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The research aims to identify the level of increase or decrease the product cost through the activity based flexible budgeting that gives us the chance to follows the cost since the product is planed to be made till it appears in the market and it also helps to fined out any problems that are expected to happen in the future and to put the costs under control, also to know much the surveying affects the perfect use for the complete resources in order to be used in the demanded way, the research is divided in to three sides ,the first is specialized for the theoretical side, the second is for the partical side, while the third side is specialized for the conclusions and recommendations.        &nbsp

Increasingly important public opinion polls steadily .... especially in electoral campaigns, sheds searchlight on the side of the US elections, in different time periods, and cited the words of experts and people involved in it, and reviews Find great development that took place in the polls and what could happen to this work It is important in the future. Display search for certain types of polls, dividing them on as stated by the experts in the United States... This division shows that the surveys of the most political processes and accuracy of information, and that their Money being made and companies specialized in the administration of this type of measuring public opinion ..... what is returned decision-making, for example, in conj

This study used a continuous photo-Fenton-like method to remediate textile effluent containing azo dyes especially direct blue 15 dye (DB15). A Eucalyptus leaf extract was used to create iron/copper nanoparticles supported on bentonite for use as catalysts (E@B-Fe/Cu-NPs). Two fixed-bed configurations were studied and compared. The first one involved mixing granular bentonite with E@B-Fe/Cu-NPs (GB- E@B-Fe/Cu-NPs), and the other examined the mixing of E@B-Fe/Cu-NPs with glass beads (glass beads-E@B-Fe/Cu-NPs) and filled to the fixed-bed column. Scanning electron microscopy (SEM), zeta potential, and atomic forces spectroscopy (AFM) techniques were used to characterize the obtained particles (NPs). The effect of flow rate and DB15 concent

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

This paper tackles in detail the functional shift of parts of speech, such as the shift of a verbal clause to an adjectival clause, along with the types of such a shift. The researcher identified the important features of participles, as well as the concept of participles, adjectives, and their types. Also, the most important changes that affect the participles during such shifts. Further, an exposition is made of the different producers through which a verbal clause is changed into an adjectival one in Russian.

      This type of functional shift in parts of speech is seen as a process of deriving most of the new words in contemporary Russian. Russian is very rich in new words, whether by way of processe