S
Shadnaz Asgari
Researcher at California State University, Long Beach
Publications - 63
Citations - 1596
Shadnaz Asgari is an academic researcher from California State University, Long Beach. The author has contributed to research in topics: Beamforming & Intracranial pressure. The author has an hindex of 19, co-authored 62 publications receiving 1300 citations. Previous affiliations of Shadnaz Asgari include California State University & University of California, Los Angeles.
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Synthesis and characterization of electrospun polyvinyl alcohol nanofibrous scaffolds modified by blending with chitosan for neural tissue engineering
Sanaz Naghavi Alhosseini,Fathollah Moztarzadeh,Masoud Mozafari,Shadnaz Asgari,Masumeh Dodel,Ali Samadikuchaksaraei,Saeid Kargozar,Newsha Jalali +7 more
TL;DR: Electrospun polyvinyl alcohol (PVA)/chitosan nano-fibrous scaffolds have been synthesized with large pore sizes as potential matrices for nervous tissue engineering and repair and it could be concluded that addition of chitOSan to the PVA scaffolds enhances viability and proliferation of nerve cells, which increases the biocompatibility of the scaffolds.
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Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine
TL;DR: The proposed automatic AF detection method has high sensitivity and specificity, and holds several interesting properties which make it a suitable choice for practical applications.
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An observational study of engineering online education during the COVID-19 pandemic.
TL;DR: In this paper, the authors conducted an observational study at California State University, Long Beach (CSU) to evaluate the impact of the COVID-19 pandemic on engineering education.
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Forecasting ICP Elevation Based on Prescient Changes of Intracranial Pressure Waveform Morphology
TL;DR: It is demonstrated that advanced ICP pulse analysis combined with machine learning could potentially leads to the forecasting of ICP elevation so that a proactive ICP management could be realized based on these accurate forecasts.
Journal Article
Collaborative Sensor Networking Towards Real-Time Acoustical Beamforming in Free-Space and Limited Reverberence
TL;DR: Results show the effective and robust operation of the proposed algorithms and their implementations on a real-time acoustical wireless testbed and a novel virtual array model applicable to the AML-DOA estimation method is proposed for reverberant scenarios.