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- 저자 : Yang Feilong (검색결과 4 건)
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Black Bridge: Scatternet Formation Algorithm for Solving a New Emerging Problem
Guo, Minyi,Yang, Yanqin,Zhang, Gongwei,Tang, Feilong,Shen, Yao Korea Information Processing Society 2009 Journal of information processing systems Vol.5 No.4
Nowadays, it has become common to equip a device with Bluetooth. As such devices become pervasive in the world; much work has been done on forming them into a network, however, almost all the Bluetooth Scatternet Formation Algorithms assume devices are homogeneous. Even the exceptional algorithms barely mentioned a little about the different characteristics of devices like computational abilities, traffic loads for special nodes like bridge nodes or super nodes, which are usually the bottleneck in the scatternet. In this paper, we treat the devices differently not only based on the hardware characteristics, but also considering other conditions like different classes, different groups and so on. We use a two-phase Scatternet Formation Algorithm here: in the first phase, construct scatternets for a specified kind of devices; in the second phase, connect these scatternets by using least other kinds of devices as bridge nodes. Finally, we give some applications to show the benefit of classification.
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Bei Wu,Chen Wang,Feilong Hei,Cun Long,Mengmeng Chen,Shengnan Yang,Jie Yu,Zhihai Ju 한국통합생물학회 2015 Animal cells and systems Vol.19 No.1
Induced pluripotent stem (iPS) cells derive from autologous somatic cells, the application prospect of iPS cells forregenerative medicine and tissue engineering is better than embryonic stem cells (ESCs) to some extent. Alveolar type II(AT II) epithelial cells play key role in the injured lung tissue regeneration and function recovery. The differentiation of iPScells into AT II cells could provide available source for injured lung treatment. In this study, rat iPS (riPS) cells wereresuscitated and proliferated for 14 days before differentiation. A modified three-step induction protocol similar to thereported ESCs inducing procedure was used in this study for the differentiation groups. Routine cell culture was done to theriPS cell control group (riPS-con). At stage 3, cells of day 7 (Diff. 7) and day 14 (Diff. 14) were collected for the real-timepolymerase chain reaction tests for gene expressions of Oct4, Nanog, SPA, SPB, SPC, SPD, and CC10. Immunofluorescencestaining of SPC and SSEA-1 was conducted. At the end of the differentiation, cell morphology becameoutstretched and epithelium-like. Cells of the Diff. 14 group positively expressed SPC and negatively expressed SSEA-1,which is contrary to the riPS-con group. In the Diff. 7 and the Diff. 14 groups, the expression of Oct4, Nanog, and SPBdecreased (P < 0.05), whereas the expression of SPA, SPC, SPD (P < 0.05), and CC10 (P > 0.05) increased. This studyindicated that riPS cells can successfully differentiate into AT II epithelial cells with the three-step induction protocol andmay be further applied to implanting in decellularized rat lung scaffolds and building a bio-artificial lung.
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Xingxi Pan,Wen Yang,Zhongyong Wen,Feilong Li,Lihua Tong,Wubing Tang 대한부인종양학회 2020 Journal of Gynecologic Oncology Vol.31 No.6
Objective: To compare survival outcomes between cervical adenocarcinoma (ADC) andsquamous cell carcinoma (SCC) using a propensity score matching (PSM) analysis based onthe Surveillance, Epidemiology, and End Results (SEER) Program. Methods: Patients diagnosed with cervical cancer between 1998 and 2016 were identifiedfrom the SEER database. The Kaplan-Meier method and Cox regression analysis were used toanalyze survival. A subgroup analysis of overall survival (OS) between patients with ADC andSCC was performed after the 1:1 PSM analysis. Results: Of the 33,148 patients, 24,591 (79.19%) had SCC and 8,557 (25.81%) had ADC. In theunmatched cohort, after adjustment in multivariate analysis, patients with ADC had a worseprognosis than patients with SCC (hazard ratio [HR]=1.12; 95% confidence interval [CI]=1.07–1.18; p<0.001). In the propensity matched cohort, Kaplan-Meier analysis and subgroup analysisshowed that ADC was associated with a worse prognosis than SCC (p=0.001). An analysisstratified by SEER stage revealed a worse prognosis for patients with ADC patients presentingwith a regional disease than patients with SCC (HR=1.24; 95% CI=1.14–1.36 p<0.001), but nostatistically significant differences were observed between the localized disease (HR=0.97; 95%CI=0.86–1.10; p=0.664) and distant disease (HR=1.09; 95% CI=0.97–1.22; p=0.162) subgroups. Conclusion: The significant differences in survival outcomes between patients with cervicalADC and SCC were only observed in the regional disease subgroup, but not in the localizeddisease and distant disease subgroups.
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Fault Diagnosis for Conventional Circuit Breaker Based on One-Dimensional Convolution Neural Network
Sun Shuguang,Zhang Tingting,Wang Jingqin,Yang Feilong 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.3
The vibration signal generated by the operating mechanism of conventional circuit breaker contains abundant mechanical state information. Aiming at traditional fault diagnosis methods that need to realize signal feature extraction based on feature selection, a fault diagnosis model based on one-dimensional convolutional neural network is proposed. In the diagnosis model, multiple convolutional neural networks are designed according to the type and degree of faults, and the network is set as a large convolutional kernel to enlarge the receptive field region; the raw vibration signal is used as the model input for training, and the corresponding fault type and degree are output after hierarchical diagnosis. The experimental results show that the model can automatically extract the fault signal features, effectively complete the fault diagnosis of the contact system for the conventional circuit breaker, and has good generalization ability. The model in this paper has a higher comprehensive diagnosis recognition rate compared with other methods, reaching 98.84%.
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