Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

The study was reflection of the impact of the widespread use of polymer Novolak composite reinforced  Glass fiber and Asbestos fiber once again with weight fraction 60% on the physical properties, which included (Hardness, Compressive deformation, compressive modulus of elasticity, Flexural modulus of elasticity, Resilience modulus, the maximum of Flexural strength, Flexural strain energy and Shear strength inner layers); it is known how much important the media as a source of bacterial contamination, which contributes directly or indirectly in the process of aging of these materials. These Novolak composite reinforced,  prepared by weight fraction of (10%) and (14%) of the Hexamethylene-tetraamine (HMTA) hardener material. It

This research is devoted to investigate relationship between both Ultrasonic Pulse Velocity and Rebound Number (Hammer Test) with cube compressive strength and also to study the effect of steel reinforcement on these relationships.
A study was carried out on 32 scale model reinforced concrete elements. Non destructive testing campaign (mainly ultrasonic and rebound hammer tests) made on the same elements. About 72 concrete cubes (15 X 15 X15) were taken from the concrete mixes to check the compressive strength.. Data analyzed.Include the possible correlations between non destructive testing (NDT) and compressive strength (DT) Statistical approach is used for this purpose. A new relationships obtained from correlations results is give

In this study, an experimental investigation had conducted for six high strength laced reinforced concrete one-way slabs to discover the behavior of laced structural members after being exposed to fire flame (high temperature). Self-compacted concrete (SCC) had used to achieve easy casting and high strength concrete. All the adopted specimens were identical in their compressive strength of ( , geometric layout 2000 750 150 mm and reinforcement specifics except those of lacing steel content, three ratios of laced steel reinforcement of (0.0021, 0.0040 and 0.0060) were adopted. Three specimens were fired with a steady state temperature of  for two hours duration and then after the specimens were cooled suddenly by spraying water. The

Nowadays, the use of recycled waste construction materials instead of aggregates is becoming popular in construction owing to its environmental benefits. This paper presents an experimental and analytical campaign to study the behavior of axially loaded columns constructed from recycled aggregates. The latter was used instead of natural aggregates, and they were collected from the waste of previous concrete constructions. Different concrete mixtures made from varying amounts of recycled aggregates ranged from 0 to 50% of the total coarse aggregate were conducted to achieve 28 MPa. The effect of steel fibers is another investigated variable with volumes ranged from 0 to 2% concerning concrete’s mixture. The experimental

Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia