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Selected Papers from the International Conference on Communications, Circuits and Systems (ICCCAS)

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

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 2999

Special Issue Editor


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College of Engineering, Qatar University, Doha P.O. Box 2713, Qatar
Interests: network security; wireless networking
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

ICCCAS is an annual conference series that has been taking place since 2002. Its 10-year history has involved thousands of delegates' participation and contributions, and ICCCAS is a forum for presenting excellent results and new challenges facing the field of communications, circuits, and systems. It brings together experts from industry, governments, and academia, experienced in engineering, design, and research, attracting many submissions from academia and industry. This Special Issue will publish some selected outstanding papers accepted by ICCCAS after they have been through extensive revisions following the format of the journal of Sensors. The distribution of published papers in this Special Issue will be balanced among the three major research fields of communication, circuits, and systems.

Prof. Dr. Maode Ma
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

  • Cognitive Radio and AI-Enabled Networks;
  • Communication and Information System Security;
  • Communication QoS, Reliability and Modeling;
  • Communication Software and Multimedia;
  • Analog and Mixed Signal Circuits and Systems;
  • Communications Circuits and Systems;
  • Sensory Circuits and Systems;
  • Nonlinear Systems and Circuit Theory;
  • Wireless Communications;
  • Artificial Intelligent & Deep Learning;

Published Papers (1 paper)

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Research

19 pages, 3053 KiB  
Article
Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation
by Xianguang Dong, Zhen Jing, Yanjie Dai, Pingxin Wang and Zhen Chen
Sensors 2022, 22(24), 9804; https://doi.org/10.3390/s22249804 - 14 Dec 2022
Cited by 1 | Viewed by 2004
Abstract
It is helpful to have a replacement strategy by predicting the number of failures of in-service electricity meters. This paper presents a failure number prediction method for smart electricity meters based on on-site fault data. The prediction model was constructed by combining Weibull [...] Read more.
It is helpful to have a replacement strategy by predicting the number of failures of in-service electricity meters. This paper presents a failure number prediction method for smart electricity meters based on on-site fault data. The prediction model was constructed by combining Weibull distribution with odds ratios, then the distribution parameters, failure prediction number, and confidence intervals of prediction number were calculated. A strategy of meter replacement and reserve were developed according to the prediction results. To avoid the uncertainty of prediction results due to the small amount of field data information, a Bayesian failure number prediction method was developed. The research results have value for making operation plans and reserve strategies for electricity meters. Full article
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