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

This research presents a new algorithm for classification the
shadow and water bodies for high-resolution satellite images (4-
meter) of Baghdad city, have been modulated the equations of the
color space components C1-C2-C3. Have been using the color space
component C3 (blue) for discriminating the shadow, and has been
used C1 (red) to detect the water bodies (river). The new technique
was successfully tested on many images of the Google earth and
Ikonos. Experimental results show that this algorithm effective to
detect all the types of the shadows with color, and also detects the
water bodies in another color. The benefit of this new technique to
discriminate between the shadows and water in fast Matlab pro

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

     The current study aimed to adopt a method for inducing callus cells and regenerating the important common red bean using different types of growth regulators such as N⁶-benzylaminopurine (BAP), Naphthalene acetic acid (NAA), and Thidiazuron (TDZ). Different types of common bean pinto cultivar explants, such as  internodes, cotyledons and roots,  were inoculated on Murashige and Skoog medium (MS) provided with different combinations of plant growth regulators, including 1- BAP (5 mg/l) 2-BAP (4.5 mg/l) NAA (0.5 mg/l), 3- BAP (4.5 mg/l), and TDZ (0.1mg/l). Callus was initiated on MS culture medium supplied with 5 mg/l BAP for all explants (internodes, cotyledons, and roots) at 50, 20, and 10% r

Autoría: Muwafaq Obayes Khudhair. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.

Background: Varicose vein (VV) is a common problem that mostly occurs in legs. This medical condition can influence the quality of life and working condition of nurses. Aim of the study: To estimate the prevalence of lower limbs varicosity and its associated risk factors among nurses. Methods: This a cross-sectional descriptive study was carried out among 100 nurses working Baghdad Teaching Hospital, Surgical Specialties Hospital, and Al- Kidney Teaching Hospital, Baghdad, Iraq from January 1st to May 10th, 2022. The participants were recruited in the study using systematic random sampling. The Occupational Sitting and Physical Activity and Aberdeen Varicose Vein Questionnaires were used for data gathering. Results: The prevalence o

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

Tanuma and Zubair formations are known as the most problematic intervals in Zubair Oilfield, and they cause wellbore instability due to possible shale-fluid interaction. It causes a vast loss of time dealing with various downhole problems (e.g., stuck pipe) which leads to an increase in overall well cost for the consequences (e.g., fishing and sidetrack). This paper aims to test shale samples with various laboratory tests for shale evaluation and drilling muds development. Shale's physical properties are described by using a stereomicroscope and the structures are observed with Scanning Electron Microscope. The shale reactivity and behavior are analyzed by using the cation exchange capacity testing and the capillary suction test is

􀀑􀀃Pure Cu (CZTSe) and Ag dopant CZTSe (CAZTSe) thin films with Ag content of 0.1 and 0.2 were fabricated on coring glass substrate at R.T with thickness of 800nm by thermal evaporation method. Comparison between the optical characteristics of pure Cu and Ag alloying thin films was done by measuring and analyzing the absorbance and transmittance spectra in the range of (400-1100)nm. Also, the effect of annealing temperature at 373K and 473K on these characteristics was studied. The results indicated that all films had high absorbance and low transmittance in visible region, and the direct bang gap of films decreases with increasing Ag content and annealing temperature. Optical parameters like extinction coefficientrefractive index, and

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha