The aim of our study is to solve a nonlinear epidemic model, which is the COVID-19 epidemic model in Iraq, through the application of initial value problems in the current study. The model has been presented as a system of ordinary differential equations that has parameters that change with time. Two numerical simulation methods are proposed to solve this model as suitable methods for solving systems whose coefficients change over time. These methods are the Mean Monte Carlo Runge-Kutta method (MMC_RK) and the Mean Latin Hypercube Runge-Kutta method (MLH_RK). The results of numerical simulation methods are compared with the results of the numerical Runge-Kutta 4th order method (RK4) from 2021 to 2025 using the absolute error, which proves that the MLH_RK method is the best and closest to the expected values. The results have been discussed after being tabulated and represented graphically. Epidemic behavior for the next two years until 2025 has been projected using the proposed methods.
The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time. Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 900 to 2700 step 900 directions. Then, we systematized each code word depending on its angle to involve four types of binary code books (i.e. Pour when , Flat when , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding procedure, with very small distortion per block, by designing s
... Show MoreInternet of Things (IoT) contributes to improve the quality of life as it supports many applications, especially healthcare systems. Data generated from IoT devices is sent to the Cloud Computing (CC) for processing and storage, despite the latency caused by the distance. Because of the revolution in IoT devices, data sent to CC has been increasing. As a result, another problem added to the latency was increasing congestion on the cloud network. Fog Computing (FC) was used to solve these problems because of its proximity to IoT devices, while filtering data is sent to the CC. FC is a middle layer located between IoT devices and the CC layer. Due to the massive data generated by IoT devices on FC, Dynamic Weighted Round Robin (DWRR)
... Show MoreBecause of cost-effective production and abundant resources of calcium, Ca-ion batteries (CIBs) are an appropriate option to alternate Li-ion batteries (LIBs). A new category of anode materials for CIBs has emerged since the successful synthesis of carbon nanotubes, which are B and N doped derivatives of it. For high-performance CIBs, BC2N nanotube (BC2NNT) has been studied as promising anode materials. In order to comprehend electrochemical attributes, cycling stability, and adsorption behavior of BC2NNT, first-principles computations have been executed. Based on nuclear magnetic resonance computations, two types of hexagonal rings (B2C2N2 (I) and BC4N (II)) were specified that are non-aromatic. Ca has adsorption on B2C2N2 and BC4N with ad
... Show MoreIn the present paper, three reliable iterative methods are given and implemented to solve the 1D, 2D and 3D Fisher’s equation. Daftardar-Jafari method (DJM), Temimi-Ansari method (TAM) and Banach contraction method (BCM) are applied to get the exact and numerical solutions for Fisher's equations. The reliable iterative methods are characterized by many advantages, such as being free of derivatives, overcoming the difficulty arising when calculating the Adomian polynomial boundaries to deal with nonlinear terms in the Adomian decomposition method (ADM), does not request to calculate Lagrange multiplier as in the Variational iteration method (VIM) and there is no need to create a homotopy like in the Homotopy perturbation method (H
... Show MoreBiodiesel as an attractive energy source; a low-cost and green synthesis technique was utilized for biodiesel preparation via waste cooking oil methanolysis using waste snail shell derived catalyst. The present work aimed to investigate the production of biodiesel fuel from waste materials. The catalyst was greenly synthesized from waste snail shells throughout a calcination process at different calcination time of 2–4 h and temperature of 750–950 ◦C. The catalyst samples were characterized using X-Ray Diffraction (XRD), Brunauer-Emmett-Teller (BET), Energy Dispersive X-ray (EDX), and Fourier Transform Infrared (FT-IR). The reaction variables varying in the range of 10:1–30:1 M ratio of MeOH: oil, 3–11 wt% catalyst loading, 50–
... Show MoreThe increasing amount of educational data has rapidly in the latest few years. The Educational Data Mining (EDM) techniques are utilized to detect the valuable pattern so that improves the educational process and to obtain high performance of all educational elements. The proposed work contains three stages: preprocessing, features selection, and an active classification stage. The dataset was collected using EDM that had a lack in the label data, it contained 2050 records collected by using questionnaires and by using the students’ academic records. There are twenty-five features that were combined from the following five factors: (curriculum, teacher, student, the environment of education, and the family). Active learning ha
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show MoreEnergy efficiency is a significant aspect in designing robust routing protocols for wireless sensor networks (WSNs). A reliable routing protocol has to be energy efficient and adaptive to the network size. To achieve high energy conservation and data aggregation, there are two major techniques, clusters and chains. In clustering technique, sensor networks are often divided into non-overlapping subsets called clusters. In chain technique, sensor nodes will be connected with the closest two neighbors, starting with the farthest node from the base station till the closest node to the base station. Each technique has its own advantages and disadvantages which motivate some researchers to come up with a hybrid routing algorit
... Show MoreThe application of the test case prioritization method is a key part of system testing intended to think it through and sort out the issues early in the development stage. Traditional prioritization techniques frequently fail to take into account the complexities of big-scale test suites, growing systems and time constraints, therefore cannot fully fix this problem. The proposed study here will deal with a meta-heuristic hybrid method that focuses on addressing the challenges of the modern time. The strategy utilizes genetic algorithms alongside a black hole as a means to create a smooth tradeoff between exploring numerous possibilities and exploiting the best one. The proposed hybrid algorithm of genetic black hole (HGBH) uses the
... Show MoreA sensitive film was manufactured Holokravaa using plastic materials the a Akougl substantive Amaid with poly alcohol Funnell addition to sensitive material Daakromat ammonium were obtained registry Qakma to diffraction efficiency of 83%