• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.111-118
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• 2022

In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.

• Advances in nano research
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• v.13 no.1
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• pp.87-96
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• 2022

Drug self-delivery systems can easily realize combination drug therapy and avoid carrier-induced toxicity and immunogenicity because they do not need non-therapeutic carrier materials. So, designing appropriate drug self-delivery systems for specific diseases can settle most of the problems existing in traditional drug delivery systems. Retinal pigment epithelium is very important for the homeostasis of retina. However, it is vulnerable to oxidative damage and difficult to repair. Worse still, the antioxidants can hardly reach the retina by non-invasive administration routes due to the ocular barriers. Herein, the targeted group (folic acid) and antioxidant (melatonin) have been grafted on the surface of ZnO quantum dots to fabricate a new kind of drug self-delivery systems as a protectant via eyedrops. In this study, the negative nanoparticles with size ranging in 4~6 nm were successfully synthesized. They could easily and precisely deliver drugs to retinal pigment epithelium via eyedrops. And they realized acid degradation to controlled release of melatonin and zinc in retinal pigment epithelium cells. Consequently, the structure of retinal pigment epithelium cells were stabilized according to the expression of ZO-1 and β-catenin. Moreover, the antioxidant capacity of retinal pigment epithelium were enhanced both in health mice and photic injury mice. Therefore, such new drug self-delivery systems have great potential both in prevention and treatment of oxidative damage induced retinal diseases.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.187-199
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• 2022

Kriging metamodel, as a flexible machine learning method for approximating deterministic analysis models of an engineering system, has been widely used for efficiently estimating slope reliability in recent years. However, the autocorrelation function (ACF), a key input to Kriging that affects the accuracy of reliability estimation, is usually selected based on empiricism. This paper proposes an adaption of the Kriging method, named as Genetic Algorithm optimized Whittle-Matérn Kriging (GAWMK), for addressing this issue. The non-classical two-parameter Whittle-Matérn (WM) function, which can represent different ACFs in the Matérn family by controlling a smoothness parameter, is adopted in GAWMK to avoid subjectively selecting ACFs. The genetic algorithm is used to optimize the WM model to adaptively select the optimal autocorrelation structure of the GAWMK model. Monte Carlo simulation is then performed based on GAWMK for a subsequent slope reliability analysis. Applications to one explicit analytical example and two slope examples are presented to illustrate and validate the proposed method. It is found that reliability results estimated by the Kriging models using randomly chosen ACFs might be biased. The proposed method performs reasonably well in slope reliability estimation.

• Geomechanics and Engineering
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• v.28 no.4
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• pp.335-346
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• 2022

Buckling failure is a typical slope instability mode that should be paid more attention to. It is difficult to provide systematic guidance for the monitoring and management of such slopes due to unclear mechanism. Here we examine buckling failure as the potential instability mode for a slope above a railway tunnel in southwest China. A comprehensive model test system was developed that can be used to conduct buckling failure experiments. The displacement, stress, and strain of the slope were monitored to document the evolution of buckling failure during the experiment. Monitoring data reveal the deformation and stress characteristics of the slope with different slipping mass thicknesses and under different top loads. The test results show that the slipping mass is the main subject of the top load and is the key object of monitoring. Displacement and stress precede buckling failure, so maybe useful predictors of impending failure. However, the response of the stress variation is earlier than displacement variation during the failure process. It is also necessary to monitor the bedrock near the slip face because its stress evolution plays an important role in the early prediction of instability. The position near the slope foot is most prone to buckling failure, so it should be closely monitored.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2789-2802
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• 2020

Small Modular Reactors (SMRs) are attracting wide attention due to their outstanding performance, extensive studies have been carried out for lead-based fast reactors (LFRs) that cooled with Lead or Lead-bismuth (LBE), and small modular natural circulation LFR is one of the promising candidates for SMRs and LFRs development. One of the challenges for the design small modular natural circulation LFR is to master the natural circulation thermal-hydraulic performance in the reactor primary circuit, while the natural circulation characteristics is a coupled thermal-hydraulic problem of the core thermal power, the primary loop layout and the operating state of secondary cooling system etc. Thus, accurate predicting the natural circulation LFRs thermal-hydraulic features are highly required for conducting reactor operating condition evaluate and Thermal hydraulic design optimization. In this study, a thermal-hydraulic analysis code is developed for small modular natural circulation LFRs, which is based on several mathematical models for natural circulation originally. A small modular natural circulation LBE cooled fast reactor named URANUS developed by Korea is chosen to assess the code's capability. Comparisons are performed to demonstrate the accuracy of the code by the calculation results of MARS, and the key thermal-hydraulic parameters agree fairly well with the MARS ones. As a typical application case, steady-state analyses were conducted to have an assessment of thermal-hydraulic behavior under nominal condition, and several parameters affecting natural circulation were evaluated. What's more, two characteristics parameters that used to analyze natural circulation LFRs natural circulation capacity were established. The analyses show that the core thermal power, thermal center difference and flow resistance is the main factors affecting the reactor natural circulation. Improving the core thermal power, increasing the thermal center difference and decreasing the flow resistance can significantly increase the reactor mass flow rate. Characteristics parameters can be used to quickly evaluate the natural circulation capacity of natural circulation LFR under normal operating conditions.

• Geomechanics and Engineering
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• v.30 no.2
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• pp.139-151
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• 2022

The mechanical properties of expansive soil are very unstable, highly sensitive to water, and thus easy to cause major engineering accidents. In this paper, the expansive soil foundation pit project of the East Huada Square in the eastern suburb of Chengdu was studied, the moisture content of the expansive soil was considered as an important factor that affecting the mechanics properties of expansive soil and the stability of the non-equal-length double-row piles in the foundation pit support. Three groups of direct shear tests were carried out and the quantitative relationships between the moisture content and shear strength τ, cohesion c, internal friction angle φ were obtained. The effect of cohesion and internal friction angle on the maximum displacement and the maximum bending moment of piles were analyzed by the finite element software MIDAS/GTS (Geotechnical and Tunnel Analysis System). Results show that the higher the moisture content, the smaller the matrix suction, and the smaller the shear strength; the cohesion and the internal friction angle are exponentially related to the moisture content, and both are negatively correlated. The maximum displacement and the maximum bending moment of the non-equal length double-row piles decrease with the increase of the cohesion and the internal friction angle. When the cohesion is greater than 33 kPa or the internal friction angle is greater than 25.5°, the maximum displacement and maximum bending moment of the piles are relatively small, however, once crossing the points (the corresponding moisture content value is 24.4%), the maximum displacement and the maximum bending moment will increase significantly. Therefore, in order to ensure the stability and safety of the foundation pit support structure of the East Huada Square, the moisture content of the expansive soil should not exceed 24.4%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.3991-4010
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• 2021

The Question Similarity Measurement of Chinese Crop Diseases and Insect Pests (QSM-CCD&IP) aims to judge the user's tendency to ask questions regarding input problems. The measurement is the basis of the Agricultural Knowledge Question and Answering (Q & A) system, information retrieval, and other tasks. However, the corpus and measurement methods available in this field have some deficiencies. In addition, error propagation may occur when the word boundary features and local context information are ignored when the general method embeds sentences. Hence, these factors make the task challenging. To solve the above problems and tackle the Question Similarity Measurement task in this work, a corpus on Chinese crop diseases and insect pests(CCDIP), which contains 13 categories, was established. Then, taking the CCDIP as the research object, this study proposes a Chinese agricultural text similarity matching model, namely, the AgrCQS. This model is based on mixed information extraction. Specifically, the hybrid embedding layer can enrich character information and improve the recognition ability of the model on the word boundary. The multi-scale local information can be extracted by multi-core convolutional neural network based on multi-weight (MM-CNN). The self-attention mechanism can enhance the fusion ability of the model on global information. In this research, the performance of the AgrCQS on the CCDIP is verified, and three benchmark datasets, namely, AFQMC, LCQMC, and BQ, are used. The accuracy rates are 93.92%, 74.42%, 86.35%, and 83.05%, respectively, which are higher than that of baseline systems without using any external knowledge. Additionally, the proposed method module can be extracted separately and applied to other models, thus providing reference for related research.

• Journal of Veterinary Science
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• v.21 no.1
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• pp.9.1-9.15
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• 2020

Regenerative therapy holds great promise in the development of cures of some untreatable diseases such as cardiovascular diseases, and pluripotent stem cells (PSCs) including induced PSCs (iPSCs) are the most important regenerative seed cells. Recently, differentiation of human PSCs into functional tissues and cells in vitro has been widely reported. However, although porcine reports are rare they are quite essential, as the pig is an important animal model for the in vitro generation of human organs. In this study, we reprogramed porcine embryonic fibroblasts into porcine iPSCs (piPSCs), and differentiated them into cluster of differentiation 31 (CD31)-positive endothelial cells (ECs) (piPSC-derived ECs, piPS-ECs) using an optimized single-layer culture method. During differentiation, we observed that a combination of GSK3β inhibitor (CHIR99021) and bone morphogenetic protein 4 (BMP4) promoted mesodermal differentiation, resulting in higher proportions of CD31-positive cells than those from separate CHIR99021 or BMP4 treatment. Importantly, the piPS-ECs showed comparable morphological and functional properties to immortalized porcine aortic ECs, which are capable of taking up low-density lipoprotein and forming network structures on Matrigel. Our study, which is the first trial on a species other than human and mouse, has provided an optimized single-layer culture method for obtaining ECs from porcine PSCs. Our approach can be beneficial when evaluating autologous EC transplantation in pig models.

• The Journal of Advanced Prosthodontics
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• v.14 no.6
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• pp.369-378
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• 2022

PURPOSE. The purpose of this in vitro study was to assess whether scanning strategies of virtual interocclusal record (VIR) affect the accuracy of VIR during intraoral scanning. MATERIALS AND METHODS. Five pairs of reference cubes were added to the digital upper and lower dentitions of a volunteer, which were printed into resin casts. Subsequently, the resin casts were articulated in the maximal intercuspal position in a mechanical articulator and scanned with an industrial computed tomography system, of which the VIR was served as a reference VIR. The investigated VIR of the upper and lower jaws of the resin master cast were recorded with an intraoral scanner according to 9 designed scanning strategies. Then, the deviation between the investigated VIRs and reference VIR were analyzed, which were measured by the deviation of the distances of six selected reference points on the upper reference cubes in each digital cast to the XY-plane between the investigated VIRs and reference VIR. RESULTS. For the deviation in the right posterior dentitions, RP group (only scanning of right posterior dentitions) showed the smallest deviation. Besides, BP group (scanning of bilateral posterior dentitions) showed the smallest deviation in the left posterior dentitions. Moreover, LP group (scanning of left posterior dentitions) showed the smallest deviation in the anterior dentitions. For the deviation of full dental arches, BP group showed the smallest deviation. CONCLUSION. Different scanning strategies of VIR can influence the accuracy of alignment of virtual dental casts. Appropriate scanning strategies of VIR should be selected for different regions of interest and edentulous situations.