Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

High frequency (HF) communications have an important role in long distances wireless communications. This frequency band is more important than VHF and UHF, as HF frequencies can cut longer distance with a single hopping. It has a low operation cost because it offers over-the-horizon communications without repeaters, therefore it can be used as a backup for satellite communications in emergency conditions. One of the main problems in HF communications is the prediction of the propagation direction and the frequency of optimum transmission (FOT) that must be used at a certain time. This paper introduces a new technique based on Oblique Ionosonde Station (OIS) to overcome this problem with a low cost and an easier way. This technique uses the

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Finite element modeling of transient temperature distribution is used to understand physical phenomena occurring during the dwell (penetration) phase and moving of welding tool in friction stir welding (FSW) of 5mm plate made of 7020-T53 aluminum alloy at 1400rpm and 40mm/min.
Thermocouples are used in locations near to the pin and under shoulder surface to study the welding tool penetration in the workpiece in advance and retreate sides along welding line in three positions (penetrate (start welding) , mid, pullout (end welding)).
Numerical results of ANSYS 12.0 package are compared to experimental data including axial load measurements at different tool rotational speeds (710rpm.900rpm.1120rpm and 1400rpm) Based on the experiment

Blades of gas turbine are usually suffered from high thermal cyclic load which leads to crack initiated and then crack growth and finally failure. The high thermal cyclic load is usually coming from high temperature, high pressure, start-up, shut-down and load change. An experimental and numerical analysis was carried out on the real blade and model of blade to simulate the real condition in gas turbine. The pressure, temperature distribution, stress intensity factor and the thermal stress in model of blade have been investigated numerically using ANSYS V.17 software. The experimental works were carried out using a particular designed and manufactured rig to simulate the real condition that blade suffers from. A new cont

Heat pipes and two‐phase thermosyphon systems are passive heat transfer systems that employ a two‐phase cycle of a working fluid within a completely sealed system. Consequently, heat exchangers based on heat pipes have low thermal resistance and high effective thermal conductivity, which can reach up to the order of (105 W/(m K)). In energy recovery systems where the two streams should be unmixed, such as airconditioning systems of biological laboratories and operating rooms in hospitals, heat pipe heat exchangers (HPHEs) are recommended. In this study, an experimental and theoretical study was carried out on the thermal performance of an air‐to‐air HPHE filled with two refrigerants as working fluids, R22 and R407c. The heat pipe he