Polymer composites were prepared using epoxy resin (EP) and unsaturated polyester (UPE) as a blend matrices, which were mixed together in different percentages (starting from 90:10) of (epoxy/polyester) respectively, and ending with (50:50) of (epoxy/polyester). The optimum mixing ratio (OMR) of the components was decided upon the results of the impact strength value of these blending ratio, which showed the highest value of (16.3) KJ/m2 for the blending ratio (80:20) of (EP/UPE) respectively.
The blend with (OMR) was chosen to be reinforced with three different weight fractions of reinforcement; the 1st one was reinforced with nano titanium oxide (TiO2) with a weight fraction (2% wt.), the 2nd one was reinforced with both nano (TiO2)

The objective of this research is to determine the impact of marketing capabilities in building the reputation of the market organization. Marketing capabilities are one of the contemporary trends that can be adopted by the organization in the implementation of all its tasks and thus it can be assisted in achieving many advantages which are the most prominent marketing reputation in the environment The research problem indicated that there is a clear failure to employ the dimensions of marketing capabilities in the organization's reputation. The National Center for Engineering Consultancy was selected as the field of application. The questionnaire was used as a tool to obtain the research data that were prepared based on a number

Material obtained from the demolition of concrete structures and milling of flexible pavements has the highest potential for recyclability. This study aimed to evaluate the performance of hot mix asphalt with the concurrent use of recycled asphalt pavement (RAP) and recycled concrete aggregate (RCA). Contents of RAP and RCA were varied from 0% to 50% by fixing the total recycling materials percentage to 50%. Penetration grade 40/50 virgin binder and waste engine oil (WEO) as rejuvenator were used in the present study. A series of tests, such as Scanning electron microscopy (SEM), Marshall stability, indirect tensile strength test, IDEAL CT, uniaxial compression test, and resilient modulus test, were carried out to assess the performance of

Background: Bowel preparation prior to
colonic surgery usually includes antibiotic
therapy together with mechanical bowel
preparation which may cause discomfort to the
patients, prolonged hospitalization and water
& electrolyte imbalance.
Objective: to assess whether elective colon
and rectal surgery may be safely performed
without preoperative mechanical bowel
preparation.
Method: the study includes all patients who
had elective large bowel resection at Medical
City – Baghdad Teaching Hospital between
Feb, 2007 to Jan, 2010. Emergency operations
were not included. The patients were randomly
assigned to the 2 study groups (with or without
mechanical bowel preparation.
Results: A to

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

: In modern optical communication system, noise rejection multiple access interference (MAI) must be rejected in dense access network (DAN). This paper will study the dual optical band pass and notch filters. They will be extracted with tunable FWHM using 10cm (PMF) with different cladding diameters formed with etching 125μm PMF after immersing it with 40% of hydrofluoric acid (HF). This fiber acts as assessing fiber to perform Sagnac interferometer with splicing regions that placed 12cm (SMF) for performing hybrid Sagnac interferometer that consists of Mach-Zehnder instead of Sagnac loop which is illuminated by using laser source with centroid wavelength of 1546.7nm and FWHM of 286 pm or 9 ns in the time domain. . Firs

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

This paper presents a hybrid approach called Modified Full Bayesian Classifier (M-FBC) and Artificial Bee Colony (MFBC-ABC) for using it to medical diagnosis support system. The datasets are taken from Iraqi hospitals, these are for the heart diseases and the nervous system diseases. The M-FBC is depended on common structure known as naïve Bayes. The structure for network is represented by D-separated for structure's variables. Each variable has Condition Probability Tables (CPTs) and each table for disease has Probability. The ABC is easy technique for implementation, has fewer control parameters and it could be easier than other swarm optimization algorithms, so that hybrid with other algorithms to reach the optimal structure. In the

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall