Qatar Foundation Annual Research Conference Proceedings Volume 2014 Issue 1

The purpose of this paper is mainly aimed to provide an energy security strategy for the petroleum production and processing in the grand challenges. Fault detection and diagnosis is the central component of abnormal event management (AEM) [1]. According to the International Federation of Automatic Control (IFAC), a fault is defined as an unpermitted deviation of at least one characteristic property or parameter of the system from the acceptable/usual/standard condition [2-4]. Generally, there are three parts in a fault diagnosis system, detection, isolation, and identification [5, 6, 7]. Depending on the performance of fault diagnosis systems, they are called FD (for fault detection) or FDI (for fault detection and isolation) or FDIA (for fault detection, isolation and analysis) systems [5]. As the increasing needs for energy grows rapidly, energy security becomes an important issue especially in petroleum production and processing. The importance can be mainly considered in following perspectives: higher system performance, product quality, human safety, and cost efficiency [5, 8]. With this in mind, the purpose of this research is to develop a Fault Detection and Isolation (FDI) system which is capable to diagnosis multiple sensor faults in nonlinear cases. In order to lead this study closer to real world applications in oil industries, the system parameters of the applied system are assumed to be unknown. In the first step of the proposed method, phase space reconstruction techniques are used to reconstruct the phase space of the applied system. This step is aimed to infer the system property by the collected sensor measurements. The second step is to use the reconstructed phase space to predict future sensor measurements, and residual signals are generated by comparing the actually measured measurements to the predicted measurements. Since, in practice, residual signals will not perfectly equal to zero in the fault-free situation, Multiple Hypothesis Shiryayev Sequential Probability Test (MHSSPT) is introduced to further process those residual signals, and the diagnostic results are presented in probability. In addition, the proposed method is extended to a non-stationary case by using the conservation/dissipation property in phase space. The proposed method is examined by both of simulated data and real process data. The three tank model is modeled according to a nonlinear laboratory setup DTS200 and introduced for generating simulated data. On the other hand, the real process data collected from a sugar factory actuator system are also used to examine the proposed method. According to our results obtained from simulations and experiments, the proposed method is capable to indicate both of healthy and faulty situations. In the end, we have to emphasize that the proposed approach is not limited in the applications of petroleum production and processing. For example, our approach can also apply to enhance the quality of water and avoid the discharges, such as leakage, in the process of water resource management. Therefore, the proposed approach not only benefits the issue of energy security but also other issues in the grand challenges.

This paper presents a novel real-time scale adaptive visual tracking framework and its use in smart traffic monitoring where the framework robustly detects and tracks vehicles from a stationary camera. Existing visual tracking methods often employ a semi-supervised appearance modeling where a set of samples are continuously extracted around the vehicle to train a discriminant classifier between the vehicles and the background. While proving their advantage, many issues are still to be addressed. One is a tradeoff between high adaptability (prone to drift) and preserving original vehicle appearance (susceptible to tracking loss with significant appearance variations). Another issue is vehicle scale changes due to perspective camera effect which increases the potential for an inaccurate update and subsequently visual drifting. Still, scale adaptability has received little attention in vision-based discriminant trackers. In this paper we propose a three-step Scale Adaptive Object Tracking (SAOT) framework that adapts to scale and appearance changes. The framework is divided into three phases: (1) vehicle localization using a diverse ensemble, (2) scale estimation, and (3) data association where detected and tracked vehicles are correlated. The first step computes vehicle position by using an ensemble based on a compressed low-dimensional feature subsets projected from high-dimension feature space by random projections. This provides the diversity needed to accommodate for individual classifiers errors and different adaptability rates. The scale estimation step, applied after vehicle localization, is computed based on matched points between a pre-stored template and the localized vehicle. This doesn't only estimate the new scale of the vehicle but also serves as a correction step to prevent drifting by estimating the displacements between correspondences. The data association step is subsequently applied to link detected vehicle of current frame with the tracked vehicles. Data association must consider factors like the absence of detected target, false detections and ambiguity. Figure 1 illustrates the framework in operation. While the vehicle detection phase is executed per frame, the continuous tracking procedure ensures that all vehicles in the scene, no matter how complex it is, are correctly accounted for. The performance of the proposed Scale Adaptive Object Tracking (SAOT) algorithm is further evaluated with a different set of sequences with scale and appearance changes, blurring, moving camera and illumination. SAOT was compared to three established trackers in the literature: Compressive Tracking , Incremental Learning for Visual Tracking and Random Project with Diverse Ensemble Tracker using standard visual tracking evaluation datasets [4]. The initial target position for all sequences was initialized using manual ground truth. Centre Location Error (CLE) and Recall are calculated to evaluate the methods. Table 1 presents the CLE errors and recall in parentheses measured on a set of 2 sequences with different challenges. It clearly demonstrates that SAOT performs better than the other trackers.

The work of our group falls within the area of Cyber Security, which is one of Qatar's Research Grand Challenges. We are working on designing a new public key cryptosystem that can improve the security of communication networks. The most widely used cryptosystem at present (like RSA) are based on the difficulty of factorization of numbers that are constructed as product of two large primes. The security of such systems was put in doubt since these systems can be attacked with a help of quantum computers. We are working on a new cryptosystem that is based on different (noncommutative) structures, like algebraic groups and supergroups. Our system is based on the difficulty of computing invariants of actions of such groups. We have designed a system that uses invariants of (super)tori of general linear (super)groups. Effectively, we are building a "trapdoor function" enabling us to find a suitable invariant of high degree and do the encoding of the message quickly and efficiently but which provides an attacker with computationally very expensive and difficult task to find an invariant of that high degree. As with every cryptosystem, the possibility of its break have to be scrutinized very carefully and the system has to be investigated independently by other researchers. We have established theoretical results about minimal degrees of invariants of a torus that are informing possible selection of parameters of our system. We continue getting more general theoretical results and we are working towards an implementation and testing of this new cryptosystem. A second part of our work is an extension from the classical case of algebraic groups to the case of algebraic supergroups. We are concentrating especially on general linear supergroups. We have described the center of the distribution superalgebras of general linear groups GL(m|n) using the concept of an integral in the sense of Haboush and computed explicitly all generators of invariants of the adjoint action of the group GL(1|1) on its distribution algebra. The center of the distribution algebra is related via the Harish-Chandra map to infinitesimal characters. Understanding of these characters and blocks would lead us to the description of the linkage principle, that is of composition factors of induced modules. Finding and proving linkage principle for supergroups over the field of positive characteristics is one of our main interests. This extends classical results from the representation theory that are giving scientists, mathematicians and physicists, a tool to find a theoretical model where the fundamental rules of symmetries of the space-continuum are realized. Better theoretical background could lead to better understanding of the experimental data and predictions confirming or contradicting our current understanding of the universe. As happened many times in the past, finding the right point of view and developing new language can often lead to different level of understanding. Therefore we value the theoretical part of our work the same way as the practical work related to the cryptosystems.

Background & Objective: Blood vessel segmentation has various applications such as proper diagnosis, surgical planning, and simulation. However, the common challenges faced in blood vessel segmentation are mainly vessels of varying width and contrast changes. In this paper, we propose a segmentation algorithm, where: (1) a histogram-based approach is proposed to determine the initial patch (seeds) and (2) on this patch, a Gauss- Hermite quadrature filter is applied across different scales to handle vessels of varying width with high precision. Subsequently, a level set method is used to perform segmentation on the filter output. Methods: In spatial domain, a Gauss-Hermite quadrature filter is basically a complex filter pair, where the real component is a line filter that can detect linear structures, and the imaginary component is an edge filter that can detect edge structures; the filter pair is used for combined line-edge detection. The local phase is the argument of the complex filter response that determines the type of structure (line/edge), and the magnitude of the response determines the strength of the structure. Since the filter is applied in different directions, all filter responses are then combined to produce an orientation invariant phase map by summing filter responses for all directions. We use 6 filters with center frequency pi/2. To handle vessels of varying width, a multi-scale integration approach is implemented. Vessels of different width appear both as lines and edges across different scales. These scales are combined to produce a global phase map that is used for segmentation. The resulting global phase map contains detailed information about line and edge structures. For blood vessel segmentation, a local phase of 90 degree indicates edge structures. Therefore, it is necessary to consider only the real part of the quadrature filter response. Edges will be found at zero crossing whereas positive and negative values will be obtained for inside and outside of line structures. Therefore, level set (LS) approach is utilized that uses the real part of the phase map as a speed function to drive the deforming contour towards the vessel boundary. In this way, the blood vessel boundary gets extracted. An initial patch on the desired image object is a requirement in this algorithm to start calculating the local phase map. It is obtained by first selecting a few possible partitions using peaks (local maxima) in the intensity histogram. Then, optimal number of seeds is obtained by an iterative clustering of these peaks using their histogram heights and grey scale difference. The seeds around the object form the patch. Results & Conclusion: The proposed method has been tested on 6 subjects of Head MRT Angiography having resolution 416×512×112. We use 6 filters of size 7×7×7 and 4 scales in this experiment. The average time required by MATLAB R14 to perform segmentation is 3 m for one subject by a 2 GB RAM and core2duo processor (without optimization). The resulted segmentation is promising and robust in terms of boundary leakage as can be observed from the Figure.

Sensors are the eyes and ears in the service of people - especially in inaccessible areas where regular maintenance or battery replacement is extremely difficult. By using thermoelectric generators, which are capable of directly converting heat flux into electrical energy, self-powered sensor systems can be established wherever temperature differences of a few Kelvin exist. After installation of the sensors, they collect and transmit their data without any need for further maintenance like battery replacement. Intelligent building automation for instance is the key for significant energy reduction in buildings. Through precise control of sun blinds and set temperature for thermostats and air conditioning, radio signal sensors help to increase a building's efficiency massively. Thermoelectric self-powered sensors have the additional potential to introduce more flexibility in the area of building technology as complex wiring is avoided. Buildings can easier be adapted to altered utilization. Structural health monitoring is another field where energy autarkic sensors could be of vital use. In-situ measurements of e.g. temperature, humidity, strain and cracks of buildings are essential in order to determine the condition of construction materials. Respective sensors are hardly accessible, wiring or battery replacement is costly or even impossible. Sensors that are driven by thermoelectric generators are maintenance-free and can help enhancing the longevity of buildings as well as reducing the maintenance costs. Furthermore, leakages in water transport systems can be reduced by in-situ monitoring by self-powered sensors and thus, reduce unnecessary water losses. The large progress in the development of low-power sensors, power management and radio communication combined with the availability of high efficiency thermoelectric generators opens the possibility to run a self-powered sensor node with temperature gradients as low as 0.8K. This potential will be presented with respect to selected fields of application.

Digital devices and computer software have the prospect to help children with intellectual challenges (IC) in learning capabilities, profession growth, and self-consciousness living. However, most tools and existing software applications that these children utilize are prepared without observance of their particular deficiency. We conduct an Arabic ontology-based learning system that presents automatically illustrations to characterize the content of stories for children with IC in the state of Qatar. We utilize different mechanisms in order to produce these illustrations which comprise: Arabic natural language processing, animal domain-based ontology, word-to-word based relationship extraction, automatic online search-engine querying. The substantial purpose of our proposed system is to ameliorate children with IC the educational, comprehension, perception, and reasoning through the generated illustrations.

In this paper we introduce and study special types of magic squares of order six. We list some enumerations of these squares. We present a parallelizable code. This code is based on the principles of genetic algorithms. A magic square is a square matrix, where the sum of all entries in each row or column and both main diagonals yields the same number. This number is called the magic constant. A natural magic square of order n is a matrix of size n×n such that its entries consist of all integers from one to square of n. We define a new class of magic squares and present some listing of the counting carried out over two years.

INTRODUCTION: Minimally-invasive robotic surgery benefits the surgeon with increased dexterity and precision, more comfortable seating, and depth perception. Indeed, the stereo-endoscopic camera of the daVinci robot provides the surgeon with a high-resolution 3D view of the surgical scene inside the patient body. To leverage this depth information using advanced computational tools (such as augmented reality or collision detection), we need a fast and accurate stereo matching algorithm, which computes the disparity (pixel shift) map between left and right images. To improve this trade-off between speed and accuracy, we propose an efficient multi-scale approach that overcomes standard multi-scale limitations due to interpolation artifacts when upsampling intermediate disparity results from coarser to finer scale. METHODS: Standard stereo matching algorithms perform an exhaustive search of the most similar patch between the reference and target images (along the same horizontal line when images are rectified). This requires a wide search range in the target image to ensure finding the corresponding pixel in the reference image (Figure 1). To optimize this search, we propose a multi-scale approach that uses the disparity map resulting from previous iteration at lower resolution. Instead of directly using the pixel position in the reference image to place the search region in the target image, we shift it by the corresponding disparity value from previous iteration and reduce the width of the search region as it is expected to be closer to the optimal solution. We also add two additional search regions shifted by disparity values at left and right adjacent pixel positions (Figure 2) to avoid errors typically related to interpolation artifacts when resizing disparity map. To avoid important overlaps between different search regions, we only add them where the disparity map has strong gradients. MATERIAL: We used stereo images from the Middlebury dataset (http://vision.middlebury.edu/stereo/data/) and stereo-endoscopic images captured at full HD 1080i resolution using a daVinci S/Si HD Surgical System. Experiments were performed with a GPU implementation on a workstation with 128GB RAM, an Intel Xeon Processor E5-2690, and an NVIDIA Tesla C2075. RESULTS: We compared the accuracy and speed between standard and proposed methods using ten images from the Middlebury dataset that has the advantage to provide ground truth disparity maps. We used the sum of square difference (SSD) as a similarity metric between patches of size 3x3 in left and right rectified images, resized to half their original size (665x555). For the standard method, we set the search range offset and width to respectively -25 and 64 pixels. For the proposed method, we initialize the disparity to 0 followed by five iterations with a search range width of 16. Results in Table 1 show that we managed to improve the average accuracy by 27% without affecting the average computation time of 120ms. CONCLUSION: We proposed an efficient multi-scale stereo matching algorithm that significantly improves accuracy without compromising speed. In future work, we will investigate the benefits of a similar approach using temporal consistency between successive frames and its use in more advanced computational tools for image-guided surgery.

The magnetizing characteristic of a Self Excited Induction Generator (SEIG) defines relationship between its magnetizing reactance and air-gap voltage. The characteristic is essential for steady state, dynamic or transient analysis of SEIGs as the magnetizing inductance is the main factor responsible for voltage build-up and its stabilization in these machines. In order to obtain essential data to get this characteristic the induction machine is subjected to synchronous speed test. The data yielded by this test can be utilised to extract complete magnetizing behaviour of the test machine. In this paper a detailed study is carried out on a single phase induction machine to obtain its magnetizing characteristic. The procedure of performing synchronous speed test to record necessary data has been explained in detail along with relevant expressions for the calculation of different parameters. The magnetizing characteristic for the investigated machine is reported in the paper.

GRAPE-X processor is an experimental processor chip designed to achieve extremely high performance per watt. It was made using TSMC's 28 nm technology, and has achieved 30 Gflops/W. This number is three times higher than the performance of best GPGPU cards announced so far, using the same 28 nm technology. The power consumption has been the main factor which limits the performance improvement of HPC systems. This is because of the break of the so-called CMOS scaling law. Until early 2000's, or when the design rule of the silicon device was larger than 130nm, shrinking the transistor size by a factor of two results in: for times more transistors, two times higher clock frequency, half the supply voltage, and the same power consumption. Thus, one could achieve 8x performance improvement. However, with transistors smaller than 130nm design rules, it has become difficult to reduce the supply voltage, resulting in only a factor-of-two performance improvement for the same power consumption. As a result, reduction in the power consumption of the processor, when it is fully in operation, has become the most important issue. In addition, it has also become important to achieve high parallel efficiency on relatively small-sized problems. With large parallel machines, high peak performance is realized, but that peak performance is in many cases not so useful, since it is achieved only for unrealistically large problems. For the problems of practical interest, the efficiencies of large scale parallel machines are sometimes surprisingly low. In order to achieve high performance-per-watt and high parallel efficiency on small problems, we developed a highly streamlined processor architecture. In order to reduce the communication overhead and improve parallel efficiency, we adopted an SIMD architecture. To reduce the power consumption, we adopted the distributed-memory-on-chip architecture, in which each of SIMD processor core has its own main memory. Based on the GRAPE-X architecture, an exa-flops (10^18 flops) system with the power consumption less than 50 MW will be possible in 2018-2019 time-frame. For many real applications including those in the cyber security area, which requires 10TB or less memory, a parallel system based on our GRAPE-X architecture will provide the highest parallel efficiency and the shortest time to the solution at the same time. Oral presentation is preferred