• Journal of Biosystems Engineering
• /
• 제27권1호
• /
• pp.45-50
• /
• 2002

This study was performed to develop thin layer drying equations fur short grain rough rice using far-infrared ray. Thin layer drying tests was conducted at four far-infrared ray temperature levels of 30, 40, 50, 60$^{\circ}C$ and two initial moisture content levels of 20.7, 26.2%(w.b.). The measured moisture ratios were fitted to Lewis and Page drying models by stepwise multiple regression analysis. Half response time of drying was affected by both drying temperature and initial moisture content at drying temperature of below 40$^{\circ}C$, but at above 40$^{\circ}C$ was mainly affected by drying temperature. Experimental constant(k) in Lewis model was a function of drying temperature, but K and N in Page model were function of drying temperature and initial moisture content. Moisture ratios predicted by two drying models agreed well with experimental values. But in the actual range of drying temperature above 30$^{\circ}C$ Page model was more suitable for predicting of drying rates.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2023년도 춘계학술발표대회
• /
• pp.687-688
• /
• 2023

Bone age assessment is a crucial task in pediatric radiology for assessing growth and development in children. In this paper, we explore the potential of Vision Transformer, a state-of-the-art deep learning model, for bone age assessment using X-ray images. We generate heatmap outputs using a pre-trained Vision Transformer model on a publicly available dataset of hand X-ray images and show that the model tends to focus on the overall hand and only the bone part of the image, indicating its potential for accurately identifying the regions of interest for bone age assessment without the need for pre-processing to remove background noise. We also suggest two methods for extracting the region of interest from the heatmap output. Our study suggests that Vision Transformer holds great potential for bone age assessment using X-ray images, as it can provide accurate and interpretable output that may assist radiologists in identifying potential abnormalities or areas of interest in the X-ray image.

• 한국측량학회지
• /
• 제38권2호
• /
• pp.141-151
• /
• 2020

Since it was first studied in 1980, solar energy analysis model for geographic information systems has been used to determine the approximate spatial distribution of terrain. However, the spatial pattern was not able to be grasped in 3D (three-dimensional) space with low accuracy due to the limitation of input data. Because of computational efficiency, using a constant value for the brightness of the sky caused the simulation results to be less reliable especially when the slope is high or buildings are crowded around. For the above reasons, this study proposed a model that predicts solar energy of vertical surfaces of buildings with four stages below. Firstly, CIE (Commission Internationale de l'Eclairage) luminance distribution model was used to calculate the brightness distribution of the sky using NREL (National Renewable Energy Laboratory) solar tracking algorithm. Secondly, we suggested a method of calculating the shadow effect using ray tracing. Thirdly, LOD (Level of Detail) 3 of 3D spatial data was used as input data for analysis. Lastly, the accuracy was evaluated based on the atmospheric radiation data collected through the ground observation equipment in Daejeon, South Korea. As a result of evaluating the accuracy, NMBE was 5.14%, RMSE 11.12, and CVRMSE 7.09%.

• 한국전자파학회논문지
• /
• 제19권7호
• /
• pp.733-740
• /
• 2008

본 논문에서는 실내 환경에서 무선 망 설계에 필요한 전파 특성 예측을 위해 3차원 광선 추적법을 이용하여 계산하는 방법을 제시했다. 실내의 경우는 벽면을 투과하는 전파, 복잡한 실내 구조물에 의한 산란 등으로 생기는 다양한 전파 경로를 정확히 모델링 하기 위해 3차원 광선 추적법을 적용하여 계산할 필요가 있다. 복잡한 실내 구조물을 수용하기 위해 물체들을 삼각형 면들로 모델링 하고, 이 삼각형 면을 이용하여 반사, 투과, 회절에 의한 효과를 고려하여 수신 전력을 계산하기 위한 ray tube를 만들고 계산의 효율성을 높이는 방법을 제시했다.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
• /
• pp.313-315
• /
• 2021

Timely and accurate diagnosis of lung diseases using Chest X-ray images has been gained much attention from the computer vision and medical imaging communities. Although previous studies have presented the capability of deep convolutional neural networks by achieving competitive binary classification results, their models were seemingly unreliable to effectively distinguish multiple disease groups using a large number of x-ray images. In this paper, we aim to build an advanced approach, so-called Ensemble Knowledge Distillation (EKD), to significantly boost the classification accuracies, compared to traditional KD methods by distilling knowledge from a cumbersome teacher model into an ensemble of lightweight student models with parallel branches trained with ground truth labels. Therefore, learning features at different branches of the student models could enable the network to learn diverse patterns and improve the qualify of final predictions through an ensemble learning solution. Although we observed that experiments on the well-established ChestX-ray14 dataset showed the classification improvements of traditional KD compared to the base transfer learning approach, the EKD performance would be expected to potentially enhance classification accuracy and model generalization, especially in situations of the imbalanced dataset and the interdependency of 14 weakly annotated thorax diseases.

• 한국방사선학회논문지
• /
• 제15권5호
• /
• pp.613-620
• /
• 2021

본 논문에서는 흉부 X선 영상에서 정상 심장과 비정상 심장(심장비대)을 분류할 수 있는 합성곱 신경망 모델을 제안하고자 한다. 학습 및 테스트 데이터로는 경북대학교병원에 내원하여 정상과 심장비대를 진단받은 환자들의 흉부 X-선 이미지를 획득하여 사용하였다. 제안된 합성곱 신경망 모델을 이용하였을 때의 정상 심장 및 비정상 심장(심장비대) 분류 정확도는 99.88%였다. 정상 심장 영상을 테스트 데이터로 사용하였을 때의 정확도, 정밀도, 재현율 및 F1 Score는 95%, 100%, 90%, 96%였다. 비정상 심장(심장비대) 영상을 테스트 데이터로 사용하였을 때의 정확도, 정밀도, 재현율 및 F1 Score는 95%, 92%, 100% 및 96%였다. 이러한 학습 및 테스트 분류 결과로 제안된 합성곱 신경망 모델은 흉부 X-선 영상의 특징 추출 및 분류에서 매우 우수한 성능을 보여주고 있다고 판단된다. 본 논문에서 제안하는 합성곱 신경망 모델은 흉부 X-선 영상의 질환 분류에 있어 유용한 결과를 보여줄 것으로 판단되며, 다른 의료 영상에서도 동일한 결과를 나타내는지 알아보기 위하여 추가적인 연구가 이루어져야 할 것이다.

• 한국전자파학회논문지
• /
• 제18권11호
• /
• pp.1231-1236
• /
• 2007

본 논문에서는 무선 망 설계에 필요한 전파 특성 예측을 위한 방법 중 하나인 광선 추적법의 속도 향상 방법을 제시했다. 빠르고 정확한 광선 추적을 위해 ray tube라는 매개체를 이용하여 전파의 반사, 투과, 회절을 계산하는데, 건물 등의 방해물이 많을수록 계산 시간이 매우 늘어나는 문제점을 해결하기 위해 중복된 계산을 줄이는 방법들을 제시했다.

• International Journal of Computer Science & Network Security
• /
• 제22권4호
• /
• pp.53-58
• /
• 2022

Pneumonia is a form of acute respiratory infection that affects the lungs. According to the World Health Organization, pneumonia is the leading cause of death for children worldwide. As a result, pneumonia was the top killer of children under the age of five years old in 2015, which is 15% of all deaths worldwide. In this paper, we used CNN model architectures to compare between the result of proposed a CNN method with VGG based model architecture. The model's performance in detecting pneumonia shows that the proposed model based on VGG can classify normal and abnormal X-rays effectively and more accurately than the proposed model used in this paper.

• 한국전자통신학회논문지
• /
• 제15권1호
• /
• pp.173-178
• /
• 2020

다중-광선 모델을 이용하여 경사면을 갖는 반-협곡 구조에서 전파 전송 손실을 해석하고 경사면의 각도에 따라 나타나는 다중-광선 전파 모델을 공식화 하였다. 경사면의 기울어진 각도에 의해 결정되는 송수신 전파의 경사면 반사경로인 제3경로와 제4경로에 대한 차단 각도를 송수신 단말의 높이와 위치를 가지고 계산하였다. 경사면 환경에서 전파 전송 손실을 예측하기 위하여 실제 경사면이 존재하는 제방 환경을 선택하여 모델링하고 시뮬레이션 하여 전파 전송 손실을 계산하였으며, 주파수 1-6GHz 대역에 대한 측정활동을 통해 전파전송 손실을 확인하였다. 시뮬레이션 결과와 측정 결과는 유사한 전파 전송 손실 경향을 보여주었으며 다양한 지형정보에 대한 전파 경로 손실 예측과 측정 결과들은 다양한 전파 업무 설계에 활용될 수 있다.

• 한국디지털건축인테리어학회논문집
• /
• 제5권1호
• /
• pp.9-16
• /
• 2005

In Interior design, light is the most important factor in deciding color, texture and illumination level which are the basic factors of spatial design. To apply rendering technologies on prediction of illuminating effect, it is important to understand and analyse the basic properties of the illumination models that are local illumination model and global illumination model. The illumination models in computer graphics express the factors which determine the surface color, texture and light distribution through the reflection. The purpose of this study is to propose the best way of shading algorithm in interior space provided by the computer, based on the experimental analysis that 5 shading methods are applied to the interior space. The results of this study were as followed. 1) Local illumination models that are Lambert shading, Ground shading and Phong shading are not suitable to the prediction of interior illumination effect. 2) Ray tracing that is global illumination model could be adopted to interior illumination effects. Ray tracing is a very versatile algorithm because of the large range of lighting effects it can model. 3) Neither radiality nor ray tracing offers a complete solution for simulating all interior illumination effects. 4) Radiosity excels at rendering diffuse-to-diffuse inter-reflections and ray tracing excels at rendering specular reflections. By merging both shading techniques, that offers the best of both. Using computer technologies to simulate lighting in preliminary design stage which will provide information for designers and occupants to determine the effect of using artificial light sources at each stage of their design process. Further study in illumination analysis, prediction of illumination effect, and lighting calculation is required as computer media expands.