Sana'a University Journal of Applied Sciences and Technology

The existence of metrics for Intelligent systems is very important in order to evaluate, manage, and classify them. Intelligent information systems (IIS) have become a significant part of our daily lives, institutions, and ongoing business, and it has become necessary to have metrics for Intelligent systems in order to measure the success of organizations in using Intelligent systems. In this study, We will choose a group of metrics for intelligent systems, work to develop them, and then determine their source and method of mitigation. It defines the phrase "intelligent systems metrics" and goes over the key metrics and guidelines that can be used to define IISM as well as which metrics have the biggest influence. The significance of each metric in gauging various intelligent systems will be determined, and when these metrics have been reviewed, the effects of each criterion on IIS will be clear.

The signature verification process has many applications, such as its use in financial operations, providing the electronic signature of documents, and providing an additional confidentiality standard to verify the identity of users in computer systems. This process has the advantage of being accepted by the community and is less intrusive compared to other biological methods. Deep learning (DL) and CNN (Convolutional Neural Network) are widely used by bioinformaticians. Due to the difficulty in extracting features in other systems or models, DL and CNN-based signature verification systems have been significantly improved. Yet Hyperparameter optimization for CNN models remains a challenging problem in designing highly efficient models with the most accurate results. It is often convolutional neural network (CNN) models that are manually designed. The proposed method is focused on a genetic algorithm that develops a population of CNN models in order to find the best fit architecture for designing an offline signature verification model. Our model is tested on more than one dataset, BHSig260-Bengali, BHSig260-Hindiin, GPDS, and CEDAR. The result of the approach proposed in this paper has the highest discrimination rate of FRR of 2.5, FAR 3.2, EER 2.35, and 97.73 %-accuracy rate.

The Vehicle Network (VANET) is a component of the Intelligent Transport System (ITS), for the exchange of messages between vehicles and roadside units (RSU). While due to the increase in the number of vehicles, there have been a lot of privacy, trust, and security challenges related to the Vehicle Network (VANET). The information exchanged between vehicles must be correct to achieve the CIA principle. Trust, privacy, and security solutions don’t apply to centralized networks. Most importantly, the lack of confidentiality, privacy, and availability. In this paper, solutions to solve security problems using hierarchical blockchain technology will be presented. Hierarchical blockchain has the advantages of unanimously emphasizing message credibility, decentralization, and immutable storage. All these advantages will provide solutions to those problems and challenges related to the security of VANETs. This paper seeks two main objectives. The first is to monitor malicious and no malicious vehicles by UAV, to validate the message before sending it via VANET. The second is a set of complex rules and specific calculations to verify the message. Consensus algorithms are also used to agree among vehicles on what is true, and to evaluate performance using the following metrics (Throughput, tolerance, latency).

Materials Science is  concerned with the development or synthesis of  new materials  . For this reason our interest is focused on the fabrication of  new materials , such as  lead free solder alloys .  Sn-In alloys offer very low melting points and bond well with copper .This study  aims to investigate The Structural and mechanical properties of (82-x)Sn -18In alloys with added copper .The Samples were prepared by melting technology From high purity (99 %) elements tin ,indium and copper .XRD showed the formation of a single phase hexagonal structure with a small copper plane, and  the addition of copper decreased  the particle size of the  (82-x)Sn -18 In. The creep test  results showed that Cu-containing solder alloys exhibited significant improvements in creep resistance. However, the average activation energy decreases with copper addition from 0.322 to 0.247 eV.               

Based on the derived analytical formulae for the optical intensity and effective beam width of a partially coherent rectangular multi-Gaussian Schell-model (RMGSM) vortex beam, we analyzed the evolution of the effective beam width of a partially coherent RMGSM vortex beam propagating in an anisotropic turbulent plasma using numerical examples. The numerical results demonstrated that the effective beam widths in the x and y directions were similar. In studies on the influences of the source parameters, one can see that an RMGSM vortex beam with a larger topological charge  and beam waist  or a smaller correlation coefficient σ evolves into a beam with a larger effective beam width. However, the influence of beam order was not evident. In addition, numerical examples proved that the effective beam width increases with increasing propagation distance and refractive index fluctuation variance  or decreasing anisotropy parameter , outer scale , and  inner scale . This study's results will be beneficial for applications in free-space optical communications.

This study conducts a comprehensive analysis of different standards frameworks in cybersecurity to identify best practices and international standards. The primary objective is to propose an appropriate cybersecurity framework that aligns with global standards, effectively reducing the risks of cyberattacks and threats to data, information, networks, and devices within institutions. By enhancing cybersecurity, the framework aims to safeguard infrastructure. It further contributes to improved management of cybersecurity risks by incorporating the best global practices and local cybersecurity legislation. Through an examination of various cybersecurity frameworks, including NIST 800-53Ar4, COBIT, and ISO27002, the study finds that NIST 800-53Ar4 is the most effective framework. The researcher recommended adopting a hybrid approach that combines elements from multiple frameworks and standards.              

The microstructure of AS10/xNi hypoeutectic alloys with (x = 0.01% and 0.05%) was investigated using X-ray diffraction (XRD) and scanning electron microscopy (SEM). Localized permanent plastic deformation (Vickers hardness (HV)) was conducted on the samples before and after sintering. After sintering, the results showed a significant improvement in hardness with the addition of Ni atoms. From the XRD map, it was found that there was a shift in the peak positions as the Ni atoms were added. This shift is a result of the incoincidence of d_hkl levels in the Al-phase before and after the addition of Ni. This mismatch in d_hkl levels is associated with the lattice defects and lattice parameters. From the SEM images, the silicon powder particles in the binary composition are large and elongated plates, whereas those in the ternary composition are small and semi-spherical particles. This reduction in the particle size of the modified alloy is attributed to the presence of Ni atoms in the alloys.