Zobrazeno 1 - 10
of 47 490
pro vyhledávání: '"A. A. Mousavi"'
Publikováno v:
Brazilian Journal of Biology, Vol 84 (2024)
Abstract Rapeseed (Brassica napus L.) is one of the most important oil crops in terms of economics, ecology, and nutrition. For the purpose of selecting the most suitable canola genotypes for quantitative and qualitative traits, an experiment was con
Externí odkaz:
https://doaj.org/article/269e656b8fd64de98ac3d89b33547173
Publikováno v:
Tulīd va Farāvarī-i Maḥṣūlāt-i Zirā̒ī va Bāghī, Vol 12, Iss 4, Pp 169-184 (2023)
It is important to determine the appropriate planting density in the conditions of using old seedlings of paddy rice. For this purpose, a field experiment was conducted as a randomized complete block design at Qaemshahr, Northern Iran, in four replic
Externí odkaz:
https://doaj.org/article/a0c419876f18428a913094124b550783
In audio and speech processing, tasks usually focus on either the audio or speech modality, even when both sounds and human speech are present in the same audio clip. Recent Auditory Large Language Models (ALLMs) have made it possible to process audi
Externí odkaz:
http://arxiv.org/abs/2409.14526
We show that on a $\sigma$-finite measure preserving system $X = (X,\nu, T)$, the non-conventional ergodic averages $$ \mathbb{E}_{n \in [N]} \Lambda(n) f(T^n x) g(T^{P(n)} x)$$ converge pointwise almost everywhere for $f \in L^{p_1}(X)$, $g \in L^{p
Externí odkaz:
http://arxiv.org/abs/2409.10510
Autor:
Naug, Avisek, Guillen, Antonio, Luna, Ricardo, Gundecha, Vineet, Rengarajan, Desik, Ghorbanpour, Sahand, Mousavi, Sajad, Babu, Ashwin Ramesh, Markovikj, Dejan, Kashyap, Lekhapriya D, Sarkar, Soumyendu
Machine learning has driven an exponential increase in computational demand, leading to massive data centers that consume significant amounts of energy and contribute to climate change. This makes sustainable data center control a priority. In this p
Externí odkaz:
http://arxiv.org/abs/2408.07841
Autor:
Pradeep, Ronak, Lee, Daniel, Mousavi, Ali, Pound, Jeff, Sang, Yisi, Lin, Jimmy, Ilyas, Ihab, Potdar, Saloni, Arefiyan, Mostafa, Li, Yunyao
The rapid advancement of Large Language Models (LLMs) and conversational assistants necessitates dynamic, scalable, and configurable conversational datasets for training and evaluation. These datasets must accommodate diverse user interaction modes,
Externí odkaz:
http://arxiv.org/abs/2408.05948
The E-learning environment offers greater flexibility compared to face-to-face interactions, allowing for adapting educational content to meet learners' individual needs and abilities through personalization and customization of e-content and the edu
Externí odkaz:
http://arxiv.org/abs/2408.12619
Autor:
Khaleghi, Seyed Saleh Mousavi, Wei, Jianyong, Liu, Yumeng, Fan, Zhengfang, Li, Kai, Crozier, Kenneth B., Dan, Yaping
Photodetectors based on two-dimensional (2D) atomically thin semiconductors suffer from low light absorption, limiting their potential for practical applications. In this work, we demonstrate a high-performance MoS2 phototransistors by integrating fe
Externí odkaz:
http://arxiv.org/abs/2408.04141
Autor:
Wang, Ziyu, Kanduri, Anil, Aqajari, Seyed Amir Hossein, Jafarlou, Salar, Mousavi, Sanaz R., Liljeberg, Pasi, Malik, Shaista, Rahmani, Amir M.
While ECG data is crucial for diagnosing and monitoring heart conditions, it also contains unique biometric information that poses significant privacy risks. Existing ECG re-identification studies rely on exhaustive analysis of numerous deep learning
Externí odkaz:
http://arxiv.org/abs/2408.10228
Autor:
Ravanelli, Mirco, Parcollet, Titouan, Moumen, Adel, de Langen, Sylvain, Subakan, Cem, Plantinga, Peter, Wang, Yingzhi, Mousavi, Pooneh, Della Libera, Luca, Ploujnikov, Artem, Paissan, Francesco, Borra, Davide, Zaiem, Salah, Zhao, Zeyu, Zhang, Shucong, Karakasidis, Georgios, Yeh, Sung-Lin, Champion, Pierre, Rouhe, Aku, Braun, Rudolf, Mai, Florian, Zuluaga-Gomez, Juan, Mousavi, Seyed Mahed, Nautsch, Andreas, Liu, Xuechen, Sagar, Sangeet, Duret, Jarod, Mdhaffar, Salima, Laperriere, Gaelle, Rouvier, Mickael, De Mori, Renato, Esteve, Yannick
SpeechBrain is an open-source Conversational AI toolkit based on PyTorch, focused particularly on speech processing tasks such as speech recognition, speech enhancement, speaker recognition, text-to-speech, and much more. It promotes transparency and
Externí odkaz:
http://arxiv.org/abs/2407.00463