This study's primary goal is to examine the characteristics of public university canteen food service. A saying goes, "Health is riches." Therefore, it not only helps them to clear their minds but also enables them to focus on their studies, families, and careers. A model was created from the information that was provided and tested using information from a survey that was carried out at a college in northwest Pennsylvania. The findings imply that staff behavior, food quality, and price are the three key factors that affect student satisfaction. Cleanliness, responsiveness, and environment are further important factors. Considering these factors (food quality, food variety, price justice, ambiance, etc.) could help people in charge of food services provide more value and satisfaction to improve students' entire educational experience.
When it comes to making assessments about public health, the mortality rate is a very important factor. The COVID-19 pandemic has exacerbated well-known biases that affect the measurement of mortality, which varies with time and place. The COVID-19 pandemic took the world off surveillance, and since the outbreak, it has caused damage that many would have thought unthinkable in the present era. By estimating excess mortality for 2020 and 2021, we provide a thorough and consistent evaluation of the COVID-19 pandemic's effects. Excess mortality is a term used in epidemiology and public health to describe the number of fatalities from all causes during a crisis that exceeds what would be expected under 'normal' circumstances. Excess mortality has been used for thousands of years to estimate health emergencies and pandemics like the 1918 "Spanish Flu"6. Positive excess mortality occurs when actual deaths exceed previous data or recognized patterns. It could demonstrate how a pandemic affects the mortality rate. The estimates of positive excess mortality presented in this research are generated using the procedure, data, and methods described in detail in the Methods section and briefly summarized in this study. We explored different regression models in order to find the most effective factor for our estimates. We predict the pandemic period all-cause deaths in locations lacking complete reported data using the Poisson, Negative Binomial count framework. By overdispersion test, we checked the assumption of the Poisson model, and then we chose the negative binomial as a good fitting model for this analysis through Akaike Information Criteria (AIC) and Standardized residual plots, after that checking the P-value<0.05; we found some significant predictors from our choosing model Negative binomial model, and the coefficient of all predictors gave the information that some factors have a positive effect, and some has a negative effect at positive excess mortality at COVID-19 (2020-2021).
In this work, we studied convergence rates using quotient convergence factors and root convergence factors, as described by Ortega and Rheinboldt, for Hestenes’ Gram–Schmidt conjugate direction method without derivatives. We performed computations in order to make a comparison between this conjugate direction method, for minimizing a nonquadratic function f, and Newton’s method, for solving ∇f=0. Our primary purpose was to implement Hestenes’ CGS method with no derivatives and determine convergence rates.
Breast cancer is the most lethal form of cancer that can strike women anywhere in the world. The most complex and tough undertaking in order to lower the death rate is the process of predicting a patient's likelihood of survival following breast cancer surgery. Due to the fact that this survival prediction is linked to the life of a woman, effective algorithms are required for the purpose of making the prognosis. It is of the utmost importance to accurately predict the survival status of patients who will have breast cancer surgery since this shows whether or not doing surgery is the actual approach for the specific medical scenario. Given the gravity of the situation, it is impossible to overstate how important it is to investigate new and improved methods of prediction in order to guarantee an accurate assessment of the patient's chances of survival. In this paper, we collect data and examine some models based on the survival of patients who underwent breast cancer surgery. The goal of this research is to evaluate the forecasting performance of various classification models, including the Linear regression model, logistic regression analysis, LDA, QDA, KNN, ANN, and Decision Tree. The results of the experiment on this dataset demonstrate the better performance of the came up with ANN approach, with an accuracy of 82.98 percent.
The purpose of this research is to learn more about women in Bangladesh and their perceptions of career options and job satisfaction. Women's labor force participation has increased dramatically in Bangladesh, as it has in many other developing countries. But despite these improvements, women still face several roadblocks in the workplace. Women's professional development and job happiness can be aided by policies and environments that take into account the unique obstacles they confront. The study uses a Univariate, Bivariate, and multivariate method, collecting information through both quantitative surveys and qualitative interviews. Participants are professional women from a wide range of fields in Bangladesh. Quantitative surveys analyze issues including work-life balance, gender bias, education status, women's violence in the job sector, support from family members, promotion prospects, and job satisfaction. The qualitative interviews dive more deeply into the women's lived experiences, shedding light on the difficulties they face and the strategies they use to overcome them. The study has both theoretical and practical significance. For practical purposes, this research will improve our understanding of the most significant obstacles to women's careers and participation in development processes and the most effective ways to overcome them. This paper will also be useful as a source of information for feminist groups and other organizations with the goal to advance women's rights and equality.
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