Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.     

How to present more readable text for people with dyslexia

The presentation of a text has a significant effect on the reading speed of people with dyslexia. This paper presents a set of recommendations to customize texts on a computer screen in a more accessible way for this target group. This set is based on an eye tracking study with 92 people, 46 with dyslexia and 46 as control group, where the reading performance of the participants was measured . The following parameters were studied: color combinations for the font and the screen background, font size, column width as well as character, line and paragraph spacings. It was found that larger text and larger character spacings lead the participants with and without dyslexia to read significantly faster . The study is complemented with questionnaires to obtain the participants’ preferences for each of these parameters, finding other significant effects. These results provide evidence that people with dyslexia may benefit from specific text presentation parameters that make text on a screen more readable. So far, these recommendations based on eye tracking data are the most complete for people with dyslexia.     

On the performance of high-gain observers with gain adaptation under measurement noise

We address the problem of state observation for a system whose dynamics may involve poorly known, perhaps even nonlocally Lipschitz functions and whose output measurement may be corrupted by noise. It is known that one way to cope with all these uncertainties and noise is to use a high-gain observer with a gain adapted on-line. The proposed method, while presented for a particular case, relies on a “generic” analysis tool based on the study of differential inequalities involving quadratic functions of the error system in two coordinate frames plus the gain adaptation law. We establish that, for bounded system solutions, the estimated state and the gain are bounded. Moreover, we provide an upper bound for the mean value of the error signals as a function of the observer parameters. Since due to perturbations the gain adaptation law may drive the observer/plant interconnection to nearby boundary of its stability region, oscillatory behavior may emerge. To overcome this issue, we suggest an adaptive procedure based on a space averaging technique involving several copies of the observer.     

On singular perturbations due to fast actuators in hybrid control systems

A stability result is given for hybrid control systems singularly perturbed by fast but continuous actuators. If a hybrid control system has a compact set globally asymptotically stable when the actuator dynamics are omitted, or equivalently, are infinitely fast, then the same compact set is semiglobally practically asymptotically stable in the finite speed of the actuator dynamics. This result, which generalizes classical results for differential equations, justifies using a simplified plant model that ignores fast but continuous actuator dynamics, even when using a hybrid feedback control algorithm.     

Hierarchical type-2 neuro-fuzzy BSP model

This paper presents a novel hybrid interval type-2 neuro-fuzzy inference system, with automatic learning of all its parameters, to handle uncertainty. This new model, called hierarchical type-2 neuro-fuzzy BSP model (T2-HNFB), combines the paradigms of the type-2 fuzzy inference systems and neural networks with recursive partitioning techniques (binary space partitioning - BSP). The model is able to automatically create and expand its own structure, to reduce limitations on the number of inputs and to extract fuzzy linguistic rules from a dataset, as well as to efficiently model and manipulate most types of uncertainty existing in real situations. In addition, it provides an interval for its output, which can be regarded as a measure of uncertainty and constitutes important information for real applications. In this context, this model overcomes the limitations of the conventional type-2 and type-1 fuzzy inference systems. Experimental results show that the results provided by the T2-HNFB model are close to and in several cases better than the best results supplied by the other models used for comparison.     

A PC-based architecture for parameter analysis of vector-controlled induction motor drive

In this article a methodology for constructing a user interface for system control and data acquisition of a drive which is suitable for three-phase induction motors (3?IM) is presented. The entire hardware implementation is shown, including power and digital stages. Communication between the computer and the controller is engaged in order to enhance an analysis of power quality, adjust the controller parameters for tuning the flux and speed loops, and performance of the embedded algorithm. USB and Ethernet protocols have been put into operation in the user front-end because a high speed sample frequency is required in order to guarantee the real-time operation of the whole system. A software interface is developed using LabVIEW environment enabling features not only as filtering signals of phase voltage and current but also power spectrum measurements. Vector-controlled drive is programmed on a digital signal processor (DSP) in order to ensure efficient use of energy in the power stage and proper tracking of the reference at low and high speeds.     

3D porosity prediction from seismic inversion and neural networks

In this work, we address the problem of transforming seismic reflection data into an intrinsic rock property model. Specifically, we present an application of a methodology that allows interpreters to obtain effective porosity 3D maps from post-stack 3D seismic amplitude data, using measured density and sonic well log data as constraints. In this methodology, a 3D acoustic impedance model is calculated from seismic reflection amplitudes by applying an L₁-norm sparse-spike inversion algorithm in the time domain, followed by a recursive inversion performed in the frequency domain. A 3D low-frequency impedance model is estimated by kriging interpolation of impedance values calculated from well log data. This low-frequency model is added to the inversion result which otherwise provides only a relative numerical scale. To convert acoustic impedance into a single reservoir property, a feed-forward Neural Network (NN) is trained, validated and tested using gamma-ray and acoustic impedance values observed at the well log positions as input and effective porosity values as target. The trained NN is then applied for the whole reservoir volume in order to obtain a 3D effective porosity model. While the particular conclusions drawn from the results obtained in this work cannot be generalized, such results suggest that this workflow can be applied successfully as an aid in reservoir characterization, especially when there is a strong non-linear relationship between effective porosity and acoustic impedance.     

A Secure Grid Medical Data Manager Interfaced to the gLite Middleware

The medical community is producing and manipulating a tremendous volume of digital data for which computerized archiving, processing and analysis is needed. Grid infrastructures are promising for dealing with challenges arising in computerized medicine but the manipulation of medical data on such infrastructures faces both the problem of interconnecting medical information systems to Grid middlewares and of preserving patients’ privacy in a wide and distributed multi-user system. These constraints are often limiting the use of Grids for manipulating sensitive medical data. This paper describes our design of a medical data management system taking advantage of the advanced gLite data management services, developed in the context of the EGEE project, to fulfill the stringent needs of the medical community. It ensures medical data protection through strict data access control, anonymization and encryption. The multi-level access control provides the flexibility needed for implementing complex medical use-cases. Data anonymization prevents the exposure of most sensitive data to unauthorized users, and data encryption guarantees data protection even when it is stored at remote sites. Moreover, the developed prototype provides a Grid storage resource manager (SRM) interface to standard medical DICOM servers thereby enabling transparent access to medical data without interfering with medical practice.     

Simple multichannel system for the measurement of the net water flux across biological tissues

This paper describes the development of a simple system for measurement of net water movement through biological membrane barriers. The system is based on the detection of a water meniscus inside a polyethylene tube, which reflects the water movement inside one hemichamber of a modified Ussing chamber containing a membrane barrier. The detection device consists of a commercial computer-controlled flat bed scanner and specifically developed software. This system allows one to perform a relatively high number of individual experiments per physical unit. It is a flexible and affordable device, which allows comparatively more information per unit to be obtained than previously described methods.     

A wavelet-VQ system for real-time video compression

This paper presents a scheme and its Field Programmable Gate Array (FPGA) implementation for a system based on combining the bi-dimensional discrete wavelet transformation (2D-DWT) and vector quantization (VQ) for image compression. The 2D-DWT works in a non-separable fashion using a parallel filter structure with distributed control to compute two resolution levels. The wavelet coefficients of the higher frequency sub-bands are vector quantized using multi-resolution codebook and those of the lower frequency sub-band at level two are scalar quantized and entropy encoded. VQ is carried out by self organizing feature map (SOFM) neural nets working at the recall phase. Codebooks are quickly generated off-line using the same nets functioning at the training phase. The complete system, including the 2D-DWT, the multi-resolution codebook VQ, and the statistical encoder, was implemented on a Xilinx Virtex 4 FPGA and is capable of performing real-time compression for digital video when dealing with grayscale 512 × 512 pixels images. It offers high compression quality (PSNR values around 35 dB) and acceptable compression rate values (0.62 bpp).