Smishing is the delivery of phishing content to mobile users via a short message service (SMS). SMS allows cybercriminals to reach out to mobile end users in a new way, attempting to deliver phishing messages, mobile malware, and online scams that appear to be from a trusted brand. This paper proposes a new method for detecting smishing by combining two detection methods. The first method is uniform resource locators (URL) analysis, which employs a novel combination of the Google engine and VirusTotal. The second method involves examining SMS content to extract efficient features and classify messages as ham or smishing based on keywords contained within them using four well-known classifiers: support vector machine (SVM), random

     Intelligent systems can be used to build systems that simulate human behavior. One such system is lip reading. Hence, lip reading is considered one of the hardest problems in image analysis, and thus machine learning is used to solve this problem, which achieves remarkable results, especially when using a deep neural network, in which it dives deeply into the texture of any input. Microlearning is the new trend in E-learning. It is based on small pieces of information to make the learning process easier and more productive. In this paper, a proposed system for multi-layer lip reading is presented. The proposed system is based on micro content (letters) to achieve the lip reading process using deep learning and auto-correction mo

     Face detection is one of the important applications of biometric technology and image processing. Convolutional neural networks (CNN) have been successfully used with great results in the areas of image processing as well as pattern recognition. In the recent years, deep learning techniques specifically CNN techniques have achieved marvellous accuracy rates on face detection field. Therefore, this study provides a comprehensive analysis of face detection research and applications that use various CNN methods and algorithms. This paper presents ten of the most recent studies and illustrate the achieved performance of each method. 

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

this research aims it measure the technical efficiency of the branches of the General Company for Land Transport, That scattered geographically at country level, by Data Envelopment analysis (DEA) technique, as this technique relies on measuring the efficiency of a set of asymmetric Decision making units, which is one of the nonparametric mathematical methods for and application related to Linear Programming, and this is what helps the General Company for Land Transport to diagnose its branches performance by benchmarking with each other and determine the performance gap. The research found that there is variation in the level of efficiency in the company's branches

  Abu Al- Qasim Qa ^,im Maqam is famous figure in political life of lranian; The life of Abu Al- Qasim Qa ^,im Maqam is full of incidents and conflicts in the period of the expansion of foreign influence in lran Abu Al- Qasim Qa ^,im Maqam has an important role in the history of Iran Modern political considered him one of the most prominent leaders to the unified Arabian nationalistic liberating Abu Al- Qasim Qa ^,im Maqam   raised in the history of the Qajar .

The research aim to know the effect of note–taking by computer method as amentalactivators in achievement of physics subject for the first intermediate class students.

To investigate from aim of the research the research sample was chosen from the first intermediate class students in Al–mutamyzat secondary school for girls. Which belongs to the general administration for the second karkh education which randomly chosen from (9) schools for distinct female students in Baghdad. Then randomly chosen two sections form three about (80) female students at (66.667%) from total sample it’s about (120) female student in the three sections. The randomly chosen too, section (a) to represent experimental group it’s about (41) female

شغلت  قضية اعداد المعلم  اهتمامات العديد من المسؤولين في قطاع التربيه والتعليم وكذلك اولياء امور الطلبه واساتذه الجامعه , ولازالت الهم الاكبر , وذلك لاختلاف سياسه اعداد المعلم من دولة واخرى وحسب الفلسفه التربويه  والمتغيرات والتطورات السريعه التي يشهدها العالم

            وفي ضوء ماتقدم , ان المعلم هو احد عناصر العمليه التربويه في اي بلد . بعد الطالب والمنه

    The aim of this research is to make a new investigation of a scientific thesis in Arabic Morphology in which an allusion occurred in relation to its real author and its title, there is alot of dropping and flaw when it was first applied due to depending on one written transcript