Zobrazeno 1 - 10
of 1 366
pro vyhledávání: '"A. Fayyazi"'
In cybersecurity, security analysts face the challenge of mitigating newly discovered vulnerabilities in real-time, with over 300,000 Common Vulnerabilities and Exposures (CVEs) identified since 1999. The sheer volume of known vulnerabilities complic
Externí odkaz:
http://arxiv.org/abs/2410.17406
Vision Transformers (ViTs) represent a groundbreaking shift in machine learning approaches to computer vision. Unlike traditional approaches, ViTs employ the self-attention mechanism, which has been widely used in natural language processing, to anal
Externí odkaz:
http://arxiv.org/abs/2407.12736
This paper presents ARCO, an adaptive Multi-Agent Reinforcement Learning (MARL)-based co-optimizing compilation framework designed to enhance the efficiency of mapping machine learning (ML) models - such as Deep Neural Networks (DNNs) - onto diverse
Externí odkaz:
http://arxiv.org/abs/2407.08192
Inter-neuron communication delays are ubiquitous in physically realized neural networks such as biological neural circuits and neuromorphic hardware. These delays have significant and often disruptive consequences on network dynamics during training
Externí odkaz:
http://arxiv.org/abs/2407.05494
The deployment of Vision Transformers (ViTs) on hardware platforms, specially Field-Programmable Gate Arrays (FPGAs), presents many challenges, which are mainly due to the substantial computational and power requirements of their non-linear functions
Externí odkaz:
http://arxiv.org/abs/2406.14854
Autor:
Karamuftuoglu, Mustafa Altay, Ucpinar, Beyza Zeynep, Fayyazi, Arash, Razmkhah, Sasan, Kamal, Mehdi, Pedram, Massoud
A novel high-fan-in differential superconductor neuron structure designed for ultra-high-performance Spiking Neural Network (SNN) accelerators is presented. Utilizing a high-fan-in neuron structure allows us to design SNN accelerators with more synap
Externí odkaz:
http://arxiv.org/abs/2402.16384
Tactics, Techniques, and Procedures (TTPs) outline the methods attackers use to exploit vulnerabilities. The interpretation of TTPs in the MITRE ATT&CK framework can be challenging for cybersecurity practitioners due to presumed expertise and complex
Externí odkaz:
http://arxiv.org/abs/2401.00280
This paper introduces NeuroBlend, a novel neural network architecture featuring a unique building block known as the Blend module. This module incorporates binary and fixed-point convolutions in its main and skip paths, respectively. There is a judic
Externí odkaz:
http://arxiv.org/abs/2307.03784
Altered expression of Csnk1a1p in Autism Spectrum Disorder in Iranian population: case-control study
Autor:
Zahra Rahmani, Dina Rahmani, Marie Saghaeian Jazi, Mohammad-Reza Ghasemi, Hossein Sadeghi, Mohammad Miryounesi, Katayoon Razjouyan, Mohammad Reza Fayyazi Bordbar
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-8 (2024)
Abstract Over the past decade, substantial scientific evidence has showed that long non-coding RNAs (lncRNAs) are extensively expressed and play a crucial role in gene modulation through a diverse range of transcriptional, and post-transcriptional me
Externí odkaz:
https://doaj.org/article/7fd5663ca4164e5c8c513987cfd54de4
Autor:
Habibolah Khazaie, Amir Jalali, Amirhossein Khazaie, Reza Mohammadi, Romina Jalali, Sobhan Bagheri Moheb, Mirfarhad Ghalebandi, Fatemeh Kashaninasab, Ali Ghaleiha, Mohammadreza Shalbafan, Seyed Mojtaba Yassini Ardekani, Azad Maroufi, Ebrahim Ezzati, Seyed Ali Dastgheib, Mohammadreza Fayyazi Bordbar, Mahboobeh Khoozan, Saeedeh Negahban, Seyed Abolfazl Ghoreishi, Farzin Rezaei, Koresh Saki, Ali Jalali, Yahya Salimi, Mohammad Raza Khodaie Ardakan
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Background Sleep disorders can be harmful to our health and treating them can also be expensive. Due to the widespread occurrence and impact of sleep disorders, it is valuable to investigate and study them from an epidemiological perspective
Externí odkaz:
https://doaj.org/article/341cdb21235947139c1d6c8d29d049c0