<p>The 5G technology is predicted to achieve the unoptimized millimeter Wave (mmWave) of 30-300 GHz bands. This unoptimized band because of the loss of mm-Wave bands, like path attenuation and propagation losses. Nonetheless, because of: (i) directional transmission paving way for beamforming to recompense for the path attenuation, and (ii) sophisticated placement concreteness of the base stations (BS) is the best alternative for array wireless communications in mmWave bands (that is to say 100-150 m). The advance in technology and innovation of unmanned aerial vehicles (UAVs) necessitates many opportunities and uncertainties. UAVs are agile and can fly all complexities if the terrains making ground robots unsuitable. The UAV may be managed either independently through aboard computers or distant controlled of a flight attendant on pulverized wireless communication links in our case 5G. Although a fast algorithm solved the problematic aspect of beam selection for 2-dimensional scenarios. This paper presents 3-dimensional scenarios for UAV. We modeled beam selection with environmental responsiveness in millimeter Wave UAV to accomplish close optimum assessments on the regular period through learning from the available situation.</p>

In recent years, the IoT) Internet of Things (IoT) allows devices to connect to the Internet that has become a promising research area mainly due to the constant emerging of the dynamic improvement of technologies and their associated challenges. In an approach to solve these challenges, fog computing came to play since it closely manages IoT connectivity. Fog-Enabled Smart Cities (IoT-ESC) portrays equitable energy consumption of a 7% reduction from 18.2% renewable energy contribution, which extends resource computation as a great advantage. The initialization of IoT-Enabled Smart Grids including (FESC) like fog nodes in fog computing, reduced workload in Terminal Nodes services (TNs) that are the sensors and actuators of the Internet of Things (IoT) set up. This paper proposes an integrated energy-efficiency model computation about the response time and delays service minimization delay in FESC. The FESC gives an impression of an auspicious computing model for location, time, and delay-sensitive applications supporting vertically -isolated, service delay, sensitive solicitations by providing abundant, ascendable, and scattered figuring stowage and system associativity. We first reviewed the persisting challenges in the proposed state-of-the models and based on them. We introduce a new model to address mainly energy efficiency about response time and the service delays in IoT-ESC. The iFogsim simulated results demonstrated that the proposed model minimized service delay and reduced energy consumption during computation. We employed IoT-ESC to decide autonomously or semi-autonomously whether the computation is to be made on Fog nodes or its transfer to the cloud.

Barium hexaferrite (BaFe12O19) has dominated many aspects of technology, serving as a permanent magnet, magnetoelectric, multiferroic, and electric motors, generators, microwave devices, and drug delivery systems. There is a challenge in the synthesis of BaFe12O19 with the coprecipitation method. As a result, research is conducted to examine the factors influencing the properties of BaFe12O19 during the preparation process, specifically on the drying temperature of the mixture. The precursors were precipitated, through some procedural steps, along with stirring at 450 rpm at a certain temperature for a while and simultaneously pouring the precipitant dropwise; the sample was dried at different temperatures. The final samples were annealed at the same rate of temperature within the same time interval. The results depicted that drying at different temperatures leads to the variation in the magnetic and microstructural properties of BaFe12O19, indicating that drying at high temperatures resulted in high coercivity with low saturated magnetization.