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RISS 인기검색어
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- 저자 : Liwei Xin (검색결과 6 건)
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Improving performance of medical image alignment through super-resolution
Liwei Deng,Yuanzhi Zhang,Jing Wang,Sijuan Huang,Xin Yang 대한의용생체공학회 2023 Biomedical Engineering Letters (BMEL) Vol.13 No.3
Medical image alignment is an important tool for tracking patient conditions, but the quality of alignment is influenced bythe effectiveness of low-dose Cone-beam CT (CBCT) imaging and patient characteristics. To address these two issues, wepropose an unsupervised alignment method that incorporates a preprocessing super-resolution process. We constructed themodel based on a private clinical dataset and validated the enhancement of the super-resolution on alignment using clinicaland public data. Through all three experiments, we demonstrate that higher resolution data yields better results in the alignmentprocess. To fully constrain similarity and structure, a new loss function is proposed; Pearson correlation coefficientcombined with regional mutual information. In all test samples, the newly proposed loss function obtains higher resultsthan the common loss function and improve alignment accuracy. Subsequent experiments verified that, combined with thenewly proposed loss function, the super-resolution processed data boosts alignment, can reaching up to 9.58%. Moreover,this boost is not limited to a single model, but is effective in different alignment models. These experiments demonstratethat the unsupervised alignment method with super-resolution preprocessing proposed in this study effectively improvedalignment and plays an important role in tracking different patient conditions over time.
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Yuepeng Sun,Liwei Xin,Guangxue Wu,Yuntao Guan 대한환경공학회 2019 Environmental Engineering Research Vol.24 No.1
Nitrogen removal, nitrous oxide (N₂O) emission and microbial community in sequencing batch and continuous-flow intermittent aeration processes were investigated. Two sequencing batch reactors (SBRs) and two continuous-flow multiple anoxic and aerobic reactors (CMRs) were operated under high dissolved oxygen (DO) (SBR-H and CMR-H) and low DO (SBR-L and CMR-L) concentrations, respectively. Nitrogen removal was enhanced under CMR and low DO conditions (CMR-L). The highest total inorganic nitrogen removal efficiency of 91.5% was achieved. Higher nitrifying and denitrifying activities in SBRs were observed. CMRs possessed higher N₂O emission factors during nitrification in the presence of organics, with the highest N₂O emission factor of 60.7% in CMR-L. SBR and low DO conditions promoted N₂O emission during denitrification. CMR systems had higher microbial diversity. Candidatus Accumulibacter, Nitrosomonadaceae and putative denitrifiers (N₂O reducers and producers) were responsible for N₂O emission.
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Simulation Study on Optimizing Neural Network in Short-Term Electric Load Prediction
Tan Zhongfu,Xin He,Ju Liwei 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.3
It researches the short-term electric load prediction and short-term electric load has the characteristics of time-varying, uncertainty, nonlinearity, etc., so the traditional linear prediction method cannot correctly describe the changing rule of the short-term electric load prediction, and neural network has the deficiencies including local minimum value of neural network, over-fitting and weak generalization ability, and the prediction accuracy is lower. In order to improve the accuracy of the short-term electric load prediction, this paper proposes a short-term electric load prediction model (IQPSO-BPNN) based on optimizing BP neural network. Firstly, it improves Quantum Particle Swarm Optimization to optimize the BP neural network parameters, and then adopts the optimized BP neural network to conduct modeling for the nonlinear change law of the short-term electric load prediction. Finally, it takes simulation test for the model performance. The simulation result shows that IPQPSO solves the problems of the BP neural network, and improve the prediction accuracy of the short-term electric load and reduce the prediction error.
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New degradation feature extraction method of planetary gearbox based on alpha stable distribution
Wenxin Qiao,Xianglong Ni,Lei Wang,Xin Lv,Liwei Chen,Fucheng Sun 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.1
The planetary transmission system has been widely used in industry because of its various advantages. And the study on degradation feature extraction method of planetary gearbox is of major significance for mechanical system prognostics and health management (PHM). In this paper, the alpha stable distribution characteristics of planetary gearbox vibration signals in performance degradation process are verified. By observing the change of alpha stable distribution for planetary gearbox degradation experiment data, a new degradation feature extraction method based on alpha stable distribution is proposed, which is called the height of probability distribution (HPD). Through comparative analysis, it is determined that HPD has better linearity and less fluctuation compared with conventional degradation features in planetary gearbox accelerated degradation stage. Moreover, in the accelerated degradation stage, the degradation trend prediction result based on HPD is closer to the actual data than conventional degradation features no matter using Wiener-based or LSSVM-based prediction method. These conclusions indicate that the newly proposed HPD works well and gives accurate estimates for condition monitoring and degradation trend prediction of planetary gearbox.
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Li, Wei,Zhang, Xiangrong,Ding, Meng,Xin, Yanfei,Xuan, Yaoxian,Zhao, Yuqing The Korean Society of Ginseng 2019 Journal of Ginseng Research Vol.43 No.4
Background: Ginsenosides have been widely used clinically for many years and were regarded as very safe. However, a few researches on the toxicities of these kinds of agents showed that some ginsenosides may have side-effect on the rats or dogs. So it is extremely necessary to further clarify the potential toxicity of ginsenosides. This study was carried out to investigate long-term toxicity and genotoxicity of 25-methoxydammarane-3, 12, 20-triol ($25-OCH_3-PPD$), a new derivative of ginsenoside, in beagle dogs. Methods: Twenty-four beagle dogs were divided randomly into four treatment groups and repeatedly orally administered with $25-OCH_3-PPD$ capsule at 60, 120, and 240 mg/kg/day for 91 consecutive days. Ames, micronucleus, and chromosomal aberration tests were established to analyze the possible genotoxicity of $25-OCH_3-PPD$. Results: There was no $25-OCH_3-PPD$einduced systemic toxicity in beagle dogs at any doses. The level of $25-OCH_3-PPD$ at which no adverse effects were observed was found to be 240 mg/kg/day. The result of Ames test showed that there was no significant increase in the number of revertant colonies of $25-OCH_3-PPD$ administrated groups compared to the vehicle control group. There were also no significant differences between $25-OCH_3-PPD$ administrated groups at all dose levels and negative group in the micronucleus test and chromosomal aberration assay. Conclusion: The highest dose level of $25-OCH_3-PPD$ at which no adverse effects were observed was found to be 240 mg/kg per day, and it is not a genotoxic agent either in somatic cells or germs cells. $25-OCH_3-PPD$ is an extremely safe candidate compound for antitumor treatment.
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