• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.455-465
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• 2021

The Molten Salt Reactor (MSR), one of the six advanced reactor types of the 4th generation nuclear energy systems, has many impressive features including economic advantages, inherent safety and nuclear non-proliferation. This paper introduces a system analysis code named TREND, which is developed and used for the steady and transient simulation of MSRs. The TREND code calculates the distributions of pressure, velocity and temperature of single-phase flows by solving the conservation equations of mass, momentum and energy, along with a fluid state equation. Heat structures coupled with the fluid dynamics model is sufficient to meet the demands of modeling MSR system-level thermal-hydraulics. The core power is based on the point reactor neutron kinetics model calculated by the typical Runge-Kutta method. An incremental PID controller is inserted to adjust the operation behaviors. The verification and validation of the TREND code have been carried out in two aspects: detailed code-to-code comparison with established thermal-hydraulic system codes such as RELAP5, and validation with the experimental data from MSRE and the CIET facility (the University of California, Berkeley's Compact Integral Effects Test facility).The results indicate that TREND can be used in analyzing the transient behaviors of MSRs and will be improved by validating with more experimental results with the support of SINAP.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.71-79
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• 2011

The objective of the imaging pipeline is to transform the original scene into a display image that appear similar, Generally, gamma adjustment or histogram-based method is modified to improve the contrast and detail. However, this is insufficient as the intensity and the chromaticity of illumination vary with geometric position. Thus, MSR (Multi-Scale Retinex) has been proposed. the MSR is based on a channel-independent logarithm, and it is dependent on the scale of the Gaussian filter, which varies according to input image. Therefore, after correcting the color, image quality degradations, such as halo, graying-out, and dominated color, may occur. Accordingly, this paper presents a novel color correction method using a modified image formation model in which the image is divided into three components such as global illumination, local illumination, and reflectance. The global illumination is obtained through Gaussian filtering of the original image, and the local illumination is estimated by using JND-based adaptive filter. Thereafter, the reflectance is estimated by dividing the original image by the estimated global and the local illumination to remove the influence of the illumination effects. The output image is obtained based on sRGB color representation. The experiment results show that the proposed method yields better performance of color correction over the conventional methods.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.739-748
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• 2014

In this paper, we propose pyramid appearance and global structure action descriptors on both RGB and depth motion history images and a model-free method for human action recognition. In proposed algorithm, we firstly construct motion history image for both RGB and depth channels, at the same time, depth information is employed to filter RGB information, after that, different action descriptors are extracted from depth and RGB MHIs to represent these actions, and then multimodality information collaborative representation and recognition model, in which multi-modality information are put into object function naturally, and information fusion and action recognition also be done together, is proposed to classify human actions. To demonstrate the superiority of the proposed method, we evaluate it on MSR Action3D and DHA datasets, the well-known dataset for human action recognition. Large scale experiment shows our descriptors are robust, stable and efficient, when comparing with the-state-of-the-art algorithms, the performances of our descriptors are better than that of them, further, the performance of combined descriptors is much better than just using sole descriptor. What is more, our proposed model outperforms the state-of-the-art methods on both MSR Action3D and DHA datasets.

• Journal of Welding and Joining
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• v.21 no.1
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• pp.66-71
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• 2003

The release of residual stress by mechanical loading and unloading is often performed in the fabrication of box structure fur steel bridge. The proper degree of loading and unloading is significant at release method of residual stress by mechanical loading because that degree is changed by material and geometric shape of welded structure. Therefore, the simulation model that could exactly analyze the release of residual stress by mechanical loading is to be necessary. In this study, the non-linear behavior of weldments under external loading and unloading, such as the decrease and increase of structure stiffness, was investigated by monitoring of nominal stress and strain. Tensile loading and unloading test and the proper degree of stress relaxation was measured by sectioning technique using strain gauge. Analysis model that is indispensable for the effective application of MSR method was established on the basis of test and measurement result.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.29 no.2
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• pp.148-156
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• 2007

Purpose: The aim of this study is the changes of upper respiratory airway space in patients with mandibular prognathism after 2-jaw orthognathic surgery in patients with skeletal classs III malocclusion. Method: We measured the lines between selected upper airway landmarks on lateral cephalometric x-ray films of skeletal class III 64 persons who had not been operated yet, were 6 months after operation. The test subjects were divided into 3 groups according to maxillary movement, as follows; maxillary advancement (MA) group, maxillary posterior impaction (MPI) group, maxillary posterior impaction and superior repositioning (MPI+MSR) group. Result: In this study, nasopharyngeal airway space in MPI+MSR group was significantly increased after operation (p<0.05). Oropharygeal and hypopharyngeal airway space in MA group and MPI group were significantly decreased after operation (p<0.05). From hyoid bone to anterior mandible point distance in MA group and MPI group were significantly decreased after operation (p<0.05). Conclusion: Oropharygeal and hypopharyngeal airway space were influenced more by mandibular set-back than maxillary movement. Maxillary movement surgery as well as mandibular setback surgery should be taken into consideration in order to minimize symptoms related to obstructive sleep apnea syndrome after operation.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.347-353
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• 2022

In this paper, we propose a method that performs a text-video retrieval model by replacing video properties using captions. In general, the exisiting embedding-based models consist of both joint embedding space construction and the CNN-based video encoding process, which requires a lot of computation in the training as well as the inference process. To overcome this problem, we introduce a video-captioning module to replace the visual property of video with captions generated by the video-captioning module. To be specific, we adopt the caption generator that converts candidate videos into captions in the inference process, thereby enabling direct comparison between the text given as a query and candidate videos without joint embedding space. Through the experiment, the proposed model successfully reduces the amount of computation and inference time by skipping the visual processing process and joint embedding space construction on two benchmark dataset, MSR-VTT and VATEX.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.1051-1056
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• 2007

The air suspension system is widely used in commercial vehicles such as buses or special purpose trucks because it improves ride better than any other types of suspension. Since the durability of vehicle parts is directly related to the safety, the evaluation of the durability at the design stage is necessary. In this research, the fatigue life of the air suspension frame for trucks is predicted by the modal stress recovery(MSR) method. Using the process proposed in this research, the fatigue life of vehicle parts can be predicted efficiently at the design stage.

• Smart Structures and Systems
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• v.2 no.1
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• pp.25-46
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• 2006

Aging wiring in buildings, aircraft and transportation systems, consumer products, industrial machinery, etc. is among the most significant potential causes of catastrophic failure and maintenance cost in these structures. Smart wire health monitoring can therefore have a substantial impact on the overall health monitoring of the system. Reflectometry is commonly used for locating faults on wire and cables. This paper compares Time domain reflectometry (TDR), frequency domain reflectometry (FDR), mixed signal reflectometry (MSR), sequence time domain reflectometry (STDR), spread spectrum time domain reflectometry (SSTDR) and capacitance sensors in terms of their accuracy, convenience, cost, size, and ease of use. Advantages and limitations of each method are outlined and evaluated for several types of aircraft cables. The results in this paper can be extrapolated to other types of wire and cable systems.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1318-1330
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• 2018

Video captioning refers to the process of extracting features from a video and generating video captions using the extracted features. This paper introduces a deep neural network model and its learning method for effective video captioning. In this study, visual features as well as semantic features, which effectively express the video, are also used. The visual features of the video are extracted using convolutional neural networks, such as C3D and ResNet, while the semantic features are extracted using a semantic feature extraction network proposed in this paper. Further, an attention-based caption generation network is proposed for effective generation of video captions using the extracted features. The performance and effectiveness of the proposed model is verified through various experiments using two large-scale video benchmarks such as the Microsoft Video Description (MSVD) and the Microsoft Research Video-To-Text (MSR-VTT).

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.807-818
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• 2022

In order to further improve the accuracy and time efficiency of behavior recognition in intelligent monitoring scenarios, a human behavior recognition algorithm based on YOLO combined with LSTM and CNN is proposed. Using the real-time nature of YOLO target detection, firstly, the specific behavior in the surveillance video is detected in real time, and the depth feature extraction is performed after obtaining the target size, location and other information; Then, remove noise data from irrelevant areas in the image; Finally, combined with LSTM modeling and processing time series, the final behavior discrimination is made for the behavior action sequence in the surveillance video. Experiments in the MSR and KTH datasets show that the average recognition rate of each behavior reaches 98.42% and 96.6%, and the average recognition speed reaches 210ms and 220ms. The method in this paper has a good effect on the intelligence behavior recognition.