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.

Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

Commercially pure titanium (cpTi) is widely used as dental implant material although it was found that titanium exhibited high modulus of elasticity and the lower corrosion tendency in oral environment. Niobium(Nb) was chosen for this study as an alternative to cpTi implant material due to its bioinert behavior and good elastic modulus and moderate cost in addition to corrosion resistance. This study was done to evaluate the effect of biomimetic coating on the surface properties of the commercially pure titanium and niobium implants by in vitro and in vivo experiments. The in vitro study was involved etching the samples of each material in HCl then soaking in 10M NaOH aqueous solution. These samples were then immersed in a 5 times concent

The Optical Fiber sensor based on the Surface Plasmon Resonance (SPR) technology has
been a successful performance sensing and presents high sensitivity. This thesis investigates the
performance of several structure of SPR sensor in field of refractive index and chemical
applications. A structure of Multi-Mode Fiber- Single Mode Fiber- Multi Mode Fiber (MMFSMF-MMF)

Localization is an essential demand in wireless sensor networks (WSNs). It relies on several types of measurements. This paper focuses on positioning in 3-D space using time-of-arrival- (TOA-) based distance measurements between the target node and a number of anchor nodes. Central localization is assumed and either RF, acoustic or UWB signals are used for distance measurements. This problem is treated by using iterative gradient descent (GD), and an iterative GD-based algorithm for localization of moving sensors in a WSN has been proposed. To localize a node in 3-D space, at least four anchors are needed. In this work, however, five anchors are used to get better accuracy. In GD localization of a moving sensor, the algo