The rapid and enormous growth of the Internet of Things, as well as its widespread adoption, has resulted in the production of massive quantities of data that must be processed and sent to the cloud, but the delay in processing the data and the time it takes to send it to the cloud has resulted in the emergence of fog, a new generation of cloud in which the fog serves as an extension of cloud services at the edge of the network, reducing latency and traffic. The distribution of computational resources to minimize makespan and running costs is one of the disadvantages of fog computing. This paper provides a new approach for improving the task scheduling problem in a Cloud-Fog environment in terms of execution time(makespan) and operating costs for Bag-of-Tasks applications. A task scheduling evolutionary algorithm has been proposed. A single custom representation of the problem and a uniform intersection are built for the proposed algorithm. Furthermore, the individual initialization and perturbation operators (crossover and mutation) were created to resolve the inapplicability of any solution found or reached by the proposed evolutionary algorithm. The proposed ETS (Evolutionary Task Scheduling algorithm) algorithm was evaluated on 11 datasets of varying size in a number of tasks. The ETS outperformed the Bee Life (BLA), Modified Particle Swarm (MPSO), and RR algorithms in terms of Makespan and operating costs, according to the results of the experiments.
Abstract
Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model
In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe
... Show MoreThe method of incineration was chosen to treat the most commonly used antimicrobial agents in Iraq (Triclabendazol, Oxfendazol, Mebendazole), which are antibiotics for children. The moisture content and chemical oxygen demand (COD) were examined and the results were (93.34, 94.88, 92.97)%, (52000, 33200, and 64000) mg/ L. The temperature was determined as a variable in the burning process (600, 500, 400)° C for the purpose of calculating the loss of ignition LOI and determining the ideal temperature. The results of the models (Triclabendazol, Oxfendazol, Mebendazole) (94.92, 93.12, 58.81% and 88.87), (62.61, 44.08%, 98.75, 84.98 and 55.086)% respectively. When mixing the three models in equal proportions, the percentage of loss was 92.8
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Business organizations are using the technological innovations like cloud computing (CC) as a developmental platform in order to improve the performance of their information systems. In that context, our paper discusses know-how in employing the public and private CC to serve as platforms to develop the evaluation system of annual employees' performance (ESAEP) at Iraqi universities. Therefore, we ask the paper question which is “Is it possible to adopt the innovative solutions of ICTs (Like: public and private CC) for finding the developmental vision about management information systems at business organizations?”. In addition, the paper aim
... Show MoreThe estimation of the parameters of linear regression is based on the usual Least Square method, as this method is based on the estimation of several basic assumptions. Therefore, the accuracy of estimating the parameters of the model depends on the validity of these hypotheses. The most successful technique was the robust estimation method which is minimizing maximum likelihood estimator (MM-estimator) that proved its efficiency in this purpose. However, the use of the model becomes unrealistic and one of these assumptions is the uniformity of the variance and the normal distribution of the error. These assumptions are not achievable in the case of studying a specific problem that may include complex data of more than one model. To
... Show MoreThroughout Agriculture has mostly relied on the use of natural fertilizers throughout human history, which are compounds that increase the nitrogen levels in the soil. Modern agriculture was made possible by the introduction of synthetic fertilizers at the end of the 19th centuryproduction of agriculture. Their application enhanced crop yields and sparked an agricultural revolution unlike anything the world had ever seen.In the near future, synthetic fertilizers are anticipated to continue to have a significant impa ct on human life, both positively and negatively. They are frequently utilized for producing all t ypes of crops and are essential to plant growth. The significance of synthetic fertilizers is their ability to provide the soil w
... Show MoreThis study aims to studying of Person and organization’s environment fit in a sample of Private bank’s reflection in its basic dimensions (Person-organization fit ,Person-Job fit, Person-group fit and Person- Person-fit )in the Work Outcomes (job satisfaction, the intention to leave the job, Job Engagement, and organizational citizenship behavior ).
The questionnair’e has been used as a basic instrument to gather data , As well as personal interviews with some of the staff of the research sample of private banks which were represented by (5) and included banks (Bank of Assyria for investment, the North Bank for Finance and Investment , Bank of the Tigris
... Show MoreThe research problem can be summarized through focusing on the environment that surrounds students and class congestion, how these factors affect directly or indirectly the academic achievement of students, how these factors affect understanding the scientific material that the student receives in this physical environment, how classroom’s components such as seats, space With which the student can move, the number of students in the same class, the lighting, whether natural or artificial, and is this lighting sufficient or not enough, the nature of the wall paint old or modern, is it comfortable for sight, the blackboard if it is Good or exhausted, In addition to air-conditioning sets in summer and winter, this is on the on
... Show MoreMost of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
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