Image processing analysis of sigmoidal Hadamard wavelet with PCA to detect hidden object

Innovative tactics are employed by terrorists to conceal weapons and explosives to perpetrate violent attacks, accounting for the deaths of millions of lives every year and contributing to huge economic losses to the global society. Achieving a high threat detection rate during an inspection of crowds to recognize and detect threat elements from a secure distance is the motivation for the development of intelligent image data analysis from a machine learning perspective. A method proposed to reduce the image dimensions with support vector, linearity and orthogonal. The functionality of CWD is contingent upon the plenary characterization of fusion data from multiple image sensors. The proposed method combines multiple sensors by hybrid fusion of sigmoidal Hadamard wavelet transform and PCA basis functions. Weapon recognition and the detection system, using Image segmentation and K means support vector machine A classifier is an autonomous process for the recognition of threat weapons regardless of make, variety, shape, or position on the suspect’s body despite concealment

Analysis of variance anova and correlation matrix for m-learning among university students

This study attempts to find out students' expectations from mobile learning (m-learning) applications. A questionnaire on students' preferences in m-learning applications was used). The data of this report were collected from the primary sources in the Institute of Computational Mathematics and Information Technologies - Department of Programming Technologies between 20th of February and 25th of March 2017. The Research survey was conducting among students of higher institutions in Kazan Russia in (Kazan federal university). A self-administered questionnaire was designed and distributed to the research population in question to obtain quick and direct responses. The survey involved a distribution of a total of 135 questionnaires after seeking the consent of the respondents out of which 124 were correctly filled and analyzed. Correlation Matrix, Chi Square, Symmetric Measures test, Simple Linear Regression was done in this study, Analysis of Variance ANOVA analysis was used on the collected data. The results showed that the availability and easy usage of mobile applications are among the most preferred characteristics of applications. Surprisingly, entertaining feature was the least expected feature by students

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population