• Journal of the Optical Society of Korea
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• 제17권5호
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• pp.384-391
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• 2013

We propose a split-encryption scheme on converting original images to multiple ciphertexts. This conversion introduces one random phase-only function (POF) to influence phase distribution of the preliminary ciphertexts. In the encryption process, the original image is mathematically split into two POFs. Then, they are modulated on a spatial light modulator one after another. And subsequently two final ciphertexts are generated by utilizing two-step phase-shifting interferometry. In the decryption process, a high-quality reconstructed image with relative error $RE=7.6061{\times}10^{-31}$ can be achieved only when the summation of the two ciphertexts is Fresnel-transformed to the reconstructed plane. During the verification process, any silhouette information was invisible in the two reconstructed images from different single ciphertexts. Both of the two single REs are more than 0.6, which is better than in previous research. Moreover, this proposed scheme works well with gray images.

• 대한의용생체공학회:의공학회지
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• 제15권2호
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• pp.183-188
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• 1994

In clinical orthopaedics, bone resoption in the cortex is often seen post operatively on X-rays or bone densitometry after total hip replacement (THR) in the form of cortical osteoporosis or atropy. Stress shielding of bone occurs, when a load, normally carried by the bone alone, is shared with an implant as a result, the bone stresses are abnormal and with remodelling analysis this may cause extensive proximal bone resoption, possibly weakening the bone bed to the point of failure. The author made finite element models of the cemented and non-cemented type implanted femoral stem with bone resorption of the proximal medial femur and studied the feed back effect of the various degree of bone resoption to THR system by parametric analysis on the stress of the femoral stem and interface. The results of the present finite element analysis implied that the extent of proximal bone resorption has the effect of more increasing stress on the distal stem tip, cement mantle and interface in both type of femoral stem and this high distal stress possibly can cause the mechanical failure of loosening or failure after THR.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1430-1432
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• 2003

Agricultural areas in the north region of Bangladesh suffer from water shortages during the dry season as well as dry spells in the monsoon period. The Teesta Barrage was constructed in 1990 to provide supplemental irrigation water during the monsoon period. After completion of the project high yielding variety of crops were introduced more in the project area. Due to this reason unforeseen needs of irrigation water during the dry season has emerged. This study reviews the current irrigation status and related constraints to a full development of the project and provides suggestions for future improvement of the project. Also suggested is to apply remote sensing technique for the management of the system as a whole. Use of remote sensing technique for the management of irrigation water resources is a new approach in Bangladesh. Application of such a powerful tool will provide better management options for large-scale irrigation projects in the country.

• Nuclear Engineering and Technology
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• 제50권2호
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• pp.280-291
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• 2018

In the framework of OECD/NEA Working Group on Fuel Safety, a RIA fuel-rod-code Benchmark Phase I was organized in 2010-2013. It consisted of four experiments on highly irradiated fuel rodlets tested under different experimental conditions. This benchmark revealed the need to better understand the basic models incorporated in each code for realistic simulation of the complicated integral RIA tests with high burnup fuel rods. A second phase of the benchmark (Phase II) was thus launched early in 2014, which has been organized in two complementary activities: (1) comparison of the results of different simulations on simplified cases in order to provide additional bases for understanding the differences in modelling of the concerned phenomena; (2) assessment of the uncertainty of the results. The present paper provides a summary and conclusions of the second activity of the Benchmark Phase II, which is based on the input uncertainty propagation methodology. The main conclusion is that uncertainties cannot fully explain the difference between the code predictions. Finally, based on the RIA benchmark Phase-I and Phase-II conclusions, some recommendations are made.

• Journal of the Korean Wood Science and Technology
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• 제49권5호
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• pp.491-503
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• 2021

Wood identification is regularly performed by observing the wood anatomy, such as colour, texture, fibre direction, and other characteristics. The manual process, however, could be time consuming, especially when identification work is required at high quantity. Considering this condition, a convolutional neural networks (CNN)-based program is applied to improve the image classification results. The research focuses on the algorithm accuracy and efficiency in dealing with the dataset limitations. For this, it is proposed to do the sample selection process or only take a small portion of the existing image. Still, it can be expected to represent the overall picture to maintain and improve the generalisation capabilities of the CNN method in the classification stages. The experiments yielded an incredible F1 score average up to 93.4% for medium sample area sizes (200 × 200 pixels) on each CNN architecture (VGG16, ResNet50, MobileNet, DenseNet121, and Xception based). Whereas DenseNet121-based architecture was found to be the best architecture in maintaining the generalisation of its model for each sample area size (100, 200, and 300 pixels). The experimental results showed that the proposed algorithm can be an accurate and reliable solution.

• Smart Structures and Systems
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• 제29권1호
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• pp.63-75
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• 2022

The raw data collected by structural health monitoring (SHM) systems may suffer multiple patterns of anomalies, which pose a significant barrier for an automatic and accurate structural condition assessment. Therefore, the detection and classification of these anomalies is an essential pre-processing step for SHM systems. However, the heterogeneous data patterns, scarce anomalous samples and severe class imbalance make data anomaly detection difficult. In this regard, this study proposes a convolutional neural network-based data anomaly detection method. The time and frequency domains data are transferred as images and used as the input of the neural network for training. ResNet18 is adopted as the feature extractor to avoid training with massive labelled data. In addition, the focal loss function is adopted to soften the class imbalance-induced classification bias. The effectiveness of the proposed method is validated using acceleration data collected in a long-span cable-stayed bridge. The proposed approach detects and classifies data anomalies with high accuracy.

• Journal of Information Processing Systems
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• 제19권1호
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• pp.109-117
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• 2023

Defect detection is one of the key factors in fabric quality control. To improve the speed and accuracy of denim fabric defect detection, this paper proposes a defect detection algorithm based on cascading feature extraction architecture. Firstly, this paper extracts these weight parameters of the pre-trained VGG16 model on the large dataset ImageNet and uses its portability to train the defect detection classifier and the defect recognition classifier respectively. Secondly, retraining and adjusting partial weight parameters of the convolution layer were retrained and adjusted from of these two training models on the high-definition fabric defect dataset. The last step is merging these two models to get the defect detection algorithm based on cascading architecture. Then there are two comparative experiments between this improved defect detection algorithm and other feature extraction methods, such as VGG16, ResNet-50, and Xception. The results of experiments show that the defect detection accuracy of this defect detection algorithm can reach 94.3% and the speed is also increased by 1-3 percentage points.

• 한국군사과학기술학회지
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• 제26권3호
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• pp.234-245
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• 2023

The Arena Fragmentation Test(AFT) is designed to analyze warhead performance by measuring fragmentation data. In order to evaluate the results of the AFT, a set of AFT images are captured by high-speed cameras. To detect objects in the AFT image set, ResNet-50 based Faster R-CNN is used as a detection model. However, because of the low resolution of the AFT image set, a detection model has shown low performance. To enhance the performance of the detection model, Super-resolution(SR) methods are used to increase the AFT image set resolution. To this end, The Bicubic method and three SR models: ZSSR, EDSR, and SwinIR are used. The use of SR images results in an increase in the performance of the detection model. While the increase in the number of pixels representing a fragment flame in the AFT images improves the Recall performance of the detection model, the number of pixels representing noise also increases, leading to a slight decreases in Precision performance. Consequently, the F1 score is increased by up to 9 %, demonstrating the effectiveness of SR in enhancing the performance of the detection model.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.655-657
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• 2021

인공지능 알고리즘을 이용한 유방암의 조기진단에 관련된 연구는 최근들어 활발하게 진행되고 있으나, 사용자의 목적에 맞는 처리속도 및 정확도 등에 다양한 한계점을 보인다. 이러한 문제를 해결하기 위해, 본 논문에서는 ImageNet에서 학습된 ResNet 모델을 현미경 기반 암세포 이미지에서 활용이 가능한 다단계 전이 학습을 제안하고, 이를 다시 전이 학습하여 초음파 유방암 영상을 양성 및 악성으로 분류하는 실험을 진행하였다. 제안된 다단계 전이 학습 알고리즘은 초음파 유방암 영상을 분류하였을 때 96% 이상의 정확도를 보였으며, 향후 암 세포주 및 실시간 영상처리 등의 추가를 통해 보다 높은 활용도와 정확도를 보일 것으로 기대한다.

• 한국세라믹학회지
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• 제39권3호
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• pp.245-251
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• 2002

깁사이트의 급속 열분해 산물인 비정질 알루미나로부터 γ-alumina bead를 제조하고, 이를 21.87%의 질산($HNO_3$)과 28.57%의 초산($CH_3COOH$)을 혼합한 용액에 침적시킨 다음 200$^{\circ}$C 온도로 3시간 수열처리하여 결정의 변화, 기공특성, $N_2$ 흡/탈착 등온선, 기계적강도 및 내열특성 등을 조사하였다. 0.1∼0.3${\mu}$m 크기의 침상 및 판상 의사베이마이트 결정은 같은 결정구조를 갖는 1∼2${\mu}$m 길이의 침상형 베이마이트 결정으로 변했고, 이를 통해 ${\gamma}$-alumina와 베이마이트 사이에는 수열반응에 기인한 가역적 상 변화가 발생한다는 사실을 알 수 있었다. 수열처리 전 ${\gamma}$-alumina bead에 비해 $N_2$ 흡착 용량이 450㎖/g에서 670㎖/g으로 증가하였고, 100∼1000${\AA}$ 범위의 기공부피는 0.15㎖/g에서 0.77㎖/g으로 증가하였으며, 기계적 강도가 1.4MPa에서 2.2MPa로 증가하였다. 또한 40vol%의 수증기를 포함한 1000$^{\circ}$C의 고온에서도 100∼1000${\AA}$ 범위의 기공을 유지하며 ${\theta}$-alumina 결정구조를 유지하는 높은 내열저항을 나타내었다.