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Öğe The Avoidance and Detection Function of Artificial Intelligence in Covid-19(Institute of Electrical and Electronics Engineers Inc., 2021) Abdulateef, A.A.; Mohammed, A.H.; Abdulateef, I.A.The whole planet today is having to fight COVID-19 with big obstacles. The COVID-19 influenced several countries around the world between December 2019 and the present day. Many organisations and scientists seek to find a vaccine and to minimize the spread of COVID-19. Artificial Intelligence is one technology that can successfully address this virus (AI). In the case of other pathogens, artificial intelligence performed very well and could help us cope with the virus COVID-19, too. It is the imagination and the information of the people who use it which will help to overcome this dilemma. In some previous instances AI played a major role in virus prevention and identification. We have an ability to detect certain aspects of the AI because of the COVID-19 crisis. Machine learning that an AI subclass is used to identify patterns and to plan valuable knowledge based on recorded data sets. At the point where used entirely, AI can exceed human efforts by speed and differentiate designs from knowledge previously ignored. However many correct and appropriate data are needed for effective implementation of AI systems. This paper discusses the AI's role in COVID-19 prevention and detection and examines numerous technological aspects of AI. This paper would also clarify where AI will contribute with likely solutions to stop the spread of COVID-19. © 2021 IEEE.Öğe Cloud Computing Security for Algorithms(Institute of Electrical and Electronics Engineers Inc., 2020) Abdulateef, A.A.; Mohammed, A.H.; Abdulateef, I.A.Distributed computing (CC), without unequivocal and direct use oversight, gives the chance of on request admittance to arrange framework, specifically to information handling and capacity limits. As of late, CC has emerged as a network of public and private server farms giving a typical online interface to customers. Edge registering is a developing model of figuring that takes handling and capacity closer to end-clients to build reaction times and capacity for reinforcement move. Versatile CC (MCC) pushes programming to cell phones by utilizing disseminated figuring. Registering and edge processing, in any case, are confronting security issues, including framework weaknesses and association identification, that quickly postpones figuring models' acknowledgment. The investigation of PC algo-lithms, which definitely create through training, is AI (ML). We assess security dangers, difficulties and arrangements that utilization at least one ML calculations in this examination report. In this report we have We study various AI calculations, including regulated, unattended, semi-administered, and improved learning, used to tackle cloud security issues. At that point we look at every innovation 's proficiency dependent on its properties, advantages and burdens. Besides, we have potential testing suggestions to stable CC models. © 2020 IEEE.Öğe Hyperledger, Ethereum and Blockchain Technology: A Short Overview(Institute of Electrical and Electronics Engineers Inc., 2021) Mohammed, A.H.; Abdulateef, A.A.; Abdulateef, I.A.Blockchain is a tamper-proof distributed ledger for tracking public or private pair transactions in pair networks that can not be retroactively changed without modifying all corresponding network blocks. The Consensus Protocol upgrades a blockchain, which guarantees a sequential, unambiguous transaction ordering. Blocks ensure that the blockchain is integral and uniform across a network of distributed nodes. Different blockchain implementations use different consensus protocols. This paper offers a brief overview of the most important discrepancies between the Hyperledger Fabric and Ethereum distributed ledger technologies (DLT). © 2021 IEEE.Öğe Performance Analyses of Channel Estimation and Precoding for Massive MIMO Downlink in the TDD System(Institute of Electrical and Electronics Engineers Inc., 2020) Abdulateef, A.A.; Ibrahim, S.M.; Mohammed, A.H.; Abdulateef, I.A.The fundamental limitation of massive MIMO technology is pilot contamination effect. This effect occurs during uplink training when terminals use the same orthogonal signals. In this paper, a pilot reuse factor with large scale fading precoding is proposed to mitigate the pilot contamination effect. The pilot reuse factor is designed to assign unique orthogonal signals to the adjacent cells. These unique orthogonal signals are reused only within the cell and hence, intra-pilot contamination is the only concern. Large scale fading precoding is then used to mitigate the intra-pilot contamination effect. The average achievable sum rate is computed for different pilot reuse factors. Experimental results through MATLAB simulation show that a higher pilot reuse factor gives better average achievable sum rates. © 2020 IEEE.Öğe Wireless Body Region Networks Abnormality Identification and Energy Saving A Study(Institute of Electrical and Electronics Engineers Inc., 2020) Al-Sabti, S.M.B.; Abdulateef, A.A.; Atilla, C.; Mohammed, A.H.Current advances in wireless body networking technologies help to escape any of the healthcare industry-related problems. Wearable biomedical devices and their related innovations are in vogue lately, with constant health surveillance being mandatory for many chronic patients. Energy conservation is critical in wireless body area networks (WBANs) since the sensor nodes are energy constraint devices. Energy conservation through data reduction approaches in WBANs is a comparatively less explored area in which the detection of probabilistic anomaly models is becoming inevitable for the prevention of serious health problems. This paper reviews wireless body area networks for anomaly detection in various applications and discusses how models can be made for the energy conservation of WBAN devices. © 2020 IEEE.
