Metoclopramide (MCP) ion selective electrodes based on metoclopramide-phosphotungstic acid (MCP-PT) ion pair complex in PVC matrix membrane were constructed. The plasticizers used were tri-butyl phosphate (TBP), di-octyl phenyl phosphonate (DOPP), di-butyl phthalate (DBPH), di-octyl phthalate (DOP), di-butyl phosphate (DBP), bis 2-ethyl hexyl phosphate (BEHP). The sensors based on TBP, DOPP, DBPH and DOP display a fast, stable and linear response with slopes 59.9, 57.7, 57.4, 55.3 mV/decade respectively at pH ranged 2-6. The linear concentration range between 1.0×10^-5 – 1.0×10^-2 M with detection limit 3.0×10^-6 and 4.0×10^-6 M for electrodes using TBP, DOPP and DBPH while e

Carbonate-clastic succession which includes the Shu'aiba, Nahr Umr and Mauddud formations are representing a part of the Barremian-Aptian Sequence (Wasi'a Group). The present study includes three boreholes (Ba-1, 4 and 8) within the Balad Oil Field. The study area is located in central Iraq. This field represents a subsurface anticline with a northwest to southeast direction axis within the Mesopotamian Zone. Eight types of microfacies were recognized in the succession of the Mauddud and Shu’aiba formations. These microfacies represent shallow open marine, restricted and semi-restricted, reef - back reef, deep open marine and basinal depositional environments. While Nahr Umr Formation includes two successions, the first is the upp

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

Realizing robust interconnectivity in a rapidly changing network topology is a challenging issue. This problem is escalating with the existence of constrained devices in a vehicular environment. Several standards have been developed to support reliable communication between vehicular nodes as the IEEE 1609 WAVE stack. Mitigating the impact of security/mobility protocols on limited capability nodes is a crucial aspect. This paper examines the burden of maintaining authenticity service that associated with each handover process in a vehicular network. Accordingly, a network virtualization-based infrastructure is proposed which tackles the overhead of IEEE 1906 WAVE standard on constrained devices existed in vehicular network. The virtualized

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