledge after selecting necessary parameters. In the Data phase, 2 and 3 dimensional data were obtained by utilizing data sharing platforms. In the next Information phase, the acquired data were generated into various procedural models according to the shape grammar, and the 2D and 3D layers were then integrated using relevant applications. In the final Knowledge phase, three-dimensional spatial analysis and storytelling contents were produced based on the integrated layer. As a result, the research suggests the following three implications for the simulation development. First, data accuracy and improvement of sharing platforms are needed in order to effectively carry out the simulation development. Second, the guidelines for district unit plans could be utilized and developed into shape grammar for procedural modeling. Third, procedural modeling is expected to be used as an alternative tool for communication and information delivery.

A study on the estimation of onion's bulb weight using multi-level model (다층모형을 활용한 양파 구중 추정 연구)

  • Kim, Junki;Choi, Seung-cheon;Kim, Jaehwi;Seo, Hong-Seok
    • The Korean Journal of Applied Statistics
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    • v.33 no.6
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    • pp.763-776
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    • 2020
  • Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.