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M

M. Moshrefi-Torbati

Researcher at University of Southampton

Publications -  40
Citations -  998

M. Moshrefi-Torbati is an academic researcher from University of Southampton. The author has contributed to research in topics: Maximum power principle & Vibration. The author has an hindex of 15, co-authored 38 publications receiving 846 citations. Previous affiliations of M. Moshrefi-Torbati include Razi University & University of Westminster.

Papers
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Signal processing techniques applied to human sleep EEG signals - a review

TL;DR: Signal processing techniques are categorised in tabular format based on their application in intensively researched sleep areas such as sleep staging, transient pattern detection and sleep disordered breathing diagnosis.
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Physical and geometrical interpretation of fractional operators

TL;DR: In this article, an interpretation of fractional operators in the time domain is given, based on the four concepts of fractal geometry, linear filters, construction of a Cantor set and physical realisation.
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Plating Uniformity of Bottom-up Copper Pillars and Patterns for IC Substrates with Additive-assisted Electrodeposition

TL;DR: In this article, the performance of the base electrolyte containing different additives was investigated by galvanostatic potential transient measurements (GM), cyclic voltammetry tests (CV) and potentiostatic measurements.
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Fabrication and characterization of biodegradable poly(3-hydroxybutyrate) composite containing bioglass.

TL;DR: A short period (28 days) in vitro bioactivity study in simulated body fluid confirmed the bioactivity of the composites, demonstrated by the formation of hydroxyapatite crystals on the Composites' surface.
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Characterization of New PEEK/HA Composites with 3D HA Network Fabricated by Extrusion Freeforming.

TL;DR: Preliminary evidence supporting initial biological safety of the new technique developed is demonstrated and results of unconfined, uniaxial compressive tests on these new PEEK/HA biocomposites with 40% HA under both static and cyclic mode were promising, showing the composites possess yield and compressive strength within the range of human cortical bone suitable for load bearing applications.