The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

Quantum key distribution (QKD) provides unconditional security in theory. However, practical QKD systems face challenges in maximizing the secure key rate and extending transmission distances. In this paper, we introduce a comparative study of the BB84 protocol using coincidence detection with two different quantum channels: a free space and underwater quantum channels. A simulated seawater was used as an example for underwater quantum channel. Different single photon detection modules were used on Bob’s side to capture the coincidence counts. Results showed that increasing the mean photon number generally leads to a higher rate of coincidence detection and therefore higher possibility of increasing the secure key rate. The secure key rat

􀀨􀀅􀀆􀀔􀀜􀀄􀀂􀀆􀀈􀀓􀀌􀀩􀀏􀀆􀀉􀀅􀀆􀀉􀀅􀀉􀀚􀀝􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀓􀀚􀀁􀀔􀀄􀀓􀀅􀀆􀀄􀀂􀀆􀀔􀀓􀀆􀀃􀀂􀀔􀀄􀀟􀀉􀀔􀀃􀀆􀀔􀀜􀀃􀀆􀀛􀀃􀀜􀀄􀀗􀀚􀀃􀀆􀀗􀀌􀀄􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀘􀀃􀀃􀀊􀀂􀀆􀀓􀀖􀀆􀀓􀀛􀀃􀀌􀀔􀀁􀀌􀀅􀀄􀀅􀀕􀀢􀀆􀀪􀀜􀀃􀀆􀀄􀀅􀀛􀀃􀀂􀀔􀀄􀀕􀀉􀀔􀀄􀀓􀀅􀀂􀀆 􀀉􀀌􀀃􀀆􀀙􀀉􀀂􀀃􀀊􀀆􀀓􀀅􀀆􀀉􀀁􀀔􀀓􀀟􀀓􀀙􀀄􀀚􀀃􀀆􀀚􀀉􀀔􀀃􀀌􀀉􀀚􀀆􀀂􀀘􀀉􀀗􀀃􀀆􀀟􀀄􀀊􀀂􀀔􀀆􀀔􀀜􀀃􀀆􀀗􀀃􀀅􀀔􀀃􀀌􀀚􀀄􀀅􀀃􀀂􀀆􀀓􀀖􀀆􀀔􀀜􀀃􀀆􀀙􀀉􀀂􀀃􀀆

Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa

The purpose of this paper is to gain a good understanding about wake region behind the car body due to the aerodynamic effect when the air flows over the road vehicle during its movement. The main goal of this study is to discuss the effect of the geometry on the wake region and the aerodynamic drag coefficient. Results will be achieved by using two different shapes, which are the fastback and the notchback. The study will be implemented by the Computational Fluid Dynamic (CFD) by using STAR-CCM+^® software for the simulation. This study investigates the steady turbulent flow using k-epsilon turbulence model. The results obtained from the simulation show that the region of the air separation behind the vehicle