A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

In recent days, the escalating need to seamlessly transfer data traffic without discontinuities across the Internet network has exerted immense pressure on the capacity of these networks. Consequently, this surge in demand has resulted in the disruption of traffic flow continuity. Despite the emergence of intelligent networking technologies such as software-defined networking, network cloudification, and network function virtualization, they still need to improve their performance. Our proposal provides a novel solution to tackle traffic flow continuity by controlling the selected packet header bits (Differentiated Services Code Point (DSCP)) that govern the traffic flow priority. By setting the DSCP bits, we can determine the appropriate p

Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

Background: Determination of local bone mineral density (BMD) with cortical thickness and bone height may offer a comprehensive description of the bone the surgeon will encounter when he or she actually sets the implant. Quantitative computed tomography (CT) (i.e., quantitative interpretation of values derived from Hounsfield units with a suitable calibration procedure) is the modality of choice to determine BMD. The aim of the present clinical study is to determine the local bone density in dental implant recipient sites using computerized tomography. Material and method: The sample consisted of (72) Iraqi patients whom referred to Al-Kharkh General hospital, Spiral CT scan Department for bone quality and quantity assessment after one wee

This study focuses on improving the safety of embankment dams by considering the effects of vibration due to powerhouse operation on the dam body. The study contains two main parts. In the first part, ANSYS-CFX is used to create the three-dimensional (3D) Finite Volume (FV) model of one vertical Francis turbine unit. The 3D model is run by considering various reservoir conditions and the dimensions of units. The Re-Normalization Group (RNG) k-ε turbulence model is employed, and the physical properties of water and the flow characteristics are defined in the turbine model. In the second phases, a 3D finite element (FE) numerical model for a rock-fill dam is created by using ANSYS®, considering the dam connection with its powerhouse

Introduction: Infection control or hospital-acquired infections are the major concern of the health care system and agencies. Critical care nurses are on the first-line contact with the patients, so on, they are most vulnerable to acquired infections. It is really important to regularly check their knowledge and practices concerning infection control. Objectives: The study aims to identify the impact of years’ experience on nurses’ knowledge and practices concerning infection control in three hospitals and center (Baghdad teaching hospital, Ibn Al-Nafees hospital, and Ibn al-Bitar center) Methodology: Cross-sectional study was conducted, the study starting from 4th of July 2020 to 13th of November 2020. Non-probability (purposive) sampl

The aim of the current research is to analyze the content of the two science books (chemistry units) for the two grades ( first and second intermediate ) according to environmental ethics, as the research community and its sample of the two science books (chemistry units) for the two grades ( first and second intermediate ), approved by the Iraqi Ministry of Education for the academic year ( 2021-2022 ), and the two researchers adopted the descriptive ( analytical ) approach, and the researchers built a standard for environmental ethics, and the validity of the tool was confirmed by presenting it to a group of experts, and then the researchers analyzed the two books in light of the standard prepared based on the implicit explicit idea, and

The present article is devoted to the analysis of Arabic phraseological units with a component hand, selected by continuous sampling from the “Training Russian-Arabic phraseological dictionary: about 900 phraseological units” by G. L. Permyakov. Arabic phraseological units with a component hand are modeled as invariant situations (by logical-semiotic models) and figurative statements are expressed by phraseological variants (according to the figurative characteristic of the hand component). The artical focuses on the fact that somatism in Arabic phraseology has a symbolic and symbolic nature, marking various situations of Arabs' behavior, their actions, deeds, rituals, emotional and psychological states, etiquette, in