The science of jurisprudence is one of the legal sciences that scholars have been interested in since the first centuries of Islam, and they wrote many books about it, and the science of manuscripts is considered one of the scientific achievements in which many scholars emerged, including Imam Al-Samaani, so I chose this manuscript related to Istism to clarify its concept and meaning for all people, The student (Ali Ahmed Abdel-Aziz Sheikh Hamad) preceded me in the investigation of part of the book, and it was facilitated for me, by the grace of God Almighty, to investigate the issue (if one of the Muslim spouses apostatized and one of the infidel spouses converted to Islam until the end of the issue of if the two spouses were taken capt

In this study, the relationship between the bare soil temperature with respect to its salinity is presented, the bare soil feature is considered only by eliminating all other land features by classifying the site location by using the support vector machine algorithm, in the same time the salinity index that calculated from the spectral response from the satellite bands is calibrated using empirical salinity value calculated from field soil samples. A 2D probability density function is used to analyze the relationship between the temperature rising from the minimum temperature (from the sunrise time) due to the solar radiation duration tell the time of the satellite capturing the scene image and the calibrated salinity index is presented. T

Calculating similarities between texts that have been written in one language or multiple languages still one of the most important challenges facing the natural language processing. This work offers many approaches that used for the texts similarity. The proposed system will find the similarity between two Arabic texts by using hybrid similarity measures techniques: Semantic similarity measure, Cosine similarity measure and N-gram ( using the Dice similarity measure). In our proposed system we will design Arabic SemanticNet that store the keywords for a specific field(computer science), by this network we can find semantic similarity between words according to specific equations. Cosine and N-gram similarity measures are used in order t

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

     This article reviews a decade of research in transforming smartphones into smart measurement tools for science and engineering laboratories. High-precision sensors have been effectively utilized with specific mobile applications to measure physical parameters. Linear, rotational, and vibrational motions can be tracked and studied using built-in accelerometers, magnetometers, gyroscopes, proximity sensors, or ambient light sensors, depending on each experiment design. Water and sound waves were respectively captured for analysis by smartphone cameras and microphones. Various optics experiments were successfully demonstrated by replacing traditional lux meters with built-in ambient light sensors. These smartphone-based measurement

The present study aims at empirically investigating the effect of vocabulary learning strategies on Iraqi intermediate school students’vocabulary performance and reading comprehension. The population of the present study includes all the 1^st year male students of  Al-Wark’a intermediate  school of Al-Risafa 1/ General  Directorate of Education for the first course of the academic year (2015-2016). To achieve the aim of the study ,a pre-test and post-test after (5) weeks of experiment are administrated .The sample of the present study consists of (100) subjects :(50) students as an experimental group and other (50) students as  a control group . The subj

     Due to the spread of “Deepfake” in our society and the impact of this phenomenon on politicians, celebrities, and the privacy of individuals in particular, as well as, on the other hand, its impact on the electoral process as well as financial fraud, all these reasons prompted us to present a research paper dealing with this phenomenon. This paper presents a comprehensive review of Deepfake, how it is created, and who has produced it. This paper can be used as a reference and information source for the methods used to limit deepfake by detecting forgeries and minimizing its impact on society by preventing it. This paper reviews the results of much research in the field of deepfake, as well as the advantages of each method, a

Euphemisms are advantageous in people’s social life by turning sensitive into a more acceptable ones so that resentful feelings and embarrassment can be avoided. This study investigates the ability of Iraqi English learners in using euphemistic expressions, meanwhile, raising their awareness and the faculty members in English teaching faculties regarding the relevance of discussing the topics that demand euphemisation. This study comprised three stages: initial test, explicit instruction with activities, and a final test for the students’ development in this domain. A test has been distributed among 50 respondents, who are at the fourth year of their undergraduate study at the University of Babylon/ College of Basic Education. The lo

Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re