Special Issue "Selected Papers from IEEE ICICE 2017"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: closed (1 March 2018)

Special Issue Editors

Guest Editor
Prof. Dr. Shoou-Jinn Chang

Department of Electrical Engineering, National Cheng Kung University, Tainan 701, Taiwan
Website | E-Mail
Interests: optical and electronic devices, semi-conductive materials, nanotechnology
Guest Editor
Prof. Dr. Teen­Hang Meen

Chair of IEEE Tainan Section Sensors Council Department of Electronic Engineering National Formosa University, Yunlin 632
Website | E-Mail
Interests: photovoltaic device; dye-sensitized solar cells; nanotechnology
Guest Editor
Dr. Stephen D. Prior

Aeronautics, Astronautics and Computational Engineering, University of Southampton, Southampton SO16 7QF, UK
Website | E-Mail
Interests: microsystem design; nanotechnology

Special Issue Information

Dear Colleagues,

2017 IEEE International Conference on Information, Communication and Engineering (ICICE 2017) will be held in Xiamen, Fujian, P.R. China on November 17–20, 2017, and will provide a unified communication platform for researchers in a wide area of topics. The special issue on “Selected papers from IEEE ICICE 2017” is expected to select excellent papers presented in ICICE 2017. Mechanical Engineering and Design Innovations are both an academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation by Mechanical Engineering includes IT-based Intelligent Mechanical Systems, Mechanics and Design Innovations, and Applied Materials on Nanosciences and Nanotechnology. These new technologies which implant intelligence to machine systems, are the interdisciplinary area combining conventional mechanical technology and new information technology.

The main goal of this special issue “Selected papers from ICICE 2017” is to discover new scientific knowledge relevant to IT-based Intelligent Mechanical Systems, Mechanics and Design Innovations, and Applied Materials on Nanosciences and Nanotechnology. We invite investigators interested in Applied System Innovation to contribute their original research articles to this Special Issue. Potential topics include, but are not limited to:

  • Intelligent mechanical manufacturing system

  • Mathematical problems on mechanical system design.

  • Smart electromechanical system analysis and design

  • Applied Materials on Nanosciences and Nanotechnology

  • Computer-aided methods for mechanical design procedure and manufacture.

  • Computer and human-machine interaction.

  • Internet Technology on mechanical system innovation.

  • Machine diagnostics & reliability

  • Human-machine interaction/Virtual reality and entertainment

  • Internet & IOT technology

Prof. Dr. Shoou-Jinn Chang
Prof. Teen­Hang Meen
Dr. Stephen D. Prior
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. Applied Sciences 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 1500 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

  • Smart electromechanical system analysis and design

  • Intelligent mechanical System

  • Applied Materials on Nanosciences and Nanotechnology

  • Internet & IOT technology

Published Papers (4 papers)

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Research

Open AccessArticle
Developing Automatic Form and Design System Using Integrated Grey Relational Analysis and Affective Engineering
Appl. Sci. 2018, 8(1), 91; https://doi.org/10.3390/app8010091
Received: 15 November 2017 / Revised: 28 December 2017 / Accepted: 4 January 2018 / Published: 10 January 2018
Cited by 4 | PDF Full-text (6766 KB) | HTML Full-text | XML Full-text
Abstract
In the modern highly competitive marketplace and global market environment, product quality improvements that abridge development time and reduce the production costs are effective methods for promoting the business competitiveness of a product in shorter lifecycles. Since the design process is the best [...] Read more.
In the modern highly competitive marketplace and global market environment, product quality improvements that abridge development time and reduce the production costs are effective methods for promoting the business competitiveness of a product in shorter lifecycles. Since the design process is the best time to control such parameters, systematically designing the processes to develop a product that more closely fits the demand requirements for the market is a key factor for developing a successful product. In this paper, a combined affective engineering method and grey relational analysis are used to develop a product design process. First, design image scale technology is used to acquire the best the design criteria factors, and then affective engineering methods are used to set the relationships between customer needs and production factors. Finally, grey relational analysis is used to select the optimal design strategy. Using this systematic design method, a higher quality product can be expanded upon in a shorter lead-time for improving business competition. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICICE 2017)
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Open AccessArticle
A Fusion Link Prediction Method Based on Limit Theorem
Appl. Sci. 2018, 8(1), 32; https://doi.org/10.3390/app8010032
Received: 3 December 2017 / Revised: 17 December 2017 / Accepted: 22 December 2017 / Published: 28 December 2017
PDF Full-text (479 KB) | HTML Full-text | XML Full-text
Abstract
The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or [...] Read more.
The theoretical limit of link prediction is a fundamental problem in this field. Taking the network structure as object to research this problem is the mainstream method. This paper proposes a new viewpoint that link prediction methods can be divided into single or combination methods, based on the way they derive the similarity matrix, and investigates whether there a theoretical limit exists for combination methods. We propose and prove necessary and sufficient conditions for the combination method to reach the theoretical limit. The limit theorem reveals the essence of combination method that is to estimate probability density functions of existing links and nonexistent links. Based on limit theorem, a new combination method, theoretical limit fusion (TLF) method, is proposed. Simulations and experiments on real networks demonstrated that TLF method can achieve higher prediction accuracy. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICICE 2017)
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Open AccessArticle
Simulation and Fabrication of HfO2 Thin Films Passivating Si from a Numerical Computer and Remote Plasma ALD
Appl. Sci. 2017, 7(12), 1244; https://doi.org/10.3390/app7121244
Received: 31 October 2017 / Revised: 24 November 2017 / Accepted: 27 November 2017 / Published: 1 December 2017
Cited by 1 | PDF Full-text (1546 KB) | HTML Full-text | XML Full-text
Abstract
Recombination of charge carriers at silicon surfaces is one of the biggest loss mechanisms in crystalline silicon (c-Si) solar cells. Hafnium oxide (HfO2) has attracted much attention as a passivation layer for n-type c-Si because of its positive fixed charges and [...] Read more.
Recombination of charge carriers at silicon surfaces is one of the biggest loss mechanisms in crystalline silicon (c-Si) solar cells. Hafnium oxide (HfO2) has attracted much attention as a passivation layer for n-type c-Si because of its positive fixed charges and thermal stability. In this study, HfO2 films are deposited on n-type c-Si using remote plasma atomic layer deposition (RP-ALD). Post-annealing is performed using a rapid thermal processing system at different temperatures in nitrogen ambient for 10 min. The effects of post-annealing temperature on the passivation properties of the HfO2 films on c-Si are investigated. Personal computer one dimension numerical simulation for the passivated emitter and rear contact (PERC) solar cells with the HfO2 passivation layer is also presented. By means of modeling and numerical computer simulation, the influence of different front surface recombination velocity (SRV) and rear SRV on n-type silicon solar cell performance was investigated. Simulation results show that the n-type PERC solar cell with HfO2 single layer can have a conversion efficiency of 22.1%. The PERC using silicon nitride/HfO2 stacked passivation layer can further increase efficiency to 23.02% with an open-circuit voltage of 689 mV. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICICE 2017)
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Open AccessArticle
Residual Stress and Deformation Analysis in Butt Welding on 6 mm SUS304 Steel with Jig Constraints Using Gas Metal Arc Welding
Appl. Sci. 2017, 7(10), 982; https://doi.org/10.3390/app7100982
Received: 13 August 2017 / Revised: 20 September 2017 / Accepted: 20 September 2017 / Published: 23 September 2017
Cited by 1 | PDF Full-text (10555 KB) | HTML Full-text | XML Full-text
Abstract
This article proposes a novel method for analyzing residual stress and deformation in butt welding on 6 mm SUS304 stainless steel plates, using MSC.MARC, a commercial finite element method software, to find the best location for jig fixtures that will minimize welding deformation. [...] Read more.
This article proposes a novel method for analyzing residual stress and deformation in butt welding on 6 mm SUS304 stainless steel plates, using MSC.MARC, a commercial finite element method software, to find the best location for jig fixtures that will minimize welding deformation. Simulation and experimental studies show that a distance of 100 mm between the jig center and the welding bead center is best for inhibiting welding deformation when the jigs experience downward displacement at 0 mm on the steel plate; the total displacement is only about 1.1 mm in the case of a 300 × 250 × 6 mm SUS304 steel plate. In addition, a numerical model shows that four jigs with pitches of 200 mm can better reduce welding deformation than six jigs with pitches of 100 mm. The largest residual stress after welding occurs around the weld bead center, and the residual stress away from the welding bead center increases gradually when jigs have been applied on the steel plate to prevent deformation. The reaction force of the jigs on the steel plate has no further effect in reducing deformation. We conclude that commercially available jigs can inhibit deformation during the welding process. Full article
(This article belongs to the Special Issue Selected Papers from IEEE ICICE 2017)
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