Qatar Foundation Annual Research Conference Proceedings Volume 2014 Issue 1

Photovoltaic (PV) cells can absorb up to 80% of the incident solar radiation of the solar spectrum, however, only certain percentage of the absorbed incident energy is converted into electricity depending on the conversion efficiency of the PV cell technology used, while the remainder energy is dissipated as heat accumulating on the surface of the cells causing elevated temperatures. Temperature rise at the PV cell level is addressed as one of the most critical issues influencing the performance of the cells causing serious degradations and shortens the life-time of the PV cells, hence cooling of the PV module during operation is essential. Hybrid PV designs which are able to simultaneously generate electrical energy and utilize the waste heat have been proven to be the most promising solution. In this study, analytical investigation of a hybrid system comprising of a Heat Pipe-based Photovoltaic-Thermoelectric Generator (HP-PV/TEG) for further enhanced performance is presented. The system presented incorporates a PV panel for direct electricity generation, a heat pipe to absorb excessive heat from the PV cells and assist uniform temperature distribution on the surface of the panel, and a thermoelectric generator (TEG) to perform direct heat-to-electricity conversion. A mathematical model based on the heat transfer process within the system is developed to evaluate the cooling capability and predict the overall thermal and electrical performances of the hybrid system. Results are presented in terms electrical efficiencies of the system. It was observed that the integration of TEG modules with PV cells aid improving the performance of the PV cells through utilizing the waste-heat available, leading to higher output power. The system presented can be applied in regions with hot desert climates where electricity demand is higher than thermal energy.

Harvesting electric energy from renewable energy resources is seen as one of the solutions to secure the energy sustainability due to depleting resources of fossil fuel, the conventional resources of electric energy. Renewable energy is typically connected to conventional distribution network which were not designed to accomodate any sources of electricity reduce the security of the energy supply system. Moreover the variency of renewable resources create many operational challenges to the distribution network operator. Higher shares of distributed energy sources lead to unpredictable network flows, greater variations in voltage, and different network reactive power characteristics as already evidence in many distribution networks. Local network constraints occurs more frequently, adversely affecting the quality of supply. Yet distribution network operators are nevertheless expected to continue to operate their networks in a secure way and to provide high-quality service to their customers. Active management of distribution network may provide some answers to these problems. Indeed, distribution management will allow grids to integrate renewable energu resources efficiently by leveraging the inherent characteristics of this type of generation. The growth of renewable energy resources requires changes to how distribution networks are planned and operated. Bi-directional flows need to be taken into account: they must be monitored, simulated and managed. This paper will describe features of smart grid concept that can be employed in distribution network for active management to facilitate the integration of renewable energy resources. The concepts include coordinated voltage control, microgrid operation and intelligent reactive power management to name a few. The development of physical testbed to test these new strategies in managing distribution network will also be described. The heart of these strategies is intelligent controller which acting as energy management system. The development of this controller will also be described and its operationality will be eplained.

Transparent electrodes that conduct electrical current and allow light to pass through are widely used as the essential component in various opto-electric devices such as light emitting diodes, solar cells, photodectectors and touch screens. Currently, Indium Tin oxide (ITO) is the best, commercially available transparent conducting electrode (TCE). However, ITO is too expensive owing high cost on indium. Furthermore ITO thin films are too brittle to be used in flexible devices. To fulfill the demand of TCEs for wide range of applications, high performance ITO alternatives are required. Herein we demonstrate an approach for the successful, solution based synthesis of high aspect ratio copper nanowires, which were later combined with reduced graphene oxide (rGO), in order to produce smooth thin film TCEs on both glass and flexible substrate. Structure and component characterization for these electrodes was carried out through Four Probe, Spectrophotometer, Scanning electron Microscope (SEM), Transmission Electron Microscope (TEM) and Atomic Field Microscopy (AFM). In addition to the morphological and electrical characterization, these samples were also tested for their durability by carrying out experiments that involved exposure to various environmental conditions and electrode bending. Our fabricated transparent electrodes exhibited high performance with a transmittance of 91.6% and a sheet resistance of 9 O/sq. Furthermore, the electrodes showed no notable loss in performance during the durability testing experiments. Such results make them as replacement for indium tin oxide as a transparent electrode and presents a great opportunity to accelerate the mass development of devices like high efficiency hybrid silicon photovoltaics via simple and rapid soluble processes.

A process is a series of actions executed in a particular environment in order to achieve a goal. It is often the case that several concurrent processes coexist in an environment in order to achieve several goals simultaneously. However, executing multiple processes is not always a possibility in an environment due to the following reasons: (1) All processes might be needed to be executed by a single agent that is not capable of executing more than one process at a time; (2) Multiple processes may have interactions between them that hamper their concurrent executions by multiple agents. As an example, there might be conflicting actions between several processes that their concurrent execution will stop those processes from achieving their goals. The existing solution to address the abovementioned complications is to merge several processes into a unified conflict-free and improved process before execution. This unified merged process is then executed by a single agent in order to achieve goals of all processes. However, we believe this is not the optimal solution because (a) in some environments, it is unrealistic to assume execution of all processes merged into one single process can be delegated to a single agent; (b) since merging is performed before actual execution of the unified process, some of the assumptions made regarding execution flow in individual processes may not be true during actual execution which will render the merged process irrelevant. In this paper, we propose a semantic web based solution to merge multiple processes during their concurrent execution in several agents in order to address the above-mentioned limitations. Our semantic web Process Merging Framework features a Web Ontology Language (OWL) based ontology called Process Merging Ontology (PMO) capable of representing a wide range of workflow and institutional Process Merging Constraints, mutual exclusivity relations between those constraints and their conditions. Process Merging Constraints should be respected during concurrent execution of processes in several agents in order to achieve execution-time process merging. We use OWL axioms and Semantic Web Rule Language (SWRL) rules in the PMO to define the formal semantics of the merging constraints. A Process Merging Engine has also been developed to coordinate several agents, each executing a process pertaining to a goal, to perform process merging during execution. This engine runs the Process Merging Algorithm that utilizes Process Merging Execution Semantics and an OWL reasoner to infer the necessary modifications in actions of each of the processes so that Process Merging Constraints are respected. In order to evaluate our framework we have merged several clinical workflows each pertaining to a disease represented as processes so that they can be used for decision support for comorbid patients. Technical evaluations show efficiency of our framework and evaluations with the help of domain expert shows expressivity of PMO in representation of merging constraints and capability of Process Merging Engine in successful interpretation of the merging constraints. We plan to extend our work to solve problems in business process model merging and AI plan merging research areas.

ORYX GTL is an environmentally responsible company committed to creating an efficient, diversified energy business, developing its employees, and adding value to Qatar's natural resources. ORYX GTL considers the monitoring and reporting consistent environmental data and setting accurate targets is a critical component to increase the operational efficiency on sustainable manner. Monitoring key metrics such as air emissions, criteria pollutants, flaring and energy can provide an opportunity to reduce the environmental impacts and cost savings. ORYX GTL has adopted a state-of-art information technology (IT) solution to enhance the data handling process in support of the company's environmental performance reports such as the greenhouse gas (GHG) accounting and reporting (A&R) program required by Qatar Petroleum (QP). The automated system to report environmental data is proven to be more efficient and accurate which also increases consistency & requires fewer resources to report the data in a reliable manner. The system selected by ORYX GTL is the Data Integration and Automation (DIA) system designed developed by Trinity Consultants on the Microsoft® .net platform. The objective of this paper is to share the challenges and experience during the design, develop and implement this advanced DIA system for critical environmental reporting functions at ORYX GTL as a part of the company's commitment to improve environmental performance. The DIA application can be used as the central data storage/handling system for all environmental data reporting. The DIA software includes several functions built on a state-of-art IT platform to achieve near real-time environmental monitoring, performance tracking, and reporting. The key functions include: -Hourly data retrieval, aggregation, validation, and reconciliation from the plant process historian on a pre-defined schedule. The data retrieved from the process historian may include data such as hourly fuel usage and continuous emission monitoring data, and sampling data collected on routine basis. -Powerful calculation engine allows user to build complex emission calculation equations. Calculated results are stored in the database for use in reporting. In addition to user specified equations, the system also includes a complete calculation module to handle complex calculations for tank emissions. -Through the web interface of the DIA, users can manage system reporting entity hierarchy and user security, set up tags/sources, create manual data entries, create/modify equations, and execute emission reports. The DIA application sends email notifications of errors of tag data and calculation results at user specified intervals. Email recipients can provide timely response to the system with proper root causes and corrective actions. -Custom reports can be designed to generate regulatory reports in the format required by QP or the Qatar Ministry of Environment. The DIA system has significantly enhanced the quality of ORYX GTL's environmental reporting by reducing human interactions required for process data extraction, validation, reconciliation, calculations, and reporting. ORYX GTL's proactive approach to implement and integrate DIA system provided the opportunity to improve reporting functions and stakeholder & regulator satisfaction as well as it ensures the principles of environmental data reporting such as complete, consistent, transparent and accurate.

The deployment of highly intelligent and efficient machine vision systems accomplished to achieve new heights in multiple fields of human activity. A successful replacement of manual intervention with their automated systems assured safety, security and alertness in the transportation field. Automatic number plate recognition (ANPR) has become a common aspect of the intelligent transportation systems. In addition to the license plate information, identifying the exact make and model of the car is suitable to provide many additional cues in certain applications. Authentication systems may find it useful with an extra confirmation based on the model of the vehicle also. Different car models are characterized by the uniqueness in the overall car shape, position and structure of headlights etc. Majority of the research works rely on frontal/rear view of car for the recognition while some others are also there based on an arbitrary viewpoint. A template matching strategy is usually employed to find an exact match for the query image from a database of known car models. It is also possible to select and extract certain discriminative features from the region of interest (ROI) in the car image. And with the help of a suitable similarity measure such as euclidean distance it is able to demarcate between the various classes/models. The main objective of the paper is to understand the significance of certain detectors and descriptors in the field of car make and model recognition. The performance evaluation of SIFT, SURF, ORB feature descriptors for implementing a car recognition system was already available in literature. In this paper, we have studied the effectiveness of various combinations of feature detectors and descriptors on car model detection. The combination of the 6 detectors DoG, Hessian, Harris Laplace, Hessian Laplace, Multiscale Harris, Multiscale Hessian with the 3 descriptors SIFT, liop and patch was tested on three car databases. Scale Invariant Feature Transform (SIFT), a popular object detection algorithm allows the user to match different images and spot the similarities between them. The algorithm based on keypoints selection and description offers feature independent of illumination, scale, noise and rotation variations. Matching between images has been executed using Euclidian distance between descriptors. For the given keypoints in the test image, the smallest Euclidian distance between corresponding descriptor and all the descriptors of the training image indicates the best match. Our experiments were carried out in MATLAB using the VLFeat ToolBox. It was found to achieve a maximum accuracy of 91.67% with DoG-SIFT approach in database 1 comprising cropped ROI of toy car images. For the database 2 consisting of cropped ROI of real car images, the Multiscale Hessian-SIFT yielded the maximum accuracy of 96.88%. The database 3 comprised of high resolution real car images with background. The testing was conducted on the cropped and resized ROI's of these images. A maximum accuracy of 93.78% was obtained when the Multiscale Harris-SIFT feature descriptor was employed. As a whole these feature detectors and descriptors succeeded in recognizing the car models with an overall accuracy above 90%.

Abstract: SCADA ( Supervisory control and data acquisition) is a system which allows a control of remote industrial equipments, over a communication channel. These legacy communication channels were designed before the cyber space era,and hence they lack any security measures in their network which makes them vulnerable to any cyber attack. RasGas a joint venture between QP and ExxonMobil, was one victim of such attack, it was hit with an unknown virus. The nuclear facility in Iran was hit with a virus called “Stuxnet”, it particulary targets Siemens industrial control systems. The goal of this project is to design a model of a SCADA system that is secured against network attacks. Lets consider for example a simple SCADA system which consist of a Water tank in a remote location and a local control room. the operator controls the water level and temperature using a control panel. The communication channels uses a TCP/IP , protocols through WIFI. The operator raises the temperature of the water by raising the power of the heater, then reads the real temperature of the heater and the water via installed sensors. We consider a man-In-The middle (Adversary) which has access to the network through WIFI. With basic skills s/he is able to redirects tcp/ip traffic to his machine (tapping) and alter data. He can for instance raise water level to reach overflow, or increase the temperature above the "danger zone", and sends back fake sensors data by modifying their response. We introduce an encryption device that encrypt the data such that without the right security credentials , the adversary wont be able to interpret the data and hence not able to modify it. The device is installed at both the control room and the remote tank, and we assume both places are physically secured. To demonstrate the Model. We design and setup a SCADA Model emulator server, that represents and serves as a Water tank, which consists of actuators and sensors. Which is connected to a work station through a network switch. We also setup an adversary workstation that taps and alters the communication between them. We Design Two hardware encryption/decryption devices using FPGA boards and connect them at the ports of both the server and control workstation which we assume to be in a secured zone. and then we analyze the flow of data stream through both secured and non secured state of the channel.

News media are usually biased toward some political views. Also, the coverage of news is limited to news reported by news agencies. Social media is currently a hub for users to report and discuss news. This includes news reported or missed by news media. Developing a system that can generate news reports from social media can give a global unbiased view on what is hot in a given region. In this talk, we present the research work performed in QCRI for two years, which tackle the problem of using social media to track and follow posts on ongoing news in different regions and for different topics. Initially, we show examples of the presence of bias in reporting news by different news media. We then explore the nature of social media platforms and list the research questions that motivated this work. The challenges for tracking topics related to news are discussed. An automatically adapting information filtering approach is presented that allows tracking broad and dynamic topics in social media. This technique enables automatically tracking posts on news in social media while coping with the high changes occurring in news stories. Our developed system, TweetMogaz, is the demoed, which is an Arabic news portal platform that generated news from Twitter. TweetMogaz reports in real-time what is happening in hot regions in the Middle East, such as Syria and Egypt, in the form of comprehensive reports that include top tweets, images, videos, and news article shared by users on Twitter. It also reports news on different topics such as sports. Moreover, Search is enabled to allow users to get news reports on any topic of interest. The demo would be showing www.tweetmogaz.com live, where emerging topics in news would appear live in front of the audience. By the end of the talk, we would show some of the interesting examples that were noticed on the website in the past year. In addition, a quick overview would be presented on one of the social studies, which was carried out based on the news trend changes on TweetMogaz. The study shows the changes of people behavior when reporting and discussing news during major political changes such as the one happened in Egypt in July 2013. This work is an outcome of two years of research in the Arabic Language Technology group in Qatar Computing Research Institute. The work is published in the form of six research and demo papers in tier 1 conferences such as SIGIR, CSCW, CIKM, and ICWSM. The TweetMogaz system is protected by two patent applications filed in 2012 and 2014. Currently the website serves around 10,000 users, and the number is expected to significantly increase when officially advertised. Please feel free to visit TweetMogaz website for checking the system live: www.tweetmogaz.com Note: A new release with a better design to the website is expected by the time of the conference

Abstract Smoking-related illnesses are costly to the NHS and a leading cause of morbidity and mortality. Pharmacological treatments including nicotine replacement, some antidepressants, and nicotine receptor partial agonists, as well as individual- and group-based behavioural approaches, can help stop people from smoking. Circa 40% of smokers attempt to quit smoking each year, yet most have rapid relapses. The development of new tools acceptable by a wide range of smokers should be of particular interest. Smartphone interventions such as text messaging have shown some promise in helping people stop smoking. However most of these studies were based on text-messaging interventions with no interactive functionality that can provide better feedback to the smoker. In addition there is increasing evidence that smart mobile phones act as a conduit to behavioural change in other forms of healthcare. A study of currently available iPhone apps for smoking cessation have shown a low level of adherence to key guidelines for smoking cessation; few, if any, recommended or linked the user to proven treatments such as pharmacotherapy, counselling or a “quit line” and smoking cessation program. Hence there is a need for clinical validation of the feasibility of app-based intervention in supporting smoking cessation programmes in community pharmacy settings. The goal of this study is to design and develop an m-health programme platform to support smoking cessation in a community setting. The primary objectives are ascertaining what users require from a mobile app-based smoking cessation system targeting and supporting smokers, and looking into the literature for similar solutions. The study also involves the design and development of an end-to-end smoking cessation management system based on these identified needs; this includes the Patients Hub, Cloud Hub, and Physician/Social Worker Hub, as well as the design and development of a decision support system based on data mining and an artificial intelligent algorithm. Finally, it will implement the system and evaluate it in a community setting.

* Background & Objectives All critical infrastructure can be modeled as networks, or systems of nodes and connections, and many systems such as the electric grid, water supply, or telecommunications exist explicitly as networks. Infrastructures are interdependent, for instance, telecommunications depend on electric power, and control of the electric grid depends increasingly upon telecommunications, creating the possibility for a negative feedback loop following a disturbance. The performance of these systems under disturbance are related to their inherent network characteristics, and network architecture plays a fundamental role in reliability. What characteristics of networks affect their robustness? Could, for instance, the vulnerability of the electric grid to cascading failure be reduced? * Methods We create a failure model of the network where each node and connection is initially in the operative state. At the first discrete time step a network element is changed to the failed state. At subsequent time steps a rule is applied which determines the state of random network elements based upon the state of their neighbors. Depending upon the rule and the distribution of the degree of connectedness of the network element, failures may be contained to a few nodes or connections, or may cascade until the entire network fails. * Results Quantitative measures from the model are the probability of network failure based upon the loss of a network element, and the expected size distribution of failure cascades. Additionally, there is a critical threshold below which infrastructure networks fail catastrophically. The electrical grid is especially vulnerable as it operates close to the stability limit, and there is a low critical threshold after which the network displays a sharp transition to a fragmented state. Failures in the electrical grid result not only in the loss of capacity in the network element itself, but load shifting to adjacent network elements, which contributes to further instability. While most failures are small, failure distributions are heavy tailed indicating occasional catastrophic failure. Many critical infrastructure networks are robust to random failure, but the existence of highly connected hubs give them a high clustering coefficient which makes the network vulnerable to targeted attacks. * Conclusions It is possible to design network architectures which are robust to two different conditions: random failure and targeted attack. It is also possible to alter architecture to increase the critical threshold at which failed network elements cause failure of the network as a whole. Surprisingly, adding more connections or capacity sometimes reduces robustness by creating more routes for failure to propagate. Qatar is in an ideal position to analyze and improve critical infrastructure from a systemic perspective. Modeling and simulation as detailed above are readily applicable to analyzing real infrastructure networks.