Qatar Foundation Annual Research Forum Volume 2012 Issue 1

Hepatocellular carcinoma (HCC) is the most common liver cancer and one of the commonest solid malignancies. High mortality rates and poor prognosis of the disease are mainly due to late diagnosis, underlying cirrhosis and resistance to chemotherapy. The risk factors of HCC include infections with hepatitis B and C viruses, along with other conditions that cause cirrhosis like: alcoholism and non-alcoholic steatohepatisis. Wnt/ß catenin signaling pathway plays a vital role in regulating the cell fate during embryogenesis and cell proliferation in adult tissues. In the absence of the Wnt ligand, beta-catenin is phosphorylated through interaction with GSK-3b, APC, axin and subsequently degraded by the ubiquitin-proteasome system. However, when the Wnt ligand binds to the receptor complex of the pathway, the destruction complex is inactivated leading to the accumulation of beta-catenin in the cytoplasm and its translocation to the nucleus where it forms complexes with TCF/LEF family that causes transcriptional activation of target genes. Recent studies suggest that cancer stem cells play a key role in liver carcinogenesis. Mutations in beta-catenin and activation of Wnt/ß-catenin signaling pathway is likely to cause abnormal proliferation and enhanced self-renewal of hepatic progenitor cells resulting in their transformation into cancer stem cells. Thus understanding the characteristics and function of liver cancer stem cells and their response to beta-catenin inhibitors is crucial to the development of novel, more effective drugs and improving patient survival. In this study we have used various drugs to target Wnt/beta-catenin signaling pathway in hepatic carcinoma cell lines. We assessed the effect of the inhibitors of beta-catenin on the expression of stem cell markers in these cell lines and will present the results of the study.

Background and Objectives: Congestion in outpatient departments (OPD) in Qatar's public hospital system is a major problem due to the demographics of the country. Despite the congestion in the general registration and assessment areas, the utilization of doctors' time is considerably low. This paradigm is propagated by (i) the inefficiencies in the appointment system, (ii) the allocation of the resources in the service design, and (iii) behavior patterns of the patients. Methods: We investigated the problem through a case study in a public hospital. First, through a careful walk-through of the patients' flow process, we identified the disruptions in the patient flows using lean principles. Simultaneously, through extensive data collection, we measured the patient flow times and resource utilization, and classified the value added- and non-value added times for the patients. Based on the observations and data collected, we propose changes for the appointment systems, patients' flow process, and allocation of resources. We benchmark the impact of our suggestions through simulation. Results: The improved solutions reduce the patient flow times by 30%. Conclusions: The patients' flow experience in public hospitals' OPDs can be significantly improved through better design of the appointment system and by eliminating wasted time in the patient flow process without investing in more resources.

Background: Previous studies indicated changes of adiponectin levels during gestation. The adiponectin gene ADIPOQ is located on chromosome 3q27. The association of two single nucleotide polymorphisms (SNPs) (rs1501299 and rs2241766) in ADIPOQ gene with risk of gestational diabetes mellitus (GDM) was investigated among Arab pregnant women residing in Qatar. Methods: A case-control association study was performed on 115 pregnant women with GDM and 130 controls from Qatar. Genotypes were determined using TaqMan real time PCR assay. Fasting serum c-peptide, leptin and adiponectin levels were determined using Multiplex ELISA technique. Results: All SNPs were within the Hardy-Weinberg Equilibrium (HWE). The frequency distribution of the genotype 276 G-T (rs1501299) revealed that (40.9%), (45.6%), had GG and (53.0%), (44.0%) had GT, and (6.1%), (10.4%) had TT between GDM and control, respectively with P value= 0.261. The frequency distribution of the genotype 45T-G (rs2241766) revealed that (20.8%), (16.1%), had TT and (69.6%), (65.4%) had TG, and (9.6%), (18.5%) had GG between GDM and control, respectively with P value= 0.117. T and G alleles were the minor alleles for 276 G-T and 45T-G with a frequency of (0.11) and (0.22), respectively. Using recessive genetic model, the logistic regression analysis reveled that the Odds ratio and 95% CI was 2.14 (1.01-4.95), p=0.04 for 45T-G and was 1.79 (0.69-4.65), p=0.22 for 276 G-T. Serum c-peptide (ng/ml), and leptin (ng/ml) was significantly lower in subjects having GG versus TT+TG alleles of 45T-G with mean and SEM (7.6±1.8 Vs. 17.3 ±1.2, p= 0.002), and (21.5± 2.5 Vs. 42.1± 2.8, p=0.035). Similar significant findings were observed for TT versus TG+GG genotypes for SNP 276G-T. Adiponectin levels (µg/ml) were not significantly different in subjects having GG versus TG+TT genotypes for 45T-G and for TT versus TG+GG genotypes for 276G-T with mean and SEM (17.1± 1.8 vs. 17.2±2.3, p=0.892 and 16.5±3.24 Vs. 19.8 ±1.8, p= 0.478), respectively. Conclusion: GG carriers of 45T-G may increase the odds of getting GDM among Arab residents in Qatar. Decreased pancreatic secretory function (C-peptide) with increased adiposity (leptin) among GG carriers of 45T-G and TT carriers of 276GT may explain its roles in the development of GDM.

An efficient method to generate cardiac tissue from other tissues has great therapeutic potential for patients suffering from cardiovascular disease. Pluripotent stem cells, such as embryonic stem (ES) cells, and so-called induced pluripotent stem (iPS) cells can be differentiated into multiple cell types, including cardiac myocytes. However, therapeutic use of these cells has several important risks, including cancer as well as loss of differentiated cell identity and function or "drift." Transdifferentiation, the generation of cell types from other differentiated cell types, is an attractive alternative because it poses little risk of cancer and may give rise to cells whose identity is locked in. However, the direct reprogramming of adult fibroblasts into cardiac myocytes is inefficient and the transcription factors that drive this process are unknown. To circumvent these hurdles we hypothesized that fetal derived cells may be more amenable to reprogramming into cardiac myocytes with defined transcription factors. To this end, fetal derived fibroblasts and mesenchymal cells were transduced with transcription factors that have been shown to play a role in myocyte specification and maintenance, including GATA4, Mef2c, Tbx5 and Nkx2.5. To test this hypothesis, the transcription factors were cloned into lentiviral vectors, which were used to infect fibroblasts and mesenchymal cells. Infected cells were then cultured in different media. To assess the efficiency of the reprogramming, RNA was extracted from infected and uninfected cells, and quantitative RT-PCR was used to evaluate the expression levels of the transcription factors and known cardiac genes. We expected to observe higher levels of the transcription factors and cardiac markers in the infected cells relative to the uninfected cells. The results showed that the infected cells expressed higher levels of the transcription factors and a few cardiac markers relative to the uninfected cells. However, due to the small increase in the levels of only a few cardiac markers, the reprogramming was concluded to be inefficient. To make the reprogramming more efficient, other as yet unrecognized transcription factors possibly in the GATA family of transcription factors and culture conditions are currently being considered.

Background: Calnexin is a lectin-like chaperone in the endoplasmic reticulum (ER) lumen, which along with calreticulin are involved in folding, maturation and trafficking of many glycoproteins. Insulin receptor and glucose transporters are among some of the proteins which are synthesized and folded in the ER. Previously, calreticulin was reported to play a role in the folding of GLUT-4 transporter as well as its stability. Furthermore, our lab reported that loss of calreticulin function results in increased insulin receptor synthesis, increased phosphorylation of Akt upon stimulation by insulin and increased glucose uptake. To date no data are available on the changes in insulin receptor pathway upon loss of calnexin chaperone. Objectives: The aim of this study is to examine changes in insulin receptor expression and insulin-mediated phosphorylation of Akt upon loss of calnexin function. Methods: Mouse embryonic fibroblast cells were serum starved overnight, then stimulated with insulin for 10 mins at 37°C. Cell lysate were prepared and Western blots with antibodies of different proteins in insulin signaling pathways were performed. Results: Our results showed a significant increase in insulin receptor expression in calnexin deficient cells. Furthermore, we observed a significant increase in the phosphorylation of Akt illustrating activation of insulin receptor pathway upon loss of calnexin function. Conclusions: In conclusion our data illustrates that loss of either of lectin like chaperones (calreticulin and calnexin) results in the activation of insulin receptor pathways via release of a negative suppressor of insulin receptor gene expression. Further research is needed to decipher the mechanism of this regulation.

The rapid growth of large data processing has meant the implementation of the MapReduce programming model as a widely accepted solution. The simple map and reduce stages have introduced convenience to programmers in order that they may quickly compose and design complex solutions for large-scale problems. Due to the ever-increasing complexity of execution logic in real-life applications, more and more MapReduce applications involve multiple correlated jobs encapsulated and executed according to a defined order. For example, a PageRank job involves two iterative MapReduce sub-jobs; the first job joins the rank and linkage table and the second one calculates the aggregated rank of each URL. Two non-iterative MapReduce sub-jobs for counting out-going URLs and assigning initial ranks are also included in the PageRank job. Besides this, MapReduce programming model lacks built-in support and optimization when the input data are shared. The performance will benefit when the shared and frequently accessed files are read from local instead of from distributed file system. This paper presents Concurrent MapReduce; a new programming model built on top of MapReduce while maintaining optimization and scheduling for big data applications that are composed of large number of shared data items. Concurrent MapReduce has three major characteristics: (1) Unlike traditional homogeneous map and reduce functions, it provides a flexible framework, which supports and manages multiple yet heterogeneous map and reduce functions. In other words, programmers are able to write many different map and reduce functions in a MapReduce job. (2) It launches multiple jobs in a task-level concurrency and a job-level concurrency manner. For job-level concurrency, the framework manages the shared data by replicating them from HDFS to the local file system to ensure data locality. For task-level concurrency, it is the programmers' responsibility to define the data to be shared. (3) We have evaluated the framework using two benchmarks: Single Source Shortest Path and String Matching. Results have demonstrated up to 4X performance speedup compared to traditional non-concurrent MapReduce.

Pipe inspection is a critical process in many industries, including oil and gas. Conventional practice relies on a range of Non-Destructive Testing (NDT) approaches such as ultrasonic and magnetic flux leakage methods. While these approaches can provide high accuracy wall thickness measurements, which can be used to monitor corrosion, they provide poor visualizations, and are typically unable to provide full pipe coverage. Moreover, they cannot be used to localize where in the pipe a defect is without expensive and possibly restricted sensors such as Inertial Navigation Systems. We have developed an automated vision-based approach that builds high-resolution 3D appearance maps of pipes and provides vehicle localization. These maps include both structure and appearance information, and can be used for direct metric measurement of pipe wall thickness, or as input to automatic corrosion detection algorithms. They may also be imported into 3D rendering engines to provide effective visualization of a pipe network. Our most recent system uses a wide angle of view fisheye camera which enables full pipe coverage and is sufficiently compact for practical applications. Our approach to mapping and localization builds from state-of-the-art visual odometry methods and extends them to deal with (visually) feature poor engineered environments. We present the results of this work using image datasets collected within our constructed pipe network. A range of empirical results are presented to validate the approach.

Arabic is a morphologically rich language. This morphological complexity results in a high out-of-vocabulary rate. That is why a lookup table for pronunciation modeling is not efficient for large vocabulary tasks. In previous research, graphemic modeling was proposed by approximating pronunciation modeling to be graphemes rather than actual phonemes. In this research, we have proposed a hybrid acoustic and pronunciation modeling approach for Arabic large vocabulary speech recognition tasks. The proposed approach benefits from both phonemic and graphemic modeling techniques, where two acoustic models are fused together. The hybrid approach also benefits from both vocalized and non-vocalized Arabic resources, which is useful because the amount of non-vocalized resources is always higher than vocalized ones. Two speech recognition baseline systems were built: phonemic and graphemic. The two baseline acoustic models were combined after two independent trainings to create a hybrid model. Pronunciation modeling was also hybrid by generating graphemic variants in addition to phonemic variants. Three techniques are proposed for pronunciation modeling: Hybrid-Or, Hybrid-And, and Hybrid-Top(n). In Hybrid-Or, either graphemic or phonemic modeling is applied for any given word. In Hybrid-And, a graphemic pronunciation is always generated in addition to existing phonemic pronunciations. Hybrid-Top(n) is a mixture of Hybrid-Or and Hybrid-And by applying Hybrid-Or on the top n high frequency words. Experiments were conducted in the large vocabulary news broadcast speech domain with a vocabulary size of 250K. The proposed hybrid approach has shown a relative reduction in WER of 8.8% to 12.6% depending on pronunciation modeling settings and the supervision in the baseline systems. In large vocabulary speech domains, acoustic and pronunciation modeling is a common problem among all Arabic colloquial varieties. Thus, for future work, the proposed approach is currently being extended and evaluated with different Arabic colloquial varieties (e.g. Qatari, Egyptian, Levantine, etc.). Moreover, the proposed technique can be applied with other morphologically rich languages like Turkish, Finnish, Korean, etc. This work was funded by a grant from the Qatar National Research Fund under its National Priorities Research Program (NPRP) award number NPRP 09-410-1-069. Reported experimental work was performed at Qatar University in collaboration with University of Illinois.

Relaying technologies have been designated as major new enabling technologies for next generation wireless broadband systems, such as 3GPP LTE-Advanced. The practical deployment of decode-and-forward (DF) relaying technologies as supported by the current standard is based on repetition coding, meaning that the relay regenerates the same codeword generated by the source node. This scheme is suboptimal. Nevertheless, it is preferred in practice due to its simple implementation. The optimal relaying schemes called cooperative coding are difficult to construct in practice and require heavy computation load at the receiver. Therefore, they are rarely implemented despite their prospected performance gains. As a simple and practical alternative, we propose a novel relaying scheme that provides a superior performance similar to the advanced cooperative coding techniques, but it is less complex to implement. Our novel scheme is called "decode-partial-forward" (DPF) because its fundamental concept of operation is based on making the relay forwards one part of the source message such that the receiver at the destination node can rely on the direct channel with the source to obtain the other part of the message. The DPF scheme is based favorably on repetition coding and maximal ratio combining techniques, which are standardized techniques with low-complexity and low computation load. Nevertheless, our novel scheme performs very close to the optimal bounds for the supported rates over relaying links. More specifically, the increase in the supported reliable transmission rates (bits/sec) using the proposed DPF scheme may exceed 30% of the supported rates using the conventional repetition coding DF scheme. Another major advantage of our proposed scheme is that it is easy to adapt flexibly based on the channel conditions of the three links of the relay channel (source-destination, source-relay, relay-destination), by adjusting the power and rate allocation at the source and relay using simple closed-form analytic formulas. Therefore, we believe that the DPF relaying scheme is an excellent option for practical deployment in the telecommunication standards due to its simplicity, adaptability and high spectral efficiency gains.

The widespread deployment of varying networking technologies, coupled with the exponential increase in end-user data demand has led to the proliferation of multi-interface enabled devices. To date, these interfaces are mainly utilized independently based on network availability, cost, and user choice. While researchers have focused on simultaneously leveraging these interfaces by aggregating their bandwidths, these solutions however, have faced a steep deployment barrier and only focused on maximizing throughput while overlooking the energy awareness which is critical for mobile devices. We therefore developed OPERETTA, shown in Figure1, an optimal deployable energy efficient bandwidth aggregation system for mobile users. Our system does not require modifications to applications, legacy servers, network infrastructure, or client kernel. If legacy servers choose to adopt our system, however, OPERETTA dynamically leverages this to achieve higher performance gains. OPERETTA is built as a middle-ware that is responsible for scheduling various connections and/or packets to different interfaces. This middleware estimates application and network interface characteristics and utilizes these estimates to take the most appropriate scheduling decisions. We formulate our scheduling problem as a mixed integer programming problem that has a special structure allowing it to be efficiently solved. This formulation allows users to achieve a desired throughput with minimal energy consumed. We evaluate OPERETTA via prototype implementation on the Windows OS, as well as via simulation, and compare the results to the optimal achievable throughput and energy consumption. Our results show that, with no changes to the current legacy servers, OPERETTA can achieve up to 150% enhancement in throughput as compared to the current operating systems, with no increase in energy consumption. In addition, with only 25% of the servers being OPERETTA-enabled, the system performance reaches the throughput upper-bound. We ultimately demonstrate that OPERETTA achieves the goals of being optimal, energy-efficient, as well as easily and incrementally deployable.

In wireless cellular systems, uneven traffic load among the cells increases call blocking rates in some cells and causes low resource utilisation in others and thus degrades user satisfaction and overall performance of the cellular system. Various centralised or semi-centralised Load Balancing (LB) schemes have been proposed to cope with this time persistent problem, however, a fully distributed Self Organising (SO) LB solution is still needed for the future cellular networks. To this end, we present a novel distributed LB solution based on an analytical framework developed on the principles of nature-inspired SO systems. A novel concept of super-cell is proposed to decompose the problem of "system-wide blocking minimization" into the local sub-problems in order to enable a SO distributed solution. Performance of the proposed solution is evaluated through system level simulations for both macro cell and femto cell based systems. Numerical results show that the proposed solution can reduce the blocking in the system close to an Ideal Central Control (ICC) based LB solution. The added advantage of the proposed solution is that it does not require heavy signalling overheads.

Background and Objectives: Radio frequency identification (RFID) has paved the way for a plethora of monitoring applications in the field of oil and gas. Degradation in liquefied petroleum gas (LPG)/ liquefied natural gas (LNG) quality and pipe infrastructure can be a nuisance for the oil and gas industry in Qatar. Hence, a human centric cyber-physical-system (CPS) utilizing hybrid wireless technologies including RFIDs and other sensor motes can detect and prevent such hazards. CPS technique can be used for the oil and gas sector in Qatar with customized framework architecture, event detection and decision algorithms. The objective of this research is to allow maintainers and administrators to perceive and decide on top of the monitoring system to increase the performance and efficiency of the whole monitoring application. Methods: The sensors collect the data and send it to the base station through collaborating wireless technologies. At the base station the data is processed and algorithms were run to detect an event such as presence of moisture, abnormal pressure, temperature and defects in a pipe's infrastructure health. Human interaction will help to further refine the data for possible false alarms. Mobile applications can be used by the users/administrators to send details of a perceived event directly to the base station. Results: Experiments were performed on the moisture detection in Wireless Research Laboratory in Texas A&M University at Qatar. On the similar note, other sensors can also be associated with the RFIDs and their data can be relayed to the server. A framework architecture was proposed for the human centric approach of the detection and monitoring system. Conclusion: We propose a system where these RFID active tags with the sensors such as pressure, temperature, flow, strain etc., in collaboration with other wireless technologies, are able to send information regarding the gas quality and pipe's infrastructure health. The collaboration of RFIDs and other technologies helps us to create a smart human centric monitoring system. This will enhance maintenance and event detection such as the presence of moisture or strain on pipe's structure. It will additionally assist in the automatic adjustment of the valve's and pump's properties according to the detected events.

The proliferation of mobile devices equipped with communication technologies such as WiFi, 3G, and 4G, coupled with the exponential growth of online social networking, have increased the demand for social-context-aware systems. These systems leverage social information provided by users with contextual awareness, particularly location, to provide real-time personalized services. With Euromonitor International indicating a 37.7 % growth in mobile phone penetration in the past five years--ICTQatar recently reporting that each household owns 3.9 devices on average--Qatar is positioned as a strong candidate not only for the consumption of such services, but also for researching, building, and testing solutions related to context-aware system challenges. We address some of these challenges and propose pragmatic solutions. Our contributions fall into the following two categories: (i) We design and implement SCOUT, a context-aware, ubiquitous system that enables real-time mobile services by providing contextually relevant information. This information can either be generated reactively based on user request, or proactively created and disseminated to potentially interested users. Our SCOUT prototype consists of an android-based mobile client interfacing with facebook's API and a load-balancing profile-matching server that interacts with a localization engine. (ii) Since mobile users may not all experience reliable mobile-to-core connectivity due to contention, cost, or lack of connectivity, we therefore extend the reach of context-aware services to disconnected mobile users by proposing a novel communication paradigm that leverages opportunistic communication. We first send the intended information to the smallest subset of connected users deemed sufficient to reach the disconnected destinations. This subset then selectively forwards, based on social profiles, this information to nodes that are more likely to meet the destinations. Our evaluation, via simulation, shows that our algorithm achieves an improvement of 25% to 80% compared to current communication paradigms, while reducing overhead by as much as 50%. With SCOUT currently operational, and based on the simulation results, our ongoing work includes integrating our communication paradigm into the real system. We are also working on integrating real-time group recommender systems that identify groups based on user location coupled with social information to provide real-time contextual group recommendations.

Background & Objectives: As the electromagnetic spectrum resource is becoming highly scarce, improving spectral efficiency is becoming extremely important for the development of future wireless communication systems. Integrating cooperative relaying techniques into wireless communication systems sheds new light on better spectral efficiency. By taking advantage of the broadcast nature of wireless communications, cooperative transmission can be used in improving communication reliability, and enhancing power and spectrum efficiency. Moreover, comparing to other emerging techniques that could achieve similar performance advantages, such as multiple-input multiple-output (MIMO) technique, cooperative communication is superior in hardware feasibility and deployment flexibility. The important advantages of cooperative communication make it one of the promising techniques for future wireless communication systems. Recently, many cooperative communication schemes have been included in different cellular standards, such as WiMAX and LTE-Advanced. However, the promised throughput and diversity gain may be lost in the presence of interferences, and hence, interference management is very important for exploiting the benefits of cooperation. This requires the need to find proper methods to prevent the interference problems, which is the main target of our current research. Methods: In this study we introduce an efficient cooperative communications scheme which maximizes the received signal-to-noise ratio (SNR) while keeping the interference levels below a certain threshold. The introduced scheme is based on two relay selection methods: max (link 2) which is based on maximizing the SNR of the second hop, and max (e2e) which aims to maximize the end-to-end SNR of the relayed link. In this method, the perfect decoding-and-forward (DF) relaying protocol is used by the relays, and the maximum ratio combining (MRC) receiver is used to combine the direct and the best selected relay links. We derive exact closed form expressions for the probability density function (PDF) of the SNR, outage probability, average capacity, and average bit error probability for the introduced cooperative schemes. Results & Conclusion: Simulations are used to validate the analytical results and an agreement is observed. The results confirm the advantage of the introduced cooperation schemes in enhancing the wireless communication system and in interference management.

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.

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.

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.

One of the radio resource management (RRM) functionalities in LTE systems, call admission control (CAC) is employed to control the number of LTE bearer requests in order to maintain the quality of service (QoS) of the admitted bearers. However, no quality guarantee can be provided due to the inherently dynamic nature of wireless communication. For example, during congestion periods when several communications experience poor channel quality or high mobility, it is highly possible that the network cannot maintain its bearers' QoS requirements. Thus, preemption schemes may be employed to alleviate the situation. As a result, resource preemption mechanism and its fairness are prominent issues as they may directly affect applications' QoS in the higher layers, as well as other network attributes such as generated revenue. In general, preemption is unavoidable in two circumstances, namely, to manage the resources among bearers when the network is overloaded as a congestion control mechanism, or, to allocate a high-priority bearer request while sufficient resources are not available. In this study, we propose a preemption technique by which each an established bearer may be preempted according to its priority as well as the amount of extra allocated resources compared to its basic data rate. We define the contribution of each bearer in the preemption through a contribution metric with tuning parameters which is presented in the form of Cobb-Douglas production function. We compare the fairness of the proposed scheme with a traditional preemption scheme by means of two well-known fairness indices, i.e. Jain's index and min-max index. We also discuss its effect on bearers' blocking and dropping probability and the total generated revenue. Through a simulation approach, we conclude substantial improvements in preemption fairness when compared to the traditional approach. We discuss that the proposed scheme does not affect the main performance measurements of the network, i.e. the bearers' blocking and dropping probabilities due to congestion. We also show that the preemption contribution metric can be effectively used by the service providers to vary the total generated revenue.

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.

This work considers the deployment of the binary consensus algorithm in wireless sensor networks (WSN). This algorithm is applied for the evaluation of the average measurement with the presence of a faulty/attacked node. As this algorithm has been tested theoretically, we deploy it in real life, including its distributed and routing features. In this paper, we propose the development, under simulation environment, of a distributed binary consensus algorithm. We formulate the algorithm into nesC derived from C language and running over the tiny operating system (TinyOS). The implementation was tested on sensor nodes using the TinyOSSimulator (Tossim) for a large number of nodes N and a testbed with a limited number of nodes. In performance evaluation, we considered the analysis of the average convergence time for node states to a consensus value. As in analytical results, in the simulations we applied the distributed algorithm for fully connected, paths, cycles Erdos Reny random, and starr-shaped graph topologies. Our achieved results of simulation and hardware implementations are consistent with theory.

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.

One of the most ambitious goals of Qatar in the next few years is to become a country based on scientific and technical researches instead of being dependent on hydrocarbons. To this end, Qatar Foundation has established a number of high caliber universities and institutes. In particular, Qatar Computing Research Institue (QCRI) is forming a scientific computing multidisciplinary group with a focus on data mining machine learning, statistical modeling and bioinformatics. We now are able to satisfy the computational statistics needs of a variety of fields, especially of biomedical researchers in Qatar. Functional magnetic resonance imaging (fMRI) is a noninvasive neuroimaging method that is widely used in cognitive neuroscience. It relies on the measurement of changes in the blood oxygenation level resulting from neural activity. The technique is widely used in cognitive neuroscience. fMRI is known to be contaminated by artifacts. Artifacts are known to have fat tailed distributions and are often skewed therefore modeling the error using a Gaussian distribution is not enough. In this paper we introduce RAFNI, an extension of AFNI, which is an fMRI open source software for the analysis of functional neuroimages. We are model the error introduced by artifacts using alpha-stable distribution. We demonstrate the applicability and efficiency of stable distributions on real fMRI. We show that the alpha-stable estimator gives better results than the OLS-based estimators.

With the advancements in computing and sensing technologies, large amounts of data are collected from various biological systems. These data are a rich source of information about the biological systems they represent. For example, time-series metabolic data can be used to construct dynamic genetic regulatory network models, which can be used not only to better understand the interactions among different genes inside a cell, but also to design intervention strategies that can cure or manage major diseases. Also, copy number data can be used to determine the locations and extent of aberrations in chromosome sequences which are associated with many diseases such as cancer. Unfortunately, measured biological data are usually contaminated with errors that mask the important features in the data. Therefore, noisy biological measurements need to be filtered to enhance their usefulness in practice. Conventional linear low-pass filtering techniques are widely used because they are computationally efficient and can be implemented online. However, they are not effective because they operate on a single scale, meaning that they define a specific frequency, above which all features are considered noise. Real biological data possesses multiscale characteristics, i.e., may contain important features having high frequencies (such as sharp changes) or noise occurring at low frequencies (such as correlated or colored noise). Filtering such data requires multiscale filtering techniques that can account for the multiscale nature of the data. In this work, different batch as well as online multiscale filtering techniques are used to denoise biological data. These techniques include standard multiscale (SMS) filtering, online multiscale (OLMS) filtering, translation invariant (TI) filtering, and boundary corrected TI (BCTI) filtering. The performances of these techniques are demonstrated and compared to those of some conventional low-pass filters (such as the mean filter and the exponentially weighted moving average filter) using two case studies. The first case study uses simulated dynamic metabolic data, while the second case study uses real copy number data. Simulation results show that significant improvement can be achieved using multiscale filtering over conventional filtering techniques.

Writer identification consists of identifying the writer of a certain handwritten document and is of high importance in forensic document examination. Indeed, numerous cases over the years have dealt with evidence provided by handwritten documents such as wills and ransom notes. Automatic methods for writer identification can be divided into codebook-based and feature-based approaches. In codebook-based approaches, the writer is assumed to act as a stochastic generator of graphemes. The probability distribution of grapheme usage is used to distinguish between writers. Feature-based approaches compare the handwritings according to some geometrical, structural or textural features. Feature-based approaches prove to be efficient and are generally preferred when there is a limited amount of available handwriting. Therefore, we are more interested in this study in this category of approaches. Writer identification is performed by comparing a query document to a set of known documents and assigning it to the closest document in term of similarity of handwriting. This is done by extracting characterizing features from the documents including: directions, curvatures, tortuosities (or smoothness), chain codes distributions and edge based directional features. These features correspond to probability distribution functions (PDF) extracted from the handwriting images to characterize writer individuality. When matching a query document against any other document, the ¬χ2 distance between their corresponding features is computed. The smaller the distance, the more likely the two documents are written by the same writer. Therefore, the identified writer is the one of the document with the smallest distance to the query document. The writer is said to be correctly identified when the identified writer corresponds to the actual writer of the query document. The performance has been evaluated on the IAM handwriting dataset, with chain code based features generally outperforming the other features reaching 71% correct identification rate. The combination of all the features lead to 76% correct identification rate. The proposed system also won the music scores writer identification contest reaching 77% identification rate. The proposed method automatically extracts features used by forensic experts in order to identify writers of handwritten document. The results show that the method is efficient and language-independent.

Online signatures are acquired using a digital tablet which provides all the trajectories of the signature, as well as the variation in pressure with respect to time. Therefore, online signature verification achieves higher recognition rates than offline signature verification. Nowadays, forensic document examiners distinguish between forgeries, in which an impostor tries to imitate a given signature of another person and disguised signatures, in which the authentic author deliberately tries to hide his/her identity with the purpose of denial at a later stage. The disguised signatures play an important role in real forensic cases but are not considered in recent literature. In this study, we used online signatures acquired using a WACOM Intuos4 digitizing tablet with a sampling rate of 200Hz, a resolution of 2000 lines/cm and a precision of 0.25mm. The pressure information is available in 1024 levels. Online signatures contain a set of samples, each sample corresponds to the point coordinates on the digitizing tablet along with the corresponding pressure (Xt; Yt; Pt) where t corresponds to time. From those three basic signals, four other are extracted: distances, angles, speeds and angular speed. In order to compare the questioned signature with the reference signature, the differences between their corresponding features are computed at both the signal level and the histogram level. This study has been evaluated on ICDAR2009 signature verification competition dataset and a new dataset of online signatures collected at Qatar University (QU-dataset). This dataset contains signatures of genuine signatures, forgeries and disguised of 194 persons. To the extent of our knowledge, this dataset is the only one that contains disguised online signatures. The best individual performing feature for the ICDAR2009 dataset is the pressure histogram difference which reaches 8% equal error rate (EER). The pressure signal difference is the best individual performing feature for the QU-dataset (29% EER). The combination of features led to 7% EER on the ICDAR2009 dataset and 22% EER on the QU-dataset. This online signature verification system deals with both forgeries and disguised signatures. Several features have been proposed and combined using different classifiers reaching promising performance for disguised signatures detection.