A ROBUST STATISTICAL ALGORITHM FOR BOUNDARY DETECTION IN LIQUID SPRAYS

2019 ◽  
Vol 29 (12) ◽  
pp. 1071-1085
Author(s):  
C. Taber Wanstall ◽  
Henning Junne ◽  
Joshua A. Bittle ◽  
Ajay Agrawal
2009 ◽  
Vol 35 (2) ◽  
pp. 132-136 ◽  
Author(s):  
Xiao-Mao LI ◽  
Lin-Lin ZHU ◽  
Yan-Dong TANG

2020 ◽  
Vol 13 (4) ◽  
pp. 798-807
Author(s):  
J. Kavitha ◽  
P. Arockia Jansi Rani ◽  
P. Mohamed Fathimal ◽  
Asha Paul

Background:: In the internet era, there is a prime need to access and manage the huge volume of multimedia data in an effective manner. Shot is a sequence of frames captured by a single camera in an uninterrupted space and time. Shot detection is suitable for various applications such that video browsing, video indexing, content based video retrieval and video summarization. Objective:: To detect the shot transitions in the video within a short duration. It compares the visual features of frames like correlation, histogram and texture features only in the candidate region frames instead of comparing the full frames in the video file. Methods: This paper analyses candidate frames by searching the values of frame features which matches with the abrupt detector followed by the correct cut transition frame with in the datacube recursively until it detects the correct transition frame. If they are matched with the gradual detector, then it will give the gradual transition ranges, otherwise the algorithm will compare the frames within the next datacube to detect shot transition. Results:: The total average detection rates of all transitions computed in the proposed Data-cube Search Based Shot Boundary Detection technique are 92.06 for precision, 96.92 for recall and 93.94 for f1 measure and the maximum accurate detection rate. Conclusion:: Proposed method for shot transitions uses correlation value for searching procedure with less computation time than the existing methods which compares every single frame and uses multi features such as color, edge, motion and texture features in wavelet domain.


Science ◽  
2021 ◽  
Vol 372 (6539) ◽  
pp. eabf1941
Author(s):  
Sandipan Ray ◽  
Utham K. Valekunja ◽  
Alessandra Stangherlin ◽  
Steven A. Howell ◽  
Ambrosius P. Snijders ◽  
...  

Abruzzi et al. argue that transcriptome oscillations found in our study in the absence of Bmal1 are of low amplitude, statistical significance, and consistency. However, their conclusions rely solely on a different statistical algorithm than we used. We provide statistical measures and additional analyses showing that our original analyses and observations are accurate. Further, we highlight independent lines of evidence indicating Bmal1-independent 24-hour molecular oscillations.


2019 ◽  
Vol 57 (6) ◽  
pp. 93-99 ◽  
Author(s):  
Zhangbing Zhou ◽  
Yaqiang Zhang ◽  
Xuefang Yi ◽  
Chao Chen ◽  
Haodi Ping

2018 ◽  
Vol 2 (3) ◽  
Author(s):  
MoonSun Jung ◽  
Amanda J Russell ◽  
Catherine Kennedy ◽  
Andrew J Gifford ◽  
Kylie-Ann Mallitt ◽  
...  

Abstract Background The Myc oncogene family has been implicated in many human malignancies and is often associated with particularly aggressive disease, suggesting Myc as an attractive prognostic marker and therapeutic target. However, for epithelial ovarian cancer (EOC), there is little consensus on the incidence and clinical relevance of Myc aberrations. Here we comprehensively investigated alterations in gene copy number, expression, and activity for Myc and evaluated their clinical significance in EOC. Methods To address inconsistencies in the literature regarding the definition of copy number variations, we developed a novel approach using quantitative polymerase chain reaction (qPCR) coupled with a statistical algorithm to estimate objective thresholds for detecting Myc gain/amplification in large cohorts of serous (n = 150) and endometrioid (n = 80) EOC. MYC, MYCN, and MYCL1 mRNA expression and Myc activity score for each case were examined by qPCR. Kaplan–Meier and Cox-regression analyses were conducted to assess clinical significance of Myc aberrations. Results Using a large panel of cancer cell lines (n = 34), we validated the statistical algorithm for determining clear thresholds for Myc gain/amplification. MYC was the most predominantly amplified of the Myc oncogene family members, and high MYC mRNA expression levels were associated with amplification in EOC. However, there was no association between prognosis and increased copy number or gene expression of MYC/MYCN/MYCL1 or with a pan-Myc transcriptional activity score, in EOC, although MYC amplification was associated with late stage and high grade in endometrioid EOC. Conclusion A systematic and comprehensive analysis of Myc genes, transcripts, and activity levels using qPCR revealed that although such aberrations commonly occur in EOC, overall they have limited impact on outcome, suggesting that the biological relevance of Myc oncogene family members is limited to certain subsets of this disease.


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