The internet of medical things (IoMT), which is expected the lead to the biggest technology in worldwide distribution. Using 5th generation (5G) transmission, market possibilities and hazards related to IoMT are improved and detected. This framework describes a strategy for proactively addressing worries and offering a forum to promote development, alter attitudes and maintain people's confidence in the broader healthcare system without compromising security. It is combined with a data offloading system to speed up the transmission of medical data and improved the quality of service (QoS). As a result of this development, we suggested the enriched energy efficient fuzzy (EEEF) data offloading technique to enhance the delivery of data transmission at the original targeted location. Initially, healthcare data was collected. Preprocessing is achieved by the normalization method. An EEEF data offloading scheme is proposed. A fruit fly optimization (FFO) technique is utilized. The performance metrics such as energy consumption, delay, resource utilization, scalability, and packet loss are analyzed and compared with existing techniques. The future scope will make use of a revolutionary optimization approach for IoMT.
Abstract: Aluminum alloys grade 6061-T6 are characterized by their excellent properties and processing characteristics which make them ideal for varieties of industrial applications under cyclic loading, aluminum alloys show less fatigue life than steel alloys of similar strength. In the current study, a nanosecond fiber laser of maximum pulse energy up to 9.9 mJ was used to apply laser shock peening process (LSP) on aluminum thin sheets to introduce residual stresses in order to enhance fatigue life under cyclic loading Box-Behnken design (BBD) based on the design of experiments (DOE) was employed in this study for experimental design data analysis, model building and optimization The effect of working parameters spot size (ω), scannin
... Show MoreThe process of coordination and joint cooperation between SAIs and internal auditors in the public sector is considered one of the very important matters in performing efficient audits and are of high quality, especially if this coordination and cooperation is implemented in accordance with international standards, as it leads to avoiding duplication in auditing work. And the distribution of work in a distribution that achieves the objectives of auditing in general and is of general benefit to the economic unit.
The research problem lies in the weakness of the relationship between internal auditing and external auditing as a result of not applying INTOSAI Standard (9150) coordination and joint cooperation
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul
... Show MorePlagiarism is becoming more of a problem in academics. It’s made worse by the ease with which a wide range of resources can be found on the internet, as well as the ease with which they can be copied and pasted. It is academic theft since the perpetrator has ”taken” and presented the work of others as his or her own. Manual detection of plagiarism by a human being is difficult, imprecise, and time-consuming because it is difficult for anyone to compare their work to current data. Plagiarism is a big problem in higher education, and it can happen on any topic. Plagiarism detection has been studied in many scientific articles, and methods for recognition have been created utilizing the Plagiarism analysis, Authorship identification, and
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This paper explores a fuzzy-logic based speed controller of an interior permanent magnet synchronous motor (IPMSM) drive based on vector control. PI controllers were mostly used in a speed control loop based field oriented control of an IPMSM. The fundamentals of fuzzy logic algorithms as related to drive control applications are illustrated. A complete comparison between two tuning algorithms of the classical PI controller and the fuzzy PI controller is explained. A simplified fuzzy logic controller (FLC) for the IPMSM drive has been found to maintain high performance standards with a much simpler and less computation implementation. The Matlab simulink results have been given for different mechanical operating conditions. The simulated
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