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Electromagnetic Wave Detection and Sensing Technology
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Electromagnetic Wave Detection and Sensing Technology

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (10 April 2024) | Viewed by 757

Special Issue Editor

Dr. Simon Lineykin

E-Mail Website
Guest Editor
Department of Mechanical Engineering and Mechatronics, Ariel University, Ariel 40700, Israel
Interests: analog electronic design; ultra-low noise systems and sensors; magneto-electric sensors; magneto-optical sensors; system design using computer aided design software; modeling and emulation of the physical processes; precision motion control and positioning; power system analysis and design; RF and Terahertz system design; THz vision systems; VLSI; MEMS; micro-robots; active cooling systems using Peltier effect; thermoelectric power generation; control systems; energy harvesting
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This issue is focused on the latest advancements and breakthroughs in detecting and sensing electromagnetic waves, along with their scientific, industrial, and technological applications. The issue covers all types of sensors that detect electromagnetic waves at any range, as well as innovative applications for communication, imaging, remote sensing, medical diagnostics, and more. It also explores methods for signal amplification and conditioning, improving sensing resolution, reducing noise levels, and other scientific and engineering solutions in this field.

This Special Issue addresses all types of sensors and detectors for electromagnetic waves and the technological methods used in their development and application.

Dr. Simon Lineykin
Guest Editor

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 submissions that pass pre-check are 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 2600 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.

Keywords

  • electromagnetic waves
  • EM sensors
  • EM wave detection
  • electromagnetic scattering
  • electromagnetic radiation
  • antennas

Published Papers (1 paper)

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Research

16 pages, 10000 KiB  
Article
Microwave Dielectric Response of Bovine Milk as Pregnancy Detection Tool in Dairy Cows
by Cindy Galindo, Guy Levy, Yuri Feldman, Zvi Roth, Jonathan Shalev, Chen Raz, Edo Mor and Nurit Argov-Argaman
Sensors 2024, 24(9), 2742; https://doi.org/10.3390/s24092742 (registering DOI) - 25 Apr 2024
Viewed by 219
Abstract
The most reliable methods for pregnancy diagnosis in dairy herds include rectal palpation, ultrasound examination, and evaluation of plasma progesterone concentrations. However, these methods are expensive, labor-intensive, and invasive. Thus, there is a need to develop a practical, non-invasive, cost-effective method that can [...] Read more.
The most reliable methods for pregnancy diagnosis in dairy herds include rectal palpation, ultrasound examination, and evaluation of plasma progesterone concentrations. However, these methods are expensive, labor-intensive, and invasive. Thus, there is a need to develop a practical, non-invasive, cost-effective method that can be implemented on the farm to detect pregnancy. This study suggests employing microwave dielectric spectroscopy (MDS, 0.5–40 GHz) as a method to evaluate reproduction events in dairy cows. The approach involves the integration of MDS data with information on milk solids to detect pregnancy and identify early embryonic loss in dairy cows. To test the ability to predict pregnancy according to these measurements, milk samples were collected from (i) pregnant and non-pregnant randomly selected cows, (ii) weekly from selected cows (n = 12) before insemination until a positive pregnancy test, and (iii) daily from selected cows (n = 10) prior to insemination until a positive pregnancy test. The results indicated that the dielectric strength of Δε and the relaxation time, τ, exhibited reduced variability in the case of a positive pregnancy diagnosis. Using principal component analysis (PCA), a clear distinction between pregnancy and nonpregnancy status was observed, with improved differentiation upon a higher sampling frequency. Additionally, a neural network machine learning technique was employed to develop a prediction algorithm with an accuracy of 73%. These findings demonstrate that MDS can be used to detect changes in milk upon pregnancy. The developed machine learning provides a broad classification that could be further enhanced with additional data. Full article
(This article belongs to the Special Issue Electromagnetic Wave Detection and Sensing Technology)
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