Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

A new method for construction ion-selective electrode (ISE) by heating reaction of methyl orange with ammonium reineckate using PVC as plasticizer for determination methyl orange and determination Amitriptyline Hydrochloried drug by formation ion-pair on electrode surface . The characteristics of the electrode and it response as following : internal solution 10-4M , pH (2.5-5) ,temperature (20-30) and response time 2 sec. Calibration response for methyl orange over the concentrationrange 10-3 -10-9 M with R=0.9989 , RSD%=0.1052, D.O.L=0.315X10-9 MEre%=(-0.877- -2.76) , Rec%.=(97.230 -101.711) .

Due to the development that occurs in the technologies of information system many techniques was introduced and played important role in the connection between machines and peoples through internet, also it used to control and monitor of machines, these technologies called cloud computing and Internet of Things. With the replacement of computing resources with manufacturing resources cloud computing named converted into cloud manufacturing.

In this research cloud computing was used in the field of manufacturing to automate the process of selecting G-Code that Computer Numerical Control machine work it, this process was applied by the using of this machine with Radio Frequency Identification and a AWS Cloud services and some of py

Capillary pressure is a significant parameter in characterizing and modeling petroleum reservoirs. However, costly laboratory measurements may not be sufficiently available in some cases. The problem amplifies for carbonate reservoirs because relatively enormous capillary pressure curves are required for reservoir study due to heterogeneity. In this work, the laboratory measurements of capillary pressure and formation resistivity index were correlated as both parameters are functions of saturation. Forty-one core samples from an Iraqi carbonate reservoir were used to develop the correlation according to the hydraulic flow units concept. Flow zone indicator (FZI) and Pore Geometry and Structure (PGS) approaches were used to identify

  A field experiment was conducted through 2010-2011 in the experimental field return to AlKut forest project near the Tigris river\ General Directorate of Horticultural and Forestry at Wasit governorate. The purpose of this research is to know the response of four cultivars of Sesame to Foliar nutrition with Boron. R.C.B.P. were used with split plot in four Replications including main plot cultivars, Ishtar, Babel, Al-Rafidain, local. While sub-plot included four concentrations of boron (0,50,100, 150) mgb/L-1.   The result showed that Al-Rafidain was superior in the average of plant height and % of oil over all cultivars, while the local cultivars gave higher average of number of branches for plant and the highest first

PC-based controller is an approach to control systems with Real-Time parameters by controlling selected manipulating variable to accomplish the objectives. Shell and tube heat exchanger have been identified as process models that are inherently nonlinear and hard to control due to unavailability of the exact models’ descriptions. PC and analogue input output card will be used as the controller that controls the heat exchanger hot stream to the desired temperature.
The control methodology by using four speed pump as manipulating variable to control the temperature of the hot stream to cool to the desired temperature.
In this work, the dynamics of cross flow shell and tube heat exchanger is modeled from step changes in cold water f