Selected Papers from the Seventh International Conference on Innovative Computing Technology (INTECH 2017)

A special issue of Technologies (ISSN 2227-7080).

Deadline for manuscript submissions: closed (31 December 2017) | Viewed by 24571

Special Issue Editors

Department of Computer Science and Technology, University of Bedfordshire, Luton LU1 3JU, UK
Interests: information systems and business systems; computer science and technology innovation; facilities management and network development; e-commerce and e-learning; implementation of webographic development; SMEs and entrepreneur (e-business perspectives); knowledge management and sustainability; smart wearable technologies; green computing and renewable energy; emerging technologies and systems development; healthcare informatics; digital enterprise and social media; business processing re-engineering; business process management and eagriculture; cloud computing and internet of things (IoT); corporate social responsibility; computer systems and monetization; engineering sustainability; digital informatics and community of practice (cop); social enterprise and healthcare informatics; consumer electronics and energy management systems; green technology and digital media; egovernment and edemocracy and evoting; informatics climatization and digital environment; forensic informatics and fina
Special Issues, Collections and Topics in MDPI journals
Research Associate, Research Centre in Real-time and Embedded Computing Systems (CISTER), Porto, Portugal
Interests: signal processing for wireless communications; MAC-PHY cross-layer design; IoT; wireless sensor networks
Instituto Superior de Contabilidade e Administraçمo do Porto, Porto, Portugal
Interests: accounting; management; methodologies of qualitative research

Special Issue Information

Dear Colleagues,

Please visit this site: http://www.dirf.org/intech/, for a detailed description of this Special Issue. The Special Issue will mainly consist of selected papers presented at the Seventh International Conference on Innovative Computing Technology (INTECH 2017).

Prof. Dr. Ezendu Ariwa
Prof. Dr. Paulino Silva
Dr. Ramiro Sámano Robles
Guest Editors

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Published Papers (3 papers)

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Research

15 pages, 450 KiB  
Article
On the Throughput Region of Wireless Random Access Protocols with Multi-Packet Reception Using Multi-Objective Optimization
by Ramiro Sámano-Robles
Technologies 2018, 6(4), 117; https://0-doi-org.brum.beds.ac.uk/10.3390/technologies6040117 - 08 Dec 2018
Cited by 1 | Viewed by 4070
Abstract
This paper presents a new approach for the analysis and characterization of the throughput region of wireless random access protocols enabled with multi-packet reception (MPR) capabilities. The derivation of a closed-form expression for the envelope of the throughput region under the assumption of [...] Read more.
This paper presents a new approach for the analysis and characterization of the throughput region of wireless random access protocols enabled with multi-packet reception (MPR) capabilities. The derivation of a closed-form expression for the envelope of the throughput region under the assumption of an arbitrary number of terminals is an open issue in the literature. To partially fill this gap, a new method based on multi-objective optimization tools is herein presented. This innovative perspective allows us to identify the envelope of the throughput region as the Pareto frontier solution that results from maximizing simultaneously all individual terminal throughput functions. To simplify this problem, a modified MPR model is proposed that mimics the conditions of collision model protocols, but it also inserts new physical (PHY) layer features that allow concurrent transmission or MPR. The N-reception model is herein introduced, where collisions of up to N signals are assumed to be always correctly resolved from a population of J terminals, where N can be related to the number of antennas or degrees of freedom of the PHY-layer used at the receiver to resolve a collision. It is shown that by using this model and under the assumption of N = J - 1 , the Pareto frontier expression can be obtained as a simple extension of the ALOHA solution. Unfortunately, for cases with N < J - 1 , the structure of the resulting determinant matrix does not allow for a simple explicit solution. To overcome this issue, a symmetrical system is proposed, and the solution is obtained by the analysis of the roots of the resulting polynomial expression. Based on this result, an equivalent sub-optimal solution for the asymmetrical case is herein identified for systems where N < J - 1 . An extension to more general reception models based on conditional reception probabilities is also presented using the proposed equivalence between the symmetric and asymmetric solutions. The results intend to shed light on the performance of MPR systems in general, and in particular to advance towards the solution of the conjecture of the equivalence between throughput and stability regions in random access. Full article
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25 pages, 3936 KiB  
Article
Mitigating Wind Induced Noise in Outdoor Microphone Signals Using a Singular Spectral Subspace Method
by Omar Eldwaik and Francis F. Li
Technologies 2018, 6(1), 19; https://0-doi-org.brum.beds.ac.uk/10.3390/technologies6010019 - 28 Jan 2018
Cited by 5 | Viewed by 6123
Abstract
Wind induced noise is one of the major concerns of outdoor acoustic signal acquisition. It affects many field measurement and audio recording scenarios. Filtering such noise is known to be difficult due to its broadband and time varying nature. In this paper, a [...] Read more.
Wind induced noise is one of the major concerns of outdoor acoustic signal acquisition. It affects many field measurement and audio recording scenarios. Filtering such noise is known to be difficult due to its broadband and time varying nature. In this paper, a new method to mitigate wind induced noise in microphone signals is developed. Instead of applying filtering techniques, wind induced noise is statistically separated from wanted signals in a singular spectral subspace. The paper is presented in the context of handling microphone signals acquired outdoor for acoustic sensing and environmental noise monitoring or soundscapes sampling. The method includes two complementary stages, namely decomposition and reconstruction. The first stage decomposes mixed signals in eigen-subspaces, selects and groups the principal components according to their contributions to wind noise and wanted signals in the singular spectrum domain. The second stage reconstructs the signals in the time domain, resulting in the separation of wind noise and wanted signals. Results show that microphone wind noise is separable in the singular spectrum domain evidenced by the weighted correlation. The new method might be generalized to other outdoor sound acquisition applications. Full article
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18 pages, 1717 KiB  
Article
Facial Expression Emotion Detection for Real-Time Embedded Systems
by Saeed Turabzadeh, Hongying Meng, Rafiq M. Swash, Matus Pleva and Jozef Juhar
Technologies 2018, 6(1), 17; https://0-doi-org.brum.beds.ac.uk/10.3390/technologies6010017 - 26 Jan 2018
Cited by 48 | Viewed by 13756
Abstract
Recently, real-time facial expression recognition has attracted more and more research. In this study, an automatic facial expression real-time system was built and tested. Firstly, the system and model were designed and tested on a MATLAB environment followed by a MATLAB Simulink environment [...] Read more.
Recently, real-time facial expression recognition has attracted more and more research. In this study, an automatic facial expression real-time system was built and tested. Firstly, the system and model were designed and tested on a MATLAB environment followed by a MATLAB Simulink environment that is capable of recognizing continuous facial expressions in real-time with a rate of 1 frame per second and that is implemented on a desktop PC. They have been evaluated in a public dataset, and the experimental results were promising. The dataset and labels used in this study were made from videos, which were recorded twice from five participants while watching a video. Secondly, in order to implement in real-time at a faster frame rate, the facial expression recognition system was built on the field-programmable gate array (FPGA). The camera sensor used in this work was a Digilent VmodCAM — stereo camera module. The model was built on the Atlys™ Spartan-6 FPGA development board. It can continuously perform emotional state recognition in real-time at a frame rate of 30. A graphical user interface was designed to display the participant’s video in real-time and two-dimensional predict labels of the emotion at the same time. Full article
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