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Special Issue "Women in Sensors"

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Prof. Dr. Debbie G. Senesky
Website
Guest Editor
Stanford University, Durand Building #254, 496 Lomita Mall, Stanford, CA 94305, USA
Interests: harsh environment sensors; wide bandgap semiconductors; compound semiconductors; high-temperature instrumentation; radiation hardened semiconductors; semiconductor sensors; optical sensors; chemical sensors; micromechanical resonators; energy harvesters; piezoelectricity; microfabrication; nanotechnology
Special Issues and Collections in MDPI journals
Prof. Dr. Nicole Jaffrezic-Renault
Website
Guest Editor

Special Issue Information

2020 is Sensors’ 20th anniversary. Since its launch in 2001, Sensors has received important support and excellent contributions from women scientists. They have served as our Editorial Board members, Guest Editors, authors, reviewers.

To celebrate and highlight the achievements of women in the sensors research area, this Special Issue, entitled "Women in Sensors", will present the sensors-related work from leading women scientists. We also hope that this Special Issue will further encourage and promote the scientific contributions of women researchers in this field.

A “Women in Sensors Award” will be launched and granted to the best paper published in this Special Issue. Each award nominee will be assessed on her paper’s originality, quality, and contribution to the field by the Evaluation Committee. The winner will receive a certificate, an award of 1000 CHF, and an opportunity to publish her next submission in Sensors free of charge.

Prof. Dr. Debbie G. Senesky
Prof. Dr. Nicole Jaffrezic-Renault
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Open AccessArticle
Human Occupancy Detection via Passive Cognitive Radio
Sensors 2020, 20(15), 4248; https://doi.org/10.3390/s20154248 - 30 Jul 2020
Abstract
Human occupancy detection (HOD) in an enclosed space, such as indoors or inside of a vehicle, via passive cognitive radio (CR) is a new and challenging research area. Part of the difficulty arises from the fact that a human subject cannot easily be [...] Read more.
Human occupancy detection (HOD) in an enclosed space, such as indoors or inside of a vehicle, via passive cognitive radio (CR) is a new and challenging research area. Part of the difficulty arises from the fact that a human subject cannot easily be detected due to spectrum variation. In this paper, we present an advanced HOD system that dynamically reconfigures a CR to collect passive radio frequency (RF) signals at different places of interest. Principal component analysis (PCA) and recursive feature elimination with logistic regression (RFE-LR) algorithms are applied to find the frequency bands sensitive to human occupancy when the baseline spectrum changes with locations. With the dynamically collected passive RF signals, four machine learning (ML) classifiers are applied to detect human occupancy, including support vector machine (SVM), k-nearest neighbors (KNN), decision tree (DT), and linear SVM with stochastic gradient descent (SGD) training. The experimental results show that the proposed system can accurately detect human subjects—not only in residential rooms—but also in commercial vehicles, demonstrating that passive CR is a viable technique for HOD. More specifically, the RFE-LR with SGD achieves the best results with a limited number of frequency bands. The proposed adaptive spectrum sensing method has not only enabled robust detection performance in various environments, but also improved the efficiency of the CR system in terms of speed and power consumption. Full article
(This article belongs to the Special Issue Women in Sensors)
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Open AccessArticle
A Paper-Based Device for Ultrasensitive, Colorimetric Phosphate Detection in Seawater
Sensors 2020, 20(10), 2766; https://doi.org/10.3390/s20102766 - 12 May 2020
Cited by 1
Abstract
High concentrations of certain nutrients, including phosphate, are known to lead to undesired algal growth and low dissolved oxygen levels, creating deadly conditions for organisms in marine ecosystems. The rapid and robust detection of these nutrients using a colorimetric, paper-based system that can [...] Read more.
High concentrations of certain nutrients, including phosphate, are known to lead to undesired algal growth and low dissolved oxygen levels, creating deadly conditions for organisms in marine ecosystems. The rapid and robust detection of these nutrients using a colorimetric, paper-based system that can be applied on-site is of high interest to individuals monitoring marine environments and others affected by marine ecosystem health. Several techniques for detecting phosphate have been reported previously, yet these techniques often suffer from high detection limits, reagent instability, and the need of the user to handle toxic reagents. In order to develop improved phosphate detection methods, the commonly used molybdenum blue reagents were incorporated into a paper-based, colorimetric detection system. This system benefited from improved stabilization of the molybdenum blue reagent as well as minimal user contact with toxic reagents. The colorimetric readout from the paper-based devices was analyzed and quantified using RGB analyses (via ImageJ), and resulted in the detection of phosphate at detection limits between 1.3 and 2.8 ppm in various aqueous media, including real seawater. Full article
(This article belongs to the Special Issue Women in Sensors)
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