Application of the Kolmogorov-Smirnov test for the recognition of gray-scale templates

1997 ◽  
Author(s):  
Josep Ferre-Borrull ◽  
Santiago Vallmitjana ◽  
Salvador Bosch ◽  
Xavier Fernandez
Keyword(s):  
Gray Scale ◽  
Kolmogorov Smirnov ◽  
Smirnov Test

Age dependency of the diabetes effects on the iris recognition systems performance evaluation results

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohammadreza Azimi ◽  
Seyed Ahmad Rasoulinejad ◽  
Andrzej Pacut
Keyword(s):  
Iris Recognition ◽  
Recognition Task ◽  
Aging Effect ◽  
Recognition System ◽  
Health Condition ◽  
Age Dependency ◽  
Biometric Systems ◽  
Kolmogorov Smirnov ◽  
Recognition Systems ◽  
Smirnov Test

AbstractIn this paper, we attempt to answer the questions whether iris recognition task under the influence of diabetes would be more difficult and whether the effects of diabetes and individuals’ age are uncorrelated. We hypothesized that the health condition of volunteers plays an important role in the performance of the iris recognition system. To confirm the obtained results, we reported the distribution of usable area in each subgroup to have a more comprehensive analysis of diabetes effects. There is no conducted study to investigate for which age group (young or old) the diabetes effect is more acute on the biometric results. For this purpose, we created a new database containing 1,906 samples from 509 eyes. We applied the weighted adaptive Hough ellipsopolar transform technique and contrast-adjusted Hough transform for segmentation of iris texture, along with three different encoding algorithms. To test the hypothesis related to physiological aging effect, Welches’s t-test and Kolmogorov–Smirnov test have been used to study the age-dependency of diabetes mellitus influence on the reliability of our chosen iris recognition system. Our results give some general hints related to age effect on performance of biometric systems for people with diabetes.

Multifractal characterization of mechanical vibration signals through improved empirical mode decomposition-based detrended fluctuation analysis

2016 ◽  
Vol 231 (22) ◽  
pp. 4139-4149 ◽  
Author(s):  
Du Wenliao ◽  
Guo Zhiqiang ◽  
Gong Xiaoyun ◽  
Xie Guizhong ◽  
Wang Liangwen ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Intrinsic Mode Functions ◽  
Vibration Signals ◽  
Multifractal Detrended Fluctuation Analysis ◽  
Mode Decomposition ◽  
Kolmogorov Smirnov ◽  
Detrended Fluctuation ◽  
Smirnov Test

A novel multifractal detrended fluctuation analysis based on improved empirical mode decomposition for the non-linear and non-stationary vibration signal of machinery is proposed. As the intrinsic mode functions selection and Kolmogorov–Smirnov test are utilized in the detrending procedure, the present approach is quite available for contaminated data sets. The intrinsic mode functions selection is employed to deal with the undesired intrinsic mode functions named pseudocomponents, and the two-sample Kolmogorov–Smirnov test works on each intrinsic mode function and Gaussian noise to detect the noise-like intrinsic mode functions. The proposed method is adaptive to the signal and weakens the effect of noise, which makes this approach work well for vibration signals collected from poor working conditions. We assess the performance of the proposed procedure through the classic multiplicative cascading process. For the pure simulation signal, our results agree with the theoretical results, and for the contaminated time series, the proposed method outperforms the traditional multifractal detrended fluctuation analysis methods. In addition, we analyze the vibration signals of rolling bearing with different fault types, and the presence of multifractality is confirmed.

scholarly journals Relationship between oral habits and spirometry maneuvers, in children

Revista CEFAC ◽  
2018 ◽  
Vol 20 (1) ◽  
pp. 37-43
Author(s):  
Rafaela Coelho Minsky ◽  
Tayná Castilho ◽  
Roseane Rebelo Silva Meira ◽  
Tatiana Godoy Bobbio ◽  
Camila Isabel Santos Schivinski
Keyword(s):  
Healthy Children ◽  
Chi Square ◽  
Cross Sectional ◽  
Public And Private ◽  
Oral Habits ◽  
Qualitative Variables ◽  
Chi Square Test ◽  
Kolmogorov Smirnov ◽  
Thumb Sucking ◽  
Smirnov Test

ABSTRACT Purpose: to analyze whether deleterious oral habits can influence the number of attempts of forced spirometry maneuvers performed by healthy children. Methods: this observational and cross-sectional analytical study included 149 healthy children aged 6-12 years attending public and private schools in Florianópolis, SC, Brazil. A validated protocol was applied for the analysis of deleterious oral habits. The children were grouped according to the number of spirometry maneuvers needed to achieve successful spirometry results, as follows: G1) children who needed 3 maneuvers; G2) 4 maneuvers; G3) 5-8 maneuvers. Data were analyzed with the Kolmogorov-Smirnov test and the Kruskal-Wallis test was applied to compare quantitative variables between the groups. The Chi-square test was used to assess the association between the groups and qualitative variables. Results: there was no association between the number of attempts and the qualitative variables evaluated by the protocol. There was also no difference between the groups regarding quantitative variables for breastfeeding time, breastfeeding occurrence, use of pacifiers, and thumb sucking. Conclusion: the presence of DOH did not influence the number of forced spirometry maneuvers, performed by the healthy children in this study.

Investigation of The Nutritional Approaches of Student Athletes During The Covid-19 Epidemic

2021 ◽  
Vol 15 (7) ◽  
pp. 1940-1944
Author(s):  
Sevcan Altun ◽  
Aykut Aksu ◽  
Osman Imamoglu ◽  
Murat Erdogdu ◽  
Kursat Karacabey
Keyword(s):  
Student Athletes ◽  
Eating Habits ◽  
T Test ◽  
Outbreak Period ◽  
Significant Difference ◽  
Package Program ◽  
Kolmogorov Smirnov ◽  
The Subject ◽  
The University ◽  
Smirnov Test

The aim of this study is to investigate the nutritional approaches of student athletes studying at the university during the coronavirus outbreak period. Participants consisted of students studying and doing sports at the University. 446 students, 246 males and 200 females, participated in the study. Besides the personal form, students were filled the questionnaire testing questionnaire. Students voluntarily participated. The surveys were done on social media. Nutritional habits questionnaire consists of 12 questions. In the preparation of the survey questions, the questions proved validity of the researches which have been done on the subject before have been used. SPSS 23.00 package program was used in statistical analyses. Kolmogorov-Smirnov test was performed to test whether the data was normally distributed and it was determined that the data showed normal distribution. Independent t-test, paired t-test, unidirectional variance analysis and LSD tests were used in statistical operations. There was no significant difference in students' nutrition approaches by gender, both in the pre-outbreak period and in the outbreak period points (p> 0.05). Nutrition scores were significantly increased during the outbreak period (p <0.001). A significant difference was found between the students who felt bad before the epidemic and those who felt well before the epidemic and their nutritional scores according to the levels they felt (p <0.05). A significant difference was found between the pre-outbreak period and post-epidemic nutrition scores of the sports faculty students (p <0.05). During the coronavirus epidemic, university student athletes have either increased their nutritional opportunities or have changed their eating habits positively to keep their immune systems strong or both. The fact that sports faculty students have better nutrition compared to other faculty students can be attributed to their taking courses in nutrition, health and similar. It is recommended to give lectures or seminars on nutrition to athlete students. Keywords: Student, Nutrition, Sports Nutrition, Nutritional Approach, Covid-19

scholarly journals Estimation of a closed population size of tadpoles in temporary pond

2017 ◽  
Vol 78 (2) ◽  
pp. 328-336
Author(s):  
M. S. C. S. Lima ◽  
J. Pederassi ◽  
C. A. S. Souza
Keyword(s):  
Population Size ◽  
Bayes Theorem ◽  
Venn Diagram ◽  
Temporary Pond ◽  
Larval Phase ◽  
Closed Population ◽  
Lotic Environment ◽  
Capture Recapture ◽  
Kolmogorov Smirnov ◽  
Smirnov Test

Abstract The practice of capture-recapture to estimate the diversity is well known to many animal groups, however this practice in the larval phase of anuran amphibians is incipient. We aimed at evaluating the Lincoln estimator, Venn diagram and Bayes theorem in the inference of population size of a larval phase anurocenose from lotic environment. The adherence of results was evaluated using the Kolmogorov-Smirnov test. The marking of tadpoles for later recapture and methods measurement was made with eosin methylene blue. When comparing the results of Lincoln-Petersen estimator corresponding to the Venn diagram and Bayes theorem, we detected percentage differences per sampling, i.e., the proportion of sampled anuran genera is kept among the three methods, although the values are numerically different. By submitting these results to the Kolmogorov-Smirnov test we have found no significant differences. Therefore, no matter the estimator, the measured value is adherent and estimates the total population. Together with the marking methodology, which did not change the behavior of tadpoles, the present study helps to fill the need of more studies on larval phase of amphibians in Brazil, especially in semi-arid northeast.

scholarly journals Data-Driven Treatment Pathways Mining for Early Breast Cancer Using cSPADE Algorithm and System Clustering

2020 ◽  
Author(s):  
Qing Yang ◽  
Ting Luo ◽  
Wei Zhang ◽  
Xiaorong Zhong ◽  
Ping He ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Treatment ◽  
Early Breast Cancer ◽  
Breast Cancer Treatment ◽  
Breast Cancer Patients ◽  
Treatment Pathways ◽  
Kolmogorov Smirnov ◽  
System Clustering ◽  
Sequence Rules ◽  
Smirnov Test

Abstract Background: Due to the multidimensional, multilayered, and chronological order of the cancer data in this study, it was challenging for us to extract treatment paths. Therefore, it was necessary to design a new data mining scheme to effectively extract the treatment path of breast cancer. To determine whether the cSPADE algorithm and system clustering proposed in this study can effectively identify the treatment pathways for early breast cancer. Methods: We applied data mining technology to the electronic medical records of 6891 early breast cancer patients to mine treatment pathways. We provided a method of extracting data from EMR and performed three-stage mining: determining the treatment stage through the cSPADE algorithm → system clustering for treatment plan extraction → cSPADE mining sequence pattern for treatment. The Kolmogorov-Smirnov test and correlation analysis were used to cross-validate the sequence rules of early breast cancer treatment pathways.Results: We unearthed 55 sequence rules for early breast cancer treatment, 3 preoperative neoadjuvant chemotherapy regimens, 3 postoperative chemotherapy regimens, and 2 chemotherapy regimens for patients without surgery. Through 5-fold cross-validation, Pearson and Spearman correlation tests were performed. At the significance level of P <0.05, all correlation coefficients of support, confidence and lift were greater than 0.89. Using the Kolmogorov-Smirnov test, we found no significant differences between the sequence distributions.Conclusions: The cSPADE algorithm combined with system clustering can achieve hierarchical and vertical mining of breast cancer treatment models. By uncovering the treatment pathways of early breast cancer patients by this method, the real-world breast cancer treatment behavior model can be evaluated, and it can provide a reference for the redesign and optimization of the treatment pathways.

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