Výsledky vyhledávání - "Ahmed Shafique"

Akademický článek

DBD plasma‐assisted coating of metal alkoxides on sulfur powder for Li–S batteries

Autor: Ahmed Shafique, Annick Vanhulsel, Vijay S. Rangasamy, Kitty Baert, Tom Hauffman, Peter Adriaensens, Mohammadhosein Safari, Marlies K. Van Bael, An Hardy, Sébastien Sallard

Publikováno v: Battery Energy, Vol 2, Iss 4, Pp n/a-n/a (2023)

Abstract Sulfur particles coated by activation of metal alkoxide precursors, aluminum–sulfur (Alu–S) and vanadium–sulfur (Van–S), were produced by dielectric barrier discharge (DBD) plasma technology under low temperature and ambient pressure

Externí odkaz: https://doaj.org/article/9948a1fcb19c4c8c9b23e0c56cfeee18

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Akademický článek

Stock market comovements among Asian emerging economies: A wavelet-based approach.

Autor: Ijaz Younis, Cheng Longsheng, Muhammad Farhan Basheer, Ahmed Shafique Joyo

Publikováno v: PLoS ONE, Vol 15, Iss 10, p e0240472 (2020)

Stock market, is one of the most important financial market which has a close relationship with a country's economy, due to which it is often called the barometer of the economy. Over the past 25 years, the stock markets have been affected by differe

Externí odkaz: https://doaj.org/article/57f1368b522943279f6958bdfccfd11e

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Towards Environmental Preference Based Speech Enhancement For Individualised Multi-Modal Hearing Aids

Autor: Kirton-Wingate, Jasper, Ahmed, Shafique, Hussain, Adeel, Gogate, Mandar, Dashtipour, Kia, Hou, Jen-Cheng, Hussain, Tassadaq, Tsao, Yu, Hussain, Amir

Since the advent of Deep Learning (DL), Speech Enhancement (SE) models have performed well under a variety of noise conditions. However, such systems may still introduce sonic artefacts, sound unnatural, and restrict the ability for a user to hear am

Externí odkaz: http://arxiv.org/abs/2402.16757

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Deep Complex U-Net with Conformer for Audio-Visual Speech Enhancement

Autor: Ahmed, Shafique, Chen, Chia-Wei, Ren, Wenze, Li, Chin-Jou, Chu, Ernie, Chen, Jun-Cheng, Hussain, Amir, Wang, Hsin-Min, Tsao, Yu, Hou, Jen-Cheng

Recent studies have increasingly acknowledged the advantages of incorporating visual data into speech enhancement (SE) systems. In this paper, we introduce a novel audio-visual SE approach, termed DCUC-Net (deep complex U-Net with conformer network).

Externí odkaz: http://arxiv.org/abs/2309.11059

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