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

Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

This paper proposes feedback linearization control (FBLC) based on function approximation technique (FAT) to regulate the vibrational motion of a smart thin plate considering the effect of axial stretching. The FBLC includes designing a nonlinear control law for the stabilization of the target dynamic system while the closedloop dynamics are linear with ensured stability. The objective of the FAT is to estimate the cubic nonlinear restoring force vector using the linear parameterization of weighting and orthogonal basis function matrices. Orthogonal Chebyshev polynomials are used as strong approximators for adaptive schemes. The proposed control architecture is applied to a thin plate with a large deflection that stimulates the axial loadin

CO2 Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting  gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by  is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests.  PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal.  Many trials have been done to ma

The unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence^. The techniques used in this paper are:

• Apparent resistivity R_wa
• R_xo /R_t

   The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic