Arabian Journal for Science and Engineering 

About: Arabian Journal for Science and Engineering is an academic journal published by Springer Nature. The journal publishes majorly in the area(s): Materials science & Heat transfer. It has an ISSN identifier of 2193-567X. Over the lifetime, 7052 publications have been published receiving 72089 citations.

Some Picture Fuzzy Aggregation Operators and Their Applications to Multicriteria Decision-Making

Abstract: The objective of the work is to present some series of the aggregation operators for the picture fuzzy sets (PFSs). As PFSs have been an extended version of the intuitionistic fuzzy set theory which not only considers the degree of acceptance or rejection but also taken into the account the degree of refusal during the analysis. Thus, by considering all these degrees, some aggregation operators, namely picture fuzzy weighted average, picture fuzzy ordered weighted average, and picture fuzzy hybrid average aggregation operators, have been proposed along with their desirable properties. A decision-making approach based on these operators has also been presented. Finally, an illustrative example has been given for demonstrating the approach.

DDoS Attack Detection and Mitigation Using SDN: Methods, Practices, and Solutions

Abstract: Distributed denial-of-service (DDoS) attacks have become a weapon of choice for hackers, cyber extortionists, and cyber terrorists. These attacks can swiftly incapacitate a victim, causing huge revenue losses. Despite the large number of traditional mitigation solutions that exists today, DDoS attacks continue to grow in frequency, volume, and severity. This calls for a new network paradigm to address the requirements of today’s challenging security threats. Software-defined networking (SDN) is an emerging network paradigm which has gained significant traction by many researchers to address the requirement of today’s data centers. Inspired by the capabilities of SDN, we present a comprehensive survey of existing SDN-based DDoS attack detection and mitigation solutions. We classify solutions based on DDoS attack detection techniques and identify requirements of an effective solution. Based on our findings, we propose a novel framework for detection and mitigation of DDoS attacks in a large-scale network which comprises a smart city built on SDN infrastructure. Our proposed framework is capable of meeting application-specific DDoS attack detection and mitigation requirements. The primary contribution of this paper is twofold. First, we provide an in-depth survey and discussion of SDN-based DDoS attack detection and mitigation mechanisms, and we classify them with respect to the detection techniques. Second, leveraging the characteristics of SDN for network security, we propose and present an SDN-based proactive DDoS Defense Framework (ProDefense). We show how this framework can be utilized to secure applications built for smart cities. Moreover, the paper highlights open research challenges, future research directions, and recommendations related to SDN-based DDoS detection and mitigation.

Modification and functionalization of multiwalled carbon nanotube (mwcnt) via fischer esterification

Abstract: Multiwalled carbon nanotubes (MWCNTs) were functionalized by different functional groups via the Fischer Esterification method. Nitric acid treatment was first used to remove the catalyst from MWCNTs and introduce carboxylic acid groups onto the surface of MWCNTs. These carboxylic groups were used as reaction precursors in the functionalization. Four functional groups―phenol, dodecylamine, 1-octadecanol, and polyethylene glycol―were successfully covalently attached to MWCNTs via amidation or esterification. The functionalized MWCNTs were then characterized by Fourier Transform Infrared (FTIR) spectroscopy, thermal analysis techniques, thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). The MWCNTs attached to the organofunctional moieties have greater versatility for further utilization in different application fields such as biology, nanocomposites, water treatment, petroleum, and petrochemical technologies. Key words : functionalized CNTs, Fischer Esterification, carboxylic acid groups, phenol, dodecylamine, 1-octadecanol, polyethylene glycol

A Nonlocal Higher-Order Shear Deformation Beam Theory for Vibration Analysis of Size-Dependent Functionally Graded Nanobeams

Abstract: In this paper, free vibration characteristics of functionally graded (FG) nanobeams based on third-order shear deformation beam theory are investigated by presenting a Navier-type solution. Material properties of FG nanobeam are supposed to change continuously along the thickness according to the power-law form. The effect of small scale is considered based on nonlocal elasticity theory of Eringen. Through Hamilton’s principle and third-order shear deformation beam theory, the nonlocal governing equations are derived and they are solved applying analytical solution. According to the numerical results, it is revealed that the proposed modeling can provide accurate frequency results for FG nanobeams as compared to some cases in the literature. The numerical investigations are presented to investigate the effect of the several parameters such as material distribution profile, small-scale effects, slenderness ratio and mode number on vibrational response of the FG nanobeams in detail. It is concluded that various factors such as nonlocal parameter and gradient index play notable roles in vibrational response of FG nanobeams.

Blockchain for COVID-19: Review, Opportunities, and a Trusted Tracking System.

Abstract: The sudden development of the COVID-19 pandemic has exposed the limitations in modern healthcare systems to handle public health emergencies. It is evident that adopting innovative technologies such as blockchain can help in effective planning operations and resource deployments. Blockchain technology can play an important role in the healthcare sector, such as improved clinical trial data management by reducing delays in regulatory approvals, and streamline the communication between diverse stakeholders of the supply chain, etc. Moreover, the spread of misinformation has intensely increased during the outbreak, and existing platforms lack the ability to validate the authenticity of data, leading to public panic and irrational behavior. Thus, developing a blockchain-based tracking system is important to ensure that the information received by the public and government agencies is reliable and trustworthy. In this paper, we review various blockchain applications and opportunities in combating the COVID-19 pandemic and develop a tracking system for the COVID-19 data collected from various external sources. We propose, implement, and evaluate a blockchain-based system using Ethereum smart contracts and oracles to track reported data related to the number of new cases, deaths, and recovered cases obtained from trusted sources. We present detailed algorithms that capture the interactions between stakeholders in the network. We present security analysis and the cost incurred by the stakeholders, and we highlight the challenges and future directions of our work. Our work demonstrates that the proposed solution is economically feasible and ensures data integrity, security, transparency, data traceability among stakeholders.