Wireless Multimedia Sensor Networks (WMSNs) are a type of sensor network that contains sensor nodes equipped with cameras, microphones; therefore the WMSNS are able to   produce multimedia data such as video and audio streams, still images, and scalar data from the surrounding environment. Most multimedia applications typically produce huge volumes of data, this leads to congestion. To address this challenge, This paper proposes Modify Spike Neural Network control for Traffic Load Parameter with Exponential Weight of Priority Based Rate Control algorithm (MSNTLP with EWBPRC). The Modify Spike Neural Network controller (MSNC) can calculate the appropriate traffi

Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic propert

In this paper, isobutane (R-600a) is used as a suitable substitute for (R-134a) when changing the length of capillary tube. And the experimental data on capillary tube are obtained under different conditions such as (subcooling and ambient temperatures) on domestic refrigerator (9ft3 size), this data shows that (R-600a) a suitable substitute for (R134a) .The test presented a model for a steady state, two-phase flow in capillary tube for vapour compression system .The numerical model depends on conservation equations (mass, energy and momentum) as wall as the equation of state for refrigerant. The solution methodology was implemented by using finite difference techniques. The system results indicate that it is possible to change the refri

Low-temperature stratification, high-volumetric storage capacity, and less-complicated material processing make phase-changing materials (PCMs) very suitable candidates for solar energy storage applications. However, their poor heat diffusivities and suboptimal containment designs severely limit their decent storage capabilities. In these systems, the arrangement of tubes conveying the heat transport fluid (HTF) plays a crucial role in heat communication between the PCM and HTF during phase transition. This study investigates a helical coil tube-and-shell thermal storage system integrated with a novel central return tube to enhance heat transfer effectiveness. Three-dimensional computational fluid dynamics simulations compare the proposed d

    Heat exchanger is an important device in the industry for cooling or heating process. To increase the efficiency of heat exchanger, nanofluids are used to enhance the convective heat . transfer relative to the base fluid. - Al2O3/water nanofluid is used as cold stream in the shell and double concentric tube heat exchanger counter current to the hot stream basis oil. These nanoparticles were of particle size of 40 nm and it was mixed with a base fluid (water) at volume
concentrations of 0.002% and 0.004%. The results showed that each of Nusselt number and overall heat transfer coefficient increased as nanofluid concentrations increased. The pressure drop of nanofluid increased slightly than the base fluid because

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat