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Joint Issue with 5th International Symposium on Computer, Consumer and Control (IS3C2020)

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".

Deadline for manuscript submissions: closed (16 March 2021) | Viewed by 10507

Special Issue Editors

Prof. Dr. Jun-Juh Yan

E-Mail Website
Guest Editor
Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung 41107, Taiwan
Interests: smart computing; robust control; secure communication; chaotic signal processing; applied mathematics
Prof. Dr. Jason Sheng-Hong Tsai

E-Mail Website
Guest Editor
Department of Electrical Engineering, National Cheng-Kung University, Tainan 701, Taiwan
Interests: robotics; numerical analysis; digital control; state-space self-tuning control; partial differential system control; optimal control

Special Issue Information

Dear Colleagues,

This Special Issue pertains to the 5th International Symposium on Computer, Consumer and Control (IS3C2020) to be held in Taichung, Taiwan, 18-20 June 2020. This conference offers a great opportunity for scientists, engineers, and practitioners to present the latest research results, ideas, developments, and applications. IS3C, held every two years, is hosted and sponsored by National Chin-Yi University of Technology, Taichung, Taiwan. As suggested by the name of the conference, the themes of this conference cover advanced multimedia, computer, telecommunication, sensors and semiconductor, 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.

This special issue includes topics with Technology, Innovation, Research & Development, Machine Learning and Consciousness, Artificial Intelligent, Automation,  Robotics, Digital redesign technology, Cognitive Systems, Digitalization, Secure communication, Process Automation, Performance Optimization. Manuscripts dealing with the implementation and development of the latest supercomputing technologies that are transferable to the above areas also fall within the scope of this special issue.

Recently, many intelligent robots have been developed for the future society. Particularly, intelligent robots should continue to perform tasks in real environments such as houses, commercial facilities and public facilities. The growing needs to automate daily tasks combined with new robot technologies are driving the development of human-friendly robots. Intelligent robots should have human-like intelligence and cognitive capabilities to co-exist with people.

Artificial intelligence is very important to provide human-friendly services by robots. Research on artificial intelligence, cognition computing, and soft computing has a long history. The concepts on adaptation, learning, and cognitive development should be introduced more intensively in the next generation robotics. Furthermore, the advent of Internet of Things, 5G wireless technology, and robotics technology may also bring brand-new emerging intelligence to robots. Therefore, This special session focuses on the intelligence of robots emerging from the adaptation, learning, and cognitive development through the interaction with people and dynamic environments from the conceptual, theoretical, methodological, and technical points of view.

This Special Issue is expected to select excellent papers both from and out of IS3C2020. We will provide an open discussion platform, where researchers, technologists, managers, entrepreneurs and investors can share experiences, opinions and expectations about the latest advances in this field.

Prof. Dr. Jun-Juh Yan
Prof. Dr. Jason Sheng-Hong Tsai
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

  • Technology, innovation, research & development
  • Nonlinear system
  • Digital redesign technology
  • Artificial intelligence
  • Secure communication
  • Robotics
  • Cognitive systems
  • Performance optimization…

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Published Papers (3 papers)

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Research

29 pages, 14241 KiB  
Article
Automated Optical Inspection System for O-Ring Based on Photometric Stereo and Machine Vision
by Fu-Sheng Yang, Chao-Ching Ho and Liang-Chia Chen
Appl. Sci. 2021, 11(6), 2601; https://doi.org/10.3390/app11062601 - 15 Mar 2021
Cited by 13 | Viewed by 3902
Abstract
This research developed an AOI (automated optical inspection) system for the O-Ring inspection. First, an AOI system was implemented to detect surface scratches, flow marks, non-fills, and indentations on elastomer O-Rings with high surface reflection coefficients. The proposed system employed multiple light source [...] Read more.
This research developed an AOI (automated optical inspection) system for the O-Ring inspection. First, an AOI system was implemented to detect surface scratches, flow marks, non-fills, and indentations on elastomer O-Rings with high surface reflection coefficients. The proposed system employed multiple light source structures to realize the photometric stereo. This method eased the identification of the O-Ring contour and Bézier control points. Then, by applying an interpolation process on these control points, we estimated the paths of the object surface. Simultaneously, regression analysis was conducted to produce a new smooth surface and then a constructed surface was compared with the model built by the photometric stereo method. The difference was deemed the candidate defect location. Overall, the detection recall rate was 100% and accuracy reached 96.56%. This paper also developed an AOI system for the O-Ring dimension measurement. The system analyzed the contour of the O-Ring and reversely calculated the Bézier curve control points. Then, those control points were used with De Casteljau’s algorithm to estimate the O-Ring dimension with high accuracy. Full article
(This article belongs to the Special Issue Joint Issue with 5th International Symposium on Computer, Consumer and Control (IS3C2020))
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19 pages, 6683 KiB  
Article
A Hybrid Wind Power Forecasting Model with XGBoost, Data Preprocessing Considering Different NWPs
by Quoc Thang Phan, Yuan Kang Wu and Quoc Dung Phan
Appl. Sci. 2021, 11(3), 1100; https://doi.org/10.3390/app11031100 - 25 Jan 2021
Cited by 33 | Viewed by 3500
Abstract
In recent years, wind energy has become a competitively priced source of energy around the world, which has created increasing challenges for system operators. Accurate wind power generation forecasting plays an important role in power systems to improve the reliable and efficient operation. [...] Read more.
In recent years, wind energy has become a competitively priced source of energy around the world, which has created increasing challenges for system operators. Accurate wind power generation forecasting plays an important role in power systems to improve the reliable and efficient operation. Therefore, numerous artificial intelligent methods such as machine learning and deep learning have been considered as solutions for accurate wind power forecasts. In addition to deterministic forecasting, the probabilistic forecasting becomes more important, because it indicates the level of uncertainty. In this paper, a hybrid forecasting model considering different Numerical Weather Prediction (NWP) models and the XGBoost training model is proposed for short-term wind power forecasting. The proposed forecasting algorithm includes data preprocessing, in which an autoencoder model is used to reduce the dimension of 20 NWP ensembles. The performance of the proposed method is investigated using historical wind power measurements and NWP results by the Taiwan Central Weather Bureau (CWB); the NWP includes spot wind speeds from WRFD, RWRF, and ensemble wind speeds from WEPS. Based on the forecasting results, the proposed model produces better performance and forecasting accuracy among other forecasting models, which reveals the importance of data preprocessing using autoencoders and the use of deep learning models in deterministic or probabilistic forecasts. Full article
(This article belongs to the Special Issue Joint Issue with 5th International Symposium on Computer, Consumer and Control (IS3C2020))
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30 pages, 2765 KiB  
Article
A Modified Functional Observer-Based EID Estimator for Unknown Continuous-Time Singular Systems
by Jason Sheng-Hong Tsai, Yang-Fang Chen, Te-Jen Su, Chia-Yuan Chang, Shu-Mei Guo, Leang-San Shieh and Jose I. Canelon
Appl. Sci. 2020, 10(7), 2316; https://doi.org/10.3390/app10072316 - 28 Mar 2020
Viewed by 2291
Abstract
This paper presents the design of a linear quadratic analog tracker (LQAT) based on the observer–Kalman-filter identification (OKID) method and the design of a modified functional observer-based equivalent input disturbance (EID) estimator for unknown square–non-square singular analog systems with unknown input and output [...] Read more.
This paper presents the design of a linear quadratic analog tracker (LQAT) based on the observer–Kalman-filter identification (OKID) method and the design of a modified functional observer-based equivalent input disturbance (EID) estimator for unknown square–non-square singular analog systems with unknown input and output disturbances. First, an equivalent mathematical model of the singular analog system is presented to simulate the time response of continuous-time linear singular analog systems to arbitrary inputs via the model conversion method. Then, for the unknown singular analog system, it constructs a linear quadratic analog tracker with state feedback and feed-forward gains based on the off-line OKID method. Furthermore, it extends the design methodology of the EID estimator for strictly proper regular systems with unknown matched–mismatched input and output disturbances to proper regular systems. It is important to mention that the newly developed modified functional observer for proper systems is used to estimate the unknown EID of singular analog systems and that the constraints on the dimensions of unknown disturbances can be eliminated by using the newly proposed EID estimation method. The contributions of this paper can be listed as follows: (1) based on both the OKID method and the discrete-to-continuous model conversion, the simulation of the time responses of the continuous-time linear singular models (which are not feasible using existing MATLAB toolboxes) become feasible; (2) for effective control of the unknown singular analog system, an off-line OKID method is proposed to design an LQAT with state feedback and feed-forward gains; and (3) based on the newly developed modified functional observer for the reduced-order proper regular system, the original EID estimator in the literature is newly extended to estimate the EID from the unknown strictly proper singular analog system, without the original dimensional constraints of the disturbances. It is important to mention that the disturbances of interest can be unknown matched–mismatched input and output disturbances. Full article
(This article belongs to the Special Issue Joint Issue with 5th International Symposium on Computer, Consumer and Control (IS3C2020))
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