In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained for each subpopulation as a vector distribution. The numerical outputs are tabulated, graphed, and compared with previous statistical estimations for 2013, 2015, and 2030, respectively. The solutions of FD and MMCFD are found to be in good agreement with small standard deviation of the means, and small measure of difference. The new MMCFD method is useful to predict intervals of random distributions for the numerical solutions of this epidemiology model with better approximation and agreement between existing statistical estimations and FD numerical solutions.
Alongside the development of high-speed rail, rail flaw detection is of great importance to ensure railway safety, especially for improving the speed and load of the train. Several conventional inspection methods such as visual, acoustic, and electromagnetic inspection have been introduced in the past. However, these methods have several challenges in terms of detection speed and accuracy. Combined inspection methods have emerged as a promising approach to overcome these limitations. Nondestructive testing (NDT) techniques in conjunction with artificial intelligence approaches have tremendous potential and viability because it is highly possible to improve the detection accuracy which has been proven in various conventional nondestr
... Show MoreThere are many ways to communicate a story, one can tell it, sing it, act it, write it, film it and can draw it. Each form of storytelling has its unique characteristics that separate it from the other forms. These distinguishing characteristics of each form does not indicate the superiority of one form over the other, on the contrary, it indicates the human ability to be creative on many levels. As students of literature, only the written form of a story is taken into account. One reason for the negligence of other forms of storytelling might be that singing and filming a story is not related to literature. But there has been a form of storytelling that uses words along with pictures which eventually became a genre of novels called grap
... Show MoreMachine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show MoreThe purpose of this paper is to develop a hybrid conceptual model for building information modelling (BIM) adoption in facilities management (FM) through the integration of the technology task fit (TTF) and the unified theory of acceptance and use of technology (UTAUT) theories. The study also aims to identify the influence factors of BIM adoption and usage in FM and identify gaps in the existing literature and to provide a holistic picture of recent research in technology acceptance and adoption in the construction industry and FM sector.
The research aims to achieve a set of objectives, the most important of which is determining the extent to which the auditors of the research sample in the Federal Bureau of Financial Supervision adhere to the requirements of the quality control system according to the Iraqi Audit Manual No. The federal financial / research sample with the quality control system according to the Iraqi audit guide No. 7), and the researcher seeks to test the main research hypothesis and sub-hypotheses, and to achieve this, a questionnaire was designed by (Google Form) and distributed electronically to the elements of the research sample, Through the statistical package program (SPSS), the results of the questionnaire were analysed. In light of the applied
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The current research included " Diagnosis of the reality of the gap for the requirements of Business Continuity Management System According to International Standard (ISO 22301: 2012) in Midland Refineries Company (Daura Refinery) " , for development of an administrative system for Business Continuity is considered a priority in the present day, and in the light of the organizations dependence on computers and information technology in work and communication with others . the international legitimacy (represented by the international organization for standardization (ISO)) remains the basis for matching and commitment , and the importance of the application of Business Continuity Management Syst
... Show MoreThe key objective of the study is to understand the best processes that are currently used in managing talent in Australian higher education (AHE) and design a quantitative measurement of talent management processes (TMPs) for the higher education (HE) sector.
The three qualitative multi-method studies that are commonly used in empirical studies, namely, brainstorming, focus group discussions and semi-structured individual interviews were considered. Twenty