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Applied Sciences
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Patent Based and Extended Research in Industry 4.0
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Patent Based and Extended Research in Industry 4.0

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

Deadline for manuscript submissions: closed (30 June 2019) | Viewed by 3448

Special Issue Editors

Prof. Dr. Chien-Hung Liu

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Guest Editor
Department of Mechanical Engineering, National Chung Hsing University, 250 Kuo Kuang Rd., Taichung 402, Taiwan
Interests: high precision instrument design; laser engineering; smart sensors and actuators; optical device; optical measurement; metrology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jyh-Horng Chou

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Guest Editor
1. Department of Electrical Engineering, National Kaohsiung University of Science and Technology, 415 Chien-Kung Road, Kaohsiung 807, Taiwan
2. Department of Mechanical Engineering, National Chung Hsing University, 250 Kuo Kuang Rd., Taichung 402, Taiwan
Interests: artificial intelligence; information technology and system integration; system modeling and simulation; system dynamics and control; integration technology of automation systems; numerical analysis and computational mathematics; robust optimization technology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chin-Sheng Chen

E-Mail Website
Guest Editor
Graduate Institute of Automation Technology, National Taipei University of Technology, 1, Sec. 3, Zhongxiao E. Rd. Taipei 10608, Taiwan
Interests: smart automation; intelligent robotics; intelligent motion control; machine vision; mechatronics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Industry 4.0 represents the fourth industrial revolution in manufacturing and industry. Industry 4.0 is the current industrial transformation with automation, data exchanges, cloud computing, cyber-physical systems, robots, big data, industry AI (Artificial Intelligence), IoT (Internet of Thing) and (semi-)autonomous industrial techniques to realize smart industry and manufacturing goals at the intersection of people, new technologies and innovation. It is also a rather vast vision and, increasingly, vast reality that also stretches beyond these technological aspects. Thus, this Special Issue will focus on publishing the patent-based and extended research in Industry 4.0. Authors are encouraged to submit their patent-based and extended research in Industry 4.0 to this Special Issue. From this collection, readers can understand scholars’ research with real applications to Industry 4.0.

Prof. Dr. Chien-Hung Liu
Prof. Dr. Jyh-Horng Chou
Prof. Dr. Chin-Sheng Chen
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. 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 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

  • Cyber-physical systems
  • Data exchanges
  • Cloud computing
  • Robots, Collaborative Industrial Robots
  • Big Data
  • Industry Artificial Intelligence, AI
  • Internet of Thing, IoT
  • Automation

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Published Papers (1 paper)

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Research

18 pages, 12435 KiB  
Article
A Cloud Image Data Protection Algorithm with Multilevel Encryption Scheme and Automated- Selection Mechanism
by Shih-Yu Li, Miguel Angel Benalcázar Hernández, Lap-Mou Tam and Chin-Sheng Chen
Appl. Sci. 2019, 9(23), 5146; https://doi.org/10.3390/app9235146 - 27 Nov 2019
Cited by 5 | Viewed by 2687
Abstract
In this paper, we present a cloud image data protection algorithm with a multilevel encryption scheme and automated-selection mechanism to maintain the privacy of cloud data contents. This algorithm is also useful for the protection of personal or commercial data uploaded to the [...] Read more.
In this paper, we present a cloud image data protection algorithm with a multilevel encryption scheme and automated-selection mechanism to maintain the privacy of cloud data contents. This algorithm is also useful for the protection of personal or commercial data uploaded to the cloud server for real-time applications, monitoring, and transmission. Fundamental and well-known in cryptography, the confusion–diffusion scheme, as well as an automated-selection mechanism (sliding pixel window) were selected as the main motor of the proposed algorithm to cipher images. First, a sliding pixel window is selected to expedite a two-stepped process, whether in small or big images. The confusion stage was designed to drastically change data from plain image to cipher image. The conversion of pixels from decimal to binary and their vertical and horizontal relocation were performed to help in this stage, not only by randomly moving bits, but also by changing the pixel values when they returned to their corresponding decimal values. Meanwhile, the diffusion stage was designed to destroy all possible existing patterns in the sliding pixel window after the confusion stage. Two hyperchaotic systems, together with a logistic map (multilevel scheme), produce pseudorandom numbers to separately conceal the original data of each subplain image through first- and second-level encryption processes. The two-stepped algorithm was designed to be easily implemented by practitioners. Furthermore, the experimental analysis demonstrates the effectiveness and feasibility of the proposed encryption algorithm after being tested using the benchmark “Lena” image, as well as the “Bruce Lee” image, the latter of which is completely different to the first one, statistically speaking. Full article
(This article belongs to the Special Issue Patent Based and Extended Research in Industry 4.0)
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