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

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

One hundred and eighty five urine samples were collected eight isolates (4.3%) were obtained and diagnosed as Staphylococcus aureus. Among 8 isolates, 5 (62.5%) S. aureus isolates were found to be enterotoxigenic, most of isolates produced at least two types of Staphylococcal enterotoxins (SEs). The production of enterotoxins in the presence or absence of Thymol extracts (aqueous and alcoholic) were estimated using a reversed passive latex agglutination (SET-RPLA) kit. The extracts reduced enterotoxin production compared with the control. Enterotoxin inhibition was observed for enterotoxin C production at minimal inhibitory concentrations (MIC) at 400 µg/ml, whereas production of enterotoxins A, B, and

This study examined the phenomenon of unemployment in Iraq and the extent of the contribution of these loans granted by banks to finance small and medium enterprises in reducing their rates. The temporal boundaries of the study included the period between (2012-2018). The spatial boundaries consisted of random sampling of six Iraqi banks) Where the government banks included (Rafidain, Rasheed and industrial), private banks included (the Iraqi Islamic Bank and the Gulf Commercial Bank and the Bank of the Middle East). In order to achieve the objective of the research in the light of the hypotheses drawn up, the research divided into three topics, the first section highlighting the reality of small and medium enterprises in Iraq and the lo

this study was perform to defined the effect of fungus Metarhiziumanisopliae Sorokin with concentrations 5x101, 5x103 and 5x105 spore/ ml and Actelic insecticide with concentration 0.001% in in rate of germinate treated string bean seeds also study effect of packed bags in two different type: jute and polypropylene bags which treated with fungal suspension pervious mention and insecticide in rate infested the string bean seeds packed in it.Results of the study showed the following: Lower rate of weight loss of cowpea seeds appear in poly propylene bags 4.41, 5.95% after six months of treatment with 5x 105 spore/ ml and Actelic insecticide respectively compared with 15.08% to control treatment. The fungal concentrations and insecticide not