Selected Papers from 2023 IET International Conference on Engineering Technologies and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 1160

Special Issue Editors


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Guest Editor
Department of Computer Science and Information Engineering, National Ilan University, Yilan City 260, Taiwan
Interests: DSP IC design; computer vision; image processing; cognitive learning
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Guest Editor
Department of Electrical Engineering, National Formosa University, Taiwan
Interests: FPGA design; digital IC design; image processing and embedded design

Special Issue Information

Dear Colleagues,

The 2023 IET International Conference on Engineering Technologies and Applications (IET ICETA 2023) will be held on October 21–23 in Yunlin, Taiwan. IET ICETA 2023 aims to provide a platform for experts, scholars, and researchers from all over the world to convene and share novel ideas on engineering fields. Authors of accepted papers are invited to submit the extended versions (at least 60% extension for the submissions) of their original papers and contributions.

The topics of interest include, but are not limited to, the following:

  • Artificial Intelligence, Machine Learning, and Deep Learning;
  • Internet of Things;
  • Audio/Video Systems and Signal Processing;
  • Semiconductors and Integrated Circuits;
  • Green Energy;
  • Mechatronic Integration;
  • Communications and Networks;
  • Automation and Control;
  • Vehicle-to-Everything and Autonomous Vehicles;
  • Big Data and Clouds;
  • Advanced Computing and Data Sciences;
  • Lean Management;
  • Smart and Intelligent Manufacturing;
  • RF and Microwaves;
  • ET Technology;
  • Power Devices and Systems;
  • Security and Privacy;
  • Computer Software and Hardware;
  • Consumer Electronics;
  • Virtual Reality, Augmented Reality, Mixed Reality, and Cinematic Reality;
  • Opto-Electronic Materials, Devices, Circuits, and Systems;
  • Advanced Materials and Devices;
  • Sensors and Actuators;
  • Sustainable Development;
  • Technology and Education;
  • Advanced Technologies and Applications.

Prof. Dr. Chih-Hsien Hsia
Prof. Dr. Chi-Chia Sun
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 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. Electronics 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 2400 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

  • artificial intelligence
  • big data and clouds
  • signal processing
  • virtual reality
  • Internet of Things

Published Papers (1 paper)

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Research

10 pages, 2343 KiB  
Article
The Influence of Geometric Parameters for Training an Artificial Neural Network to Predict the Band Structure of 1-D Fishbone Photonic Crystal
by Fu-Li Hsiao, Chien-Chung Chen, Chuan-Yu Chang, Yi-Chia Huang and Ying-Pin Tsai
Electronics 2024, 13(7), 1285; https://doi.org/10.3390/electronics13071285 - 29 Mar 2024
Viewed by 482
Abstract
With the rising demand for the transmission of large amounts of information over long distances, the development of integrated light circuits is the key to improving this technology, and silicon photonics have been developed with low absorption in the near-infrared range and with [...] Read more.
With the rising demand for the transmission of large amounts of information over long distances, the development of integrated light circuits is the key to improving this technology, and silicon photonics have been developed with low absorption in the near-infrared range and with sophisticated fabrication techniques. To build devices that work in different functionalities, photonic crystals are one of the most used structures due to their ability to manipulate light. The investigation of photonic crystals requires the calculation of photonic band structures and is usually time-consuming work. To reduce the time spent on calculations, a trained ANN is introduced in this study to directly predict the band structures using only a minimal amount of pre-calculated band structure data. A well-used 1-D fishbone-like photonic crystal in the form of a nanobeam is used as the training target, and the influence of adjusting the geometric parameters is discussed, especially the lattice constant and the thickness of the nanobeam. To train the ANN with very few band structures, each of the mode points in the band structure is considered as a single datapoint to increase the amount of training data. The datasets are composed of various raw band structure data. The optimized ANN is introduced at the end of this manuscript. Full article
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