The interest in green energy in recent years is very noticeable, as this energy is a very important alternative that can replace fuel in many applications, most notably electric power generation, so work must be done to develop a form of this energy such as wind energy by working on the development of turbines. The DMST method provided by Qblade software is an integrated tool for making a simulation of a vertical axis wind turbine (VAWT). The simulation was carried out on vertical axis wind turbines, designing turbine blades according to symmetrical NACA0018, and calculating some parameters such as power, torque and power coefficient. It is found that this type of turbine can be improved by treating the blade edges that cont

Poultry often intake energy to meet their energy needs, which is associated with both more fat and protein deposition, which is also conditioned by the presence of adequate other nutritional nutrients. The most significant supplement in creature sustenance or diets is protein, with exceptional thought given to the proportion among energy and protein in consumes less calories (energy: protein ratio EPR). This implies that a specific protein level relates with the fundamental measure of energy in the eating regimen. The article evaluated the manipulation of energy to protein ratio and its effect on broiler performance and carcass lipid profile. The author's methodology depends on analyzing and comparing other scientists’ studies and work

Wireless Body Area Sensor Network (WBASN) is gaining significant attention due to its applications in smart health offering cost-effective, efficient, ubiquitous, and unobtrusive telemedicine. WBASNs face challenges including interference, Quality of Service, transmit power, and resource constraints. Recognizing these challenges, this paper presents an energy and Quality of Service-aware routing algorithm. The proposed algorithm is based on each node's Collaboratively Evaluated Value (CEV) to select the most suitable cluster head (CH). The Collaborative Value (CV) is derived from three factors, the node's residual energy, the distance vector between nodes and personal device, and the sensor's density in each CH. The CEV algorithm operates i

This research presents results on the full energy peak efficiency of a high purity germanium (HPGe) detector from point source as a function of photon energy and source-detector distance. The directions of photons emitted from the source and the photon path lengths in the detector were determined by Monte Carlo technique. A major advantage of this technique is the short computation time compared to the experiments. Another advantage is the flexibility for inputting detector-related parameters (such as source–detector distance, detector radius, length and attenuation coefficient) into the algorithm developed, thus making it an easy and flexible method to apply to other detector systems and configurations. It has been designed and writte

Inefficient wastewater disposal and wastewater discharge problems in water bodies have led to increasing pollution in water bodies.  Pollutants in the river contribute to increasing the biological oxygen demand (BOD), total suspended solids (SS), total dissolved solids (TDS), chemical oxygen demand (COD), and toxic metals render this water unsuitable for consumption and even pose a significant risk to human health. Over the last few years, water conservation has been the subject of growing awareness and concern throughout the world, so this research focused on review studies of researches that studied the importance of water quality of wastewater treated disposal in water bodies and modern technology to management w

      The present paper concern with minimax shrinkage estimator technique in order to estimate Burr X distribution shape parameter, when prior information about the real shape obtainable as original estimate while known scale parameter.

 Derivation for Bias Ratio, Mean squared error and the Relative Efficiency equations.

 Numerical results and conclusions for the expressions mentioned above were displayed. Comparisons for proposed estimator with most recent works were made.

In the last decades, using mineral admixture in concrete became very necessary to improve concrete properties and reduce CO₂ emissions associated with the cement production process. Subsequently, more sustainable concrete can be obtained.  Ternary blended cement containing two different types of mineral admixture can achieve ambitious steps in this trend. In this research, the synergic effects of mineral admixtures in ternary blended cement and its effects on concrete fresh properties, strength, durability, and efficiency factors of mineral admixture in ternary blended cement, were reviewed. The main conclusion reached after reviewing many literature pieces is that the concrete with ternary blended cement

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and