In this paper it is required to enhance the performance of a mechanical system (here: a Hoisting System) where it is preferred to lift a different payloads with approximately the same speed of lifting and keeping at the same time the good performance, and this of course needs some intelligence of the system which will be responsible on measuring the present load and taking into account the speed and performance desired in order to achieve the requirements or the criteria. The process therefore is a Mechatronics System design which includes a measuring system, a control or automation technique, and an actuating system. The criteria built here in this research using a given Hoist system's characteristics and parameters and changing one of

The reclamation of makeup water is studied in terms of breakthrough time (i.e., the leakage of the cations). Makeup water was subjected to lab-scale ion exchangers of two types: strong acid cation and weak base anion exchanger. The experimental investigation was directed to study the ion exchanger performance in terms of four different parameters (i.e., copper concentration, total dissolved solids (TDS), feed rate and bed depth). Box-Wilson composite rotatable design was adopted in designing the experiments. Breakthrough times of the effluent stream are measured in terms of copper concentration of 2 to 25 ppm, TDS concentration of 250 to 1250 ppm, feed rate of 0.38 to 5.34 l/h and bed depth of 5 to 70 cm. Simulation the effect of the stu

The research deals with a new type of high-performance concrete with improved physical properties, which was prepared by using metal additives minutes (Metakaolin) and by studing their impact on the properties of mortar and concrete high-performance through destructive and non destructive tests. This type of concrete is used broadly in public buildings and in other structures . The research involved a number of experiments such as finding the activity index of burned at a temperature of 750 º C according to the standard ( ASTM C-311/03), as well as casting models for the cubic mortar mixtures and concrete containers at different rates of metakaolin ranging between (5% - 20%) as an added part to the cement mix to get a high- compressive

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

The pharmacokinetics and bioequivalence of a newly developed extended-released (ER) tablet containing 400 mg pentoxifylline as a test product was compared with the reference brand product Trental^® 400 mg ER tablet produced by Sanofi-Aventis. Two separate studies were conducted simultaneously. The first study was conducted under fasting condition, whereas, the second study was conducted under fed condition; using the same batches of the test and reference products in both studies. In each study, both products were administered to 32 healthy male adult volunteers applying a single-dose, two-treatment, two-period, two-sequence, randomized crossover design with one-week washout period between dosing. Twenty two blood samples we

Introduction: Dental fear is defined as the patient’s specific reaction towards stress related to dental treatment in which the stimulus is unkn..

   Nonlinear regression models are important tools for solving optimization problems. As traditional techniques would fail to reach satisfactory solutions for the parameter estimation problem.  Hence, in this paper, the BAT algorithm  to estimate the parameters of  Nonlinear Regression models is used . The simulation study is considered to investigate the performance of the proposed algorithm with the maximum likelihood (MLE) and Least square (LS) methods. The results show that the Bat algorithm provides accurate estimation and it is satisfactory for the parameter estimation of the nonlinear regression models than MLE and LS methods depend on Mean Square error.

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

Background: Chronic otitis media (COM) of mucosal or squamous type is a common problem in otolaryngology practice, the active form of COM is characterized by discharge of pus and is treated by antibiotics to start with, the appropriate antibiotic should be prescribed to avoid antibiotic abuse and guarantee good outcome. Objectives:The objective of this study is to identify the causative organisms of active chronic active otitis media both (mucosal, squamous) type and test their sensitivity to various anti- microbial agents &compare with abroad studies.Methods:A prospective study was done on eighty patients, different ages and sexes were taken and carful history and examination was done, examination under microscope was done with carf

Biological image edge detection preserving the important structural properties in an image. Detecting accurate edges are very important for analyzing the basic properties associated with a biological image. Gradient operator plays very important role in edge detection. In this paper the images had been using are color biological images taken from microbiology laboratory at the biological department college of science Al-MustansiriyhUniversity and the effect of gradient operation have applied on around 10 different biological color images but view only two. In our proposed approach comparative of various gradient of biological image include (gradient of image, gradient of image using first order derivative edge detection (Soble,Prewitt,Ro