• Nuclear Engineering and Technology
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• 제55권8호
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• pp.2927-2934
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• 2023

The influence of the atmospheric radon background on the airborne gamma spectrum can seriously affect researchers' judgement of ground radiation information. However, due to load and endurance, unmanned aerial vehicle (UAV)-borne gamma-ray spectrometry is difficulty installing upward-looking detectors to monitor atmospheric radon background. In this paper, an advanced spectral-ratio method was used to correct the atmospheric radon background for a UAV-borne gamma-ray spectrometry in Inner Mongolia, China. By correcting atmospheric radon background, the ratio of the average count rate of U window in the anomalous radon zone (S5) to that in other survey zone decreased from 1.91 to 1.03, and the average uranium content in S5 decreased from 4.65 mg/kg to 3.37 mg/kg. The results show that the advanced spectral-ratio method efficiently eliminated the influence of the atmospheric radon background on the UAV-borne gamma-ray spectrometry to accurately obtain ground radiation information in uranium exploration. It can also be used for uranium tailings monitoring, and environmental radiation background surveys.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권3호
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• pp.881-895
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• 2023

Modern image inpainting techniques based on deep learning have achieved remarkable performance, and more and more people are working on repairing more complex and larger missing areas, although this is still challenging, especially for facial image inpainting. For a face image with a huge missing area, there are very few valid pixels available; however, people have an ability to imagine the complete picture in their mind according to their subjective will. It is important to simulate this capability while maintaining the identity features of the face as much as possible. To achieve this goal, we propose a three-stage network model, which we refer to as the identity and structure feature refinement network (ISFRNet). ISFRNet is based on 1) a pre-trained pSp-styleGAN model that generates an extremely realistic face image with rich structural features; 2) a shallow structured network with a small receptive field; and 3) a modified U-net with two encoders and a decoder, which has a large receptive field. We choose structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), L1 Loss and learned perceptual image patch similarity (LPIPS) to evaluate our model. When the missing region is 20%-40%, the above four metric scores of our model are 28.12, 0.942, 0.015 and 0.090, respectively. When the lost area is between 40% and 60%, the metric scores are 23.31, 0.840, 0.053 and 0.177, respectively. Our inpainting network not only guarantees excellent face identity feature recovery but also exhibits state-of-the-art performance compared to other multi-stage refinement models.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.516-522
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• 2023

The co-precipitation process plays a key role in the decontamination of radionuclides from low and intermediate levels of liquid waste. For that reason, the removal of Cs ions from waste solution by the co-precipitation method was carried out. A simulated liquid waste (¹³³Cs) was prepared from a 0.1 M CsCl solution, while wastewater generated by washing steel ash served as a representative of radioactive cesium solution (¹³⁷Cs). By co-precipitation, potassium ferrocyanide was applied for the adsorption of Cs ions, while nickel nitrate and iron sulfate were selected for supporting the precipitation. The amount of residual Cs ions in the CsCl solution after precipitation and filtration was determined by ICP-OES, while the radioactivity of ¹³⁷Cs was measured using a gamma-ray spectrometer. After cesium removal, the amount of cesium appearing in both XRD and SEM-EDS was analyzed. The removal efficiency of ¹³³Cs was 60.21% and 51.86% for nickel nitrate and iron sulfate, respectively. For the ash-washing solution, the removal efficiency of ¹³⁷Cs was revealed to be more than 99.91% by both chemical agents. This implied that the co-precipitation process is an excellent strategy for the effective removal of radioactive cesium in waste solution treatment.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1439-1447
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• 2023

The fuel cycle characteristics of the IVG.1M reactor were studied within the framework of the research reactor conversion program to modernize the IVG.1M reactor. Optimum use of the nuclear fuel and reactor was achieved through routine methods which included partial fuel reloading combined with scheduled maintenance operations. Since, the additional problem in planning the fuel cycle of the IVG.1M reactor was the poisoning of the beryllium parts of the core, reflector, and control system. An assessment of the residual power and composition of spent fuel is necessary for the selection and justification of the technology for its subsequent management. Computational studies were performed using the MCNP6.1 program and the neutronics model of the IVG.1M reactor. The proposed scheme of annual partial fuel reloading allows for maintaining a high reactor reactivity margin, stabilizing it within 2-4 β_eff for 20 years, and achieving a burnup of 9.9-10.8 MW × day/kg U in the steady state mode of fuel reloading. Spent fuel immediately after unloading from the reactor can be placed in a transport packaging cask for shipping or safely stored in dry storage at the research reactor site.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.136-136
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• 2021

In this study, a deep convolutional neural network (DCNN) model is proposed for short-term precipitation forecasting using weather radar-based images. The DCNN model is a combination of convolutional neural networks, autoencoder neural networks, and U-net architecture. The weather radar-based image data used here are retrieved from competition for rainfall forecasting in Korea (AI Contest for Rainfall Prediction of Hydroelectric Dam Using Public Data), organized by Dacon under the sponsorship of the Korean Water Resources Association in October 2020. This data is collected from rainy events during the rainy season (April - October) from 2010 to 2017. These images have undergone a preprocessing step to convert from weather radar data to grayscale image data before they are exploited for the competition. Accordingly, each of these gray images covers a spatial dimension of 120×120 pixels and has a corresponding temporal resolution of 10 minutes. Here, each pixel corresponds to a grid of size 4km×4km. The DCNN model is designed in this study to provide 10-minute predictive images in advance. Then, precipitation information can be obtained from these forecast images through empirical conversion formulas. Model performance is assessed by comparing the Score index, which is defined based on the ratio of MAE (mean absolute error) to CSI (critical success index) values. The competition results have demonstrated the impressive performance of the DCNN model, where the Score value is 0.530 compared to the best value from the competition of 0.500, ranking 16^th out of 463 participating teams. This study's findings exhibit the potential of applying the DCNN model to short-term rainfall prediction using weather radar-based images. As a result, this model can be applied to other areas with different spatiotemporal resolutions.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.652-654
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• 2021

본 연구에서는 경추부위 멕켄지운동에 관한 결과를 체계적 고찰함으로써 멕켄지 운동에 대한 근거를 마련하고자 하였다. 2015년부터 2021년 6월까지 출판된 국내논문을 대상으로 하였다. 논문의 검색을 위한 데이터베이스 검색엔진은 국내의 표적 검색원인 한국 학술정보와 한국교육학술정보원(KERIS)가 운영하는 학술연구정보서비스 RISS(http://www.riss4u.net)에서 인터넷을 통하여 실시하여 8편의 논문을 분석하였다. 본 연구에서 분석된 8편의 국내 논문은 실험군1을 포함하는 8편의 논문 중 맥켄지 운동을 적용한 논문은 4편, 어깨안정화 운동을 적용한 논문이 3편이었고, 멀리건 운동을 적용한 논문이 1편이었다. 실험군 2를 포함하는 6편의 논문 중 맥켄지 운동만 적용한 논문은 4편, 멀리건 운동을 함께 적용한 논문이 1편, 카이로프랙틱을 함께 적용한 논문이 1편이었다. 운동 효과를 평가한 관절가동범위에 관한 논문은 3편과 두개척추각을 평가한 관한 논문은 2편에서도 유의한 차이를 보였다. 경추 자세에 관한 논문은 1편과 거리 변화에 관한 논문은 1편에서 멕켄지 운동에 대한 효과를 보였다. 근활성도에 관한 논문은 4편 중 근육마다 멕켄지만 적용한 그룹보다 멕켄지와 다른 운동을 동시에 같이 시행한 실험군이 대조군에 비해 유의한 차이를 보였으며 통증에 관한 논문 4편에서도 멕켄지만 적용한 그룹보다 멕켄지와 다른 운동 특히 카이로프랙틱을 적용한 실험군이 대조군에 비해 유의한 차이를 보였다. 이에, 본 연구에서는 경추부위에 멕켄지 운동은 통증, 근활성도, 관절가동범위, 경추자세등에서 그 효과를 증명하였다.

• 대한토목학회논문집
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• 제30권5D호
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• pp.513-522
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• 2010

도시인구 과밀현상, 지상도로교통망 포화 등의 문제를 해결하기 위한 효율적 토지활용방안으로 지하도로교통망, 복합단지, 저장시설 등 다양한 형태의 지하구조물 건설이 증가하고 있다. 본 연구에서는 지하구조물 시공 시 열악한 환경에 적합한 작업자의 3차원 위치와 통신 연락을 위한 현장지원 통합관리시스템 개발의 경제적 타당성 분석을 수행하였다. 본 분석을 위해 터널 및 지하철건설을 대상으로 현장조사 및 작업자 설문조사를 수행하여 현행 지하구조물 건설 현장관리 프로세스 분석, 문제점 파악 및 시스템 도입을 통해 발생할 것으로 예상되는 편익의 정량적 도출을 실시하였으며, 본 시스템 도입으로 발생할 것으로 예상되는 사고감소, 현장관리비 절감, 생산성 향상을 편익으로 추정하고 경제성 분석기법인 편익/비용비(B/C), 순 현재가치(NPV), 내부수익률(IRR)을 활용하여 시스템 도입의 경제적 타당성 분석을 수행하였다. 분석 결과, 편익/비용비는 1.79로 도출되었으며, 순현재가치와 내부수익률은 각 103,423,797원, 47.01%로 산출되어, 본 시스템 도입의 경제성을 확보할 수 있는 것으로 분석되었으며, 변수들의 불확실성을 고려하여 민감도 분석을 실시하였다.

• 영어영문학
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• 제56권1호
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• pp.25-45
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• 2010

While environmental ethics, a relatively new field of philosophy, has gained its practical power in the contemporary world, the ethics of ecological poetry has not been studied well and the relationship between poetry and ethics has also been troubled for a long time. How can it be probed, interrogated, and constructed in ecological criticism? Attempting to steer some critical focus to the topic of ethics and poetic language, this essay is to elucidate these questions within the ecological traits of Mary Oliver's poems. In the process of revisiting Oliver's poems, this essay tries to rescue the poet Oliver, one of the most gifted poets in contemporary American poetic landscape, but a long-neglected one, and questions of ethics which have been evaded for a long time in ecological criticism. Oliver's ecological imagination at once invites readers to become other in the outer world in a most spontaneous way and re-questions the fundamental distance between the self and the other in the process of becoming other. Challenging the humanistic view of nature, she opens the various layers of becoming other: from the possible state of perfect merging to the sad recognition of the impossibility of merging, from the happy moment of rebirth beyond death, to the conflicting moment of being-together. In the different cycles and levels of becoming other, Oliver's poetry completes the poetics of relation in the components of 'self-in-relation.' In those different layers of relations, the ethics of ecological poetry is newly explored rather than residing in the safe net of goodness or sympathy between the self and the other, or the stark division between the two. Oliver's witty, sensitive, sometimes sad eyes toward others, therefore, entice readers to move from the established view of nature to the extraordinary moment of encountering it, thus accomplishing the ethics of beings, not just of ecological poetry.

• 대한임베디드공학회논문지
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• 제18권6호
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• pp.267-275
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• 2023

This paper presents the development of specialized software for annotating volume-of-interest on ¹⁸F-FDG PET/CT images with the goal of facilitating the studies and diagnosis of head and neck cancer (HNC). To achieve an efficient annotation process, we employed the SE-Norm-Residual Layer-based U-Net model. This model exhibited outstanding proficiency to segment cancerous regions within ¹⁸F-FDG PET/CT scans of HNC cases. Manual annotation function was also integrated, allowing researchers and clinicians to validate and refine annotations based on dataset characteristics. Workspace has a display with fusion of both PET and CT images, providing enhance user convenience through simultaneous visualization. The performance of deeplearning model was validated using a Hecktor 2021 dataset, and subsequently developed semi-automatic annotation functionalities. We began by performing image preprocessing including resampling, normalization, and co-registration, followed by an evaluation of the deep learning model performance. This model was integrated into the software, serving as an initial automatic segmentation step. Users can manually refine pre-segmented regions to correct false positives and false negatives. Annotation images are subsequently saved along with their corresponding ¹⁸F-FDG PET/CT fusion images, enabling their application across various domains. In this study, we developed a semi-automatic annotation software designed for efficiently generating annotated lesion images, with applications in HNC research and diagnosis. The findings indicated that this software surpasses conventional tools, particularly in the context of HNC-specific annotation with ¹⁸F-FDG PET/CT data. Consequently, developed software offers a robust solution for producing annotated datasets, driving advances in the studies and diagnosis of HNC.

• 대한의용생체공학회:의공학회지
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• 제45권2호
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• pp.90-94
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• 2024

Diagnosing wounds presents a significant challenge in clinical settings due to its complexity and the subjective assessments by clinicians. Wound deep learning algorithms quantitatively assess wounds, overcoming these challenges. However, a limitation in existing research is reliance on specific datasets. To address this limitation, we created a comprehensive dataset by combining open dataset with self-produced dataset to enhance clinical applicability. In the annotation process, machine learning based on Gradient Vector Flow (GVF) was utilized to improve objectivity and efficiency over time. Furthermore, the deep learning model was equipped U-net with residual blocks. Significant improvements were observed using the input dataset with images cropped to contain only the wound region of interest (ROI), as opposed to original sized dataset. As a result, the Dice score remarkably increased from 0.80 using the original dataset to 0.89 using the wound ROI crop dataset. This study highlights the need for diverse research using comprehensive datasets. In future study, we aim to further enhance and diversify our dataset to encompass different environments and ethnicities.