|
|
|
|
|
Bohdan Petryshyn, Serhii Postupaiev, Soufiane Ben Bari and Armantas Ostreika
The development of autonomous driving models through reinforcement learning has gained significant traction. However, developing obstacle avoidance systems remains a challenge. Specifically, optimising path completion times while navigating obstacles is ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jiangtao Chen, Jiao Zhao, Wei Xiao, Luogeng Lv, Wei Zhao and Xiaojun Wu
Given the randomness inherent in fluid dynamics problems and limitations in human cognition, Computational Fluid Dynamics (CFD) modeling and simulation are afflicted with non-negligible uncertainties, casting doubts on the credibility of CFD. Scientifica...
ver más
|
|
|
|
|
|
|
|
|
|
|
Touraj Farsadi, Majid Ahmadi, Melin Sahin, Hamed Haddad Khodaparast, Altan Kayran and Michael I. Friswell
In the field of aerospace engineering, the design and manufacturing of high aspect ratio composite wings has become a focal point of innovation and efficiency. These long, slender wings, constructed with advanced materials such as carbon fiber and employ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ehab Alkhateeb, Ali Ghorbani and Arash Habibi Lashkari
This research addresses a critical need in the ongoing battle against malware, particularly in the form of obfuscated malware, which presents a formidable challenge in the realm of cybersecurity. Developing effective antivirus (AV) solutions capable of c...
ver más
|
|
|
|
|
|
|
|
|
|
|
George Papazafeiropoulos and Vagelis Plevris
To facilitate the precise design of earthquake-resistant structures, it is imperative to accurately evaluate the impact of seismic events on these constructions and predict their responses. OpenSeismoMatlab, a robust, free ground motion data processing s...
ver más
|
|
|
|
|
|
|
|
|
|
|
Abdul Rehman Khalid, Nsikak Owoh, Omair Uthmani, Moses Ashawa, Jude Osamor and John Adejoh
In the era of digital advancements, the escalation of credit card fraud necessitates the development of robust and efficient fraud detection systems. This paper delves into the application of machine learning models, specifically focusing on ensemble met...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zahid Masood, Muhammad Usama, Shahroz Khan, Konstantinos Kostas and Panagiotis D. Kaklis
Generative models offer design diversity but tend to be computationally expensive, while non-generative models are computationally cost-effective but produce less diverse and often invalid designs. However, the limitations of non-generative models can be...
ver más
|
|
|
|
|
|
|
|
|
|
|
Fan Zhu, Meng Zhang, Fuxuan Ma, Zhihua Li and Xianqiang Qu
Wind turbine towers experience complex dynamic loads during actual operation, and these loads are difficult to accurately predict in advance, which may lead to inaccurate structural fatigue and strength assessment during the structural design phase, ther...
ver más
|
|
|
|
|
|
|
|
|
|
|
Filippo Giorcelli, Sergej Antonello Sirigu, Giuseppe Giorgi, Nicolás Faedo, Mauro Bonfanti, Jacopo Ramello, Ermanno Giorcelli and Giuliana Mattiazzo
Among the challenges generated by the global climate crisis, a significant concern is the constant increase in energy demand. This leads to the need to ensure that any novel energy systems are not only renewable but also reliable in their performance. A ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xiyun Ge, Hongkun Zhou, Junbo Zhao, Xiaowei Li, Xinyu Liu, Jin Li and Chengming Luo
With the extensive application of sensor technology in scientific ocean research, ocean resource exploration, underwater engineering construction, and other fields, underwater target positioning technology has become an important support for the ocean fi...
ver más
|
|
|
|
|
|