• 디지털융복합연구
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• 제17권9호
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• pp.327-335
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• 2019

1970년대는 많은 애니메이션 영화가 활발히 제작되었던 한국 애니메이션의 전성기라 불린다. 하지만, 당시 해외 애니메이션의 수입 방영과 해외 제작사의 하청작업 또한 많았으며, 자체 제작된 많은 애니메이션이 해외 원작을 모방하였다는 표절 논란이 꾸준히 제기되고 있다. 특히, 일본 애니메이션의 캐릭터 디자인에 대한 도용이 여전히 많은 애니메이션 마니아로부터 비판받고 있는 실정이다. 이에, 본 논문은 1970년대와 1980년대 한국 애니메이션 중 표절이 의심되는 작품을 중심으로 그 요인과 유형에 대해 분석하는 것을 목적으로 한다. 이를 위한 연구의 전개는 첫째, 예술창작에 있어서 표절의 정의 및 구성요건에 대해 문헌을 중심으로 고찰하고, 둘째, 1970년에서 1980년대 까지 표절애니메이션의 요인에 대해 정치 이념, 산업 정책, 제작 구조, 저작권 인식 측면을 중심으로 살펴본다. 셋째, 당시 제작된 한국 애니메이션 중 28편을 대상으로 캐릭터의 형상과 색상을 중심으로 한 여섯 가지 항목으로 디자인의 도용과 표절의 정도에 대해 전문가 설문을 통한 사례비교 분석을 진행한다. 한국 애니메이션의 표절에 대한 사회 문화 산업적 요인과 그 유형을 종합적으로 분석한 본 연구는 한국 애니메이션에 대한 성찰적 관점을 제시하는 연구로 그 학술적 가치가 있으리라 사료된다.

• Composites Research
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• 제32권5호
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• pp.206-210
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• 2019

직조 구조의 복합재의 쓰임이 자동차, 항공 산업 등 여러 분야로 확장됨에 따라, 직조 복합재의 신뢰성 문제 및 물성예측에 대한 필요성이 대두되었다. 본 연구에서는 직조 구조가 다른 복합재료의 물성 예측을 위한 유한요소해석을 수행하여 실험으로 얻은 정적 물성과의 유사성을 검증하였고, 효과적인 모델링 방법을 개발하였다. 직조 구조의 특성을 반영하기 위하여 모델링은 메소 스케일의 대표 체적 요소(RVE)를 이용하였다. 섬유 다발과 순수 기지를 분리하여 3차원 모델링을 진행하였다. 하신 파괴 기준(Hashin's failure criteria)을 적용하여 요소의 파괴 유무를 판단하였고, 해석 모델은 복합재에 적합한 점진적 파괴 모델을 사용하였다. 최종적으로, 직조 구조에 따른 복합재의 물성을 성공적으로 예측하여 본 모델링 및 해석 기법에 대한 적합성을 검증하였다.

• 대한의용생체공학회:의공학회지
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• 제42권3호
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• pp.80-85
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• 2021

We developed a model to classify the absence of cervical cancer using deep learning from the cervical image to which the histogram equalization algorithm was applied, and to compare the performance of each model. A total of 4259 images were used for this study, of which 1852 images were normal and 2407 were abnormal. And this paper applied Image Sharpening(IS), Histogram Equalization(HE), and Contrast Limited Adaptive Histogram Equalization(CLAHE) to the original image. Peak Signal-to-Noise Ratio(PSNR) and Structural Similarity index for Measuring image quality(SSIM) were used to assess the quality of images objectively. As a result of assessment, IS showed 81.75dB of PSNR and 0.96 of SSIM, showing the best image quality. CLAHE and HE showed the PSNR of 62.67dB and 62.60dB respectively, while SSIM of CLAHE was shown as 0.86, which is closer to 1 than HE of 0.75. Using ResNet-50 model with transfer learning, digital image-processed images are classified into normal and abnormal each. In conclusion, the classification accuracy of each model is as follows. 90.77% for IS, which shows the highest, 90.26% for CLAHE and 87.60% for HE. As this study shows, applying proper digital image processing which is for cervical images to Computer Aided Diagnosis(CAD) can help both screening and diagnosing.

• 대한방사선기술학회지:방사선기술과학
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• 제44권6호
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• pp.655-661
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• 2021

Positron emission tomography (PET) images is affected by acquisition time, short acquisition times results in low gamma counts leading to degradation of image quality by statistical noise. Noise2Void(N2V) is self supervised denoising model that is convolutional neural network (CNN) based deep learning. The purpose of this study is to evaluate denoising performance of N2V for PET image with a short acquisition time. The phantom was scanned as a list mode for 10 min using Biograph mCT40 of PET/CT (Siemens Healthcare, Erlangen, Germany). We compared PET images using NEMA image-quality phantom for standard acquisition time (10 min), short acquisition time (2min) and simulated PET image (S2 min). To evaluate performance of N2V, the peak signal to noise ratio (PSNR), normalized root mean square error (NRMSE), structural similarity index (SSIM) and radio-activity recovery coefficient (RC) were used. The PSNR, NRMSE and SSIM for 2 min and S2 min PET images compared to 10min PET image were 30.983, 33.936, 9.954, 7.609 and 0.916, 0.934 respectively. The RC for spheres with S2 min PET image also met European Association of Nuclear Medicine Research Ltd. (EARL) FDG PET accreditation program. We confirmed generated S2 min PET image from N2V deep learning showed improvement results compared to 2 min PET image and The PET images on visual analysis were also comparable between 10 min and S2 min PET images. In conclusion, noisy PET image by means of short acquisition time using N2V denoising network model can be improved image quality without underestimation of radioactivity.

• Structural Engineering and Mechanics
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• 제81권6호
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• 한국염색가공학회지
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• 제34권4호
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• pp.284-301
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• 2022

The limitations of food production caused by global warming, consumption of soil fertility, and land shortage have demanded the development of alternative foods. Their market has been increasing, and in particular, there is an urgent need for an alternative meat. Among them, the non-slaughtered cell-cultured meat that can be manufactured in the laboratory, that is, cultured meat, is in the spotlight, which can solve the problem of meat consumption while including the advantages of meat. It is classified into minced cultured meat and structured one with a structure similar to that of real meat. The latter is currently facing limitations related scaffolds, cells, and the multiplicative problems, and many attempts are being made to solve them. The complex problem is related to secure texture and taste as well as structural similarity to actual meat. To solve the problems, it is necessary to lay emphasis on cells, there are fat cells and vascular cells, and the most fundamental cells, muscle cells. These are the main cells that control the texture and nutrients of meat, and unlike other cells, they grow in the form of fibers. A myofibril (also known as a muscle fibril) is a basic rod-like organelle of a muscle cell, which is a quantitatively major component of meat, and one of the tissues that maintain the appearance of the body and bones. In this review article, we focused on the growth of muscle cells into long, tubular cells known as muscle fibers using the fabricated fibrous scaffold, and reviewed not only research results for muscle tissue engineering but also various results in the related fields for the last five years.

• 한국재료학회지
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• 제32권8호
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• pp.345-353
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• 2022

In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 × 256 pixels (high resolution: HR) from TEM measurements and 32 × 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO₄ nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.

• 대한통합의학회지
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• 제11권1호
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• pp.43-51
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• 2023

Purpose : This study suggests that the unique chakra arrangement of Tibetan singing bowls resembles the mantra of chakra lotus in the tantric tradition and the structure of chakra ascent, The two aim at the liberation of consciousness and confirm that they have a body, mind, and conscious healing mechanism. Methods : First, the structural characteristics of Tibetan singing bowls arrangement and chakra lotus mantra arrangement were investigated through the consideration of previous studies. Next, the healing mechanism of Tibetan singing bowls, which has been learned in Nepal, was examined through previous studies and literature to clarify that the rise of chakra in the two systems has a balance of body, mind, and consciousness and aims at liberation of consciousness. Results : The arrangement of Tibetan chakras is similar to the mantra of chakra lotus. Both have a structure in which the auxiliary sound of the previous chakra is interlocked with the structure of being the main sound of the next chakra to raise the chakra. At this time, the rise of the chakra is the liberation of consciousness by the ultimate purpose. Conclusion : Tibetan chakra are structurally similar to chakra lotus mantras and chakra ascents, as they have a theoretical background to tantric traditions. Chakra is the quality of inner consciousness that is conveyed to the outside and expressed in its own actions. Therefore, chakras should be well coordinated to lead our lives healthily. In this point, the chakra arrangement of Tibetan singing bowls is a system that exposes the inner balance to the outside and heals us more directly. Therefore, Tibetan singing bowls therapy has an integrated medical value in restoring our mind and body balance. Because chakras are dimensions of consciousness, the study of chakras is abstract or lacking, so more systematic and scientific study of chakras is needed.

• Imaging Science in Dentistry
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• 제52권4호
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• pp.393-398
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• 2022

Purpose: This study proposed a generative adversarial network (GAN) model for T2-weighted image (WI) synthesis from proton density (PD)-WI in a temporomandibular joint(TMJ) magnetic resonance imaging (MRI) protocol. Materials and Methods: From January to November 2019, MRI scans for TMJ were reviewed and 308 imaging sets were collected. For training, 277 pairs of PD- and T2-WI sagittal TMJ images were used. Transfer learning of the pix2pix GAN model was utilized to generate T2-WI from PD-WI. Model performance was evaluated with the structural similarity index map (SSIM) and peak signal-to-noise ratio (PSNR) indices for 31 predicted T2-WI (pT2). The disc position was clinically diagnosed as anterior disc displacement with or without reduction, and joint effusion as present or absent. The true T2-WI-based diagnosis was regarded as the gold standard, to which pT2-based diagnoses were compared using Cohen's ĸ coefficient. Results: The mean SSIM and PSNR values were 0.4781(±0.0522) and 21.30(±1.51) dB, respectively. The pT2 protocol showed almost perfect agreement(ĸ=0.81) with the gold standard for disc position. The number of discordant cases was higher for normal disc position (17%) than for anterior displacement with reduction (2%) or without reduction (10%). The effusion diagnosis also showed almost perfect agreement(ĸ=0.88), with higher concordance for the presence (85%) than for the absence (77%) of effusion. Conclusion: The application of pT2 images for a TMJ MRI protocol useful for diagnosis, although the image quality of pT2 was not fully satisfactory. Further research is expected to enhance pT2 quality.