Faculty Members researchs

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Aldaej, A., Krause, P. (2014). An Enhanced Approach to Semantic Markup of VLEs Content Based on Schema.org. In 4th Int. Workshop on Learning and Education with the Web of Data–13th Int. Semantic Web Conference. Riva del Garda, Italy. عبدالعزيز عبدالله الداعج

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Aldaej, A., Krause, P. (2014). SocialLearn Demo. Making it Matter: Supporting education in the developing world through open and linked data, LINKEDUP Project, London, UK, 16th May, 2014. عبدالعزيز عبدالله الداعج

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Aldaej, A., Krause, P. (2013). E-Learning evolution: Semantic Web and social networking. 3rd Postgraduate Research Conference, University of Surrey, Guildford, UK, 29th-30th January 2013. عبدالعزيز عبدالله الداعج

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Aldaej, A., Krause, P. & Strømmen-Bakhtiar, A. (2012). E-Learning evolution: Next Steps Semantic web and foundations of E-learning. In Proceedings of World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education 2012, Montreal, عبدالعزيز عبدالله الداعج

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Development of a Spatial Decision Support System for Farms Management الصادق عبدالله الجاك فضل الله

Mechanized agricultural operations are needed to increase productivity, efficiency and competitiveness of farms. Likewise, developing and promoting appropriate new technologies are needed in the decision making and management process. Farm decision-makers are faced with not only the need to manage traditional facilities, but, also, complex environmental management requirements. This research project aims to develop a conceptual model for a farm Spatial Decision Support System. The model uses Decision Support System (DSS) and Geographical Information System (GIS) to handle farm spatial and attribute information. The real power of GIS derives from the integration of database and graphics capabilities with engineering design, analytical, and cost models. Importance of research stems from its association with the community of Al-Kharj area. It is expected that the proposed system will be an effective tool for the advance of decision-making process on farms,  and will  contain many types of  descriptive, quantitative and spatial analysis models, that can be easily and friendly used.

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End-to-End Route Reliability in Pervasive Multi-Channel Multi-Radio (PMCMR) Scheme for MANETS Usman Tariq

Multi-channel multi radio wireless communications technologies have changed the trend of traditional routing based Quality of Service (QoS) in wireless-mesh networks. This avalanche of growth in multimedia communication is trigged by Multi-Channel Multi-Radio Wireless Mesh Networks (MCMR-WMNs). 

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Pattern recall in networks of chaotic neurons محمد عمر الحوارات

This research investigates the potential utility of chaotic dynamics in neural information processing. A novel chaotic spiking neural network model is presented which is composed of non-linear dynamic state (NDS) neurons. The activity of each NDS neuron is driven by a set of non-linear equations coupled with a threshold based spike output mechanism. If time-delayed self-connections are enabled then the network stabilises to a periodic pattern of activation. Previous publications of this work have demonstrated that the chaotic dynamics which drive the network activity ensure that an extremely large number of such periodic patterns can be generated by this network. This paper presents a major extension to this model which enables the network to recall a pattern of activity from a selection of previously stabilised patterns.

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The Nonlinear Dynamic State neuron محمد عمر الحوارات

This research is concerned with using nonlinear dynamics to greatly enhance the 
range of possible behaviours of artificial neurons. A novel neuron model is presented which 
has a dynamic internal state defined by a set of nonlinear equations, together with a 
threshold driven spike output mechanism. With the aid of spike feedback control the model is 
able to stabilise one of a large number of Unstable Periodic Orbits in its internal dynamics. 
These orbits correspond to dynamic states of the neuron each of which generates a ...

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Reconfigurable Hardware Accelerator for protein sequence alignment using Smith-Waterman algorithm عاطف علي ابراهيم محمد

Bioinformatics and computational biology (BCB) is a rapidly developing Multidisciplinary field which covers a wide range of areas, including genomic sequence alignments. It is a main tool in molecular biology in searching for similarity between sequences. Sequence alignment has many important real world applications. For example, if some information about one of the sequences is already known (e.g., the sequence represents a cancerous gene) then this information could be transferred to the other unknown sequences, which could be vital in early disease diagnosis and drug engineering. Other applications include the study of evolutionary development, forensic, and the history of species and their groupings. With the wide growth of genomic data, searching for a sequence homology over huge databases (often measured in gigabytes) is unable to produce results within a realistic time, hence the need for acceleration. Since the exponential increase of biological databases as a result of the human genome project (HGP), supercomputers and other parallel architectures such as the special purpose Very Large Scale Integration (VLSI) chip, Graphic Processing Unit (GPUs) and Field Programmable Gate Arrays (FPGAs) have become popular acceleration platforms. FPGAs generally offer more flexibility, higher performance and lower overheads. Nonetheless, the number of researchers working on FPGA-based accelerators for sequence alignment and BCB applications in general, remains low. This is due mainly to the relative newness of the two areas, but more importantly, perhaps, to the knowledge gap between bioinformaticians and molecular biologists on the one side and hardware design engineers on the other side. In...

FPGA-Based Coprocessor for DNA sequence alignment using Stevens-Song optimized algorithm عاطف علي ابراهيم محمد

One of the focal objectives of molecular genetics is the determination of the genetic basis of human disease. Respectable advancement has been made in this respect as of late; most prominently the production of the human genome in 2001, an exertion that took two decades to finish. However, new genome sequencing technology is getting available that will drastically decrease the measure of time it takes to get sequence data from a sample of DNA. These developments will permit investigations of human variety at the genetic level. Such studies hold incredible guarantee for enabling important discoveries in figuring out which nucleotides and genes in the human genome hold data about human susceptibility to specific disease. There are significant computing challenges connected with the new sequencing products that emerge because of the immense volumes of data that these machines produce. The human genome comprises of roughly 3 billion base-pairs. The most costly computational task in genome sequencing (utilizing the prevailing Whole Genome Shotgun Sequencing approach) is the alignment of short fragments of the genome being sequenced against a reference genome. There may be several million of such fragments that need to be aligned so as to sequence a single genome. Current methodologies to tackle this issue utilizing traditional PCs may take tens to countless CPU hours to complete the alignment necessities for sequencing of a single human genome. Even high performance cluster computers with huge numbers of CPUs may take several weeks to complete the fundamental calculations. A reconfigurable PC is a...

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