In this paper, we estimate the survival function for the patients of lung cancer using different nonparametric estimation methods depending on sample from complete real data which describe the duration of survivor for patients who suffer from the lung cancer based on diagnosis of disease or the enter of patients in a hospital for period of two years (starting with 2012 to the end of 2013). Comparisons between the mentioned estimation methods has been performed using statistical indicator mean squares error, concluding that the survival function for the lung cancer by using shrinkage method is the best
Let be an n-Banach space, M be a nonempty closed convex subset of , and S:M→M be a mapping that belongs to the class mapping. The purpose of this paper is to study the stability and data dependence results of a Mann iteration scheme on n-Banach space
The paired sample t-test for testing the difference between two means in paired data is not robust against the violation of the normality assumption. In this paper, some alternative robust tests have been suggested by using the bootstrap method in addition to combining the bootstrap method with the W.M test. Monte Carlo simulation experiments were employed to study the performance of the test statistics of each of these three tests depending on type one error rates and the power rates of the test statistics. The three tests have been applied on different sample sizes generated from three distributions represented by Bivariate normal distribution, Bivariate contaminated normal distribution, and the Bivariate Exponential distribution.
Measuring goat weight on a farm is carried out by two methods. The first method conventionally measures the chest girth (CG) and body length (BL), while the second is performed using a scale. This study aimed to facilitate the CG and BL measurements to estimate goat weight more efficiently through image processing. The endpoints of CG and BL were determined automatically using binary large object (BLOB) segmentation. The images of 120 goats were taken at three different shooting distances of 50 cm, 70 cm, and 90 cm. The statistical testing of the three scenarios in this study explained that the ideal distance to take pictures is the basis for determining whether or not the size of the circumference and BL is appropriate as a fea
... Show MoreThe deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p
... Show MoreToday, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate
... Show MoreThis paper discusses estimating the two scale parameters of Exponential-Rayleigh distribution for singly type one censored data which is one of the most important Rights censored data, using the maximum likelihood estimation method (MLEM) which is one of the most popular and widely used classic methods, based on an iterative procedure such as the Newton-Raphson to find estimated values for these two scale parameters by using real data for COVID-19 was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. The duration of the study was in the interval 4/5/2020 until 31/8/2020 equivalent to 120 days, where the number of patients who entered the (study) hospital with sample size is (n=785). The number o
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