• 제목/요약/키워드: Assessment of Accuracy

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GPS에 의한 LiDAR DEM의 정확도 평가 (Accuracy Assessment of LiDAR DEM Using GPS)

  • 강준묵;윤희천;이창복;박준규
    • 한국측량학회지
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    • 제24권5호
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    • pp.443-451
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    • 2006
  • DEM(Digital Elevation Model)은 그 용도가 매우 다양하여 토목, 군사, 통신, 환경, 국토계획 등의 분야에서 그 활용이 날로 증가하고 있다. LiDAR 측량이 다른 측량 기법에 비해 우수한 DEM 성과를 제시하고 있는 것으로 나타나고 있으나 수직 위치에 대한 정확도를 구체적으로 평가한 연구는 아직 부족한 편이다. 이에 본 연구에서는 LiDAR DEM에 대한 정확도를 평가하기 위하여 항공 LiDAR 측량을 통해 생성된 DEM을 기준으로 총 35점의 특이점을 선점하여 GPS 측량을 실시하였으며, 이를 바탕으로 LiDAR에 의하여 생성된 DEM과 현지 GPS 측량 성과와의 정확도 분석을 수행하여 정표고에 대한 $RMSE{\pm}0.109m$를 확보하였다. 이는 국토지리정보원에서 고시한 축척 1:500, 1:1,000 기준의 허용 오차 범위 이내의 값으로 대축척 DEM구축 분야에 항공 LiDAR측량이 매우 유용하게 활용될 수 있음을 제시한 것이며 LiDAR 관련 DEM 응용 분야에서의 기반 자료로 그 활용이 기대된다.

Computerized bone age estimation system based on China-05 standard

  • Yin, Chuangao;Zhang, Miao;Wang, Chang;Lin, Huihui;Li, Gengwu;Zhu, Lichun;Fei, Weimin;Wang, Xiaoyu
    • Advances in nano research
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    • 제12권2호
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    • pp.197-212
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    • 2022
  • The purpose of this study is to develop an automatic software system for bone age evaluation and to evaluate its accuracy in testing and feasibility in clinical practice. 20394 left-hand radiographs of healthy children (2-18 years old) were collected from China Skeletal Development Survey data of 1998 and China Skeletal Development Survey data of 2005. Three experienced radiologists and China-05 standard maker jointly evaluate the stages of bone development and the reference bone age was determined by consensus. 1020 from 20394 radiographs were picked randomly as test set and the remaining 19374 radiographs as training set and validation set. Accuracy of the automatic software system for bone age assessment is evaluated in test set and two clinical test sets. Compared with the reference standard, the automatic software system based on RUS-CHN for bone age assessment has a 0.04 years old mean difference, ±0.40 years old in 95% confidence interval by single reading, a 85.6% percentage agreement of ratings, a 93.7% bone age accuracy rate, 0.17 years old of MAD, 0.29 years old of RMS; Compared with the reference standard, the automatic software system based on TW3-C RUS has a 0.04 years old mean difference, a ±0.38 years old in 95% confidence interval by single reading, a 90.9% percentage agreement of ratings, a 93.2% bone age accuracy rate, a 0.16 years of MAD, and a 0.28 years of RMS. Automatic software system, AI-China-05 showed reliably accuracy in bone age estimation and steady determination in different clinical test sets.

Optimization of SWAN Wave Model to Improve the Accuracy of Winter Storm Wave Prediction in the East Sea

  • Son, Bongkyo;Do, Kideok
    • 한국해양공학회지
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    • 제35권4호
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    • pp.273-286
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    • 2021
  • In recent years, as human casualties and property damage caused by hazardous waves have increased in the East Sea, precise wave prediction skills have become necessary. In this study, the Simulating WAves Nearshore (SWAN) third-generation numerical wave model was calibrated and optimized to enhance the accuracy of winter storm wave prediction in the East Sea. We used Source Term 6 (ST6) and physical observations from a large-scale experiment conducted in Australia and compared its results to Komen's formula, a default in SWAN. As input wind data, we used Korean Meteorological Agency's (KMA's) operational meteorological model called Regional Data Assimilation and Prediction System (RDAPS), the European Centre for Medium Range Weather Forecasts' newest 5th generation re-analysis data (ERA5), and Japanese Meteorological Agency's (JMA's) meso-scale forecasting data. We analyzed the accuracy of each model's results by comparing them to observation data. For quantitative analysis and assessment, the observed wave data for 6 locations from KMA and Korea Hydrographic and Oceanographic Agency (KHOA) were used, and statistical analysis was conducted to assess model accuracy. As a result, ST6 models had a smaller root mean square error and higher correlation coefficient than the default model in significant wave height prediction. However, for peak wave period simulation, the results were incoherent among each model and location. In simulations with different wind data, the simulation using ERA5 for input wind datashowed the most accurate results overall but underestimated the wave height in predicting high wave events compared to the simulation using RDAPS and JMA meso-scale model. In addition, it showed that the spatial resolution of wind plays a more significant role in predicting high wave events. Nevertheless, the numerical model optimized in this study highlighted some limitations in predicting high waves that rise rapidly in time caused by meteorological events. This suggests that further research is necessary to enhance the accuracy of wave prediction in various climate conditions, such as extreme weather.

우울증 환자의 자살 위험 평가의 훈련을 위한 생성형 인공지능 챗봇의 의학적 교육 활용 사례: 일개 한의과대학 학생을 중심으로 (Utilization of Generative Artificial Intelligence Chatbot for Training in Suicide Risk Assessment of Depressed Patients: Focusing on Students at a College of Korean Medicine)

  • 권찬영
    • 동의신경정신과학회지
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    • 제35권2호
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    • pp.153-162
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    • 2024
  • Objectives: Among OECD countries, South Korea has been having the highest suicide rate since 2018, with 24.1 deaths per 100,000 people reported in 2020. The objectie of this study was to examine the use of generative artificial intellicence (AI) chatbots to train third-year Korean medicine (KM) students in conducting suicide risk assessments for patients with depressive disorders to train students for their clinical practice skills. Methods: The Claude 3 Sonnet model was utilized for chatbot simulations. Students performed mock consultations using standardized suicide risk assessment tools including Ask Suicide-Screening Questions (ASQ) tool and ASQ Brief Suicide Safety Assessment. Experiences and attitudes were collected through an anonymous online survey. Responses were rated on a 1~5 Likert scale. Results: Thirty-six students aged 22~30 years participated in this study. Their scores for interest and appropriateness (4.66±0.57), usefulness (4.60±0.61), and overall experience (4.63±0.60) were high. Their evaluation of the usability of artificial intelligence chatbot was also high at 4.58±0.70 points. However, their trust in chatbot responses (Q12) was lower (3.86±0.99). Common issues related to dissatisfaction included conversation disruptions due to token limits and inadequate chatbot responses. Conclusions: This is the first study investigating generative AI chatbots for suicide risk assessment training in KM education. Students reported high satisfaction, although their trust in chatbot accuracy was moderate. Technical limitations affected their experience. These preliminary findings suggest that generative AI chatbots hold promise for clinical training, particularly for education in psychiatry. However, improvements in response accuracy and conversation continuity are needed.

수치지도 일반화 위치정확도 품질평가 (The Positional Accuracy Quality Assessment of Digital Map Generalization)

  • 박경식;임인섭;최석근
    • 한국측량학회지
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    • 제19권2호
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    • pp.173-181
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    • 2001
  • 수치지도 일반화 과정을 통해 생성된 수치지도의 공간데이터에 관한 품질을 평가하는 것은 매우 중요하다. 본 연구에서는, 공간데이터 품질유지 측면에서, 변환된 수치지도 데이터가 해당 축척의 수치지도 규정 및 정확도에 위배되지 않도록 하기 위해 이론적 기대정확도의 허용범위를 살펴보고 공간데이터의 품질 평가 기준을 정립하였다. 그리고, 대축척 수치지도를 소축척 수치지도로 변환할 때, 단순화, 완만화, 정리 등과 같은 처리과정을 통해 복잡성을 감소시키게 되면 공간적인 위치변화는 항상 발생하게 될 것이다. 따라서, 각 지점의 변환된 위치에 관한 공간정확도를 분석하는 것은 매우 힘든 일이기 때문에 평가방법으로서 버퍼링기법을 이용하였다. 비록 축척 1/1,000 및 l/5,000에 대한 일반적인 위치오차의 허용범위는 관련법규를 기준으로 결정되었다 하더라도, 각 처리요소에 적용된 알고리즘들은 서로 다른 특성을 가지고 있기 때문에, 알고리즘에 따라 적절한 매개변수와 허용오차를 결정하지 않는다면, 일반화 처리후의 허용범위를 만족할 수 없을 것이다. 허용범위에 근거를 둔 각 알고리즘의 변수에 관한 본 연구에서의 실험결과는 단순화 및 위치오차의 매개변수가 각각 0.2617 m, 0.4617 m를 나타내고 있었다.

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Diffusion-weighted Magnetic Resonance Imaging for Predicting Response to Chemoradiation Therapy for Head and Neck Squamous Cell Carcinoma: A Systematic Review

  • Sae Rom Chung;Young Jun Choi;Chong Hyun Suh;Jeong Hyun Lee;Jung Hwan Baek
    • Korean Journal of Radiology
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    • 제20권4호
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    • pp.649-661
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    • 2019
  • Objective: To systematically review the evaluation of the diagnostic accuracy of pre-treatment apparent diffusion coefficient (ADC) and change in ADC during the intra- or post-treatment period, for the prediction of locoregional failure in patients with head and neck squamous cell carcinoma (HNSCC). Materials and Methods: Ovid-MEDLINE and Embase databases were searched up to September 8, 2018, for studies on the use of diffusion-weighted magnetic resonance imaging for the prediction of locoregional treatment response in patients with HNSCC treated with chemoradiation or radiation therapy. Risk of bias was assessed by using the Quality Assessment Tool for Diagnostic Accuracy Studies-2. Results: Twelve studies were included in the systematic review, and diagnostic accuracy assessment was performed using seven studies. High pre-treatment ADC showed inconsistent results with the tendency for locoregional failure, whereas all studies evaluating changes in ADC showed consistent results of a lower rise in ADC in patients with locoregional failure compared to those with locoregional control. The sensitivities and specificities of pre-treatment ADC and change in ADC for predicting locoregional failure were relatively high (range: 50-100% and 79-96%, 75-100% and 69-95%, respectively). Meta-analytic pooling was not performed due to the apparent heterogeneity in these values. Conclusion: High pre-treatment ADC and low rise in early intra-treatment or post-treatment ADC with chemoradiation, could be indicators of locoregional failure in patients with HNSCC. However, as the studies are few, heterogeneous, and at high risk for bias, the sensitivity and specificity of these parameters for predicting the treatment response are yet to be determined.

골결손부 치유과정에서 cone beam형 전산화단층영상의 정확도 (The accuracy of the imaging reformation of cone beam computed tomography for the assessment of bone defect healing)

  • 강호덕;김규태;최용석;황의한
    • Imaging Science in Dentistry
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    • 제37권2호
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    • pp.69-77
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    • 2007
  • Purpose: To evaluate the accuracy of the imaging reformation of cone beam computed tomography for the assessment of bone defect healing in rat model. Materials and Methods: Sprague-Dawley strain rats weighing about 350 gms were selected. Then critical size bone defects were done at parietal bone with implantation of collagen sponge. The rats were divided into seven groups of 3 days, 1 week, 2 weeks, 3 weeks, 4 weeks, 6 weeks, and 8 weeks. The healing of surgical defect was assessed by multi planar reconstruction (MPR) images and three-dimensional (3-D) images of cone beam computed tomography, compared with soft X-ray radiograph and histopathologic examination. Results: MPR images and 3-D images showed similar reformation of the healing amount at 3 days, 1 week, 2 weeks, and 8 weeks, however, lower reformation at 3 weeks, 4 weeks, and 6 weeks. According to imaging-based methodologies, MPR image revealed similar reformation of the healing amount than 3-D images compare with soft X-ray image. Among the four threshold values for 3-D images, 400-500 HU revealed similar reformation of the healing amount. Histopathologic examination confirmed the newly formed trabeculation correspond with imaging-based methologies. Conclusion: MPR images revealed higher accuracy of the imaging reformation of cone beam computed tomography and cone beam computed tomography is a clinically useful diagnostic tool for the assessment of bone defect healing.

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상용 소프트웨어를 통해 자동 생성된 정사영상의 정확도 평가 (Accuracy Assessment of Orthophotos Automatically Generated by Commercial Software)

  • 최경아;박선미;이임평;김성준
    • 한국측량학회지
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    • 제25권5호
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    • pp.415-425
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    • 2007
  • 본 연구는 항공라이다데이터와 항공영상을 융합하여 정사영상을 제작하고, 항공영상만으로 자동영상정합을 통해 제작된 정시영상과 비교 분석하였다. 제작된 정시영상의 정확도평가를 위해 육안검사를 통한 정성적 분석과 주요 건물에 대한 수평좌표불일치, 경계좌표 및 유사도의 측정을 통한 정량적 분석을 수행하였다. 육안검사와 수평좌표불일치량을 기준으로 라이다데이터를 이용한 정사영상이 상대적으로 엄밀정사영상에 근접한 것으로 나타났다. 그러나, 경계좌표와 유사도측정의 결과로 폐색영역에 대한 이중매핑에 보다 민감하게 노출된다는 것을 알 수 있었다. 따라서, 이중매핑에 대한 효과적인 해결방법을 적용하거나 폐색영역이 발생하지 않는 사진중심 영역에서는 라이다데이터를 이용하여 엄밀정사영상에 대한 자동제작이 가능할 것으로 판단된다.