Gran Crisis

La extensión y la duración de esta Gran Crisis ha adquirido tanta envergadura que sería inocente creer que tras ella las cosas seguirán siendo más o menos como antes. No sabemos con exactitud cómo será el porvenir, pero sin duda diferirá sustantivamente de este presente.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Sparsely spread CDMA - A statistical mechanics-based analysis

Sparse code division multiple access (CDMA), a variation on the standard CDMA method in which the spreading (signature) matrix contains only a relatively small number of nonzero elements, is presented and analysed using methods of statistical physics. The analysis provides results on the performance of maximum likelihood decoding for sparse spreading codes in the large system limit. We present results for both cases of regular and irregular spreading matrices for the binary additive white Gaussian noise channel (BIAWGN) with a comparison to the canonical (dense) random spreading code. © 2007 IOP Publishing Ltd

Optical types of inland and coastal waters

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions

Optical types of inland and coastal waters

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions

High-performance reconstruction of CT medical images by using out-of-core methods in GPU

Background and objective:Since Computed Tomography (CT) is one of the most widely used medical imaging tests, it is essential to work on methods that reduce the radiation the patient is exposed to. Although there are several possible approaches to achieve this, we focus on reducing the exposure time through sparse sampling. With this approach, efficient algebraic methods are needed to be able to generate the images in real time, and since their computational cost is high, using high-performance computing is essential. Methods:In this paper we present a GPU (Graphics Processing Unit) software for solving the CT image reconstruction problem using the QR factorization performed with out-of-core (OOC) techniques. This implementation is optimized to reduce the data transfer times between disk, CPU, and GPU, as well as to overlap input/output operations and computations. Results:The experimental study shows that a block cache stored on main page-locked memory is more efficient than using a cache on GPU memory or mirroring it in both GPU and CPU memory. Compared to a CPU version, this implementation is up to 6.5 times faster, providing an improved image quality when compared to other reconstruction methods. Conclusions:The software developed is an optimized version of the QR factorization for GPU that allows the algebraic reconstruction of CT images with high quality and resolution, with a performance that can be compared with state-of-the-art methods used in clinical practice. This approach allows reducing the exposure time of the patient and thus the radiation dose

Few-View CT Image reconstruction via Least-Squares Methods: assessment and optimization

The use of iterative algebraic methods applied to the reconstruction of Computed Tomography (CT) Medical Images is proliferating to reconstruct high-quality CT images using far fewer views than through analytical methods. This would imply reducing the dose of X-rays applied to patients who require this medical test. Least-squares methods are a promising approach to reconstruct the images with few projections obtaining high quality. In addition, since these techniques involve a high computational load, it is necessary to develop efficient methods that make use of high-performance computing (HPC) tools to accelerate reconstructions. In this paper, three LeastSquares methods are analyzed: LSMB (Least-Squares Model Based), LSQR (Least Squares QR) and LSMR (Least Squares Minimal Residual), to determine whether the LSMB method provides a faster convergence and thus lower computational times. Moreover, a block version of both the LSQR and LSMR methods was implemented. With them, multiple right-hand sides (multiple slices) can be solved at the same time, taking advantage of the parallelism obtained with the implementation of the methods using the Intel Math Kernel Library (MKL). The two implementations are compared in terms of convergence, time, and quality of the images obtained, reducing the number of projections and combining them with a regularization and acceleration technique. The experiments show how the implementations are scalable and obtain images of good quality from a reduced number of views, being the LSQR method better suited for this application

Optical Camera Communication as an Enabling Technology for Microalgae Cultivation

International audienceOptical Camera Communication (OCC) systems have a potential application in microalgae production plants. In this work, a proof-of-concept prototype consisting of an artificial lighting photobioreactor is proposed. This reactor optimises the culture’s photosynthetic efficiency while transmitting on-off keying signals to a rolling-shutter camera. Upon reception, both signal decoding and biomass concentration sensing are performed simultaneously using image processing techniques. Moreover, the communication channel’s theoretical modelling, the data rate system’s performance, and the plant distribution requirements and restrictions for a production-scale facility are detailed. A case study is conducted to classify three different node arrangements in a real facility, considering node visibility, channel capacity, and space exploitation. Finally, several experiments comprising radiance evaluation and Signal-to-Noise Ratio (SNR) computation are performed at different angles of view in both indoor and outdoor environments. It is observed that the Lambertian-like emission patterns are affected by increasing concentrations, reducing the effective emission angles. Furthermore, significant differences in the SNR, up to 20 dB, perceived along the illuminated surface (centre versus border), gradually reduce as light is affected by greater dispersion. The experimental analysis in terms of scattering and selective wavelength attenuation for green (Arthrospira platensis) and brown (Rhodosorus marinus) microalgae species determines that the selected strain must be considered in the development of this system

Demonstration of a Sub-Pixel Outdoor Optical Camera Communication Link

International audienceOptical Camera Communication (OCC) is an Optical Wireless Communication (OWC) technology that relies on general-purpose cameras to perform not only image-related tasks but also to receive data from optical sources. In general terms, OCC has been extensively studied in indoor scenarios and can be a competent and cost-effective alternative solution for wireless data transmission in Smart Cities for medium to long links up to hundreds of meters. In this paper, the feasibility of establishing an outdoor sub-pixel communication link is demonstrated. In this experiment, single 5 mm white LED transmitters located at distances of 90 and 130 m send simultaneous optical codes to a receiver based on a commercial camera, achieving a signal-to noise ratio of 20 dB and 13 dB, respectively. This work shows that although the geometrical projection within the transmitters image is less than the pixel area, it is still possible to establish an effective communication link, with 8 bps per transmitter. At 130 m, the best performance was an error rate of 7;2 10-3, and for 90 m, no errors were detected

Wireless Sensor Networks Using Sub-Pixel Optical Camera Communications: Advances in Experimental Channel Evaluation

International audienceOptical wireless communications in outdoor scenarios are challenged by uncontrollable atmospheric conditions that impair the channel quality. In this paper, different optical camera communications (OCC) equipment are experimentally studied in the laboratory and the field, and a sub-pixel architecture is raised as a potential solution for outdoor wireless sensor networks (WSN) applications, considering its achievable data throughput, the spatial division of sources, and the ability of cameras to overcome the attenuation caused by different atmospheric conditions such as rain, turbulence and the presence of aerosols. Sub-pixel OCC shows particularly adequate capabilities for some of the WSN applications presented, also in terms of cost-effectiveness and scalability. The novel topology of sub-pixel projection of multiple transmitters over the receiver using small optical devices is presented as a solution using OCC that re-uses camera equipment for communication purposes on top of video-monitoring