Background: presence of lingual vascular foramina and canals in the interforaminal regionmay increase the risk ofsurgical complications during implant placement or any surgical procedure in this area.Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended AL- Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canals

Background: presence of lingual vascular foramina and canals in the interforaminal region may increase the risk ofsurgical complications during implant placement or any surgical procedure in this area. Aim of this study is the radiological evaluation of the anatomic characteristic of the lingual foramina and their vascular canals in the anterior of the mandible using cone beam computed tomography. Materials and Methods: Prospective study including 72 Iraqi subjects (31 male and 41 female) ranging from 20 to 59 years, all subjects attended Al-Sharaa dental clinic in AL-Najaf AL-Ashraf city, scanned with CBCT from September 2016 to February 2017. Using 3dimentional and sagittal cross section to detect lingual foramina and their vascular canal

Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia applications. To

Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia appli

The research aims to contribute to the consolidation of scientific knowledge of compliance control and its role in verifying the proper disposal of funds to manage the wheel of the economy towards achieving targeted development and preserving public money, as well as clarifying the role of tax revenues in strengthening the public treasury and achieving social justice. The analytical descriptive approach was adopted in the process of analyzing The quantitative data collected through personal interviews, and the research reached a set of conclusions, the most important of which is the contribution of compliance control according to its three principles. (Transparency, accountability, and inclusiveness) on the availability

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

The concept of the order sum graph associated with a finite group based on the order of the group and order of group elements is introduced. Some of the properties and characteristics such as size, chromatic number, domination number, diameter, circumference, independence number, clique number, vertex connectivity, spectra, and Laplacian spectra of the order sum graph are determined. Characterizations of the order sum graph to be complete, perfect, etc. are also obtained.

The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem.  The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

The levels of circulating angiogenic and anti-angiogenic factors, namely vascular endothelial growth factor–A (VEGF-A) and soluble vascular endothelial growth factor receptor-1 (sVEGFR-1), have been linked to the development of renal dysfunction due to the proliferation of microvasculature within the kidneys of type 2 diabetic (T2DM) patients. The study aims to scrutinize serum levels of VEGF and sVEGFR-1 in a sample of Iraqi diabetic nephropathy patients to support their reliability as markers for the prediction of nephropathy in type 2 diabetes mellitus patients as well as to assess the ACE inhibitor’s effect on the levels of these two markers. Method: The ninety participants of this case-control study were split into three gr

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.