scholarly journals Consistent quantitative gene product expression: #1. Automated identification of regenerating bone marrow cell populations using support vector machines

2016 ◽  
Vol 89 (11) ◽  
pp. 978-986 ◽  
Author(s):  
Andrew P. Voigt ◽  
Lisa Eidenschink Brodersen ◽  
Laura Pardo ◽  
Soheil Meshinchi ◽  
Michael R. Loken
Keyword(s):  
Bone Marrow ◽  
Support Vector Machines ◽  
Gene Product ◽  
Bone Marrow Cell ◽  
Marrow Cell ◽  
Support Vector ◽  
Cell Populations ◽  
Automated Identification ◽  
Vector Machines ◽  
Product Expression

Bone Marrow Cell Populations Mimicking Common Acute Lymphoblastic Leukemia in Infants with Stage IV-S Neuroblastoma

1991 ◽  
Vol 86 (2) ◽  
pp. 86-89 ◽  
Author(s):  
M. Mandel ◽  
G. Rechavi ◽  
Y. Neumann ◽  
M Biniaminov ◽  
F. Brok-Simoni ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Acute Lymphoblastic Leukemia ◽  
Bone Marrow Cell ◽  
Lymphoblastic Leukemia ◽  
Marrow Cell ◽  
Stage Iv ◽  
Cell Populations

Two-Stage Automated Operational Modal Analysis Based on Power Spectrum Density Transmissibility and Support-Vector Machines

2021 ◽  
pp. 2150068
Author(s):  
Zhi-Wei Chen ◽  
Kui-Ming Liu ◽  
Wang-Ji Yan ◽  
Jian-Lin Zhang ◽  
Wei-Xin Ren
Keyword(s):  
Support Vector Machines ◽  
Power Spectrum ◽  
Modal Analysis ◽  
Power Spectrum Density ◽  
Support Vector ◽  
Svm Classifier ◽  
Automated Identification ◽  
Two Stage ◽  
Vector Machines ◽  
Spectrum Density

Power spectrum density transmissibility (PSDT) functions have attracted widespread attention in operational modal analysis (OMA) because of their robustness to excitations. However, the selection of the peaks and stability axes are still subjective and requires further investigation. To this end, this study took advantage of PSDT functions and support-vector machines (SVMs) to propose a two-stage automated modal identification method. In the first stage, the automated identification of peaks is achieved by introducing the peak slope (PS) as a critical index and determining its threshold using the SVM classifier. In the second stage, the automated identification of the stability axis is achieved by introducing the relative difference coefficients (RDCs) of the modal parameters as indicators and determining their thresholds using the SVM classifier. To verify its feasibility and accuracy, the proposed method was applied to an ASCE-benchmark structure in the laboratory and in a high-rise building installed with a structural health monitoring system (SHMS). The results showed that the automated identification method could effectively eliminate spurious modes and accurately identify the closely spaced modes. The proposed method can be automatically applied without manual intervention, and it is robust to noise. It is promising for application to the real-time condition evaluation of civil structures installed with SHMSs.

Action of dipyridamole on megakaryocytopoiesis in regenerating and static bone marrow cell populations

1992 ◽  
Vol 114 (6) ◽  
pp. 1813-1816
Author(s):  
I. N. Ivansenko ◽  
Yu. A. Blyudzin ◽  
D. N. Chernyakova ◽  
V. A. Almazov ◽  
G. E. Arkad'eva
Keyword(s):  
Bone Marrow ◽  
Bone Marrow Cell ◽  
Marrow Cell ◽  
Cell Populations
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