ABSTRACT

            This study aimed to choose top stocks through technical analysis tools specially the indicator called (ratio of William index), and test the ability of technical analysis tools in building a portfolio of shares efficient in comparison with the market portfolio. These one technical tools were used for building one portfolios in 21 companies on specific preview conditions and choose 10 companies for the period from (March 2015) to (June 2017). Applied results of the research showed that Portfolio yield for companies selected according to the ratio of William index indicator (0.0406) that

In this investigation, metal matrix composites (MMC_s) were manufactured by using powder technology. Aluminum 6061 is reinforced with two different ceramics particles (SiC and B₄C) with different volume fractions as (3, 6, 9 and 12 wt. %). The most important applications of particulate reinforcement of aluminum matrix are: Pistons, Connecting rods etc. The specimens were prepared by using aluminum powder with 150 µm in particle size and SiC, B₄C powder with 200 µm in particle size. The chosen powders were mixed by using planetary mixing setup at 250 rpm for 4hr.with zinc stearate as an activator material in steel ball milling. After mixing process the powders were compacted by hydraulic

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Fibro-adenoma is the most common lesion of the breast, it occurs in25%of asymptomatic women (1,2 )
It is usually a disease of early reproductive life, the peak incidence is between the ages15 and 35 years.(3,4) It presents as firm highly mobile, non tender mass .(5)
Less than 5% of fibro-adenomas grow rapidly and display the clinical and histologic characteristics of giant fibro-adenoma which is defined as a-tumour either having a diameter greater than 5 cm. And /or amass weighing more than 500 grams, and are conventionally a benign tumor of breast.(6)
Giant fibro-adenomas appear as well-circumscribed but not encapsulated masses on mammography and solid and the texture is homogenous and hypoechoic with low level echoes on U/S. (

The main purpose of the research is to diagnose the importance of the role that strategic memory plays with its three variables (content, structure, and processes) in helping the human resource department to use the COSO model with its five components (culture and governance, strategy and objectives, performance, communications and information, and feedback) in auditing activities and tasks Her own. As the research problem emphasized the existence of a lack of cognitive perception, of the importance of strategic memory, and the investment of its components in the rationalization of the application of the COSO model. and therefore it can be emphasized that the importance of the research is to provide treatments for problems relate

Purpose: The aim of this study is to examine knowing the real role and impact of manufacturing flexibility on competitiveness through operations management practices, which is to determine the role and impact of manufacturing flexibility on competitiveness directly in the General Company for the Battery Industry. On the other hand, identifying the indirect role of flexible manufacturing systems in enhancing competitiveness.   Theoretical framework: The main purpose of the theoretical framework is to identify all the dimensions and variables included in the current study, and thus form a deep scientific view of the study and its variables.   Design/methodology/approach: field coexistence, personal interviews, and classification of

Abstract

Abstract has many advantages as has historically been one of the regions leading cultural centers . for centuries , it has been a center of commertial and financial operations in Iraq. it is also rich in archeological sites and natural resources, but because of its wars and implementation of urban development strategies are effective and sustainable , so contracted the secretariat of Baghdad with the company (khatib and scirntiffic) for the preparation of the comprehensive development plan for the city of Baghdad in 2030 and funded by the world bank and the fact that the plan was approved ( three stages of it ) and only one phase remains the fourth stage, which is under discussion the aim of the