In this study, we introduce new a nanocomposite of functionalize graphene oxide FGO and functionalize multi wall carbon nanotube (F-MWCNT-FGO).The formation of nanocomposite was confirmed by FT-IR ,XRD and SEM. The magnitude of the dielectric permittivity of the (F-MWCNT-FGO) nanocomposite appears to be very high in the low frequency range and show a unique negative permittivity at frequencies range from 400 Hz to 4000Hz. The ac conductivity of nanocomposite reaches 23.8 S.m-1 at 100Hz.

Rutting is a predominant distress in asphalt pavements, particularly in hot climatic regions. This study systematically investigated the high-temperature performance of hot mix asphalt modified with five nanomaterials, namely, nano-silica (NS), nano-alumina (NA), nano-titanium (NT), nano-zinc (NZ), and carbon nanotubes (CNTs), under consistent laboratory conditions. Modification dosages were selected up to 10% for NS, NA, and NT, and up to 5% for NZ and CNTs. The experimental methodology comprised the following: (i) binder rheological characterization through rotational viscosity, G*/sinδ, and multiple stress creep recovery (MSCR) to quantify rutting susceptibility; (ii) chemical and microstructural assessments using Fourier transf

Iraqi bentonite is used as main material for preparing ceramic samples with the additions of alumina and magnesia. X-ray diffractions analyses were carried out for the raw material at room temperature. The sequence of mineral phase's transformations of the bentonite for temperatures 1000 ,1100 ,1200 and 1250 ºC reflects that it finally transformed in to mullite 39.18% and cristobalite 62.82%. Samples of different weight constituent were prepared. The effect of its constitutional change reveals through its heat treatments at 1000,1100,1200,1250and 1300ºC .The samples of additions less than 15% of alumina and magnesia could not stand up to 1300ºC while the samples of addition more than 15% are stable .That is shown by analy

Background: syndrome X or metabolic syndrome is a collection of multiple diseases mainly visceral obesity , hypertriglyceridemia , decrease HDL level, hypertension and elevated fasting blood glucose that lead to accelerated atherosclerosis through multiple mechanisms, one of the most important is increase inflammation of the vessels manifested by elevated high sensitivity C reactive protein (hs-CRP).Objective: The aim of the study was to assess the prevalence of elevatedhs CRP in people with metabolic syndrome and atherosclerosis complication (IHD, Cerebrovascular disease, peripheral vascular disease) and metabolic syndrome without these complication.Patients and methods:;This is a cross sectional study carried out in Diabetic referral c

Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co

Mobile ad hoc network security is a new area for research that it has been faced many difficulties to implement. These difficulties are due to the absence of central authentication server, the dynamically movement of the nodes (mobility), limited capacity of the wireless medium and the various types of vulnerability attacks. All these factor combine to make mobile ad hoc a great challenge to the researcher. Mobile ad hoc has been used in different applications networks range from military operations and emergency disaster relief to community networking and interaction among meeting attendees or students during a lecture. In these and other ad hoc networking applications, security in the routing protocol is necessary to protect against malic

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

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