The effectiveness of (200 m) of the events of extreme intensity and this is characterized by training in the anaerobic energy system prevailing in the result of this privacy as these are based on the physical abilities and functional indicators identified in this direction and hence the importance of research in the evaluation of training programs on the basis of physical abilities and some indicators of the functionality of the hostile 200 m . The study aimed to: 1. Evaluation of training programs according to physical abilities and some functional indicators of hostile men.The researchers used the descriptive analytical method to suit the nature of the research. The researchers selected them research sample by the deliberate method of the

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

The artificial intelligence techniques such as neural networks and fuzzy systems play an important role to disconnect flexion & expansion of the swing leg, the earth response force of the other foot has been redesigned. Under that paper, we think the fuzzy controller plan issue for yield following flawed genuine investigation of nonlinear systems. For examination, an essential fuzzy control plot has been bristly developed dependent on a current methodology delegate under the field. In this paper, the Feedforward Neural Network has been implemented with integer, fixed point and floating point data representations. Additionally, The Fuzzy Logic Controllers in both analog and digital forms has been implemented in hardware. Both designs use les

The deterioration of buried sewers during their lifetime can be affected by several factors leading to bad performance and can damage the infrastructure similar to other engineering structures. The Hydraulic deterioration of the buried sewers caused by sewer blockages while the structural deterioration caused by sewer collapses due to sewer specifications and the surrounding soil characteristics and the groundwater level. The main objective of this research is to develop deterioration models, which are used to predict changes in sewer condition that can provide assessment tools for determining the serviceability of sewer networks in Baghdad city. Two deterioration models were developed and tested using statistical software SPSS, the

The Carbonate-clastic succession in this study is represented by the Shuaiba and Nahr Umr Formations deposited during the Albian - Aptian Sequence. The present study includes petrography, microfacies analyses, and studying reservoir characterizations for 5 boreholes within West Qurna oil field in the study area. According to the type of study succession (clastic – Carbonate) there are two types of facies analyses:-Carbonate facies analysis, which showed five major microfacies were recognized in the succession of the Shuaiba Formation, bioclastic mudstones to wackstone, Orbitolina wackestone to packstone, Miliolids wackestone, Peloidal wackestone to packstone and mudstone to wackestone identified as an open shelf toward the deep basin.

The advancement of science and technology in recent years has led to heavy and diversified production and thus market congestion in various goods and services; which led to an increase of competition among advertisers in order to meet the needs and wishes and to upgrade to the level of consumers. These upgrades have imposed an increase in the usage of the promotions, including advertising in terms of quantity and quality, to influence and persuade customers innovatively and creatively using all available mass media.

The research aims to identify the attitudes of residents of poor areas towards television advertisements for medicines, and the impact of those advertisements on them in terms of making purch