bluuebunny/crossref_metadata_2025 huggingface dataset:
A novel wavelet-based multimodal compression scheme for joint image-signal compression
Authors: Boubchir Larbi , Brahimi Tahar , Fournier Régis , Naït-Ali Amine
Published: October 2012

Background:
Nowadays, by considering the important advances in multimedia and networks including telemedicine applications, the amount of information to store and/or transmit has dramatically increased over time. To overcome the limitations of transmission channels or storage systems, data compression is considered a useful tool. In general, data compression addresses the problem of reducing the amount of data required to represent any digital data including images and signals. This can be achieved by removing redundant information where the main challenge is to reduce the bit-rate while preserving a high quality of the information.

Objective:
This work aims to propose a new multimodal compression methodology allowing compression of jointly various data, not necessary of the same type, using only one codec.

Method:
The proposed joint signal-image compression methodology consists of inserting the wavelet coefficients of a decomposed signal in the details region of a wavelet transformed image at the finest scale (i.e., the highest frequency sub-bands: horizontal details, vertical details, or diagonal details) according to a spiral way. The mixture is afterwards compressed using the well-known SPIHT algorithm (Set Partitioning In Hierarchical Trees). This process is inverted by decoding the mixture, then separating the signal from the image using a separation function applied to the insertion detail sub-band area. Next, the signal and image are reconstructed using inverse wavelet transformation followed by a dequantization step. Figure 1 illustrates the corresponding compression scheme.

Results:
The proposed method was evaluated on medical images with biomedical signals. The experimental results obtained show that this method provides better performance compared to the basic version based on inserting the signal samples in the spatial domain of the image to the encoding phase. This is confirmed by an important obtained improvement in terms of PSNR (Peak Signal to Noise Ratio) and PRD% (Mean Square Difference).
Geographic Information Systems as a promising area of Education and Scientific research in Qatar
Authors: Azaz Lotfy Kamal
Published: October 2012

Geographic information systems (GIS) (also known as Geospatial information systems or Geotechnology) are computer software and hardware systems designed to capture, store and manipulate all types of geographical data, as well as analyze, manage, and display geographic information for informing decision making. Users of GIS range from communities, research institutions, environmental scientists, health organisations, land use planners, businesses, and government agencies at all levels. Numerous examples of applications of GIS are available in many different journals and are frequent topics of presentations at conferences in the natural and social sciences. For a long time, GIS has been a well-established and independent discipline throughout American and European Universities; however, there is no single University in the Arab World or even in the Middle East--as far as the author knows--that offers an undergraduate program for this important discipline. Qatar can be the pioneer in this field in the region by offering such a program through Qatar University or any higher education institute in the state. The benefits of opening such a program are numerous to be calculated. Qualified human resources in the field of GIS are in high demand not only in the region but at international level as well. The U.S. Department of Labor has designated Geotechnology (GIS) as one of the three "mega-technologies" of the 21st century—right up there with Nanotechnology and Biotechnology. Opening GIS undergraduate program in Qatar will make the state The "Kaaba" of this science in the region and will attract students from different states, which will generate scientific and financial revenue. Moreover, the host institute of this suggested program can establish an international research centre for GIS to carry out studies for the benefit of the region and beyond. Implementing such a proposal will have great impact on the Computing and Information Technology Research discipline, which is one of Qatar's core research areas.
Everything happens somewhere: The role of geospatial analyses in government, environmental planning and research
Authors: Ross Robert Arden , Foeken Jurgen , Jameson Jeremy , Strohmenger Christian , Febbo Eric
Published: October 2012

With expansion in the fields of urbanization, technical development and industrialization, Qatar faces the challenge of advancing urban and industrial development while ensuring effective safety and environmental management. Whether assessing environmental quality, the impact of a metro system, or emergency response planning, decision making relies on the integration of disparate sources of data. Geospatial referencing provides a unifying framework from which civil engineering, public policy and research decisions can be made within a web-based environment.

The foundation of a geospatial reference system should be the surface geology of the country and its marine habitats. In addition to bedrock geology, the database should include features such as lineaments, drainages, land movement studies, karst features and soil types. Marine data include biota, sediment types, water quality, hydrodynamic data, and ecological sensitivity. In an arid climate, where water resources are key considerations, it is important to have a consistent geological framework for both surface and near surface geology. Accordingly, the near surface, aquifers should have a sequence stratigraphic analysis.

Within a web-based infrastructure, geospatial data can be accessible to many users with access controls set by data owners and can be appropriated to user needs. Such a geodatabase mapping tool may combine 3 functions: 1) database/resource-a query tool for government, industry and the public, 2) an evaluation tool allowing the end user forward modeling/impact assessment and cause/effect analysis capability, 3) a communication tool for decision making--where results from a query may be circulated to a linked forum of specialists for consideration.

The emergence of web-based, spatial referencing GIS tools shows great promise in many key aspects of public policy and research, including data storage, data analysis, and decision making. The vision is the implementation of integrated diverse multi-scale, multi-disciplinary spatial data from geological rock samples to cutting edge multi-spectral satellite imagery for use in solving complex geological, geophysical, geotechnical and environmental problems.
Distributed rendering of computer-generated images on commodity compute clusters
Authors: Bouhali Othmane , Sheharyar Ali
Published: October 2012

Rendering of computer-generated imagery (CGI) is a very compute-intensive process. Rendering time of individual frames may vary from a few seconds to several hours depending on the scene complexity, output resolution and quality. For example, a short animation project may be about two minutes in length. It comprises 3600 frames at 30 frames per second (fps). An average rendering time for a fairly simple frame can be approximately 2 minutes, resulting in a total of 120 hours to render a simple 2-minute animation. Fortunately, animation rendering is a highly parallelizable activity as frames can be computed independently of each other. A typical animation studio has a render farm, a sophisticated cluster of special computers (nodes) used to render 3D graphics. By spreading the rendering of individual frames across hundreds of machines, the overall render time is reduced significantly.

Researchers and students in a university do not usually have a render farm available. Some universities have general-purpose compute clusters but these are used mainly for running complex numerical simulations. Although rendering on these clusters is doable but it usually involves using generic queue manager (e.g. Condor, Portable Batch System PBS) rather than specialized render queue manager (e.g. DrQueue, Qube!), due to which rendering workflow becomes tedious. This paper presents a solution to create a render frame-like environment using compute-cluster resources and most importantly by using the existing render queue manager. This way, researchers and students can be presented with a rendering environment similar to any animation studio. Several benchmarking results will be presented to prove the potential benefit of this method in terms of execution time, simplicity and portability.
Information aspects of quantum systems
Authors: Abdel-Aty Mahmoud
Published: October 2012

Information dynamics of different quantum systems under influence of both a phonon bath in contact with the resonator and irreversible decay of the qubits is considered. The focus of our analysis is devoted to multilevel atoms and the effects arising from the coupling to the reservoir. Even in the presence of the reservoirs, the inherent entanglement is found to be rather robust. Due to this fact, together with control of system parameters, the system may therefore be especially suited for quantum information processing. Information entropy, entropy squeezing and wehrl entropy are discussed as indicators of entanglement. Our findings also shed light on the evolution of open quantum many-body systems.
Accessibility research efforts needed in Qatar
Authors: Banes David , Zetterström Erik
Published: October 2012

Background and Objectives:
Mada, Qatar's Center for Assistive Technology, is a non-profit organization that strives to empower and enable people with disabilities through ICT. During late 2011 and early 2012, Mada conducted research to identify barriers to accessibility in Qatar

Methods:
In the survey, the key groups of respondents were identified including disabled people themselves. A combination of quantitative and qualitative methods were applied. The results were validated through the Assistive Technology Research Forum formed by Mada, which analyzed the survey results and gave additional input. These were further validated in discussions with disabled people's organizations as part of the input to the Mada future strategy.

Results:
The survey indicated the following major results:
*People with visual impairment had both a high awareness and usage rate.
*People with physical and hearing disabilities were very aware of available assistive technology but the usage rate was still low.
*People with learning disabilities were not aware of available assistive technology and hence the usage rate was unsurprisingly low.

Based on these findings, the AT Research Forum identified the following priority areas, which could potentially have a very high impact on barriers to accessibility in Qatar:

*Arabic crowd sourced free symbol set
*Improved statistical source on needs and a registry for easy user communication
*Development of a free Arabic text to speech.
*Wayfinding technologies for the blind incorporating enhanced technologies in emergency situations
*Research into enhanced literacy amongst the deaf community when provided with text based communication solutions

In addition, it was possible to highlight some crucial issues that which impeded uptake of technology, including:

*The lack of accessible Arabic digital content
*The limitations of current OCR technologies
*The lack of useful Arabic continuous speech
*Arabic word prediction and the lack of a significant available corpus

Conclusions:
The areas identified are fundamental projects with a very high impact in Qatar. They would best be addressed through collaboration and funding. Such collaborations bridge the private and academic sectors with specialist input from an organization supporting disabled people such as Mada.
Model-free fuzzy intervention in biological phenomena
Authors: Nounou Hazem , Nounou Mohamed Numan , Meskin Nader , Datta Aniruddha
Published: October 2012

An important objective of modeling biological phenomena is to develop therapeutic intervention strategies to move an undesirable state of a diseased network towards a more desirable one. Such transitions can be achieved by the use of drugs to act on some genes/metabolites that affect the undesirable behavior. Biological phenomena are complex processes with nonlinear dynamics that cannot be perfectly described by a mathematical model due to several challenges such as the scarcity of biological data. Therefore, the need for model-free nonlinear intervention strategies that are capable of guiding the target variables to their desired values often arises. Addressing such a need is the main focus of this work.

In many applications, fuzzy systems have been found to be very useful for parameter estimation, model development and control design of nonlinear processes. In this work, a model-free fuzzy intervention strategy (that does not require a mathematical model of the biological phenomenon) is proposed to guide the target variables of biological systems to their desired values. The proposed fuzzy intervention strategy is applied to two biological models: a glycolytic-glycogenolytic pathway model and a purine metabolism pathway model. The simulation results of the two case studies show that the fuzzy intervention schemes are able to guide the target variables to their desired values. Moreover, sensitivity analyses are conducted to study the robustness of the fuzzy intervention algorithm to variations in model parameters, and contamination due to measurement noise, in the two case studies, respectively.
e-Security: Methodologies and approaches for the United Arab Emirates Online Business
Authors: Akhter Fahim
Published: October 2012

Background and Objectives
As e-commerce functions in a more perplex and conjoint environment than traditional businesses, a higher degree of trust is required between the users and online businesses. Uncertainties inherent to the current e-commerce environment give rise to a lack of trust and reliability in e-commerce partnerships, thereby reducing confidence and creating barriers to trade.

The reason why most users and businesses in United Arab Emirates (U.A.E) are still skeptical about e-commerce involves perceived security risks associated with conducting online business. Online users consciously or subconsciously analyze the provided level of security based on their experience in order to decide whether to conduct business with the specific company or else to move on to the next company. There is a need for a better understanding of hostile environments fueled by financially-motivated, targeted cyber threats that affect consumer's decision-making behavior. The purpose of the study is to identify the factors that support the implementation and acceptance of security in e-commerce among corporations in throughout the United Arab Emirates. The study will explored the common cyber attacks that threaten the U.A.E. online businesses and will describe methodologies and approaches that can be developed to respond to those threats.

Methods:
A descriptive web-based survey will be adopted as an appropriate method to collect initial data from users due to its cost effectiveness, rapid turnaround, high response volume, and ability to cover a large geographical area. The combination of questions both close- and open-ended will be selected. The URL of the survey will be electronically distributed among participant using mailing lists from the Dubai chamber of commerce.

Results and Conclusions:
Statistics of participants from seven states of the U.A.E will be accessed and discussed here. Complete responses will be chosen out of anonymous responses for further analysis. Quantitative data will be fed into a statistical framework for researchers to understand and analyze the relationship among different responses.
QR Cache: Linking mLearning theory to practice in Qatar
Authors: Power Robert
Published: October 2012

Background and Objectives:
Virtually ubiquitous mobile and wireless network coverage combined with high mobile device penetration create an opportunity for mobile learning (mLearning) research to focus on linking theory and practice. The QR Cache project at College of the North Atlantic-Qatar (CNA-Q) evolved from the desire of students to use their own mobile devices, and the need for situated mLearning solutions to training demands of Qatar's technical workforce. QR Cache was developed as a set of exemplars of situated mobile reusable learning objects (RLOs) for students studying introductory computer hardware devices and concepts. The QR Cache project uses a Design-Based Research (DBR) approach to study the development of the RLOs, as well as the link between instructional design and established learning theories. Moore's Transactional Distance Theory and Koole's FRAME model are used to provide theoretical grounding for both design decisions and results interpretation.

Methods:
Participants used their own mobile devices to scan Quick Response (QR) codes affixed to computer equipment. The QR codes redirected their smartphones to websites with information on the English names and some basic facts about the devices. Participants then completed an online questionnaire about their experiences. Survey responses were analyzed for indicators of transactional distance, as well as the domains of effective mLearning design outlined by the FRAME model.

Results:
Eight students completed the online questionnaire in the pilot phase. All participants were easily able to access the RLOs using their own mobiles. Responses indicated that they found the situated learning strategy desirable. Students also indicated that they revisited the RLOs several times and that the activities generated interaction in the form of discussions with their peers and instructors.

Conclusions:
Student experiences with the QR Cache RLOs demonstrate low levels of transactional distance between learners and content, their peers, and instructors. They also show a strong convergence of the learner, social and device usability aspects of the FRAME model required optimizing the mLearning experience. However, the limited number of pilot phase participants makes it difficult to provide generalizations. Expanding the research to include more participants in a subsequent phase would address this limitation.
Arabic named entity operational recognition system
Authors: Karam Shiekha Ali , Jaoua Ali , Elloumi Samir
Published: October 2012

Extracting named entities is an important step for information extraction from a text, based on a given ontology. Dealing with Arabic language invokes an additional number of challenges compared to English, French and other languages within similar families. The major difficulties involve complex morphological systems, no capitalization, and no standardization of Arabic writing. The Arabic language has a rich and complex morphological landscape due to its highly inflected nature. Usually, any Arabic lemma word can be constructed using different internal structure, prefixes and suffixes. Furthermore, there is no standardization of Arabic writing because of the spelling inconsistency of Arabic words.
In this work, we propose an operational hybrid approach combining dictionary-based and rule-based detection for extracting seven categories of named entities which are organization by name, date, interval, price/value, percentage, currency and unit. The dictionary-based approach performs exact or approximate matching of the words with prepared Arabic organization names. In case of non-exact matching with the dictionary words, the approximate matching is an efficient solution for morphological difficulties. Specificities of Arabic language are also processed by rule-based detection, which is based on capturing the entities patterns in terms of regular expressions or patterns provided by experts.
We evaluated our Arabic name entity recognition system using financial news articles and we obtained around an 80% of recognition rate.
Scalability evaluation of cluster size for MapReduce applications in elastic compute clouds
Authors: Zhang Fan , Sakr Majd F
Published: October 2012

The MapReduce programming model is a widely accepted solution to address the rapid growth of the so-called big-data processing demands. Various MapReduce applications with a huge volume of input data can run on an elastic compute cloud composed of many computing instances. This elastic compute cloud is best represented by a virtual cluster, such as Amazon EC2. Performance prediction of MapReduce applications would help in understanding their scalability pattern. However, it is challenging due to the complex interaction of the MapReduce framework and the underlying highly-parameterized virtualized resources. Furthermore, MapReduce's high-dimension space of configuration paremeters which adds to the prediction complexity.

We have evaluated a series of representative MapReduce applications on Amazon EC2, and identified how the cluster size affects the execution times. The scaling curve of all applications are studied to discover the scalability pattern. Our major findings are as follows: (1) The execution times of MapReduce applications follow a power-law distribution, (2) For map-intensive applications, the power-law scalability starts from a small cluster size, and (3) For reduce-intensive applications, the power-law scalability starts from a lager cluster size.

We attempted to fit our scalability performance results using three regression methods: polynomial regression, exponential regression and power regression. By measuring the Root Squared Mean Error (RSME), the power regression performs best at performance prediction compared with the other methods evaluated. This was the case across all the benchmark applications studied.

Our performance prediction methods will aid cloud users in choosing appropriate computing resources, both virtual and physical, from small-scale experimental test runs for cost saving.
Performance of spectrum sharing systems with two-way relaying and multiuser diversity
Authors: Yang Liang , Alouini Mohamed-Slim , Qaraqe Khalid
Published: October 2012

In this paper, we consider a spectrum sharing network with two-way relaying and multiuser diversity. More specifically, one secondary transmitter with the best channel quality is selected and splits its partial power to relay its received signals to the primary users by using the amplify-and-forward relaying protocol. We derive a tight approximation for the resulting outage probability. Based on this formula, the performance of the spectral sharing region and the cell coverage are analyzed. Numerical results are given to verify our analysis and are discussed to illustrate the advantages of our newly proposed scheme.
Computational intelligence in power electronics and electric drive control
Authors: Jamil Mohammad , Iqbal Atif , Al-Naemi Mohammad
Published: October 2012

Power Electronics converters are finding growing applications in industries and house hold devices. The growing automation in industrial applications needs highly complex power electronics systems to process the electric power. The controls of power electronic converters are still posing challenges due to their required precision. Several control strategies are developed and reported in the literature including Pulse Width Modulation (PWM), model predictive control, sliding mode control etc. The development of computational intelligence techniques are artificial intelligence, fuzzy logic, adaptive neuro-fuzzy inference system, genetic algorithms etc. The basic idea is to incorporate the human intelligence in the control system so it makes intelligent decisions. The paper presents an over-view of the application of computational intelligence techniques for control of power electronic converters. Computational Intelligence (CI) has been in focus for quite long time, and it is well known that CI techniques can help in solving complex multidimensional problems which are difficult to solve by conventional methods. Computational Intelligence technology is growing rapidly and its applications in various fields is being tested. Power electronics converters is one of the major application areas where this technology can play a vital and decisive role. Recent development of powerful digital signal processors and field programmable gate arrays is making implementation of Computational Intelligence technology economical with improvement of performance, compact and more competitive. Evidently, the future impact of this CI technology on power electronics converter control is very significant and utilizable.
Concurrency characterization of MapReduce applications for improved performance on the cloud
Authors: Hammoud Mohammad , Sakr Majd
Published: October 2012

Driven by the increasing and successful prevalence of MapReduce as an analytics engine on the cloud, this work characterizes the Map phase in Hadoop MapReduce to guide its configuration and improve overall performance. MapReduce is one of the most effective realizations of large-scale data-intensive cloud computing platforms. Hadoop is an open source implementation of MapReduce and is currently enjoying wide popularity. Hadoop has a high-dimensional space of configuration parameters (~200 parameters) that poses a burden on practitioners, like computation scientists, system researchers, and business analysts, to set for efficient and cost-effective execution. In this work we observe that MapReduce application performance is highly influenced by Map concurrency, defined in terms of two configurable parameters, the number of available map slots and the number of map tasks running over the slots. As Map concurrency is varied, we show that some inherent MapReduce characteristics allow systematic and well-informed prediction of MapReduce performance response (runtime increase or decrease). We propose Map Concurrency Characterization, MC2, a predictor for MapReduce performance response. MC2 allows for optimized configuration of the Map phase and, consequently, enhanced Hadoop performance.

Current related schemes require mathematical modeling, simulation, dynamic instrumentation, static analysis of unmodified MapReduce application code, and/or actual performance measurements. In contrast, MC2 simply bases its decisions on MapReduce characteristics that are affected by Map concurrency. We implemented MC2 and conducted comprehensive experiments on a private cloud and on Amazon EC2 using Hadoop 0.20.2. Our results show that MC2 can correctly predict MapReduce performance response and provide up to 2.3X speedup in runtime for the tested benchmarks. This performance improvement allows MC2 to further serve in reducing cost in a cloud setting. We believe that MC2 offers a timely contribution to the data analytics domain on the cloud, especially as Hadoop usage continues to grow beyond companies like Google, Microsoft, Facebook and Yahoo!.
Performance analysis of distributed beamforming in a spectrum sharing system
Authors: Yang Liang , Alouini Mohamed-Slim , Qaraqe Khalid
Published: October 2012

In this paper, we consider a distributed beamforming scheme (DBF) in a spectrum sharing system where multiple secondary users share the spectrum with the licensed primary users under an interference temperature constraint. We assume that DBF is applied at the secondary users. We first consider optimal beamforming and compare it with the user selection scheme in terms of the outage probability and bit-error-rate performance. Since perfect feedback is difficult to obtain, we then investigate a limited feedback DBF
scheme and develop an outage probability analysis for a random vector quantization (RVQ) design algorithm. Numerical results are provided to illustrate our mathematical formalism and verify our analysis.
Novel applications of optical flow in measuring particle fields in dense crowded scenes at Hajj 2011
Authors: Kiyani Khurom Hussain , Aldea Emanuel , Petrou Maria
Published: October 2012

Background & Objectives:
The Hajj and minor Muslim pilgrimage of Umrah, present some of the most densely crowded human environments in the world, and thus offer an excellent testbed for the study of dense crowd dynamics. Accurate characterisation of such crowds is crucial to improve simulations that are ubiquitously applied to crowded environments such as train stations, and which require a high degree of detailed parameterisation. Accurate measurements of key crowd parameters can also help to develop better strategies for mitigating disasters such as the tragic stampede of 2006 that killed over 300 pilgrims during the Hajj. With Qatar set to be one of the major cultural centres in the region, e.g. hosting 2022 FIFA World Cup, the proper control and management of large singular events is paramount for safety and Qatar's standing on the international stage. We aim to use the unique video data gathered from Hajj 2011, to assess the dynamics of very dense crowded environments with a particular focus on dangerous crowd instabilities and systemic shocks.

Methods:
We make use of increasingly complex optical flow algorithms (Horn-Schunck, Lucas-Kanade, TV-L1) to extract the instantaneous velocity field between each pair of frames in the videos. From these velocity vector fields we then construct the pedestrian (Lagrangian) flow field by the use of texture advection techniques that initially seed the flow with particles or random noise.

Results:
We present results of the above application of optical flow and texture advection methods to the data we collected in a field study during Hajj 2011. Particularly, we aim to illustrate the specific flow patterns that arise in such crowded environments. We also aim to present the preliminary results of a pilot multiple camera stereovision study conducted in the London Central Mosque on a Friday when the mosque was particularly crowded.
MegaMorph: Multi-wavelength measurements of nearby galaxy structures
Authors: Vika Marina , Bamford Steven P , Haeussler Boris , Rojas Alex
Published: October 2012

Fitting an analytic function to the two-dimensional surface brightness profile of a galaxy provides a powerful method of quantifying its internal structure. The resulting parameters reveal the size, shape and luminosity of the galaxy and its separate structural components (e.g., disk and bulge). Current galaxy fitting softwares packages consider only a single waveband image at a time. However, variations in stellar populations between and within galaxy structures mean that their observed properties depend on wavelength. Correctly studying the physical properties of galaxy components requires that these wavelength variations be accounted for. Multi-wavelength studies are presently possible, but require significant compromises: either the fits to each band must be done independently, or, one band must be favored for determining structural parameters, which are then imposed on fits to the other bands. Both of these approaches waste valuable information, and therefore result in suboptimal decompositions.

Our project, 'MegaMorph', is developing a next-generation tool for decomposing galaxies, in terms of both their structures and stellar populations. We aim to present a modified version of the two-dimensional galaxy fitting software, GALFIT, developed as part of our MegaMorph project. These new additions enable a galaxy to be fit using images at many different wavelengths simultaneously. All the available data is therefore used to constrain a wavelength-dependent model of the galaxy, resulting in more robust, physically meaningful, component properties. We verify the advantages of our technique by applying it to a sample of 160 well-studied galaxies at redshifts smaller than 0.025, with ugriz imaging from the Sloan Digital Sky Survey to demonstrate how the resulting decompositions allow us to study the links between stellar population and galaxy structure in detail.

Furthermore, we illustrate the advantages of our new method with regard to galaxy surveys, by fitting a sample of ~4000 artificially redshifted images of the galaxies described above. Our technique enables physical parameters of galaxy components to be robustly measured at lower signal-to-noise and resolution than would otherwise be possible. This paves the way for detailed statistical studies of the physical properties of galaxy disks and bulges.
Analysis of mobility impact on interference for short-range cognitive radio networks
Authors: Ekti Ali Riza , Serpedin Erchin , Qaraqe Khalid A
Published: October 2012

Background & Objectives:
Cognitive radios (CRs) strive to utilize the white holes in the radio frequency (RF) spectrum in an opportunistic manner. Because interference is an inherent and a very critical design parameter for all sorts of wireless communication systems, many of the recently emerging wireless technologies prefer smaller size coverage with reduced transmit power in order to decrease interference. Prominent examples of short-range communication systems trying to achieve low interference power levels are CR relays in CR networks and femtocells in next generation wireless networks (NGWNs). It is clear that a comprehensive interference model including mobility is essential especially in elaborating the performance of such short-range communication scenarios. This work focuses on analyzing how interference evolves in time under long and short term fading. Such an analysis is essential, because once the interference behavior is understood, it can be managed in a better way. Also, NGWNs and CRs can be designed in such a way that arduous and expensive planning stage is omitted. This way, deployment costs can be reduced drastically.

Methods:
It is known that received signal in a general wireless propagation environment includes the effects of both long- and short-term fading. Therefore, a logarithmic transformation reveals the individual impact of each fading phenomenon. The two-dimensional (2D) random walk model is incorporated into the physical layer signal model.

Results:
The results show that relatively larger displacements in short primary-user-receiver (PU-Rx) and secondary-user-transmitter (SU-Tx) separations lead to drastic power level fluctuations in the observed interference power levels. The impact of path loss is one of the major factors changing the future interference conditions for low-speed mobility scenarios especially within short communication ranges.

Conclusions:
It is shown that long-term fading plays a crucial role for the temporal evolution of interference for NGWNs and CRs. By using the interference statistics, the design and deployment of future cellular mobile radio systems in Qatar could be optimized. This is crucial, especially for rapidly changing network topographies as is the case with the city of Doha. Even for well-established network topographies, the proposed method provides an analytical way of examining and managing the interference.
Image processing on the Cloud: Characterizing edge detection on biomedical images
Authors: Sakr Majd , Hammoud Mohammad , Reddy Manoj Dareddy
Published: October 2012

In order to analyze and deduce valuable information from big image data, we have developed a framework for distributed image processing in Hadoop MapReduce. A vast amount of scientific data is now represented in the form of images from sources like medical tomography. Applying algorithms on these images has been continually limited by the processing capacity of a single machine. MapReduce created by Google presents a potential solution. MapReduce efficiently parallelizes computation by distributing tasks and data across multiple machines. Hadoop, an open source implementation of MapReduce, is gaining a widespread popularity due to features such as scalability and fault tolerance. Hadoop is primarily used with text-based input data. Its ability to process image data and its performance behavior with image processing have not been fully explored. We propose a framework that efficiently enables image processing on Hadoop and characterizes its behavior using a state-of-the-art image processing algorithm, Edge Detection.
Existing approaches in distributed image processing suffer from two main problems: (1) input images need to be converted to a custom file format and (2) image processing algorithms require adherence to a specific API that might impose some restrictions on applying some algorithms to Hadoop. Our framework avoids these problems by: (1) bundling all small images into one large file that can be seamlessly parsed by Hadoop and (2) relaxing any restriction by allowing a direct porting of any image processing algorithm to Hadoop. A R educe-less job is then launched where the code for processing images and a mechanism to write the images back individually to HDFS are included in Mappers. We have tested the framework using Edge Detection on a dataset of 3760 biomedical images. Besides, we characterized Edge Detection along several dimensions, such as degree of parallelism and network traffic patterns. We observed that varying the number of map tasks has a significant impact on Hadoop's performance. The best performance was obtained when the number of map tasks equals the number of available slots as long as the application resource demand is satisfied. Compared to the default Hadoop configuration, a speedup of 2.1X was achieved.
Analysing existing set theoretic and program specification diagrams
Authors: Fetais Noora , Cheng Peter
Published: October 2012

This research is aimed at evaluating the usability of notational systems that are used for specifying programs. We provide a conceptual analysis of the development of constraint diagrams (CD) as a diagrammatic notation which developed to support program specification. A detailed analysis of multi-case comparisons of formal languages and graphical systems for expressing logic and program constructs was conducted in order to trace how the development of the notations overcame the limitations of earlier generations of notations. By following the evolution of logic diagrams, we consider why and how they have been successively revised to increase their expressivity or their ease of comprehensibility and use. Visualizations of logic were proposed over the centuries. Leonhard Euler presented Euler diagrams, John Venn generalized Euler diagrams and presented Venn diagrams, and Charles Peirce extended Venn diagrams by increasing their expressiveness and presented Venn-Peirce diagrams. The modifications from Peirce to Shin concentrate on restoring visual clarity, but without loss of expressive power. Based on that, Constraint Diagrams were presented by Stuart Kent for constraint specification, behavioural specification, and relational navigation. We found that the gradual changes in diagrams from Euler Circles through Venn, Peirce, Shin to Constraint Diagrams share three complementary common themes: (1) to increase the expressiveness, (2) to increase the logical power of the formality of the system, and (3) to enhance the visual clarity. Depending on the purpose of designing a diagram, the priority of a theme over other themes is granted. For example, both Venn and Peirce adopted the same kind of solution in order to achieve these improvements: to introduce new syntactic objects, that is, shadings by Venn, and x's, o's, and lines by Peirce. However, on the negative side, these revised systems suffer from a loss of visual clarity, mainly because of the introduction of more arbitrary conventions. The modifications from Peirce to Shin concentrate on restoring visual clarity, but without loss of expressive power. The extension from these diagrams resulted in CD, which allows relational navigation (expressions involving two place predicates), is more expressive than previous diagrams, and has higher visual clarity and logical power.
Binary consensus in sensor motes
Authors: Al-Nakhala Noor , Abdaoui Abderrazak , Riley Ryan , El-Fouly Tarek
Published: October 2012

Background and Objectives:
In this work, we explore the implementation of the binary consensus algorithm in wireless sensor networks. Binary consensus is used to allow a collection of distributed entities to reach consensus regarding the answer to a binary question. Existing work on the algorithm focuses on simulation of the algorithm under the assumption of a fully connected network topology and unlimited messaging capabilities. In this new work, we adapt the algorithm to function in wireless sensor networks where the topology might not be fully connected and the number of messages sent should be minimized in order to save power.

Methods:
We are deploying and testing our implementation in a hardware embedded systems, mainly IRIS Motes. Our implementation of the binary consensus algorithm is written in NesC and runs on the Tiny Operating System (TinyOS). The implementation was tested on 11 sensor nodes, with current plans to test it on far more.

Results:
To support our hardware implementation results, a simulation using the Tiny Operating System SIMulator (TOSSIM) was done. Our results in hardware implementation and simulation are consistent with the original binary consensus algorithm.

Conclusion:
In this work, we adapted the binary consensus algorithm for use in wireless sensor networks. Our implementation for a small number of IRIS motes shows correct results consistent with those of simulation. In future work we will evaluate the effectiveness of the algorithm when scaled to hundreds of sensor motes.
Qatar Carbonates and Carbon Storage Research Centre: Status update after three years of fundamental research
Authors: Macdonald Iain , Maitland Geoffrey
Published: October 2012

There are still specific areas where our knowledge of carbon storage is in need of improvement, particularly in carbonate reservoirs, since currently we extrapolate data from limited sources and the predictive modelling technologies employed have a level of uncertainty that needs to be addressed. We will highlight our efforts through the Qatar Carbonates and Carbon Storage Research Centre (a $70 million, 10 year research programme with currently 20 PhD students and 10 postdoctoral researchers along with 14 faculty members) to investigate the underlying science and engineering concerning carbonate reservoir characterisation, rock-fluid-CO₂ interactions and multiphase flow experiments under reservoir conditions linked to complimentary simulation and modelling advances, including the rapidly developing field of digital rocks. This has involved developing unique HTHP experimental rigs and pioneering new modelling techniques, enhancing the toolbox available to engineers and geoscientists to select suitable reservoirs and optimally design CO₂ storage processes. These capabilities extend over molecular-pore-core-field scales. We have four focused research laboratories (Qatar Stable Isotope Lab; Qatar Thermophysical Property Lab; Qatar Complex Fluids Lab; Qatar CCS Multiscale Imaging Lab) and will discuss the highlights of major research findings to date in the context of carbon storage in the Middle East.
Kinetic modeling of GTL product distribution over a promoted cobalt catalyst
Authors: Todic Branislav , Ma Wenping , Jacobs Gary , Davis Burtron , Bukur Dragomir
Published: October 2012

Qatar is the world leader in fuel production from gas-to-liquid (GTL) technology and home of the largest GTL plant in the world (Pearl GTL, a joint development by Qatar Petroleum and Shell). In the GTL process natural gas is converted into liquid fuels and waxes. Fischer-Tropsch synthesis (FTS) is the key part of that process. FTS is a heterogeneously catalyzed reaction in which a mixture of CO and H₂ is converted into a wide range of hydrocarbon products. Advanced design and optimization of large scale FTS reactors requires a detailed knowledge of reaction chemistry. Kinetic models used for this application need to be robust, physically reasonable and fundamental. This study will present one such a model. Experiments were conducted in a 1-L slurry reactor over 25% Co/0.48% Re/Al₂O₃ catalyst. A broad range of operating conditions was achieved (i.e., temperatures of 478, 493 and 503 K, pressures 1.5 and 2.5 MPa, H2/CO feed ratio 1.4 and 2.1 and gas space velocities of 1.0-22.5 NL/g-cat/h). Rate laws for the kinetic model have been derived using the CO-insertion mechanism and chain-length-dependent 1-olefin desorption concept. The model accounts for the formation of n-paraffins and 1-olefins. CO hydrogenation and insertion of CO into the growing chain are considered to be rate determining, as well as the chain termination steps. Non-isothermal model parameters are estimated by minimization of a multi-response objective function. A global minimum is obtained with the hybrid genetic algorithm and a total of 696 experimental responses used in the estimation. Estimated model parameters are meaningful, considering physicochemical tests and statistical tests. They are also in a good agreement with previously reported values for activation energies. The model fit is in good agreement with experimental data and the mean absolute relative residual (MARR) was 24%. The model also provides a good prediction of CO and H₂ rates of consumption, with a MARR of 17.7 and 16.1%, respectively. The main advantage of the proposed model is its ability to explain and predict the main features of GTL product distribution in a physically meaningful and fundamental way over a wide range of industrially relevant process conditions.
An energy integration approach for gas-to-liquid process
Authors: Al-Nuaimi Ibrahim , AlNouss Ahmed , Bani Nasser Layal
Published: October 2012

Gas-to-liquid (GTL) products have increasingly become a promising energy resources over the past two decades. Qatar possesses the third largest proven reserve of natural gas in the world, with a net capacity approaching 900 tcf (trillion cubic foot). This has motivated Qatar to develop a long term vision, involving the investment of huge expenditures into world-class commercial plants that convert natural gas into value-added liquid hydrocarbon products. This vision was translated into the Oryx GTL plant in late 2006 and the Shell Pearl GTL plant reported to be the largest in the world, which began operations officially at the end of 2011, leading Qatar to be described as the world capital of GTL. The substantial usage of energy in Fischer-Tropsch (FT) GTL processes and the complexity of energy distribution throughout the process offer opportunities for heat integration and waste heat recovery. The objective of this paper is to carry out an energy integration analysis for a typical GTL process.

The approach was started with process simulation to develop the base-case data for the process. Next, energy integration tools were used to optimize energy distribution, heat exchange, and waste heat recovery. Finally, simulation and techno-economic analysis were utilized to assess the performance of the proposed design changes and their economic viability.

The resultant pinch diagram showed that a single pinch case was faced with a fixed driving force of 10 oC, in which both external cooling and heating utilities were required to satisfy energy needs. Meanwhile, the Grand Composite Curve (GCC) showed that flue gases cover most of the heating utility while cooling water covers all the required cooling utility. Moreover, the waste heat recovery study supported by HYSYS software illustrated considerable recoveries in steam qualities from discharged flue gases within the FT reactor section.

In conclusion, energy integration on a GTL process was realized to be a promising one as the targets for net energy savings were found to be close to 40%. Additionally, generation of various qualities of steam can be obtained in a cost-effective manner. At the top of it, most of the recommended projects have attractive payback periods, below six years.