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Special Issue "Selected Papers from 2014 International Symposium on Computer, Consumer and Control (IS3C 2014)"

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A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (15 March 2014)

Special Issue Editors

Guest Editor
Prof. Dr. Hsiung-Cheng Lin

Department of Electronic Engineering, National Chin-Yi University of Technology
Website | E-Mail
Interests: microprocessor applications; practical applications of control system; network supervised control; graphical interface control; power harmonics tracking and analysis; neural network and applications
Guest Editor
Prof. Dr. Wen-Yuan Chen

Department of Electronic Engineering, National Chin-Yi University of Technology, Taichung, Taiwan
Website | E-Mail
Interests: image processing; multi-media compressed technique; multi-media communication; computer programming; and computer game design

Special Issue Information

Dear Colleagues,

IS3C 2014 is the International Symposium on Computer, Consumer and Control sponsored by IEEE and National Chin-Yi University of Technology. This conference offers a great opportunity for scientists, engineers, and practitioners to present the latest research results, ideas, developments, and applications, as well as to facilitate interactions between scholars and practitioners. We cordially invite you to attend the IS3C 2014, which will be held in Taichung City, Taiwan on June 10-12, 2014. As suggested by the name of the conference, the theme of this conference covers advanced multimedia, computer, telecommunication, semiconductor, consumer electronics, renewable energy, systems and control, and digital signal processing. Original high-quality papers related to this theme are especially solicited, including theories, methodologies, and applications in Computing, Consumer and Control. All accepted papers will be included in IS3C 2014 Proceedings, published IEEE Xplore with CD-ROM , and will be applied for EI Compendex/ISTP index.

Original papers describing current research in the following themes are invited in

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 & Microwave Engineering


TRACK 4 - SEMICONDUCTOR

  • Systems on Chip
  • Application of Microelectronics
  • Device Modeling, Simulation and Design
  • Material and New Fabrication Facilities Technologies
  • Nano Technology

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://is3c2014.ncuteecs.org/index.php

Prof. Dr. Hsiung-Cheng Lin
Prof. Dr. Wen-Yuan Chen
Guest Editors

Submission

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. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as 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 refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors 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 1800 CHF (Swiss Francs).


Published Papers (10 papers)

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Research

Open AccessArticle An Adaptive Supervisory Sliding Fuzzy Cerebellar Model Articulation Controller for Sensorless Vector-Controlled Induction Motor Drive Systems
Sensors 2015, 15(4), 7323-7348; doi:10.3390/s150407323
Received: 13 March 2014 / Revised: 13 March 2015 / Accepted: 16 March 2015 / Published: 25 March 2015
Cited by 2 | PDF Full-text (1234 KB) | HTML Full-text | XML Full-text
Abstract
This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and
[...] Read more.
This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes. Full article
Open AccessArticle Active Disaster Response System for a Smart Building
Sensors 2014, 14(9), 17451-17470; doi:10.3390/s140917451
Received: 20 March 2014 / Revised: 11 September 2014 / Accepted: 11 September 2014 / Published: 18 September 2014
Cited by 4 | PDF Full-text (2723 KB) | HTML Full-text | XML Full-text
Abstract
Disaster warning and surveillance systems have been widely applied to help the public be aware of an emergency. However, existing warning systems are unable to cooperate with household appliances or embedded controllers; that is, they cannot provide enough time for preparedness and evacuation,
[...] Read more.
Disaster warning and surveillance systems have been widely applied to help the public be aware of an emergency. However, existing warning systems are unable to cooperate with household appliances or embedded controllers; that is, they cannot provide enough time for preparedness and evacuation, especially for disasters like earthquakes. In addition, the existing warning and surveillance systems are not responsible for collecting sufficient information inside a building for relief workers to conduct a proper rescue action after a disaster happens. In this paper, we describe the design and implementation of a proof of concept prototype, named the active disaster response system (ADRS), which automatically performs emergency tasks when an earthquake happens. ADRS can interpret Common Alerting Protocol (CAP) messages, published by an official agency, and actuate embedded controllers to perform emergency tasks to respond to the alerts. Examples of emergency tasks include opening doors and windows and cutting off power lines and gas valves. In addition, ADRS can maintain a temporary network by utilizing the embedded controllers; hence, victims trapped inside a building are still able to post emergency messages if the original network is disconnected. We conducted a field trial to evaluate the effectiveness of ADRS after an earthquake happened. Our results show that compared to manually operating emergency tasks, ADRS can reduce the operation time by up to 15 s, which is long enough for people to get under sturdy furniture, or to evacuate from the third floor to the first floor, or to run more than 100 m. Full article
Open AccessArticle A Trustworthy Key Generation Prototype Based on DDR3 PUF for Wireless Sensor Networks
Sensors 2014, 14(7), 11542-11556; doi:10.3390/s140711542
Received: 12 March 2014 / Revised: 15 May 2014 / Accepted: 25 June 2014 / Published: 30 June 2014
Cited by 3 | PDF Full-text (870 KB) | HTML Full-text | XML Full-text
Abstract
Secret key leakage in wireless sensor networks (WSNs) is a high security risk especially when sensor nodes are deployed in hostile environment and physically accessible to attackers. With nowadays semi/fully-invasive attack techniques attackers can directly derive the cryptographic key from non-volatile memory (NVM)
[...] Read more.
Secret key leakage in wireless sensor networks (WSNs) is a high security risk especially when sensor nodes are deployed in hostile environment and physically accessible to attackers. With nowadays semi/fully-invasive attack techniques attackers can directly derive the cryptographic key from non-volatile memory (NVM) storage. Physically Unclonable Function (PUF) is a promising technology to resist node capture attacks, and it also provides a low cost and tamper-resistant key provisioning solution. In this paper, we designed a PUF based on double-data-rate SDRAM Type 3 (DDR3) memory by exploring its memory decay characteristics. We also described a prototype of 128-bit key generation based on DDR3 PUF with integrated fuzzy extractor. Due to the wide adoption of DDR3 memory in WSN, our proposed DDR3 PUF technology with high security levels and no required hardware changes is suitable for a wide range of WSN applications. Full article
Open AccessArticle Android Platform Based Smartphones for a Logistical Remote Association Repair Framework
Sensors 2014, 14(7), 11278-11292; doi:10.3390/s140711278
Received: 14 March 2014 / Revised: 13 June 2014 / Accepted: 16 June 2014 / Published: 25 June 2014
Cited by 1 | PDF Full-text (689 KB) | HTML Full-text | XML Full-text
Abstract
The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management
[...] Read more.
The maintenance of large-scale systems is an important issue for logistics support planning. In this paper, we developed a Logistical Remote Association Repair Framework (LRARF) to aid repairmen in keeping the system available. LRARF includes four subsystems: smart mobile phones, a Database Management System (DBMS), a Maintenance Support Center (MSC) and wireless networks. The repairman uses smart mobile phones to capture QR-codes and the images of faulty circuit boards. The captured QR-codes and images are transmitted to the DBMS so the invalid modules can be recognized via the proposed algorithm. In this paper, the Linear Projective Transform (LPT) is employed for fast QR-code calibration. Moreover, the ANFIS-based data mining system is used for module identification and searching automatically for the maintenance manual corresponding to the invalid modules. The inputs of the ANFIS-based data mining system are the QR-codes and image features; the output is the module ID. DBMS also transmits the maintenance manual back to the maintenance staff. If modules are not recognizable, the repairmen and center engineers can obtain the relevant information about the invalid modules through live video. The experimental results validate the applicability of the Android-based platform in the recognition of invalid modules. In addition, the live video can also be recorded synchronously on the MSC for later use. Full article
Open AccessArticle A Distributed Air Index Based on Maximum Boundary Rectangle over Grid-Cells for Wireless Non-Flat Spatial Data Broadcast
Sensors 2014, 14(6), 10619-10643; doi:10.3390/s140610619
Received: 14 March 2014 / Revised: 2 June 2014 / Accepted: 12 June 2014 / Published: 17 June 2014
PDF Full-text (5484 KB) | HTML Full-text | XML Full-text
Abstract
In the pervasive computing environment using smart devices equipped with various sensors, a wireless data broadcasting system for spatial data items is a natural way to efficiently provide a location dependent information service, regardless of the number of clients. A non-flat wireless broadcast
[...] Read more.
In the pervasive computing environment using smart devices equipped with various sensors, a wireless data broadcasting system for spatial data items is a natural way to efficiently provide a location dependent information service, regardless of the number of clients. A non-flat wireless broadcast system can support the clients in accessing quickly their preferred data items by disseminating the preferred data items more frequently than regular data on the wireless channel. To efficiently support the processing of spatial window queries in a non-flat wireless data broadcasting system, we propose a distributed air index based on a maximum boundary rectangle (MaxBR) over grid-cells (abbreviated DAIM), which uses MaxBRs for filtering out hot data items on the wireless channel. Unlike the existing index that repeats regular data items in close proximity to hot items at same frequency as hot data items in a broadcast cycle, DAIM makes it possible to repeat only hot data items in a cycle and reduces the length of the broadcast cycle. Consequently, DAIM helps the clients access the desired items quickly, improves the access time, and reduces energy consumption. In addition, a MaxBR helps the clients decide whether they have to access regular data items or not. Simulation studies show the proposed DAIM outperforms existing schemes with respect to the access time and energy consumption. Full article
Open AccessArticle Railway Crossing Risk Area Detection Using Linear Regression and Terrain Drop Compensation Techniques
Sensors 2014, 14(6), 10578-10597; doi:10.3390/s140610578
Received: 14 March 2014 / Revised: 31 May 2014 / Accepted: 4 June 2014 / Published: 16 June 2014
PDF Full-text (1198 KB) | HTML Full-text | XML Full-text
Abstract
Most railway accidents happen at railway crossings. Therefore, how to detect humans or objects present in the risk area of a railway crossing and thus prevent accidents are important tasks. In this paper, three strategies are used to detect the risk area of
[...] Read more.
Most railway accidents happen at railway crossings. Therefore, how to detect humans or objects present in the risk area of a railway crossing and thus prevent accidents are important tasks. In this paper, three strategies are used to detect the risk area of a railway crossing: (1) we use a terrain drop compensation (TDC) technique to solve the problem of the concavity of railway crossings; (2) we use a linear regression technique to predict the position and length of an object from image processing; (3) we have developed a novel strategy called calculating local maximum Y-coordinate object points (CLMYOP) to obtain the ground points of the object. In addition, image preprocessing is also applied to filter out the noise and successfully improve the object detection. From the experimental results, it is demonstrated that our scheme is an effective and corrective method for the detection of railway crossing risk areas. Full article
Open AccessArticle Robust Sensing of Approaching Vehicles Relying on Acoustic Cues
Sensors 2014, 14(6), 9546-9561; doi:10.3390/s140609546
Received: 14 March 2014 / Revised: 22 May 2014 / Accepted: 26 May 2014 / Published: 30 May 2014
Cited by 1 | PDF Full-text (596 KB) | HTML Full-text | XML Full-text
Abstract
The latest developments in automobile design have allowed them to be equipped with various sensing devices. Multiple sensors such as cameras and radar systems can be simultaneously used for active safety systems in order to overcome blind spots of individual sensors. This paper
[...] Read more.
The latest developments in automobile design have allowed them to be equipped with various sensing devices. Multiple sensors such as cameras and radar systems can be simultaneously used for active safety systems in order to overcome blind spots of individual sensors. This paper proposes a novel sensing technique for catching up and tracking an approaching vehicle relying on an acoustic cue. First, it is necessary to extract a robust spatial feature from noisy acoustical observations. In this paper, the spatio-temporal gradient method is employed for the feature extraction. Then, the spatial feature is filtered out through sequential state estimation. A particle filter is employed to cope with a highly non-linear problem. Feasibility of the proposed method has been confirmed with real acoustical observations, which are obtained by microphones outside a cruising vehicle. Full article
Open AccessArticle An Optimal Current Observer for Predictive Current Controlled Buck DC-DC Converters
Sensors 2014, 14(5), 8851-8868; doi:10.3390/s140508851
Received: 16 March 2014 / Revised: 9 May 2014 / Accepted: 12 May 2014 / Published: 19 May 2014
Cited by 2 | PDF Full-text (1289 KB) | HTML Full-text | XML Full-text
Abstract
In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed
[...] Read more.
In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally. Full article
Open AccessArticle Cooperative Spectrum Sensing Schemes with the Interference Constraint in Cognitive Radio Networks
Sensors 2014, 14(5), 8037-8056; doi:10.3390/s140508037
Received: 12 March 2014 / Revised: 24 April 2014 / Accepted: 28 April 2014 / Published: 5 May 2014
Cited by 5 | PDF Full-text (397 KB) | HTML Full-text | XML Full-text
Abstract
In this paper, we propose cooperative spectrum sensing schemes, called decode-and-forward cooperative spectrum sensing (DF-CSS) scheme and amplify-and-forward cooperative spectrum sensing (AF-CSS) scheme, in cognitive radio networks. The main goals and features of the proposed cooperative spectrum sensing schemes are as follows: first,
[...] Read more.
In this paper, we propose cooperative spectrum sensing schemes, called decode-and-forward cooperative spectrum sensing (DF-CSS) scheme and amplify-and-forward cooperative spectrum sensing (AF-CSS) scheme, in cognitive radio networks. The main goals and features of the proposed cooperative spectrum sensing schemes are as follows: first, we solve the problem of high demand for bandwidth in a soft decision scheme using in our proposed schemes. Furthermore, the impact of transmission power of relaying users which is determined by the interference constraint on sensing performance of cooperative spectrum sensing schemes is also investigated. Second, we analyze the sensing performance of our proposed cooperative spectrum sensing schemes in terms of detection probability and interference probability, respectively. We take into account the interference caused by secondary user (SU) to primary user (PU) in the case that the transmission power of the relaying users exceeds a predefined interference constraint assigned by the primary user. The simulation results show that in cooperative spectrum sensing schemes the total sensing performance depends not only on the interference tolerance level, but also on the relay protocols used. We also prove that high transmission power of relaying users increases the interference between the secondary networks and the primary network. Full article
Open AccessArticle The Enhanced Locating Performance of an Integrated Cross-Correlation and Genetic Algorithm for Radio Monitoring Systems
Sensors 2014, 14(4), 7541-7562; doi:10.3390/s140407541
Received: 14 March 2014 / Revised: 20 April 2014 / Accepted: 21 April 2014 / Published: 24 April 2014
Cited by 2 | PDF Full-text (1580 KB) | HTML Full-text | XML Full-text
Abstract
The rapid development of wireless broadband communication technology has affected the location accuracy of worldwide radio monitoring stations that employ time-difference-of-arrival (TDOA) location technology. In this study, TDOA-based location technology was implemented in Taiwan for the first time according to International Telecommunications Union
[...] Read more.
The rapid development of wireless broadband communication technology has affected the location accuracy of worldwide radio monitoring stations that employ time-difference-of-arrival (TDOA) location technology. In this study, TDOA-based location technology was implemented in Taiwan for the first time according to International Telecommunications Union Radiocommunication (ITU-R) recommendations regarding monitoring and location applications. To improve location accuracy, various scenarios, such as a three-dimensional environment (considering an unequal locating antenna configuration), were investigated. Subsequently, the proposed integrated cross-correlation and genetic algorithm was evaluated in the metropolitan area of Tainan. The results indicated that the location accuracy at a circular error probability of 50% was less than 60 m when a multipath effect was present in the area. Moreover, compared with hyperbolic algorithms that have been applied in conventional TDOA-based location systems, the proposed algorithm yielded 17-fold and 19-fold improvements in the mean difference when the location position of the interference station was favorable and unfavorable, respectively. Hence, the various forms of radio interference, such as low transmission power, burst and weak signals, and metropolitan interference, was proved to be easily identified, located, and removed. Full article

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