Convection heat transfer in a horizontal channel provided with metal foam blocks of two numbers of pores per unit of length (10 and 40 PPI) and partially heated at a constant heat flux is experimentally investigated with air as the working fluid. A series of experiments have been carried out under steady state condition. The experimental investigations cover the Reynolds number range from 638 to 2168, heat fluxes varied from 453 to 4462 W/m², and Darcy number 1.77x10^-5, 3.95x10^-6. The measured data were collected and analyzed. Results show that the wall temperatures at each heated section are affected by the imposed heat flux variation, Darcy number, and Reynolds number variation. The var

This paper reports an experimental study regarding the influence of vertical oscillations on the natural convection heat transfer from a vertical channel. An experimental set-up was constructed and calibrated; the vertical channel was tested in atmosphere at 25o
C. The channel-to-ambient temperature difference was varied with the power supply to the electrical heater ranging between
15W to 70W divided into five levels. Data sets were measured under different operating condition from a test rig under six vibrating velocities (VVs) levels ranging from (5-30 m/s) in addition to the stationary state. The results show that the maximum heat transfer enhancement factor (E) occurs at Rayleigh number (Ra=2.328×103 ) and vibrational Reynol

     Intelligent systems can be used to build systems that simulate human behavior. One such system is lip reading. Hence, lip reading is considered one of the hardest problems in image analysis, and thus machine learning is used to solve this problem, which achieves remarkable results, especially when using a deep neural network, in which it dives deeply into the texture of any input. Microlearning is the new trend in E-learning. It is based on small pieces of information to make the learning process easier and more productive. In this paper, a proposed system for multi-layer lip reading is presented. The proposed system is based on micro content (letters) to achieve the lip reading process using deep learning and auto-correction mo

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

    In this paper, we studied the scheduling of  jobs on a single machine.  Each of n jobs is to be processed without interruption and becomes available for processing at time zero. The objective is to find a processing order of the jobs, minimizing the sum of maximum earliness and maximum tardiness. This problem is to minimize the earliness and tardiness values, so this model is equivalent to the just-in-time production system. Our lower bound depended on the decomposition of the problem into two subprograms. We presented a novel heuristic approach to find a near-optimal solution for the problem. This approach depends on finding efficient solutions for two problems. The first problem is minimizing total completi

In this research, has been to building a multi objective Stochastic Aggregate Production Planning model for General al Mansour company Data with Stochastic  demand under changing of market and uncertainty environment in aim to draw strong production plans.  The analysis to derive insights on management issues regular and extra labour costs and the costs of maintaining inventories and good policy choice under the influence medium and optimistic adoption of the model of random has adoption form and had adopted two objective functions total cost function (the core) and income and function for a random template priority compared with fixed forms with objective function and the results showed that the model of two phases wit

This research presents a numerical study to simulate the heat transfer by forced convection as a result of fluid flow inside channel’s with one-sided semicircular sections and fully filled with porous media. The study assumes that the fluid were Laminar , Steady , Incompressible and inlet Temperature was less than Isotherm temperature of a Semicircular sections .Finite difference techniques were used to present the governing equations (Momentum, Energy and Continuity). Elliptical Grid is Generated using Poisson’s equations . The Algebraic equations were solved numerically by using (LSOR (.This research studied the effect of changing the channel shapes on fluid flow and heat transfer  in two cases ,the first: cha

          In this paper, we have investigated some of the most recent energy efficient routing protocols for wireless body area networks. This technology has seen advancements in recent times where wireless sensors are injected in the human body to sense and measure body parameters like temperature, heartbeat and glucose level. These tiny wireless sensors gather body data information and send it over a wireless network to the base station. The data measurements are examined by the doctor or   physician and the suitable cure is suggested. The whole communication is done through routing protocols in a network environment. Routing protocol consumes energy while helping non-stop communic

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha