Let R-n be the set of all rational functions of the type r(z) = f (z)/w(z) , , where f (z) is a polynomial of degree at most n and w(z) =Pi(n)(j=1) (z - a(j)) ,|a(j)| > 1 for 1 <= j <= n . In this paper, we extend some famous results concerning to the growth of polynomials by T. J. Rivlin, A. Aziz and others to the rational functions with prescribed poles and thereby obtain the analogous results for such rational functions with restricted zeros.
A new probability model for positively skewed datasets like economic data, medical, engineering and other sciences was developed in this paper. The new distribution is named the Topp-Leone Flexible Weibull distribution and it was generated using the Topp-Leone-G family of distributions. This new distribution has three parameters and it is very flexible in fitting several and different datasets. Its basic mathematical properties were studied and the method of maximum likelihood estimation was used for the estimation of model parameters. A real life dataset was used to illustrate the flexibility of the distribution and it was found that the new model provides a better fit to real life datasets than the Topp Leone Burr XII, Topp Leone Lomax and Exponentiated Generalized Flexible Weibull distributions.
The present article examines the effect of weakening the value of the national currency and macroeconomic indicators by considering the political effects of sanctions on stock prices and the SVAR structural self-regression model for the years 1370-1397. According to the SVAR estimates, an 89 percent increase in oil revenue will boost the stock price index, as well as a financial crisis and sanctions, a weakening of the national currency and a production gap of 11, 86, respectively. 53 and 12 percent of the stock price index, also based on the results of immediate reaction functions, the shocks received by endogenous variables up to the first two periods; it goes up and then goes down. In terms of economic structure and the principles of economics, a steady rise in the dollar will lead to economic prosperity and a decrease in the stock price index, but if this increase is temporary, the economic boom in the stock market will not be observed. In general, due to the different infrastructures, patterns and economic conditions of the country, a separate study of how the Iranian stock market is affected by the uncertainty of government monetary policy, government fiscal policy and government foreign exchange policy can be in the country's major decisions. Provide an accurate view of how Iran's financial market is changing as a result of these fluctuations.
The goal of any profit organization is to bolster its revenue by providing useful suggestions to its customer base. In order to achieve this, vast research is being undertaken by companies such as Netflix and Amazon on their Recommendation Systems and providing users with choices, they are most likely to click on. The purpose of this paper is to provide a holistic view of types of Recommendation Engines and how they are implemented, scaled and can provide a basis for revenue generation. The focus would be to implement a Recommendation Engine on PySpark using the ALS (Alternate Least Square) method. Besides, Neo-4j and Cypher query language for implementing recommendations on a graph database and analyzing how heterogeneous information can be levied to tackle the infamous cold start problem in recommender engines would be explored. The dataset used for analysis is the Group-lens 100K Movie-lens dataset and the algorithm is implemented to best fit the dataset. Further, an in-depth comparison of several techniques has been carried out on the basis of different metrics, hyper-parameter selection and the number of epochs used. The claims have been justified by evaluating the performance of the model depending on the different use cases, thus aiding in predictive analytics of the movie, as per the interest of the customer using visualization tools.
The matrix-variate generalized hyperbolic distribution is heavy-tailed mixed continuous skewed probability distribution. This distribution has multi applications in the field of economics, risk management, especially in stock modeling. This paper includes the estimate of the location matrix theta for the multivariate partial linear regression model, which is one of the multivariate semiparametric regression models when the random error follows a matrix-variate generalized hyperbolic distribution in the Bayesian technique depending on non-informative and informative prior information, estimating the location matrix under balanced and unbalanced loss function and the shape parameters (lambda, psi, nu), skewness matrix (delta), the scale matrix (Sigma) are known. In addition, estimation the smoothing parameter by a proposed method depending on the rule of thumb, the proposed kernel function depending on the mixed Gaussian kernel. the researchers concluded when non-informative and informative prior information is available that the posterior probability distribution for the location matrix theta is a matrix-variate generalized hyperbolic distribution, through the experimental side, it was found that the proposed kernel function is overriding than the Gaussian kernel function in estimate the location matrix and under informative prior information.
In this paper, we investigated the performance of Bayesian Computational methods for estimating the parameters of the multinomial Logistic regression model. We discussed two of the most common Bayesian computational algorithms: the Random walk Metropolis-Hastings (RWM) and Slice algorithms and their application to estimating the parameters of the addiction model as well as comparing the performance of these algorithms using the mean square error (MSE) criterion. The results revealed that the performance of the algorithms is excellent, with a slight superiority to the RWM algorithm.
In this paper, we introduced the estimation of parameters for distributions that have multi-double truncation by the maximum likelihood method. We depended in the applied study on data of disease of Covid-19 by using one double truncation. Some statistical data were analyzed and unknown parameters and were compared with some distribution.
The variety of weighted Average techniques that fall within the structure of exploratory data analysis (EDA) has driven a diversity of competitive results of data analysis. In spite of this variation, the outcomes obtained from the Hanning procedure have some similarities, which makes judging and analysis of data are difficult somehow. Many searches were attitude to get the best performance of technique to give a kind of satisfaction for the researchers who work on the area of EDA. The proposed method is based on calculating the weighted average by applying geometric and harmonic mean to be compared with the existing technique that uses the arithmetic mean. The application of the proposal techniques is done on daily financial data in Malaysia that issues Sukuk of funds in Islamic banking and financial business. The results of applying the proposed techniques on real data sets showed a competitive performance for these standards in the field of comparison of techniques undergoing the smoothing procedures.
The current analysis employs the Riccati and modified simple equation methods to retrieve new optical solitons for highly dispersive nonlinear Schrodinger-type equation (NLSE). With cubic-quintic-septic law (also known as a polynomial) of refractive index and perturbation terms having cubic nonlinearity, 1-optical solitons in the form of hyperbolic, periodic, and rational are derived. the two schemes offer an influential mathematical tool for solving NLSEs in various areas of applied sciences.
SARS-CoV-2 and the consequential COVID-19 virus is one of the major concerns of the 21st century. Pertaining to the novelty of the disease, it became necessary to discover the efficacy of deep learning techniques in the quick and consistent discovery of COVID-19 based on chest X-ray and CT scan image analysis. In this related work, Prognostic tool using regression was designed for patients with COVID-19 and recognizing prediction patterns to make available important prognostic information on mortality or severity in COVID-19 patients. And reliable convolutional neural network (CNN) architecture models (DenseNet, VGG16, ResNet, Inception Net)to institute whether it would work preeminent in terms of accuracy as well as efficiency with image datasets with Transfer Learning. CNN with Transfer Learning were functional to accomplish the involuntary recognition of COVID-19 from numerary chest X-ray and CT scan images. The experimental results emphasize that selected models, which is formerly broadly tuned through suitable parameters, executes in extensive levels of COVID-19 discovery against pneumonia or normal or lung opacity through the precision of up to 87% for X-Ray and 91% intended for CT scans. © 2022, Semnan University, Center of Excellence in Nonlinear Analysis and Applications. All rights reserved.
In this paper, a class of harmonic univalent functions has been studied by using q-analogue of the derivative operator for complex harmonic functions. We have obtained a sufficient condition, a representation theorem for this harmonic univalent functions class and some other geometric properties.
In this paper, we introduce a new 2-parameters family of distributions named [0,1] Truncated Inverse Weibull - G family ([0,1] TIW-G) family, to generate new types of continues distributions. A special model namely, [0,1] Truncated Inverse Weibull Rayleigh distribution ([0,1] TIWR) distribution is considered and defined and some of the statistical properties are derived. Parameter's estimations using MLE method is provided and a simulation is given to determine the accuracy of the method used above. To demonstrate the utility of the distribution in nowday's applications, we explore and investigate the death rates of COVID-19 in Iraq in the period from 14 December 2020 to 30 April 2021.
In this paper, (h(1), h(2))-convex and s-convex functions are merged to form (h(1), h(2), s)-convex function. Inequalities of the Hermite-Hadamard (H-H) and Fejer's types will then be extended by using the (h(1), h(2), s)-convex function and its derivatives. Some special cases for these extended H-H and Fejer's inequalities are also explored in order to get the previously specified results. The relationship between newly constructed Hermite-Hadamard (H - H) and Fejer's types of inequalities with the average (mean) values are also discussed.
One of the goals of financial institutions is to strengthen the economic infrastructure in developing the financial sphere. In this regard, financial institutions should take the necessary planning to increase their incomes, and if they do not pay attention, the consequences can be predicted for this group of economic activists Increasing income and reducing the risk of bankruptcy are among the most important goals for financial institutions and enterprises. Therefore, considering the increase of income and the integration approach based on the selection of partners in the field of banking, this paper presents a mathematical model based on reducing the risk of bankruptcy. The multi-objective genetic algorithm method has been used to solve and optimize the model. The proposed method was implemented on real data related to ten Iranian banks and the results led to the formation of a financial firm with a combination of banks to maximize the income and minimize the bankruptcy risk.
The paper deals with two different aspects of wavelet frames. First, we obtain a necessary condition on irregular wavelet frames on local fields of positive characteristic and in the second aspect, we present some results on the perturbation of wavelet frames, when we disturb the mother function of a wavelet frame or dilation parameter. All the results have been carried without the compactness of support neither on generating function nor on its Fourier transform.
A new probability model for positively skewed datasets like economic data, medical, engineering and other sciences was developed in this paper. The new distribution is named the Marshall Olkin Topp Leon Exponential distribution and it was generated using the Marshall Olkin Topp Leon-G family of distributions. It has three parameters and it is very flexible in fitting several and different datasets. Its basic mathematical properties were studied and two methods like maximum likelihood estimation via Gray Wolf optimization and Conjugate Gradient used for the estimation of model parameters. A real-life dataset was used to illustrate the flexibility of the distribution and it was found that the new model provides a better fit to real-life datasets than other distributions.
In this paper, we review some research works on exploring image processing in digital spaces using fixed point theorems. The basic concepts of digital images are mentioned. Moreover, we prove some theorems on digital metric spaces by replacing the conditions in the previously established theorem with a suitable condition.
Phenomena depending on their past history or their past state have received more importance. The mathematical models of these phenomena can be described by differential equations of a hereditary or a self-referred type. This paper is devoted to study the solvability of a state-dependent or self-referred integral equation via Chandrasekhar kernel. The investigation of this problem is motivated by the results from, Eder [10], Feckan [11] and Buica [3] who initiated the study of state dependent differential equations. Here, the existence and the uniqueness of the solution of this state-dependent integral equation via Chandrasekhar kernel have been discussed. The data dependency of the solution on some functions has been studied.
In this paper, we proposed and studied a delayed HIV pathogenesis model with saturation incidence, both virus-to -cell and cell-to-cell transmission. We address the basic reproduction number R0, the characteristic equations, and local stability of feasible equilibria are established. Where the delay incorporates both virus-to-cell and cell-to-cell transmission. Moreover, we discuss the existence of Hopf Bifurcation when a delay is used as a bifurcation parameter. Numerical simulations are performed to satisfy our theoretical results.
The line graph of the graph Gamma denoted by L(Gamma) is a graph with a vertex set consists of the sets of edges of Gamma and two vertices are adjacent in L(Gamma) if they are incident in Gamma. In this article, we discuss and determine the effect of operations on the line graphs of simple graphs.
