scholarly journals Stress-Strength Parameter Estimation under Small Sample Size: A Testing Hypothesis Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Hassan Alsuhabi ◽  
Mohammad Mehdi Saber ◽  
M. M. Abd El-Raouf
Keyword(s):  
Sample Size ◽  
Small Sample Size ◽  
Asymptotic Properties ◽  
Large Data ◽  
Small Sample ◽  
Strength Parameter ◽  
Unbiased Test ◽  
Distribution Of Components ◽  
Strength Models ◽  
Almost All

In this paper, uniformly most powerful unbiased test for testing the stress-strength model has been presented for the first time. The end of the paper is recommending a method which is appropriate for no large data where a normal asymptotic distribution is not applicable. The previous methods for inference on stress-strength models use almost all the asymptotic properties of maximum likelihood estimators. The distribution of components is considered exponential and generalized logistic. A corresponding unbiased confidence interval is constructed, too. We compare presented methodology with previous methods and show the method of this paper is logically better than other methods. Interesting result is that our recommended method not only uses from small sample size but also has better result than other ones.

scholarly journals Patch Based Collaborative Representation with Gabor Feature and Measurement Matrix for Face Recognition

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Zhengyuan Xu ◽  
Yu Liu ◽  
Mingquan Ye ◽  
Lei Huang ◽  
Hao Yu ◽  
...  
Keyword(s):  
Face Recognition ◽  
Sample Size ◽  
Small Sample Size ◽  
Large Data ◽  
Linear Representation ◽  
Small Sample ◽  
Collaborative Representation ◽  
Measurement Matrix ◽  
Gabor Feature ◽  
The Impact

In recent years, sparse representation based classification (SRC) has emerged as a popular technique in face recognition. Traditional SRC focuses on the role of the l1-norm but ignores the impact of collaborative representation (CR), which employs all the training examples over all the classes to represent a test sample. Due to issues like expression, illumination, pose, and small sample size, face recognition still remains as a challenging problem. In this paper, we proposed a patch based collaborative representation method for face recognition via Gabor feature and measurement matrix. Using patch based collaborative representation, this method can solve the problem of the lack of accuracy for the linear representation of the small sample size. Compared with holistic features, the multiscale and multidirection Gabor feature shows more robustness. The usage of measurement matrix can reduce large data volume caused by Gabor feature. The experimental results on several popular face databases including Extended Yale B, CMU_PIE, and LFW indicated that the proposed method is more competitive in robustness and accuracy than conventional SR and CR based methods.

scholarly journals Lineage analysis of human papillomavirus type 39 in cervical samples of Iranian women

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Neda Hosseini ◽  
Zabihollah Shoja ◽  
Arash Arashkia ◽  
Amir-Hossein Khodadadi ◽  
Somayeh Jalilvand
Keyword(s):  
Sample Size ◽  
Small Sample Size ◽  
Small Sample ◽  
Long Control Region ◽  
E6 Gene ◽  
Sequence Variations ◽  
Geographical Regions ◽  
Hpv Types ◽  
Almost All ◽  
Larger Sample

Abstract Background The data with regards to the regional variants of distinct HPV types is of great value. Accordance with this, this study aimed to investigate the sequence variations of E6 gene and long control region of HPV 39 among normal, premalignant and malignant cervical samples in order to characterize the frequent HPV 39 variants circulating in Tehran, Iran. Methods In total, 70 cervical samples (45 normal, 16 premalignant, and 9 malignant samples) infected with HPV 39 were analyzed by nested-PCR and sequencing. Results Our results revealed that all samples belonged to A lineage. Almost all sequences (98.6%) were classified in A1 sublineage and only one sample (1.4%) was A2 sub lineage. Conclusions Our findings showed that lineages A, sublineage A1, is dominant in Tehran, Iran. However, the small sample size was the most important limitations of this study. Further studies with larger sample size from different geographical regions of Iran are necessary to estimate the pathogenicity risk of HPV 39 variants in this population.

Application of Ultrasound Elastography for Assessing Intestinal Fibrosis in Inflammatory Bowel Disease: Fiction or Reality?

2020 ◽  
Vol 21 ◽  
Author(s):  
Roberto Gabbiadini ◽  
Eirini Zacharopoulou ◽  
Federica Furfaro ◽  
Vincenzo Craviotto ◽  
Alessandra Zilli ◽  
...  
Keyword(s):  
Inflammatory Bowel Disease ◽  
Sample Size ◽  
Bowel Disease ◽  
Small Sample Size ◽  
Shear Wave Elastography ◽  
Small Sample ◽  
Ultrasound Elastography ◽  
Invasive Technique ◽  
Intestinal Fibrosis ◽  
Inflammatory Bowel

Background: Intestinal fibrosis and subsequent strictures represent an important burden in inflammatory bowel disease (IBD). The detection and evaluation of the degree of fibrosis in stricturing Crohn’s disease (CD) is important to address the best therapeutic strategy (medical anti-inflammatory therapy, endoscopic dilation, surgery). Ultrasound elastography (USE) is a non-invasive technique that has been proposed in the field of IBD for evaluating intestinal stiffness as a biomarker of intestinal fibrosis. Objective: The aim of this review is to discuss the ability and current role of ultrasound elastography in the assessment of intestinal fibrosis. Results and Conclusion: Data on USE in IBD are provided by pilot and proof-of-concept studies with small sample size. The first type of USE investigated was strain elastography, while shear wave elastography has been introduced lately. Despite the heterogeneity of the methods of the studies, USE has been proven to be able to assess intestinal fibrosis in patients with stricturing CD. However, before introducing this technique in current practice, further studies with larger sample size and homogeneous parameters, testing reproducibility, and identification of validated cut-off values are needed.

scholarly journals Confirming known planetary trends using a photometrically selected Kepler sample

2020 ◽  
Author(s):  
Jonah T Hansen ◽  
Luca Casagrande ◽  
Michael J Ireland ◽  
Jane Lin
Keyword(s):  
Sample Size ◽  
Robust Statistics ◽  
Narrow Band ◽  
Small Sample Size ◽  
Small Sample ◽  
Fitting Algorithm ◽  
Statistical Studies ◽  
The Rich ◽  
Host Stars ◽  
High Metallicity

Abstract Statistical studies of exoplanets and the properties of their host stars have been critical to informing models of planet formation. Numerous trends have arisen in particular from the rich Kepler dataset, including that exoplanets are more likely to be found around stars with a high metallicity and the presence of a “gap” in the distribution of planetary radii at 1.9 R⊕. Here we present a new analysis on the Kepler field, using the APOGEE spectroscopic survey to build a metallicity calibration based on Gaia, 2MASS and Strömgren photometry. This calibration, along with masses and radii derived from a Bayesian isochrone fitting algorithm, is used to test a number of these trends with unbiased, photometrically derived parameters, albeit with a smaller sample size in comparison to recent studies. We recover that planets are more frequently found around higher metallicity stars; over the entire sample, planetary frequencies are 0.88 ± 0.12 percent for [Fe/H] < 0 and 1.37 ± 0.16 percent for [Fe/H] ≥ 0 but at two sigma we find that the size of exoplanets influences the strength of this trend. We also recover the planet radius gap, along with a slight positive correlation with stellar mass. We conclude that this method shows promise to derive robust statistics of exoplanets. We also remark that spectrophotometry from Gaia DR3 will have an effective resolution similar to narrow band filters and allow to overcome the small sample size inherent in this study.

scholarly journals The use of diversity indices for local assessment of marine sediment quality

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shinya Hosokawa ◽  
Kyosuke Momota ◽  
Anthony A. Chariton ◽  
Ryoji Naito ◽  
Yoshiyuki Nakamura
Keyword(s):  
Community Structure ◽  
Sample Size ◽  
Small Sample Size ◽  
Benthic Communities ◽  
Sediment Quality ◽  
Diversity Indices ◽  
Small Sample ◽  
Species Density ◽  
Local Case ◽  
Two Indices

AbstractDiversity indices are commonly used to measure changes in marine benthic communities. However, the reliability (and therefore suitability) of these indices for detecting environmental change is often unclear because of small sample size and the inappropriate choice of communities for analysis. This study explored uncertainties in taxonomic density and two indices of community structure in our target region, Japan, and in two local areas within this region, and explored potential solutions. Our analysis of the Japanese regional dataset showed a decrease in family density and a dominance of a few species as sediment conditions become degraded. Local case studies showed that species density is affected by sediment degradation at sites where multiple communities coexist. However, two indices of community structure could become insensitive because of masking by community variability, and small sample size sometimes caused misleading or inaccurate estimates of these indices. We conclude that species density is a sensitive indicator of change in marine benthic communities, and emphasise that indices of community structure should only be used when the community structure of the target community is distinguishable from other coexisting communities and there is sufficient sample size.

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