Special Issue "Selected Papers from 2016 International Symposium on Computer, Consumer and Control (IS3C 2016)"

A special issue of Algorithms (ISSN 1999-4893).

Deadline for manuscript submissions: closed (15 October 2016).

Special Issue Editor

Guest Editor
Prof. Dr. Hsiung-Cheng Lin

Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung, Taiwan
Website | E-Mail
Interests: power electronics; neural networks; network supervisory systems; adaptive filter design; power harmonics tracking and analysis

Special Issue Information

Dear Colleagues,

IS3C2016 is The Third International Symposium on Computer, Consumer and Control, sponsored by the National Chin-Yi University of Technology, and was formally technically co-sponsored by the IEEE Computer Society and IEEE Industrial Electronics Society. This conference offers a great opportunity for scientists, engineers, and practitioners to present the latest research results, ideas, developments, and applications. The IEEE sponsored IS3C, held every two years, is hosted by the National Chin-Yi University of Technology and Xi’an University of Science and Technology, 4–6 July, 2016, in Xi’an, China, where Xi’an is well known for its exclusive historic image of thousands of years in China. As suggested by the name of the conference, the themes of this conference cover advanced multimedia, computer, telecommunication, sensors and semiconductors, consumer electronics, renewable energy, systems and control, and digital signal processing. Original, high-quality papers, related to these themes are especially solicited, including theories, methodologies, and applications in Computing, Consumer, and Control. All accepted papers will be published in the conference proceedings and submitted to the IEEE Xplore database, as well as EI index. Selected papers will be recommended to related SCI/EI journals for a Special Issue publication.

Original papers in the following themes (but not limited to them) are invited:

TRACK 1—COMPUTER

  • Computer Networks, Mobile Computing, and Web Technologies
  • Digital Content, Information Security, and Web Service
  • Software Engineering, SOA, and Databases
  • Artificial Intelligence, Knowledge Discovery, and Fuzzy Systems
  • Digital Right and Watermarking

TRACK 2—MULTIMEDIA

  • Hardware and Software for Multimedia Systems
  • Virtual Reality, AR, MR, 3D Processing and Application
  • Signal, Audio, Speech Analysis and Processing
  • Image Processing and Applications
  • Computer Vision, Motion, Tracking Algorithms and Applications

TRACK 3—TELECOMMUNICATION

  • Wireless and Mobile Communication
  • High Frequency and Microwave Circuits
  • RFID Technology and Applications
  • Internet Applications
  • Radio and Microwave Engineering

TRACK 4—SEMICONDUCTOR

  • Systems on Chip
  • Application of Microelectronics
  • Device Modeling, Simulation and Design
  • Material and New Fabrication Facilities Technologies
  • Nano Technology
  • Sensors
  • Sensing technology
  • Sensor materials
  • Micro Electro Mechanical Systems
  • Microactuators

TRACK 5—CONSUMER ELECTRONICS

  • Human–Machine Interfaces
  • Robots
  • Computer and Microprocessor-Based Control
  • Automotive Electronics
  • Display System Design and Implementation

TRACK 6—RENEWABLE ENERGY

  • Renewable Energy Technologies
  • Photovoltaic and Wind Energy Technologies
  • Power Conversions
  • Applications of Power Electronics in Power Systems
  • Smart Grid Systems

TRACK 7—SYSTEMS AND CONTROL

  • System Modeling and Simulation, Dynamics and Control
  • Intelligent and Learning Control
  • Robotics and Mechatronics
  • Robust and Nonlinear Control
  • Biomedical Systems and Control

TRACK 8—DIGITAL SIGNAL PROCESSING

  • Digital Signal Processing Theory and Methods
  • Statistical Signal Processing and Applications
  • Biomedical and Biological Signal Processing
  • Neural Networks, Fuzzy Systems, Expert Systems, Genetic Algorithms and Data Fusion for Signal Processing
  • Embedded Systems for Signal Processing

Website: http://is3c2016.ncuteecs.org/

Prof. Dr. Hsiung-Cheng Lin
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 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. Algorithms 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 1000 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

  • Algorithms in engineering problems solving
  • System design and on-line control
  • Networks and computer applications
  • Computational modeling

Published Papers (7 papers)

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Research

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Open AccessArticle
An On-Line Tracker for a Stochastic Chaotic System Using Observer/Kalman Filter Identification Combined with Digital Redesign Method
Algorithms 2017, 10(1), 25; https://doi.org/10.3390/a10010025
Received: 15 November 2016 / Revised: 8 February 2017 / Accepted: 9 February 2017 / Published: 15 February 2017
Cited by 3 | PDF Full-text (2655 KB) | HTML Full-text | XML Full-text
Abstract
This is the first paper to present such a digital redesign method for the (conventional) OKID system and apply this novel technique for nonlinear system identification. First, the Observer/Kalman filter Identification (OKID) method is used to obtain the lower-order state-space model for a [...] Read more.
This is the first paper to present such a digital redesign method for the (conventional) OKID system and apply this novel technique for nonlinear system identification. First, the Observer/Kalman filter Identification (OKID) method is used to obtain the lower-order state-space model for a stochastic chaos system. Then, a digital redesign approach with the high-gain property is applied to improve and replace the observer identified by OKID. Therefore, the proposed OKID combined with an observer-based digital redesign novel tracker not only suppresses the uncertainties and the nonlinear perturbations, but also improves more accurate observation parameters of OKID for complex Multi-Input Multi-Output systems. In this research, Chen’s stochastic chaotic system is used as an illustrative example to demonstrate the effectiveness and excellence of the proposed methodology. Full article
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Open AccessArticle
A Pilot-Pattern Based Algorithm for MIMO-OFDM Channel Estimation
Algorithms 2017, 10(1), 3; https://doi.org/10.3390/a10010003
Received: 12 September 2016 / Revised: 7 December 2016 / Accepted: 13 December 2016 / Published: 28 December 2016
Cited by 4 | PDF Full-text (1103 KB) | HTML Full-text | XML Full-text
Abstract
An improved pilot pattern algorithm for facilitating the channel estimation in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems is proposed in this paper. The presented algorithm reconfigures the parameter in the least square (LS) algorithm, which belongs to the space-time block-coded [...] Read more.
An improved pilot pattern algorithm for facilitating the channel estimation in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems is proposed in this paper. The presented algorithm reconfigures the parameter in the least square (LS) algorithm, which belongs to the space-time block-coded (STBC) category for channel estimation in pilot-based MIMO-OFDM system. Simulation results show that the algorithm has better performance in contrast to the classical single symbol scheme. In contrast to the double symbols scheme, the proposed algorithm can achieve nearly the same performance with only half of the complexity of the double symbols scheme. Full article
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Open AccessArticle
A No Reference Image Quality Assessment Metric Based on Visual Perception
Algorithms 2016, 9(4), 87; https://doi.org/10.3390/a9040087
Received: 30 August 2016 / Revised: 8 December 2016 / Accepted: 12 December 2016 / Published: 16 December 2016
Cited by 8 | PDF Full-text (6425 KB) | HTML Full-text | XML Full-text | Correction
Abstract
Nowadays, how to evaluate image quality reasonably is a basic and challenging problem. In view of the present no reference evaluation methods, they cannot reflect the human visual perception of image quality accurately. In this paper, we propose an efficient general-purpose no reference [...] Read more.
Nowadays, how to evaluate image quality reasonably is a basic and challenging problem. In view of the present no reference evaluation methods, they cannot reflect the human visual perception of image quality accurately. In this paper, we propose an efficient general-purpose no reference image quality assessment (NRIQA) method based on visual perception, and effectively integrates human visual characteristics into the NRIQA fields. First, a novel algorithm for salient region extraction is presented. Two characteristics graphs of texture and edging of the original image are added to the Itti model. Due to the normalized luminance coefficients of natural images obey the generalized Gauss probability distribution, we utilize this characteristic to extract statistical features in the regions of interest (ROI) and regions of non-interest respectively. Then, the extracted features are fused to be an input to establish the support vector regression (SVR) model. Finally, the IQA model obtained by training is used to predict the quality of the image. Experimental results show that this method has good predictive ability, and the evaluation effect is better than existing classical algorithms. Moreover, the predicted results are more consistent with human subjective perception, which can accurately reflect the human visual perception to image quality. Full article
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Open AccessArticle
Evaluation of Cloud Services: A Fuzzy Multi-Criteria Group Decision Making Method
Algorithms 2016, 9(4), 84; https://doi.org/10.3390/a9040084
Received: 26 August 2016 / Revised: 23 November 2016 / Accepted: 28 November 2016 / Published: 16 December 2016
Cited by 4 | PDF Full-text (385 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents a fuzzy multi-criteria group decision making method for evaluating the performance of Cloud services in an uncertain environment. Intuitionistic fuzzy numbers are used to better model the subjectivity and imprecision in the performance evaluation process. An effective algorithm is developed [...] Read more.
This paper presents a fuzzy multi-criteria group decision making method for evaluating the performance of Cloud services in an uncertain environment. Intuitionistic fuzzy numbers are used to better model the subjectivity and imprecision in the performance evaluation process. An effective algorithm is developed based on the technique for order preference by similarity to the ideal solution and the Choquet integral operator for adequately solving the performance evaluation problem. An example is presented for demonstrating the applicability of the proposed method for solving the multi-criteria group decision making problem in real situations. Full article
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Open AccessArticle
Fault Sensing Using Fractal Dimension and Wavelet
Algorithms 2016, 9(4), 66; https://doi.org/10.3390/a9040066
Received: 25 August 2016 / Revised: 30 September 2016 / Accepted: 30 September 2016 / Published: 11 October 2016
Cited by 1 | PDF Full-text (2112 KB) | HTML Full-text | XML Full-text
Abstract
A new fusion sensing (FS) method was proposed by using the improved fractal box dimension (IFBD) and a developed maximum wavelet coefficient (DMWC) for fault sensing of an online power cable. There are four strategies that were used. Firstly, the traditional fractal box [...] Read more.
A new fusion sensing (FS) method was proposed by using the improved fractal box dimension (IFBD) and a developed maximum wavelet coefficient (DMWC) for fault sensing of an online power cable. There are four strategies that were used. Firstly, the traditional fractal box dimension was improved to enlarge the feature distances between the different fault classes. Secondly, the IFBD recognition algorithm was proposed by using the improved fractal dimension feature extracted from the three-phase currents for the first stage of fault recognition. Thirdly, the DMWC recognition algorithm was developed based on the K-transform and wavelet analysis to establish the relationship between the maximum wavelet coefficient and the fault class. Fourthly, the FS method was formed by combining the IFBD algorithm and the DMWC algorithm in order to recognize the 10 types of short circuit faults of online power. The designed test system proved that the FS method increased the fault recognition accuracy obviously. In addition, the parameters of the initial angle, transient resistance, and fault distance had no influence on the FS method. Full article
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Open AccessArticle
Noise Reduction of Steel Cord Conveyor Belt Defect Electromagnetic Signal by Combined Use of Improved Wavelet and EMD
Algorithms 2016, 9(4), 62; https://doi.org/10.3390/a9040062
Received: 17 July 2016 / Revised: 3 September 2016 / Accepted: 13 September 2016 / Published: 26 September 2016
Cited by 3 | PDF Full-text (2940 KB) | HTML Full-text | XML Full-text
Abstract
In order to reduce the noise of a defect electromagnetic signal of the steel cord conveyor belt used in coal mines, a new signal noise reduction method by combined use of the improved threshold wavelet and Empirical Mode Decomposition (EMD) is proposed. Firstly, [...] Read more.
In order to reduce the noise of a defect electromagnetic signal of the steel cord conveyor belt used in coal mines, a new signal noise reduction method by combined use of the improved threshold wavelet and Empirical Mode Decomposition (EMD) is proposed. Firstly, the denoising method based on the improved threshold wavelet is applied to reduce the noise of a defect electromagnetic signal obtained by an electromagnetic testing system. Then, the EMD is used to decompose the denoised signal and then the effective Intrinsic Mode Function (IMF) is extracted by the dominant eigenvalue strategy. Finally, the signal reconstruction is carried out by utilizing the obtained IMF. In order to verify the proposed noise reduction method, the experiments are carried out in two cases including the defective joint and steel wire rope break. The experimental results show that the proposed method in this paper obtains the higher Signal to Noise Ratio (SNR) for the defect electromagnetic signal noise reduction of steel cord conveyor belts. Full article
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Other

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Open AccessCorrection
Correction: A No Reference Image Quality Assessment Metric Based on Visual Perception. Algorithms 2016, 9, 87
Algorithms 2017, 10(2), 60; https://doi.org/10.3390/a10020060
Received: 19 May 2017 / Revised: 25 May 2017 / Accepted: 25 May 2017 / Published: 26 May 2017
PDF Full-text (448 KB) | HTML Full-text | XML Full-text
Abstract
We would like to make the following change to our article [1]. [...] Full article
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