Zobrazeno 1 - 10
of 20 393
pro vyhledávání: '"P. A. Nana"'
Autor:
Koya, Alemayehu Nana, Sapunova, Anastasiia, Sanamreddy, Nageswar Reddy, Zou, Yanqiu, Ma, Qifei, Kotsifak, Domna, Jin, Huaizhou, Jin, Shangzhong, Vavassori, Paolo, Garoli, Denis
The compositional asymmetry of Janus micro- and nanoparticles gives unprecedented opportunities to manipulate such composite particles with different stimuli to achieve enhanced optical, magnetic and photothermal responses, which can be exploited for
Externí odkaz:
http://arxiv.org/abs/2411.16191
Autor:
Gyimah, Nana Kankam, Mwakalonge, Judith, Comert, Gurcan, Siuhi, Saidi, Akinie, Robert, Sulle, Methusela, Ruganuza, Denis, Izison, Benibo, Mukwaya, Arthur
In this paper, we present an automated machine learning (AutoML) approach for network intrusion detection, leveraging a stacked ensemble model developed using the MLJAR AutoML framework. Our methodology combines multiple machine learning algorithms,
Externí odkaz:
http://arxiv.org/abs/2411.15920
The Schr\"odingerisation method combined with the autonomozation technique in \cite{cjL23} converts general non-autonomous linear differential equations with non-unitary dynamics into systems of autonomous Schr\"odinger-type equations, via the so-cal
Externí odkaz:
http://arxiv.org/abs/2411.10999
Mild cognitive impairment (MCI) is a major public health concern due to its high risk of progressing to dementia. This study investigates the potential of detecting MCI with spontaneous voice assistant (VA) commands from 35 older adults in a controll
Externí odkaz:
http://arxiv.org/abs/2411.04158
Recently, there has been growing interest in simulating time-dependent Hamiltonians using quantum algorithms, driven by diverse applications, such as quantum adiabatic computing. While techniques for simulating time-independent Hamiltonian dynamics a
Externí odkaz:
http://arxiv.org/abs/2411.03180
Autor:
Guseynov, Nikita, Liu, Nana
The ability to effectively upload data onto quantum states is an important task with broad applications in quantum computing. Numerous quantum algorithms heavily rely on the ability to efficiently upload information onto quantum states, without which
Externí odkaz:
http://arxiv.org/abs/2411.01131
Autor:
Chy, Md Kamrul Hasan, Buadi, Obed Nana
This paper introduces a Machine Learning-Driven website Platform and Browser Extension designed to quickly enhance online security by providing real-time risk scoring and fraud detection for website legitimacy verification and consumer protection. Th
Externí odkaz:
http://arxiv.org/abs/2411.00368
Autor:
Chen, Ying, Wang, Guoan, Ji, Yuanfeng, Li, Yanjun, Ye, Jin, Li, Tianbin, Zhang, Bin, Pei, Nana, Yu, Rongshan, Qiao, Yu, He, Junjun
Despite the progress made by multimodal large language models (MLLMs) in computational pathology, they remain limited by a predominant focus on patch-level analysis, missing essential contextual information at the whole-slide level. The lack of large
Externí odkaz:
http://arxiv.org/abs/2410.11761
Autor:
Li, Mingtao, Wang, Yiming, Pei, Cuiying, Zhang, Mingxin, Li, Nana, Guan, Jiayi, Amboage, Monica, Adama, N-Diaye, Kong, Qingyu, Qi, Yanpeng, Yang, Wenge
We report a comprehensive study of electronic band structure for single-layer (SL) and bilayer (BL) RP-nickelates probed by in-situ HP X-ray absorption near edge spectroscopy (XANES). At ambient pressure (AP), the energy splitting delta_E of d_3z^2-r
Externí odkaz:
http://arxiv.org/abs/2410.04230
We propose an adaptive control strategy for the simultaneous estimation of topology and synchronization in complex dynamical networks with unknown, time-varying topology. Our approach transforms the problem of time-varying topology estimation into a
Externí odkaz:
http://arxiv.org/abs/2409.08404