Zobrazeno 1 - 10
of 32 822
pro vyhledávání: '"Okan, A"'
We propose a novel approach for boosting the realized gain in enhanced directivity arrays with both active and parasitic dipoles as radiating elements. The optimization process involves two main objectives: maximizing the end-fire gain and minimizing
Externí odkaz:
http://arxiv.org/abs/2410.16014
Autor:
Caune, Laura, Skoric, Luka, Blunt, Nick S., Ruban, Archibald, McDaniel, Jimmy, Valery, Joseph A., Patterson, Andrew D., Gramolin, Alexander V., Majaniemi, Joonas, Barnes, Kenton M., Bialas, Tomasz, Buğdaycı, Okan, Crawford, Ophelia, Gehér, György P., Krovi, Hari, Matekole, Elisha, Topal, Canberk, Poletto, Stefano, Bryant, Michael, Snyder, Kalan, Gillespie, Neil I., Jones, Glenn, Johar, Kauser, Campbell, Earl T., Hill, Alexander D.
Quantum error correction (QEC) will be essential to achieve the accuracy needed for quantum computers to realise their full potential. The field has seen promising progress with demonstrations of early QEC and real-time decoded experiments. As quantu
Externí odkaz:
http://arxiv.org/abs/2410.05202
Autor:
Orhan, Okan K., Bello, Frank Daniel, Abadía, Nicolás, Hess, Ortwin, Donegan, John F., O'Regan, David D.
Plasmonic near-field transducers (NFTs) play a key role in administering nanoscale heating for a number of applications ranging from medical devices to next generation data processing technology. We present a novel multi-scale approach, combining qua
Externí odkaz:
http://arxiv.org/abs/2408.14451
We propose a novel Neural Steering technique that adapts the target area of a spatial-aware multi-microphone sound source separation algorithm during inference without the necessity of retraining the deep neural network (DNN). To achieve this, we fir
Externí odkaz:
http://arxiv.org/abs/2408.12982
High-entropy alloys (HEAs) exhibit exceptional catalytic performance due to their complex surface structures. However, the vast number of active binding sites in HEAs, as opposed to conventional alloys, presents a significant computational challenge
Externí odkaz:
http://arxiv.org/abs/2408.11238
Autor:
Strauss, Martin, Köpüklü, Okan
This paper introduces an area-based source separation method designed for virtual meeting scenarios. The aim is to preserve speech signals from an unspecified number of sources within a defined spatial area in front of a linear microphone array, whil
Externí odkaz:
http://arxiv.org/abs/2408.09810
Autor:
Ebadi, Zohreh, Molaei, Amir Masoud, Alexandropoulos, George C., Abbasi, Muhammad Ali Babar, Cotton, Simon, Tukmanov, Anvar, Yurduseven, Okan
Localizing near-field sources considering practical arrays is a recent challenging topic for next generation wireless communication systems. Practical antenna array apertures with closely spaced elements exhibit direction-dependent mutual coupling (M
Externí odkaz:
http://arxiv.org/abs/2408.07202
Autor:
Ebadi, Zohreh, Molaei, Amir Masoud, Abbasi, Muhammad Ali Babar, Cotton, Simon, Tukmanov, Anvar, Yurduseven, Okan
Localizing near-field sources considering practical arrays is important in wireless communications. Array-based apertures exhibit mutual coupling between the array elements, which can significantly degrade the performance of the localization method.
Externí odkaz:
http://arxiv.org/abs/2407.19597
Autor:
Atalar, Okan, Arbabian, Amin
Photoelastic modulators are optical devices with a broad range of applications. These devices typically utilize a transverse interaction mechanism between acoustic and optical waves, resulting in a fundamental trade-off between the input aperture and
Externí odkaz:
http://arxiv.org/abs/2407.04821
The Rise of Artificial Intelligence in Educational Measurement: Opportunities and Ethical Challenges
Autor:
Bulut, Okan, Beiting-Parrish, Maggie, Casabianca, Jodi M., Slater, Sharon C., Jiao, Hong, Song, Dan, Ormerod, Christopher M., Fabiyi, Deborah Gbemisola, Ivan, Rodica, Walsh, Cole, Rios, Oscar, Wilson, Joshua, Yildirim-Erbasli, Seyma N., Wongvorachan, Tarid, Liu, Joyce Xinle, Tan, Bin, Morilova, Polina
The integration of artificial intelligence (AI) in educational measurement has revolutionized assessment methods, enabling automated scoring, rapid content analysis, and personalized feedback through machine learning and natural language processing.
Externí odkaz:
http://arxiv.org/abs/2406.18900