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Walaa H. Saadeh

Researcher at Jordan University of Science and Technology

Publications -  17
Citations -  784

Walaa H. Saadeh is an academic researcher from Jordan University of Science and Technology. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 2, co-authored 2 publications receiving 618 citations.

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EMI shielding effectiveness of carbon based nanostructured polymeric materials: A comparative study

TL;DR: In this paper, the microstructure, electromagnetic interference shielding effectiveness (SE), DC electrical conductivity, AC electrical conductivities and complex permittivity of nanostructured polymeric materials filled with three different carbon nanofillers of different structures and intrinsic electrical properties were investigated.
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Hybrids of conductive polymer nanocomposites

TL;DR: In this paper, the authors investigated the synergistic effect of nanofillers co-dispersion on conductive networks formation and found that an EMI SE and electrical conductivity similar to that of the 5-wt% CNT/ABS nanocomposite can be obtained by using a hybrid nanocomposition which contains 4 ¾wt% carbon black and 1 ¾% carbon nanotubes.
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Noninvasive Blood Glucose Monitoring Systems Using Near-Infrared Technology—A Review

Aminah Hina, +1 more
- 27 Jun 2022 - 
TL;DR: This review paper briefly discusses the noninvasive glucose measuring technologies and their related research work and focuses on Near Infrared (NIR) technology and NIR Photoplethysmography (PPG) for blood glucose prediction.
Journal ArticleDOI

A 186μW Photoplethysmography-Based Noninvasive Glucose Sensing SoC

TL;DR: A high precision near-infrared Photoplethysmography (PPG) based noninvasive glucose monitoring System on Chip (SoC) with a fully differential Analog Frontend with nonlinear medium Gaussian support-vector-regression (NMG-SVR) for glucose estimation.
Proceedings ArticleDOI

A 208μW PPG-based Glucose Monitoring SoC using Ensembled Boosted Trees

TL;DR: A noninvasive glucose monitoring system-on-chip (SoC) based on near-infrared (NIR) Photoplethysmography (PPG) is proposed in this paper and improves (accuracy/power) figure of merit (FoM) by 5.5% compared to the state-of-the-artwork.