Zobrazeno 1 - 10
of 820
pro vyhledávání: '"Ghanem, Mohamed"'
Publikováno v:
GMS Interdisciplinary Plastic and Reconstructive Surgery DGPW, Vol 13, p Doc02 (2024)
Arthrodesis of the knee joint has proven effective in the treatment of chronic periprosthetic infections as well as in cases of previous multiple revision surgery after total knee replacement with insufficiency of the extensor apparatus. In this case
Externí odkaz:
https://doaj.org/article/1f58d8573f774acd920bbd3f5005013a
Publikováno v:
GMS Interdisciplinary Plastic and Reconstructive Surgery DGPW, Vol 13, p Doc01 (2024)
Mega-endoprostheses enable wide management options in the treatment of primary and periprosthetic fracture of the lower extremities. In this study, we report on the use of custom-made subtotal diaphyseal endoprosthetic replacement in treatment of int
Externí odkaz:
https://doaj.org/article/4e3b0d1c05c94f99abb194bf4c0b36de
Publikováno v:
The 11th IEEE International Conference on Social Networks Analysis, Management and Security (SNAMS-2024)
This Research proposes a Novel Reinforcement Learning (RL) model to optimise malware forensics investigation during cyber incident response. It aims to improve forensic investigation efficiency by reducing false negatives and adapting current practic
Externí odkaz:
http://arxiv.org/abs/2410.15028
This paper investigates the application of Deep Reinforcement Learning (DRL) for attributing malware to specific Advanced Persistent Threat (APT) groups through detailed behavioural analysis. By analysing over 3500 malware samples from 12 distinct AP
Externí odkaz:
http://arxiv.org/abs/2410.11463
Timeline Analysis (TA) plays a crucial role in Timeline Forensics (TF) within the field of Digital Forensics (DF). It focuses on examining and analyzing time-based digital artefacts, such as timestamps derived from event logs, file metadata, and othe
Externí odkaz:
http://arxiv.org/abs/2409.02572
This research focused on enhancing post-incident malware forensic investigation using reinforcement learning RL. We proposed an advanced MDP post incident malware forensics investigation model and framework to expedite post incident forensics. We the
Externí odkaz:
http://arxiv.org/abs/2408.01999
Autor:
Farzaan, Mohammed Ashfaaq M., Ghanem, Mohamed Chahine, El-Hajjar, Ayman, Ratnayake, Deepthi N.
The escalating sophistication and volume of cyber threats in cloud environments necessitate a paradigm shift in strategies. Recognising the need for an automated and precise response to cyber threats, this research explores the application of AI and
Externí odkaz:
http://arxiv.org/abs/2404.05602
Publikováno v:
GMS Interdisciplinary Plastic and Reconstructive Surgery DGPW, Vol 9, p Doc01 (2020)
Externí odkaz:
https://doaj.org/article/74bbebbe336a453896cd2a9b9696acb9
Publikováno v:
GMS Interdisciplinary Plastic and Reconstructive Surgery DGPW, Vol 8, p Doc18 (2019)
Type IV allergies to nickel sulfate, potassium dichromate and/or cobalt chloride are supposed to be associated with aseptic loosening, pain or infections in patients with hip arthroplasty. However, there is debate on any causal relation between type
Externí odkaz:
https://doaj.org/article/39472300e7884ef987eef05e55891a09
Training neural networks on NP-complete problems typically demands very large amounts of training data and often needs to be coupled with computationally expensive symbolic verifiers to ensure output correctness. In this paper, we present NeuRes, a n
Externí odkaz:
http://arxiv.org/abs/2402.08365