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.
The paper present design of a control structure that enables integration of a Kinematic neural controller for trajectory tracking of a nonholonomic differential two wheeled mobile robot, then proposes a Kinematic neural controller to direct a National Instrument mobile robot (NI Mobile Robot). The controller is to make the actual velocity of the wheeled mobile robot close the required velocity by guarantees that the trajectory tracking mean squire error converges at minimum tracking error. The proposed tracking control system consists of two layers; The first layer is a multi-layer perceptron neural network system that controls the mobile robot to track the required path , The second layer is an optimization layer ,which is impleme
... Show MoreAqueous extract of poppy plant) Papaver nudicaule) with five concentrations (50, 100, 150, 200 and 250) mg/l were used to anesthetize fingerlings of the common carp Cyprinus carpio (Mean total length 8.91 ± 0.31 cm and mean total weight 7.72 ± 1.19 gm) instead of the traditional use of MS-222. Results showed that extracted solution of poppy have partial and overall anesthesia effect on these fishes with inverse relationship between the concentrations used and the time needed to reach partial and overall anesthesia, and also direct relationship between concentrations used and time needed for fish recovery. Best results were obtained by using a concentration of 250 mg/l, where time for partial anesthesia was 8 ± 1.52 m
... Show MoreThe importance of this research comes from the possibility of achieving positive interaction between accounting and tax through the interest in setting accounting standards and adapting them to local tax legislation, as the adoption of the application of the international standard (IAS 12) for income taxes helps to measure and determine the base for income tax and may lead to an increase in the tax outcome. Through the reliance of enterprises on many accounting bases, and that the tax administration in Iraq depends on the element of personal judgment in determining the tax base, which leads to lack of objectivity in determining the tax outcome, as the impact of the accounting standard (IAS 12) on the tax base and tax outcome is one of th
... Show MoreStructural and optical properties were studied as a function of Nano membrane after prepared, for tests. Nano membrane was deposited by the spray coating method on substrates (glass) of thickness 100 mm. The X-ray diffraction spectra of (CNTs, WO3) were studied. AFM tests are good information about the roughness, It had been designed electrolysis cell and fuel cell. Studies have been performed on electrochemical parameters.
As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec
... Show MoreAnomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the
... Show MoreThe method binery logistic regression and linear discrimint function of the most important statistical methods used in the classification and prediction when the data of the kind of binery (0,1) you can not use the normal regression therefore resort to binary logistic regression and linear discriminant function in the case of two group in the case of a Multicollinearity problem between the data (the data containing high correlation) It became not possible to use binary logistic regression and linear discriminant function, to solve this problem, we resort to Partial least square regression.
In this, search the comparison between binary lo
... Show MoreModern trends have appeared recently in educational thought that call for the achievement of the outcomes of the educational process. Some of these trends are the development of individual thinking skills, considering the individual differences, and learning basic skills. The five-year learning cycle is one of these models. It is called as five-year learning cycle because it passes through five stages. These five stages are: (operate - discover - clarify - expand – Evaluate), which make the learner as the main axis for activating thinking processes. This can be done by organizing study materials through research, investigation, and identifying concepts by himself, as in learning sports skills that depend on motor performance and teamwork,
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