Proved the validity of all mixtures or not to accept the bees and then resistant infection worm wax Minor has accepted honey bee colonies all mixtures beeswax with paraffin wax industrial all ratios used made ??of a mixture to DVD waxy full and used naturally in breeding Houdnth In store honey and pollen evendiversified Bravian and natural wax

Bee keping projects is one of the most important agricltural investment projects because it generate profit in a short period . In addition to the multiplicity of products and other benefits . Research aimed at study the feasibility of two projects one hand in the origin of the Al – Mashrok since 2006 , kicking off with ten hives , and the scond proposal , kicking of 100 hives using the criteria of the world bank . Results showed that the bee keeping projects is economically feasible, whether small or large .. Even when the analysis of the sensitivity of the project to changes which may occur in the price of output and resources by reducing costs and increasing revenues by 10% it remains economically viable .

Sliding Mode Controller (SMC) is a simple method and powerful technique to design a robust controller for nonlinear systems. It is an effective tool with acceptable performance. The major drawback is a classical Sliding Mode controller suffers from the chattering phenomenon which causes undesirable zigzag motion along the sliding surface. To overcome the snag of this classical approach, many methods were proposed and implemented. In this work, a Fuzzy controller was added to classical Sliding Mode controller in order to reduce the impact chattering problem. The new structure is called Sliding Mode Fuzzy controller (SMFC) which will also improve the properties and performance of the classical Sliding Mode control

The background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art

In this article, performing and deriving the probability density function for Rayleigh distribution by using maximum likelihood estimator method and moment estimator method, then crating the crisp survival function and crisp hazard function to find the interval estimation for scale parameter by using a linear trapezoidal membership function. A new proposed procedure used to find the fuzzy numbers for the parameter by utilizing (     to find a fuzzy numbers for scale parameter of Rayleigh distribution. applying two algorithms by using ranking functions to make the fuzzy numbers as crisp numbers. Then computed the survival functions and hazard functions by utilizing the real data application.

This paper investigates the performance evaluation of two state feedback controllers, Pole Placement (PP) and Linear Quadratic Regulator (LQR). The two controllers are designed for a Mass-Spring-Damper (MSD) system found in numerous applications to stabilize the MSD system performance and minimize the position tracking error of the system output. The state space model of the MSD system is first developed. Then, two meta-heuristic optimizations, Simulated Annealing (SA) optimization and Ant Colony (AC) optimization are utilized to optimize feedback gains matrix K of the PP and the weighting matrices Q and R of the LQR to make the MSD system reach stabilization and reduce the oscillation of the response. The Matlab softwar

    Osteoarthritis (OA) is a disease of human joints, especially the knee joint, due to significant weight of the body. This disease leads to rupture and degeneration of parts of the cartilage in the knee joint, which causes severe pain. Diagnosis of this disease can be obtained through X-ray. Deep learning has become a popular solution to medical issues due to its fast progress in recent years. This research aims to design and build a classification system to minimize the burden on doctors and help radiologists to assess the severity of the pain, enable them to make an optimal diagnosis and describe the correct treatment. Deep learning-based approaches, such as Convolution Neural Networks (CNNs), have been used to detect knee OA usin