The industrial sector of the important drivers of economic activity sectors due to having the capabilities and the potential to qualify biggest contribution to the economic development of the country, which requires the availability of a higher degree of safety in industrial organizations, and the preservation of the lives of employees and workers in emergency situations, and that all the work is not without its dangers, which produces in a year of uncertainty in the possible events get in the future, therefore, reduce the dangers that could be exposed to industrial organizations and management are at the heart of the strategic direction which works to stimulate thinking about the future and respond to the changes that occur in theextern

Background: The purpose of this study is to evaluate the care of multiple trauma victims with maxillofacial injuries in terms of epidemiological distributions, types of injuries, the related different modalities of surgical treatments delivered, and their complications. Materials and Methods: This prospective study was performed on 50 patients with multiple traumas including maxillofacial injuries, caused by different etiological factors, who were brought first to the surgical emergencies department of the Medical City then referred to the Maxillofacial unit in the Specialized Surgeries Hospital, Baghdad, Iraq, during the period from April 2007 to April 2008. Information was documented prospectively from the time of the emergency call to

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

    The anatomical features of leaves and stems of seven species belonging to five genera of the Papaveraceae family were studied, including: Fumaria bracteosa Pomel, 1875; Glaucium grandiflorum Boissier & A. Huet,1856; Hypecoum pendulum Linnaeus, 1753; Papaver fugax Poiret,1804; Papaver macrostomum Boissier & A. Huet, 1867; Papaver rhoeas Linnaeus, 1753 and Roemeria refracta de Candolle,1821. The results showed that the anticlinal cell walls of the adaxial surface were more thickened in P. fugax, H. pendulum, P. macrostomum and R.refracta, while it was thin in P. rhoeas. The cur

The highest incidence of injury is seen in adolescent playing pivoting sports such as soccer, basketball, and handball. Objective: To examine the effectiveness of a neuromuscular prevention program in reducing knee and ankle injuries in adolescent male soccer players.

Abstract

             This paper follows the growing interest and continuity of Islamic finance products worldwide, which has encouraged the formulation of financial institutions based on the concepts of Islamic Sharia in many countries of the world and is no longer limited to Islamic countries only, and  Not exclusive to Muslims which is due to Islamic finance services and their ability to apply in non-Islamic societies, and perhaps what encouraged the development and progress of this industry Islamic history, which was attended by many different models With the development of trade's share between different countries as well as trips carried out by Muslims

The Internet of Things (IoT) is an expanding domain that can revolutionize different industries. Nevertheless, security is among the multiple challenges that it encounters. A major threat in the IoT environment is spoofing attacks, a type of cyber threat in which malicious actors masquerade as legitimate entities. This research aims to develop an effective technique for detecting spoofing attacks for IoT security by utilizing feature-importance methods. The suggested methodology involves three stages: preprocessing, selection of important features, and classification. The feature importance determines the most significant characteristics that play a role in detecting spoofing attacks. This is achieved via two techniques: decision tr