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of 2 423 380
pro vyhledávání: '"Ali, A A"'
Federated Learning (FL) is a distributed learning technique that maintains data privacy by providing a decentralized training method for machine learning models using distributed big data. This promising Federated Learning approach has also gained po
Externí odkaz:
http://arxiv.org/abs/2411.05173
In this research, we define two concepts; random matrix and mean square stability. Studying the stability of solutions for perturbed random differential systems is included. Partial moments of the second order were verified, which determines the stab
Externí odkaz:
http://arxiv.org/abs/2411.04929
In this study, we investigate the performance of the sparse identification of nonlinear dynamics (SINDy) algorithm and the neural ordinary differential equations (ODEs) in identification of the underlying mechanisms of open ocean Lagrangian drifter h
Externí odkaz:
http://arxiv.org/abs/2411.04350
Autor:
Zhiany, Saeed, Ghassemi, Fatemeh, Abbasimoghadam, Nesa, Hodaei, Ali, Ataollahi, Ali, Kovács, József, Ábrahám, Erika, Sirjani, Marjan
Hybrid Rebeca is introduced for modeling asynchronous event-based Cyber-Physical Systems (CPSs). In this work, we extend Hybrid Rebeca to allow the modeling of non-deterministic time behavior. We provide a set of rules to define the semantic model of
Externí odkaz:
http://arxiv.org/abs/2411.03160
This paper introduces a real-time Vehicle Collision Avoidance System (V-CAS) designed to enhance vehicle safety through adaptive braking based on environmental perception. V-CAS leverages the advanced vision-based transformer model RT-DETR, DeepSORT
Externí odkaz:
http://arxiv.org/abs/2411.01963
Current work includes a study of the very rare case called intruder nuclear levels, where there are only seven nuclei in nature. Such cases occur when the first excited state is . The current study included only three nuclei: . The nuclear model used
Externí odkaz:
http://arxiv.org/abs/2410.20566
Autor:
TehraniJamsaz, Ali, Bhattacharjee, Arijit, Chen, Le, Ahmed, Nesreen K., Yazdanbakhsh, Amir, Jannesari, Ali
Recent advancements in Large Language Models (LLMs) have renewed interest in automatic programming language translation. Encoder-decoder transformer models, in particular, have shown promise in translating between different programming languages. How
Externí odkaz:
http://arxiv.org/abs/2410.20527
Autor:
Ali, Parvez, Baby, Annmaria, Xavier, D. Antony, Varghese, Eddith Sarah, A., Theertha Nair, Ali, Haidar
The modern era always looks into advancements in technology. Design and topology of interconnection networks play a mutual role in development of technology. Analysing the topological properties and characteristics of an interconnection network is no
Externí odkaz:
http://arxiv.org/abs/2411.04135
We present an advanced approach to medical question-answering (QA) services, using fine-tuned Large Language Models (LLMs) to improve the accuracy and reliability of healthcare information. Our study focuses on optimizing models like LLaMA-2 and Mist
Externí odkaz:
http://arxiv.org/abs/2410.16088
While recent advances in deep learning (DL) for surgical scene segmentation have yielded promising results on single-center and single-imaging modality data, these methods usually do not generalize well to unseen distributions or modalities. Even tho
Externí odkaz:
http://arxiv.org/abs/2410.14821