Simplification of new fashion design methods

Mechanical degradation hampers the practical usage of polymers for turbulent drag reduction
application. Mechanical degradation refers to the chemical process in which the activation energy of
polymer chain scission is exceeded by mechanical action on the polymer chain, and bond rupture
occurs. When a water-soluble polymer and surfactant are mixed in water solution, the specific structures
(aggregates) are formed, in which polymer film is formed around micelle. In this work, Xanthan gum (XG) –
Sodium lauryl ether sulfate (SELS) complex formation and its effect on percentage viscosity reduction
(%VR) was studied. It was found that SELS surfactant reduced the mechanical degradation of XG much
more efficiently than th

In this research, the influence of the fermentation treatments and baking in Iraqi’s flour type (Ibaa 99, Al-rashed, Tamus, Abu-grabe) and Turkish flour type (Muaamel) on phytic acid was investigated. In whole wheat flour, the phytic acid was (1500, 1290, 1450, 1230, 1440 ( mg/ 100 g flour respectively, and the inorganic phosphorous was (29.18, 25.15, 23.89, 20.85, 22.83) mg/100 g flour respectively. The dough prepared from flour with a higher phytic acid content also contained higher amount of phytic acid. During fermentation, degradation of phytic acid occurred. The cumulative loss of phytic acid after fermentation in all type of dough was ~ 23, 22, 34, 26 and 27% respectively،While increased of inorganic phosphorous occurred. The c

Background: For many decades, the ECG was the
workhorse of non-invasive cardiac test and today although
other techniques provide more details about the structural
anomalies in congenital heart diseases, ECG is likely to be
part of clinical evaluation of patients with such diseases
because it is inexpensive, easy to perform and in certain
situations may be both sensitive and specific.
Objective: this study carried out to identify the pattern of
ECG study in patients with TOF.
Methods: this is a retrospective study of 200 patients
with TOF, referred to Ibn Al-Bitar cardiac center from
April 1993 to May 1999. The diagnosis of TOF established
by echocrdiographic, catheterization and angiographic
study.

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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

For aspirin estimated, a molecularly imprinted polymer MIP-ASP electrodes were generated by electro-polymerization process, the electrodes were prepared by combining the template (aspirin) with (vinyl acetate (VA), 1-vinylimidizole (VIZ) as a functional monomer and N, N-methylene bisacrylamide (MBAA) as crosslinkers using benzoyl peroxide (BPO) as an initiator. The efficiency of the membrane electrodes was analyzed by differential pulse voltammetry (DPV). Four electrodes were synthesized using two different plasticizers, di-butyl sebacate (DBS), di-octyl phthalate (DOP) in PVC matrix. Scanning electron microscopy (SEM) was used to describe the generated MIP, studying the electrodes properties, the slope, detection limit, and life