There is an assumption implicit but fundamental theory behind the decline by the time series used in the estimate, namely that the time series has a sleep feature Stationary or the language of Engle Gernger chains are integrated level zero, which indicated by I (0). It is well known, for example, tables of t-statistic is designed primarily to deal with the results of the regression that uses static strings. This assumption has been previously treated as an axiom the mid-seventies, where researchers are conducting studies of applied without taking into account the properties of time series used prior to the assessment, was to accept the results of these tests Bmanueh and delivery capabilities based on the applicability of the theo

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

Self-driving automobiles are prominent in science and technology, which affect social and economic development. Deep learning (DL) is the most common area of study in artificial intelligence (AI). In recent years, deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. Different studies investigated a variety of significant technologies for autonomous vehicles, including car navigation systems, path planning, environmental perception, as well as car control. End-to-end learning control directly converts sensory data into control commands in autonomous driving. This research aims to identify the most accurate pre-trained Deep Neural Network (DNN) for predicting the steerin

     The importance of this research is due to its importance goals, Which are about the attempt of researchers to investigate the probability of depending on businesses^, environments to transform organizations^, performance in away that enhance the leading  role of organizations  in their environments , and through views of a number of the staff working in the foundation of technical institutes in Mosul.  .

     After deciding the methodology of the study that ,in one hand ,performs the goals of the study , and achieving a suitable theoretical framework to present the concepts of businesses^, environments and the leadin

The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

Biological drugs have an active substance that is made by a living organism or derived from a living organism. They are one of the important therapy options used in a wide range of diseases especially life-threatening diseases. Biological therapy opens new opportunities for treating different diseases for which drug therapy is minimal, but they have considerable differences in the safety consequences in comparison with non-biological drugs. The aim of the current study was to assess the post-marketing safety profile of biological drugs used in Iraqi hospitals by the analysis of the reported adverse drug reactions regarding their severity, seriousness, preventability, expectedness, and outcome. It is a retrospective study of the individu

This study was designed to show the inhibitory effect of different concentrations of alcoholic extract of Borage officinalis on the Monoamine oxidase (MAO) and Acetylcholinesterase (AChE) enzymes in human serum. The results obtained from the study exhibited that alcoholic extract of Borage officinalis caused inhibition to enzymes activity with all concentrations of the extract. The results also showed that when the concentration of the extract was (0.001 mg/ml), the percentage of inhibition was (4.3% with MAO and 15.2% with AChE) and this percentage increases until reaching up to (74.7% with MAO and 84.18% with AChE) when the concentration of the extract was (0.1 mg/ml). From the kinetic parameters, studies found that alcoholic extract o