The migration from IPv4 to IPv6 can not be achieved in a brief period, thus both protocols co-exist at certain years. IETF Next Generation Transition Working Group (NGtrans) developed IPv4/IPv6 transition mechanisms. Since Iraq infrastructure, including universities, companies and institutions still use IPv4 protocol only. This research article tries to highlight, discuss a required transition roadmap and extend the local knowledge and practice on IPv6. Also, it introduces a prototype model using Packet tracer (network simulator) deployed for the design and implementation of IPv6 migration. Finally, it compares and evaluates the performance of IPv6, IPv4 and dual stack using OPNET based on QoS metrics such as throughput, delay and point to

    Artificial Neural Network (ANN) is widely used in many complex applications. Artificial neural network is a statistical intelligent technique resembling the characteristic of the human neural network.  The prediction of time series from the important topics in statistical sciences to assist administrations in the planning and make the accurate decisions, so the aim of this study is to analysis the monthly hypertension in Kalar for the period (January 2011- June 2018) by applying an autoregressive –integrated- moving average model  and artificial neural networks and choose the best and most efficient model for patients with hypertension in Kalar through the comparison between neural networks and Box- Je

Background: Periodontal diseases are inflammatory disorders caused by the accumulation of oral biofilm and the host response to this accumulation which characterized by exaggerated leukocytes and neutrophils attraction to the sites of inflammation by chemoattractants which are a very important part of the pathogenesis of periodontal diseases. This study aimed to determine and compare the clinical periodontal parameters and the leukocyte cell types in the peripheral blood between patients with gingivitis and periodontitis with different severities compared to healthy controls. Materials and methods: This study included 150 male subjects aged between 35-50 years. They were divided into three groups: gingivitis group (n=30), periodontitis p

Background: Preoperative radiographical assessment of the maxillofacial lesions is of a great importance in guiding the surgeon during surgical procedure in reducing post-operative complications. This study highlighted the application of CBCT scan in the assessment of maxillofacial cystic and cystic like lesions as a part of advanced radiology Materials and methods: A total of 20 patients (15 males and 5 females) participated in this prospective study. CBCT scan (Kodak 9500 CBCT) with (DICOM) software utilized to perform scanning to all patients in order to assess lesion extension, morphological features and it’s relation to the adjacent vital structures. Results: In this study, the total cystic and cystic like lesions involving the

 Background: pedicular screw fixation is rapidly becoming a widely used method of spinal instrumentation. Despite improvement in design of instruments and surgical technique and the use of intra-operative fluoroscopy, pedicle cortical perforations occur endangering nearby neurovascular or extra vertebral structures.
Objective: This is a prospective (consecutive cases study) designed for Evaluation of incidence of pedicle screw misplacement in our study sample, compare our results to what is published in literature.
Patients and Method: This study involved 25 adult patients ( 10 males and 15 females ) their age ranged between ( 18 and 70 years) who underwent spinal surgery with pedicle screw fixation for different disorders of

Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a

This study delves into the realm of advanced cooling techniques by examining the performance of a two-stage parallel flow indirect evaporative cooling system enhanced with aspen pads in the challenging climate of Baghdad. The objective was to achieve average air dry bulb temperatures (43 ^oC) below the ambient wet bulb temperatures (24.95 ^oC) with an average relative humidity of 23%, aiming for unparalleled cooling efficiency. The research experiment was carried out in the urban environment of Baghdad, characterized by high temperature conditions. The investigation focused on the potential of the two-stage parallel flow setup, combined with the cooling capability of aspen pads, to surpass the limitat