The accurate 3-D coordinate's measurements of the global positioning systems are essential in many fields and applications. The GPS has numerous applications such as: Frequency Counters, Geographic Information Systems, Intelligent Vehicle Highway Systems, Car Navigation Systems, Emergency Systems, Aviations, Astronomical Pointing Control, and Atmospheric Sounding using GPS signals, tracking of wild animals, GPS Aid for the Blind, Recorded Position Information, Airborne Gravimetry and other uses. In this paper, the RTK DGPS mode has been used to create precise 3-D coordinates values for four rover stations in Baghdad university camp. The HiPer-II Receiver of global positioning system was used to navigate the coordinate value. The results wil

<p><span>This research deals with the feasibility of a mobile robot to navigate and discover its location at unknown environments, and then constructing maps of these navigated environments for future usage. In this work, we proposed a modified Extended Kalman Filter- Simultaneous Localization and Mapping (EKF-SLAM) technique which was implemented for different unknown environments containing a different number of landmarks. Then, the detectable landmarks will play an important role in controlling the overall navigation process and EKF-SLAM technique’s performance. MATLAB simulation results of the EKF-SLAM technique come with better performance as compared with an odometry approach performance in terms of measuring the

High vehicular mobility causes frequent changes in the density of vehicles, discontinuity in inter-vehicle communication, and constraints for routing protocols in vehicular ad hoc networks (VANETs). The routing must avoid forwarding packets through segments with low network density and high scale of network disconnections that may result in packet loss, delays, and increased communication overhead in route recovery. Therefore, both traffic and segment status must be considered. This paper presents real-time intersection-based segment aware routing (RTISAR), an intersection-based segment aware algorithm for geographic routing in VANETs. This routing algorithm provides an optimal route for forwarding the data packets toward their destination

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

Periodontal disease is typically treated with mechanical debridement of the tooth surface. It may, however, be insufficient to eradicate pathogenic microorganisms on its own. Because of the microbial etiology of periodontitis, systemic or local antibiotic therapy is used as an adjunct treatment. The present study aimed to determine the effects of curcumin gel on Porphyromonas gingivalis. Eleven patients with stage II and III periodontitis were registered in the study. A double-blinded split-mouth design followed. Periodontal pockets were distributed into 2 groups; the test group received scaling and root planing along with curcumin gel, while the control group received scaling and root planing along with a placebo gel. Plaque index,

This research include design and implementation of an Iraqi cities database using spatial data structure for storing data in two or more dimension called k-d tree .The proposed system should allow records to be inserted, deleted and searched by name or coordinate. All the programming of the proposed system written using Delphi ver. 7 and performed on personal computer (Intel core i3).

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

A Tonido cloud server provides a private cloud storage solution and synchronizes customers and employees with the required cloud services over the enterprise. Generally, access to any cloud services by users is via the Internet connection, which can face some problems, and then users may encounter in accessing these services due to a weak Internet connection or heavy load sometimes especially with live video streaming applications overcloud. In this work, flexible and inexpensive proposed accessing methods are submitted and implemented concerning real-time applications that enable users to access cloud services locally and regionally. Practically, to simulate our network connection, we proposed to use the Raspberry-pi3 m