Investigation regarding queue length dynamics have been explored using various kinds of models including ordinary differential equations (ODEs). ODEs possess the advantageous property of having a continuous-time representation of queue length dynamics, thus its adoption in this article in modelling various scenarios as system of first-order ODEs. Specifically, a multi-server queue is considered and a numerical approach for solving first-order ODEs using MATLAB is adopted to obtain approximate solutions of the resultant models. The results display the dynamics of the queue length in each scenario, thus showing the usefulness of ODEs in analysing the behaviour of queues using system of ODEs.

Semiconductor laser is used in processing many issues related to the scientific, military, medical, industrial and agricultural fields due to its unique properties such as coherence and high strength where GaN-based components are the most efficient in this field. Current technological developments mention to the strong connection of GaN with sustainable electronic and optoelectronic devices which have high-efficiency. The threshold current density of Al0.1Ga0.9N/GaN triple quantum well laser structure was investigated to determine best values of the parameters affecting the threshold current density that are well width, average thickness of active region, cavity length, reflectivity of cavity mirrors and optical confinement factor. The opt

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

Chemotherapy is one of the most efficient methods for treating cancer patients. Chemotherapy aims to eliminate cancer cells as thoroughly as possible. Delivering medications to patients’ bodies through various methods, either oral or intravenous is part of the chemotherapy process. Different cell-kill hypotheses take into account the interactions of the expansion of the tumor volume, external drugs, and the rate of their eradication. For the control of drug usage and tumor volume, a model based smooth super-twisting control (MBSSTC) is proposed in this paper. Firstly, three nonlinear cell-kill mathematical models are considered in this work, including the log-kill, Norton-Simon, and hypotheses subject to parametric uncertainties and exo

Lagrange series and the Bessel function are two classical methods that were created by series expanding from Taylor series. In this paper, the purpose of those two methods was to find the values of the eccentric anomaly for one period (0–360)°. The Matlab program is used to apply the results, the input parameters were eccentricity (0–1), mean anomaly (0–360)°, and finally the parameter W (1–13). The program does not need a tolerance to obtain a precise value for eccentric anomaly like other iterative and non-iterative methods to stop the program; it will stop after completing the required period from 0° to 360° for a body that is determined by the solver. The output will be the final value of the eccentric anomaly. Furthermore,