BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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

The modernity of election practices of the elections in Iraq, according to the democratic approach, has led to a struggle between political rival forces reflecting a deep pressure on the tools involved in the management, marketing or control of these elections across the general social level. Hence the problem of research resides in answering the following question: What is the nature and size of the pressures affecting the media performance of Al-Iraqia News channel before the legislative elections of 2018 in Iraq?
      The objectives of the research were the following:
1. to identify the nature of the pressures that limit the Al-Iraqia News channel’s perfo

The study involved preparing a new compound by combining between 2-hydroxybenzaldehyde and (Z)-3-hydrazineylideneindolin-2-one resulting in Schiff bases and metal ions: Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) forming stable minerals-based-Schiff complexes. The formation of resulting Schiff bases is detected spectrally using LC-Mss which gave corresponding results with theoretical results, 1H-NMR proves the founding of N=CH signal, FT-IR indicates the occurrence of imine band and UV-VIs mean is proved the ligand formation. On the other hand, minerals-based-Schiff was characterized using the same spectral means that relied with ligand (Schiff bases). Those means gave satisfactory results and proved the suggested distinguishable geometries.