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Selected Papers from the 7th Computer Science and Electronic Engineering...
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Selected Papers from the 7th Computer Science and Electronic Engineering Conference (CEEC) 2015

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: closed (15 February 2016) | Viewed by 52592

Special Issue Editor

Dr. Laith Al-Jobouri

E-Mail Website
Guest Editor
School of Computer Science and Electronic Engineering, University of Essex, Colchester, Essex CO4 3SQ, UK
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The 7th Computer Science and Electronic Engineering Conference (CEEC) will be held 24–25 September, 2015, at the School of Computer Science and Electronic Engineering, University of Essex, United Kingdom. For more information about the conference please use this link: http://ceec.uk/

Selected papers that presented at the conference are invited to submit their extended versions to this Special Issue of the journal Computers after the conference and, at the latest, by 15 February, 2016. Submitted papers should be extended to the size of regular research or review articles with 50% extension of new results. All submitted papers will undergo our standard peer-review procedure. Accepted papers will be published in Open Access format in Computers and collected together in this Special Issue website. There are no page/publication charges for this journal.

As there are no publication charges for this journal, please prepare and format your paper according to the Instructions for Authors. Use the LaTeX or Microsoft Word template file of the journal (both are available from the Instructions for Authors page). Manuscripts should be submitted online via our susy.mdpi.com editorial system.

Laith Al-Jobouri
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 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. Computers 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). 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.

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Published Papers (6 papers)

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Research

3441 KiB  
Article
Color Reduction in an Authenticate Live 3D Point Cloud Video Streaming System
by Zainab Sultani, Rana F. Al-Tuma and Sandro Wefel
Computers 2016, 5(3), 17; https://doi.org/10.3390/computers5030017 - 26 Jul 2016
Cited by 1 | Viewed by 8609
Abstract
In this paper, an authenticate live 3D point cloud video streaming system is presented, using a low cost 3D sensor camera, the Microsoft Kinect. The proposed system is implemented on a client-server network infrastructure. The live 3D video is captured from the Kinect [...] Read more.
In this paper, an authenticate live 3D point cloud video streaming system is presented, using a low cost 3D sensor camera, the Microsoft Kinect. The proposed system is implemented on a client-server network infrastructure. The live 3D video is captured from the Kinect RGB-D sensor, then a 3D point cloud is generated and processed. Filtering and compression are used to handle the spatial and temporal redundancies. A color histogram based conditional filter is designed to reduce the color information for each frame based on the mean and standard deviation. In addition to the designed filter, a statistical outlier removal filter is used. A certificate-based authentication is used where the client will verify the identity of the server during the handshake process. The processed 3D point cloud video is live streamed over a TCP/IP protocol to the client. The system is evaluated in terms of: compression ratio, total bytes per points, peak signal to noise ratio (PSNR), and Structural Similarity (SSIM) index. The experimental results demonstrate that the proposed video streaming system have a best case with SSIM 0.859, PSNR of 26.6 dB and with average compression ratio of 8.42 while the best average compression ratio case is about 15.43 with PSNR 18.5128 dB of and SSIM 0.7936. Full article
(This article belongs to the Special Issue Selected Papers from the 7th Computer Science and Electronic Engineering Conference (CEEC) 2015)
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2998 KiB  
Article
Intelligent Intrusion Detection of Grey Hole and Rushing Attacks in Self-Driving Vehicular Networks
by Khattab M. Ali Alheeti, Anna Gruebler and Klaus McDonald-Maier
Computers 2016, 5(3), 16; https://doi.org/10.3390/computers5030016 - 22 Jul 2016
Cited by 62 | Viewed by 11232
Abstract
Vehicular ad hoc networks (VANETs) play a vital role in the success of self-driving and semi self-driving vehicles, where they improve safety and comfort. Such vehicles depend heavily on external communication with the surrounding environment via data control and Cooperative Awareness Messages (CAMs) [...] Read more.
Vehicular ad hoc networks (VANETs) play a vital role in the success of self-driving and semi self-driving vehicles, where they improve safety and comfort. Such vehicles depend heavily on external communication with the surrounding environment via data control and Cooperative Awareness Messages (CAMs) exchanges. VANETs are potentially exposed to a number of attacks, such as grey hole, black hole, wormhole and rushing attacks. This work presents an intelligent Intrusion Detection System (IDS) that relies on anomaly detection to protect the external communication system from grey hole and rushing attacks. These attacks aim to disrupt the transmission between vehicles and roadside units. The IDS uses features obtained from a trace file generated in a network simulator and consists of a feed-forward neural network and a support vector machine. Additionally, the paper studies the use of a novel systematic response, employed to protect the vehicle when it encounters malicious behaviour. Our simulations of the proposed detection system show that the proposed schemes possess outstanding detection rates with a reduction in false alarms. This safe mode response system has been evaluated using four performance metrics, namely, received packets, packet delivery ratio, dropped packets and the average end to end delay, under both normal and abnormal conditions. Full article
(This article belongs to the Special Issue Selected Papers from the 7th Computer Science and Electronic Engineering Conference (CEEC) 2015)
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1573 KiB  
Article
Optimization of Nano-Process Deposition Parameters Based on Gravitational Search Algorithm
by Norlina Mohd Sabri, Nor Diyana Md Sin, Mazidah Puteh and Mohamad Rusop Mahmood
Computers 2016, 5(2), 12; https://doi.org/10.3390/computers5020012 - 8 Jun 2016
Cited by 2 | Viewed by 6979
Abstract
This research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The [...] Read more.
This research is focusing on the radio frequency (RF) magnetron sputtering process, a physical vapor deposition technique which is widely used in thin film production. This process requires the optimized combination of deposition parameters in order to obtain the desirable thin film. The conventional method in the optimization of the deposition parameters had been reported to be costly and time consuming due to its trial and error nature. Thus, gravitational search algorithm (GSA) technique had been proposed to solve this nano-process parameters optimization problem. In this research, the optimized parameter combination was expected to produce the desirable electrical and optical properties of the thin film. The performance of GSA in this research was compared with that of Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Artificial Immune System (AIS) and Ant Colony Optimization (ACO). Based on the overall results, the GSA optimized parameter combination had generated the best electrical and an acceptable optical properties of thin film compared to the others. This computational experiment is expected to overcome the problem of having to conduct repetitive laboratory experiments in obtaining the most optimized parameter combination. Based on this initial experiment, the adaptation of GSA into this problem could offer a more efficient and productive way of depositing quality thin film in the fabrication process. Full article
(This article belongs to the Special Issue Selected Papers from the 7th Computer Science and Electronic Engineering Conference (CEEC) 2015)
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6470 KiB  
Article
Continuity-Aware Scheduling Algorithm for Scalable Video Streaming
by Atinat Palawan, John C. Woods and Mohammed Ghanbari
Computers 2016, 5(2), 11; https://doi.org/10.3390/computers5020011 - 30 May 2016
Cited by 1 | Viewed by 7115
Abstract
The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth availability, loss, delay and delay variation (jitter). This paper [...] Read more.
The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth availability, loss, delay and delay variation (jitter). This paper presents a scheduling algorithm that modifies the stream of scalable video to combat jitter. The algorithm provides unequal look-ahead by safeguarding the base layer (without the need for overhead) of the scalable video. The results of the experiments show that our scheduling algorithm reduces the number of frames with a violated deadline and significantly improves the continuity of the video stream without compromising the average Y Peek Signal-to-Noise Ratio (PSNR). Full article
(This article belongs to the Special Issue Selected Papers from the 7th Computer Science and Electronic Engineering Conference (CEEC) 2015)
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450 KiB  
Article
Video over DSL with LDGM Codes for Interactive Applications
by Laith Al-Jobouri, Filippo Casu, Martin Fleury and Julián Cabrera
Computers 2016, 5(2), 9; https://doi.org/10.3390/computers5020009 - 23 May 2016
Cited by 2 | Viewed by 7937
Abstract
Digital Subscriber Line (DSL) network access is subject to error bursts, which, for interactive video, can introduce unacceptable latencies if video packets need to be re-sent. If the video packets are protected against errors with Forward Error Correction (FEC), calculation of the application-layer [...] Read more.
Digital Subscriber Line (DSL) network access is subject to error bursts, which, for interactive video, can introduce unacceptable latencies if video packets need to be re-sent. If the video packets are protected against errors with Forward Error Correction (FEC), calculation of the application-layer channel codes themselves may also introduce additional latency. This paper proposes Low-Density Generator Matrix (LDGM) codes rather than other popular codes because they are more suitable for interactive video streaming, not only for their computational simplicity but also for their licensing advantage. The paper demonstrates that a reduction of up to 4 dB in video distortion is achievable with LDGM Application Layer (AL) FEC. In addition, an extension to the LDGM scheme is demonstrated, which works by rearranging the columns of the parity check matrix so as to make it even more resilient to burst errors. Telemedicine and video conferencing are typical target applications. Full article
(This article belongs to the Special Issue Selected Papers from the 7th Computer Science and Electronic Engineering Conference (CEEC) 2015)
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606 KiB  
Article
An Efficient Decoder for the Recognition of Event-Related Potentials in High-Density MEG Recordings
by Christoph Reichert, Stefan Dürschmid, Rudolf Kruse and Hermann Hinrichs
Computers 2016, 5(2), 5; https://doi.org/10.3390/computers5020005 - 12 Apr 2016
Cited by 6 | Viewed by 9741
Abstract
Brain–computer interfacing (BCI) is a promising technique for regaining communication and control in severely paralyzed people. Many BCI implementations are based on the recognition of task-specific event-related potentials (ERP) such as P300 responses. However, because of the high signal-to-noise ratio in noninvasive brain [...] Read more.
Brain–computer interfacing (BCI) is a promising technique for regaining communication and control in severely paralyzed people. Many BCI implementations are based on the recognition of task-specific event-related potentials (ERP) such as P300 responses. However, because of the high signal-to-noise ratio in noninvasive brain recordings, reliable detection of single trial ERPs is challenging. Furthermore, the relevant signal is often heterogeneously distributed over several channels. In this paper, we introduce a new approach for recognizing a sequence of attended events from multi-channel brain recordings. The framework utilizes spatial filtering to reduce both noise and signal space considerably. We introduce different models that can be used to construct the spatial filter and evaluate the approach using magnetoencephalography (MEG) data involving P300 responses, recorded during a BCI experiment. Compared to the accuracy achieved in the BCI experiment performed without spatial filtering, the recognition rate increased significantly to up to 95.3% on average (SD: 5.3%). In combination with the data-driven spatial filter construction we introduce here, our framework represents a powerful method to reliably recognize a sequence of brain potentials from high-density electrophysiological data, which could greatly improve the control of BCIs. Full article
(This article belongs to the Special Issue Selected Papers from the 7th Computer Science and Electronic Engineering Conference (CEEC) 2015)
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