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Special Issue "I3S 2018 Selected Papers"

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

Deadline for manuscript submissions: 31 January 2019

Special Issue Editors

Guest Editor
Prof. Dr. Vladimir M. Mirsky

Brandenburg University of Technology Cottbus-Senftenberg, Senftenberg, Germany
Website | E-Mail
Guest Editor
Prof. Dr. Gianluigi Ferrari

Department of Engineering and Architecture, University of Parma, Italy, Parco Area delle Scienze, 181/A, 43124 Parma, Italy
Website | E-Mail
Phone: (+39) 0521906513
Interests: communications; networking; signal processing; Internet of Things; smart systems
Guest Editor
Prof. Dr. Chien-Hung Liu

Department of Mechanical Engineering, National Chung Hsing University, 250 Kuo Kuang Rd., Taichung 402, Taiwan
Website | E-Mail
Fax: +886 4 2287 7170
Interests: high precision instrument design; laser engineering; smart sensors and actuators; optical device; optical measurement; metrology

Special Issue Information

Dear Colleagues,

This Special Issue was created in collaboration with the 6th International Symposium on Sensor Science (I3S 2018) and 4th SPINTECH Technology Thesis Award, held 6–8 August, 2018, in Kenting, Taiwan. It comprises six topical sessions that covers the most exciting aspects of sensor science (see below for a list of topics). The conference participants are cordially invited to contribute a full manuscript to this Special Issue and receive a 20% discount on the publishing fees. This Special Issue will be open for submission from 9 August 2018 to 31 January 2019.

Session 1: Physical Sensors
Session Chair: Prof. Dr. Bahram Nabet, Drexel University, USA

Session 2: Sensor Networks
Session Chair: Prof. Dr. Francisco Falcone, Universidad Publica de Navarra, UPNA, Spain

Session 3: Sensors Applications
Session Chair: Dr. Debbie G. Senesky, Stanford University, USA

Session 4: Biosensors
Session Chair: Prof. Dr. Michael J. Schöning, Aachen University of Applied Sciences, Germany

Session 5: Chemical Sessors
Session Chair: Prof. Dr. Vladimir M. Mirsky, Brandenburg University of Technology Cottbus-Senftenberg, Senftenberg, Germany

Session 6: IoT Sensor and Application
Session Chair: Prof. Dr. Gianluigi Ferrari, University of Parma, Italy

Prof. Dr. Vladimir M. Mirsky

Prof. Dr. Gianluigi Ferrari
Prof. Dr. Chien-Hung Liu
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 monthly 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 1800 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 (1 paper)

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Open AccessArticle Humanoid Identification of Fabric Material Properties by Vibration Spectrum Analysis
Sensors 2018, 18(6), 1820; https://doi.org/10.3390/s18061820
Received: 8 May 2018 / Revised: 27 May 2018 / Accepted: 30 May 2018 / Published: 5 June 2018
PDF Full-text (3513 KB) | HTML Full-text | XML Full-text | Supplementary Files
In daily contexts, fabrics embodied in garments are in contact with human body all the time. Since fabric material properties—such as softness or fineness—can be easily sensed by human fingertips, fabric materials can be roughly identified by fingertip sliding. Identification by simply touching
[...] Read more.
In daily contexts, fabrics embodied in garments are in contact with human body all the time. Since fabric material properties—such as softness or fineness—can be easily sensed by human fingertips, fabric materials can be roughly identified by fingertip sliding. Identification by simply touching and sliding is convenient and fast, although the room for error is always very large. In this study, a highly discernible fabric humanoid identification method with a fingertip structure inspired tactile sensor is designed to investigate the fabric material properties by characterizing the power spectrum integral of vibration signal basing on fast Fourier transform integral S(FFT), which is generated from a steel ball probe rubbing against a fabric surface at an increasing sliding velocity and normal load, respectively. kv and kw are defined as the slope values to identify the fabric surface roughness and hardness. A sample of 21 pieces of fabric categorized by yarn weight, weave pattern, and material were tested by this method. It was proved that the proposed humanoid sensing method has more efficient compared with fingertip sliding while it is also much more accurate for fabric material identification. Our study would be discussed in light of textile design and has a great number of potential applications in humanoid tactile perception technology. Full article
(This article belongs to the Special Issue I3S 2018 Selected Papers)

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