Qatar Foundation Annual Research Conference Proceedings Volume 2014 Issue 1

The profound economic growth in the Arabian Gulf states over the past few decades has had a great impact on the lifestyle of the Qatari population. There has been a rapid appearance of fast food restaurants and other hallmarks of western society. These influences have been accompanied by a higher energy intake and decreased levels of physical activity. The potential impact on the younger population is particularly alarming. Throughout the recent past, the prevalence of type 2 diabetes (T2DM) among children and adolescents has increased significantly due to the high prevalence of obesity. Obese children can have a higher risk of premature mortality due to consequent cardiometabolic morbidity. According to WHO, obesity-induced medical conditions have now led to excess mortality surpassing that associated with tobacco. However, data on the body weight status of Qatari children are lacking for the past ten years. This study estimates the magnitude of the increase in BMI among Qatari adolescents (aged 12-18 years), by comparing our data (obtained during 2009) with published results from 2003 [Bener et al, JHPN 2005;23(3):250-8]. The present data originate from a pilot study on lung function conducted in Qatar in 2009. The subjects were chosen by random sampling of Qatari students attending government schools (grade 7-12). For our study, only students aged 12-18 years are included, resulting in a total number of 705 participants (400 girls and 305 boys). Although a large variety of data was collected, our study focused only on height, weight and BMI. The results reveal a substantial increase in BMI during this 7 year period for both Qatari boys and girls. For boys aged 12 years, mean BMI increased by 2 Kg m-2 which became a 5 Kg m-2 increase at the age of 17 years, and possibly as much as 8 Kg m-2 by 18 years. By contrast, the increase in mean BMI for girls remained more or less constant between the age of 12 years and 17 years, fluctuating between 2 Kg m-2 and 4 Kg m-2, before reaching almost 7 Kg m-2 at the age of 18 years. Using International Obesity Task Force (IOTF) criteria, the overall prevalence of Qatari children who were overweight or obese was 26.5% (boys) and 23.1% (girls) in 2003 [Bener, Food Nutr Bull 2006;27(1):39-45], and 47.2% (boys) and 40.8% (girls) in 2009. For boys, this represents a 21% increase, with a corresponding increase of 18% for girls. These results show that during this 7-year period, the prevalence of overweight and obesity among both boys and girls has increased by more than 75%. Based on these figures, the prevalence of childhood obesity is alarmingly high and points to an acute need for intervention, and a need for local research into the most appropriate and effective actions. In addition, there is also a need to systematically collect regular and ongoing observational data regarding body weight status of adolescent Qataris in order to continue to monitor this situation.

An electronic library is a computer-managed set of collections with services tailored for its user communities. The project team—a collaboration of four universities (Qatar University - QU, Virginia Tech, Pennsylvania State University, Texas A & M University), the Qatar National Library - QNL, and consultants—focused on the two project aims for Qatar: building community and building infrastructure (i.e., collections and information services). Thus we fit with Qatar's Thematic Pillar of Research on Computing and Information Technology, and overlap with a number of Research Grand Challenges (e.g., Cyber-security; Managing the Transition to a Diversified, Knowledge-based Society, and Culture, Arts, Heritage, Media and Language within the Arabic Context). With regard to our aim of building an electronic library community in Qatar, we have: 1. Participated in the Special Library Association Gulf Chapter, hosted in Qatar, to create awareness about electronic libraries; 2. Launched a consulting center at QU Library—with more than 30 new reference works, online educational resources, and specialized databases—and are sharing knowledge with librarians and information professionals to support those interested in collections and services; 3. Established a collaboration with Gulf Studies at QU, so we can identify and host content on this topic, and assist QU researchers and students; and 4. Collected citation-based and non-citation-based metrics (altmetrics), for Qatar and 35 nations that are competing with Qatar's annual scholarly production. We published a new approach for comparing the metrics and evaluating country-level scholarly impact. 5. Studied the evolving scholarly activities and needs of researchers in Qatar, and compared them with our findings from USA, informing ELISQ about requirements and solutions appropriate for international electronic libraries. With regard to our aim of building electronic library infrastructure in Qatar, we have built collections and provided related services: 1. Penn State's SeerSuite software is running at QU, allowing users to search the metadata and full-text of collections of PDF files from scholarly articles, e.g., QScience papers. SeerSuite gathers scholarly documents and automatically extracts metadata (authors, venues etc.) from crawled WWW content, allowing QNL and other libraries to harvest that metadata using OAI-PMH.. SeerSuite is being improved for searching on the content of the figures and tables in scholarly documents. 2. An historical collection of old Arabic documents has been assembled, indexed, and made accessible as well as data/text mined. 3. Using our QU server running Heritrix, gathered our first Arabic collection (8GB from 2,200 PDF files), from Qatari newspapers (Al-Rayah, Al-Watan, Qatar News Agency, Al-Arab, and Al-Sharq). This news collection was indexed with Apache Solr and is available for searching. Building upon the IPTC system we created a categorization system (taxonomy) for news stories, and then applied it through machine learning to train classifiers to aid browsing. 4. Both QNL and QU are building Web archives of portions of the WWW in Qatar, adapting Heritrix and the Wayback Machine, thus preserving history, culture, and Arabic content (including news, sports, government information, and university webpages) for future use and scholarly study.

In the 130 years since the invention of the legacy electric power system concept, electrical generation has been adjusted to match electrical consumption (i.e., the "load") as it varies throughout the time of day and seasons. This "generation follows load" paradigm is a major roadblock to the large-scale incorporation of renewable energy into the national power grid since energy sources such as wind and solar provide inconsistent, variable power that cannot easily be controlled to follow consumption. As a result, today's centrally planned and controlled power system design is no longer adequate. This paper is to introduce a new control approach to enable a "load follows generation" paradigm where a flexible engineered system with distributed control at the users' sites will revolutionize the power industry. Customers will be able to generate power on-site, purchase power from a variety of sources (including each other), sell power back to the grid, select the level of the supply reliability they wish to purchase, and choose how to manage their electricity use. The resulting solution will make the electricity grid significantly more efficient and robust by facilitating extensive use of renewable energy sources and reducing end-use losses in the system. With renewable energy sources widely distributed (e.g., roof-top solar panels and wind farms), the proposed approach will allow exchange of power among utilities, market service providers, consumers, and aggregators (services representing many loads), and also allow power exchange within a customer site. By incorporating this flexibility into their operations, utilities will be able to adjust the overall load they must serve to match available power. This "load follows generation" approach is essential to allow unhindered inclusion of low-emission renewables in the electricity grid. At the same time it makes consumers active agents in the energy exchange. Earlier research addressed discrete aspects of the scientific challenges, but the new approach called Flexible Load Energy eXchange (FLEX) will provide the system-level, holistic approach to achieve its vision. The overarching goal is to develop the science, technology, and control system design required to enable energy exchange between the customer and other parties in the electricity energy exchange ecosystem to unlock the huge potential of renewable generation. A central impediment is the stochastic variability of renewable energy sources such as wind and solar, prompting some to question if dependence on renewable sources will ever be viable. Even when wind (which tends to produce at night) and solar (produced during the day) are combined, severe variations in generation require huge adjustments (termed "ramping" within the industry), and spinning (on-line) reserves using conventional generation. This paper explores the missing critical component of smart grid development: smart and flexible loads. In addition, power interruptions, which are often caused by generation/load imbalances or faults on end-user radial connections, will be greatly reduced in a FLEX-enabled power grid by on-site or alternate customer generation. FLEX will also enable customer participation to create new market arrangements, such as wholesale and retail options, and incentives to increase energy efficiency not previously available.

The aim of this research is to investigate the utilisation of Computational Intelligence (CI) methods for constructing a World Cybersecurity Indicator (WCI) to enable consistent and transparent assessments of the cybersecu- rity capabilities of nation's through the utilisation of Synthetic Composite Indicators (SCI's) concept for ranking their readiness and progress. SCI are assessment tools usually constructed to evaluate and contrast entities perfor- mance by aggregating intangible measures in many areas such as technology and innovation. SCI key value is inhibited in its capacity to aggregate com- plex and multi-dimensional variables into a single meaningful value. As a result, SCIs have been considered as one of the most important tools for macro-level and strategic decision making. Considering the shortcomings of the existing SCI, this study is proposing a CI approach to develop a new WCI. The suggested approach utilizes Fuzzy Proximity Knowledge Mining technique to build the qualitative taxonomy initially, and Fuzzy c-mean is employed to form a macro level cybersecurity indicator. To illustrate the method of construction a fully worked application is pre- sented. The application employs real variables of possible threats to the In- formation and Communication Technology (ICT). The weighting and aggre- gation results obtained were compared against classical approaches namely Principal Component Analysis, Factor Analysis and the Geometric Mean to weight and aggregate SCI's. The proposed model has the capability of weighting and aggregating major cybersecurity indicators into a single value that ranks nations even with limited data points. The validity and robustness of the WCI is evaluated using Monte Carlo simulation. In order to show the value added by the new cybersecurity index, the WCI is applied to the Middle East and North Africa (MENA) region as a special case study and then generalised. In total seventy-three countries were included, that are representative of developed, developing and under- developed nations. The nal and overall ranking results obtained, suggest novel and unbiased way compared to traditional or statistical methods when building, the WCI.

Social computing has led to new approaches for Knowledge Translation (KT) by overcoming the temporal and geographical barriers experienced in face-to-face KT settings. Social computing based discussion forums allow the formulation of communities of practice whereby a group of professionals disseminate their knowledge and experiences through online discussions on specialized topics. In order to successfully build an online community of practice, it is important to improve the connectivity between like-minded community members and between like-topic discussions. In this paper we present a Medical Online Discussion Analysis and Linkages (MODAL) method to identify affinities between members of an online social community by applying: (a) social network analysis to understand their social communication patterns during KT; and (b) semantic content analysis to establish affinities between different discussions and professionals based on their communicated content. Our approach is to establish linkages between users and discussions at the semantic and contextual levels—i.e. we do not just link discussions that share exact medical terms, rather we link practitioners and discussions that share semantically and contextually similar medical terms, thus accounting for vocabulary variations, concept hierarchies and specialized clinical scenarios. MODAL incorporates two novel semantic similarity methods to analyze online discussions using: (i) the Generalized Vector Space Model (GVSM) that leverages semantic and contextual similarity to find similarities between discussion threads and between practitioners; and (ii) an extension of the Balanced Genealogy Model (BGM) so that we are able to address non-leaf mappings, issues of homonymity noted in medical terminologies, and further contextualization of the similarity measures using information content measures. We have implemented a similarity metric that captures the concept of "interest" between users or threads, i.e., a numeric measure of how interested user A is in user B, or how much of the information contained in thread A is related to thread B. MODAL measures the "interest" one professional has in another professional within the online community, and then uses this metric to identify those professionals that are sought by other professionals for expert advice—the content experts. Furthermore, by incorporating the interest measures with SNA, MODAL is able to identify the content experts within the community, and analyze the content of their conversations to determine their areas of expertise. Given the short and unstructured nature of online communications, we use the MeSH medical lexicons and the medical text analysis tools, i.e. Metamap, to map the unstructured narrative of online discussions to formal medical keywords based on the MeSH lexicon. MODAL is tested on two online professional communities of healthcare practitioners: (a) Pediatric Pain Mailing List is a community of 460 clinicians from around the world--over a four year period 2505 messages were shared on 783 different discussion threads; (b) SURGINET is a community of 865 clinicians from around the world that use the forum to discuss general surgical issues-it contains over 17000 messages on 2111 threads by 231 users. MODAL is able to identify content experts and link like-minded practitioners based on the content of their conversations rather than on direct ties between them.

One of the main issues accompanied with the high penetration of PV distributed generation (DG) systems in low voltage (LV) networks is the overvoltage challenge. The amount of injected power to the grid is directly related to the voltage at the point of common coupling (PCC), which necessitates limiting the amount of injected power to the grid to conservative values compared to the available capacity from the PV panels particularly at light loading. In order to mitigate the tradeoff between injecting the maximum amount of electrical power and voltage rise phenomena, many control schemes were suggested in order to optimize the operation of PV DG energy sources as well as maintaining safe voltage levels. Unlike these conventional methods, this paper proposes a combined PV inverter-based distributed generation and flywheel energy storage system to ensure improved voltage regulation as well as making use of the maximum available power from the PV source at any instant, decoupling its relation with the terminal voltage. The concluded assumptions were simulated through Matlab/Simulink and verified experimentally.

Online social networks and online real time communication tools gained large popularity in the last years. In the Arab spring they emerged as one of the main tools to exchange ideas and to organize activities. Many users were unaware that their communication and their interaction patterns are traced. After the Arab spring and after the information demystified by Edward Snowden, users are becoming security aware and look for alternative technologies to communicate securely. Our contribution in this presentation is twofold, first we present the current technological developments in computer science and networking technologies that envision to provide tools to the users, so that their communication is secured and impossible to track. Based on peer-to-peer-technologies, known from file-sharing applications, several solutions for secure, reliable and untraceable communication already exist. In addition, opportunistic and delay-tolerant networks, provide asynchronous "online" communication which do not even use the Internet infrastructure, thus making it even harder to identify and to trace. As a second contribution, we present a technological framework based on peer-to-peer networking, which allows to build platforms for online social network. In depth, we show how this framework is capable to provide common functionality of online social networks, but at the same time is privacy-aware and impossible to trace or to shut of. The framework uses fully decentralized data storage and sophisticated cryptography for the user management, secure communication and access control to the data of the users. The quality of the presented framework, in terms of performance and communication costs, has been evaluated in simulations with up to 10,000 network nodes as well as in test with up to 30 participants. Our findings are, that up to now the usability, economical pressure and the security of (centralized) communication tools were incompatible. This observation changes with decentralized solutions which do not come with economic pressure. Both secure and usable solutions are about to emerge, fully distributed and secure, which will be impossible to shut down or to trace. For the future it will be interesting, whether the presented decentralized technology will be ignored or whether it will disrupt the economics and the market of social networks, like it was the case with Napster and the music industry, a case in which decentralized peer-to-peer networking unfolded it potential.

Cyber-Physical Systems (CPS) rely on advancements in fields such as robotics, mobile computing, sensor networks, controls, and communications, to advance complex real-world applications including aerospace, transportation, factory automation, and intelligent systems. The multidisciplinary nature of effective CPS research, diverts specialized researchers' efforts towards building expensive and complex testbeds for realistic experimentation, thus, delaying or taking the focus away from the core potential contributions to be made. We present Up and Away (UnA), a cheap and generic testbed composed of multiple autonomously controlled Unmanned Ariel Vehicle (UAV) quadcopters. Our choice of using UAVs is due to the their deployment flexibility and maneuverability enabling a wide range of CPS research evaluations in areas such as 3D localization, camera sensor networks, target surveillance, and traffic monitoring. Furthermore, we provide a vision-based localization solution that uses color tags to identify different objects in varying light intensity environments and use that system to control the UAVs within a specific area of interest. However, UnA's architecture is modular so that the localization system can be replaced by any other system (e.g. GPS) as deployment conditions change. UnA enables interaction with real world objects, treating them as CPS input, and uses the UAVs to carry out CPS specific tasks while providing sensory information from the UAV's array of sensors as output. We also provide an API that allows the integration of simulation code that will obtain input from the physical world (e.g. targets to track) then provide control parameters (i.e. number of quadcopters and destinations coordinates) to the UAVs. The UnA architecture is depicted in Figure 1a. To demonstrate the promise of UnA, we use it to evaluate another research contribution we make in the area of smart surveillance, particularly that of target coverage using mobile cameras. Optimal camera placement to maximize coverage has been shown to be NP-complete for both area and target coverage. Motivated by the need for practical computationally efficient algorithms to autonomously control mobile visual sensors, we propose efficient near-optimal algorithms for finding the minimum number of cameras to cover a high ratio of targets. First, we develop a basic method, called cover-set coverage to find the location/direction of a single camera for a group of targets. This method is based on finding candidate points for each possible camera direction and spanning the direction space via discretizing camera pans. We then propose two algorithms, (1) Smart Start K-Camera Clustering (SSKCAM) and (2) Fuzzy Coverage (FC), which divide targets into multiple clusters and then use the cover-set coverage method to find the camera location/direction for each cluster. Overall, we were able to integrate the implementation of these algorithms with the UnA testbed to witness real-time assessment of our algorithms as shown in Figure 1b.

In today's world, the need for more energy seems to be ever increasing. The high cost and limited sources of fossil fuels, in addition to the need to reduce greenhouse gasses, have made renewable energy sources (RES) attractive in today's world economy. However, the fluctuating and intermittent nature of these RES causes variations of power flow that can significantly affect the stability and operation of the electrical grid. In addition, the power output of these RES is not as easy to adjust to changing demand cycles as the output from the traditional power sources. To overcome these problems, energy from these RES must be stored when excess is produced and then released, when production levels are less than the required demand. Therefore, in order for RES to become completely reliable as primary sources of energy, energy storage systems (ESS) is a crucial factor. The impact of the ESS in future grid is receiving more attention than ever from system designers, grid operations and regulators. Energy storage technologies have the potential to support our energy system's evolution, they can be used for multiple applications, such as: energy management, backup power, load leveling, frequency regulation, voltage support, and grid stabilization. In this work, an overview of the current and future energy storage technologies used for electric power applications is carried out. Furthermore, an assessment of the dynamic performance of energy storage technologies for the stabilization and control of the power flow of emerging smart grid will be presented. The EES can enhance the operation security and ensure the continuity of energy supply in future smart grids.

Power system stability is one of the main factors in performance of electrical system. A control system must retain frequency and voltage size under any distortion such as sudden increase in load, to leave a generator from circuit or cut off a transmission line in a constant level. In this paper, Honey-Bee Mating Optimization (HBMO) algorithm has been used to design power system stabilizer. It is based on the mating between queen and bees. Meta-heuristics honey-bee mating optimization algorithm is considered to be as intelligent algorithm. Simulation results show that HBMO algorithm is simple to solve optimization issues. It works based on the changes in the system to adapt with reality and increase flexible parameters in comparison with other methods. Furthermore, considering performance level, it has suitable standard deviation and convergence of approximation.