This paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA)) for measureing the closeness between curves. Root Mean Square Errors is used for the implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables model, results are more preferable than the independent response method. The models are demonstrated by both a simulation data and real data.
Using the Internet, nothing is secure and as we are in need of means of protecting our data, the use of passwords has become important in the electronic world. To ensure that there is no hacking and to protect the database that contains important information such as the ID card and banking information, the proposed system stores the username after hashing it using the 256 hash algorithm and strong passwords are saved to repel attackers using one of two methods: -The first method is to add a random salt to the password using the CSPRNG algorithm, then hash it using hash 256 and store it on the website. -The second method is to use the PBKDF2 algorithm, which salts the passwords and extends them (deriving the password) before being ha
... Show MoreStructural buildings consist of concrete and steel, and these buildings have confronted many challenges from various aggressive environments against the materials manufactured from them. It contains high water levels and buildings whose concrete cover may be damaged and thus lead to the deterioration and corrosion of steel. It was important to have an alternative to steel, such as the glass fiber reinforced polymer (GFRP), which is distinguished by its great effectiveness in resisting corrosion, as well as its strong tensile resistance. Still, one of its drawbacks is that it has a low modulus of elasticity. This research article aims to conduct a numerical study using the nonlinear fi
Local and global bifurcations of food web model consists of immature and mature preys, first predator, and second predator with the current of toxicity and harvesting was studied. It is shown that a trans-critical bifurcation occurs at the equilibrium point
Cholelithiasis is one of the commonest surgical problems and one of the most common gastrointestinal diseases throughout the world but its pathogenesis remains unclear. Many theories have been proposed forward to explain the mechanism of stone formation. It is not fully clear if symptomatic gallstone disease is associated with a specific pattern of some biochemical abnormalities, as lipid profile and fasting blood sugar in serum of patients.
This study was designed to estimate lipid profile and fasting blood sugar in the sera of patients with cholelithiasis in comparison with normal individuals (control).
In this study, 104(male=16, female=88) were symptomatic gallstone patients (aged 42.79± 12.18 years), and 38(male=6
... Show MoreThe interplay of predation, competition between species and harvesting is one of the most critical aspects of the environment. This paper involves exploring the dynamics of four species' interactions. The system includes two competitive prey and two predators; the first prey is preyed on by the first predator, with the former representing an additional food source for the latter. While the second prey is not exposed to predation but rather is exposed to the harvest. The existence of possible equilibria is found. Conditions of local and global stability for the equilibria are derived. To corroborate our findings, we constructed time series to illustrate the existence and the stability of equilibria numerically by varying the different values
... Show MoreEsculin (ESCN) is used in the pharmaceutical industry with intravenous effect, stimulant and anti-inflammatory capillaries, like vitamin P. It is a significant component of many anti-inflammatory remedies such as esqusan, esflazid and anavenol [14]. It is also found in numerous other remedies available in the market such as proctosone, anustat, and ariproct.
To determine experimental conditions, to elucidate retention behavior of esculin in HILIC mode. Moreover, to suggest new ways to separate and determinate esculin in ointments.
Two hydrophilic c
Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
... Show MoreLinear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in