987 resultados para Over sampling


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The poor performance of TCP over multi-hop wireless networks is well known. In this paper we explore to what extent network coding can help to improve the throughput performance of TCP controlled bulk transfers over a chain topology multi-hop wireless network. The nodes use a CSMA/ CA mechanism, such as IEEE 802.11’s DCF, to perform distributed packet scheduling. The reverse flowing TCP ACKs are sought to be X-ORed with forward flowing TCP data packets. We find that, without any modification to theMAC protocol, the gain from network coding is negligible. The inherent coordination problem of carrier sensing based random access in multi-hop wireless networks dominates the performance. We provide a theoretical analysis that yields a throughput bound with network coding. We then propose a distributed modification of the IEEE 802.11 DCF, based on tuning the back-off mechanism using a feedback approach. Simulation studies show that the proposed mechanism when combined with network coding, improves the performance of a TCP session by more than 100%.

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Given a parametrized n-dimensional SQL query template and a choice of query optimizer, a plan diagram is a color-coded pictorial enumeration of the execution plan choices of the optimizer over the query parameter space. These diagrams have proved to be a powerful metaphor for the analysis and redesign of modern optimizers, and are gaining currency in diverse industrial and academic institutions. However, their utility is adversely impacted by the impractically large computational overheads incurred when standard brute-force exhaustive approaches are used for producing fine-grained diagrams on high-dimensional query templates. In this paper, we investigate strategies for efficiently producing close approximations to complex plan diagrams. Our techniques are customized to the features available in the optimizer's API, ranging from the generic optimizers that provide only the optimal plan for a query, to those that also support costing of sub-optimal plans and enumerating rank-ordered lists of plans. The techniques collectively feature both random and grid sampling, as well as inference techniques based on nearest-neighbor classifiers, parametric query optimization and plan cost monotonicity. Extensive experimentation with a representative set of TPC-H and TPC-DS-based query templates on industrial-strength optimizers indicates that our techniques are capable of delivering 90% accurate diagrams while incurring less than 15% of the computational overheads of the exhaustive approach. In fact, for full-featured optimizers, we can guarantee zero error with less than 10% overheads. These approximation techniques have been implemented in the publicly available Picasso optimizer visualization tool.

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Altitude variations of the mass concentration of black carbon, number concentration of composite aerosols are examined along with the columnar spectral aerosol optical depths using state of the art instruments and the Angstrom parameters are inferred from the ground based measurements at several altitude levels, en route from Manora Peak, Nainital (similar to 1950 m above mean sea level) to a low altitude station Haldwani (similar to 330 m above mean sea level) at its foothill within an aerial distance of <10,000 m. The measurements were done during the winter months (November-February) of 2005, 2006 and 2007 under fair weather conditions. The results show a rapid decrease in all the measured parameters with increase in altitude, with >60% contribution to the AOD coming from the regions below 1000 m. The Angstrom wavelength exponent remained high in the well mixed region, and decreased above. The normalized AOD gradient was used to estimate aerosol mixing height, which was found to be in the altitude range 1000-1500 m, above which the particle concentrations are slowly varying as a function of altitude. The heating rate at the surface is found to be maximum but decreases sharply with increase in altitude. Analysis of the wavelength dependence of absorption aerosol optical depth (AAOD) showed that the aerosol absorption over the site is generally due to mixed aerosols. (C) 2011 Elsevier Ltd. All rights reserved.

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Atmospheric perturbations due to the annular solar eclipse were monitored to understand its influence on the meteorological parameters from surface to the lower stratosphere. A strong inversion at 13 km and an abnormal warming in the upper troposphere were noticed on the eclipse day. A decrease in tropopause height associated with increase in temperature caused anomalous warming. Considerable attenuation of incoming solar radiation resulted in abrupt increase of air temperature during the next 24 h followed by sharp decrease in relative humidity. The time lag is attributed to the distance from the totality and the response time between tropopause and surface layer. (C) 2011 Elsevier Ltd. All rights reserved.

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An analysis of the pressure variation over an aerofoil with integrated Shape Memory Alloy (SMA) wire is reported. A computational model based on finite elements and potential flow computation is proposed to obtain the deflections of the upper and the lower skins of the aerofoil subjected to aerodynamic pressure and hysteretic deformation of the SMA wire. The computational model couples a one-dimensional phenomenological constitutive model of SMA wire with the laminar incompressible aerodynamic pressure induced deformation of the aerofoil skins. The SMA wires are actuated by thermoelectric control system with auxiliary compensator feeding the piezoelectric stack actuators to adjust the hysteretic dynamics of the SMA wire. At each step of this coupled deformation process, the deflected/morphed shape of the aerofoil is d while recalculating to get the pressure distribution. Panel method based on incompressible and inviscid flow is employed for this purpose. The aerodynamic lift is then obtained from the pressure distributions. Numerical results on the variation of coefficient of pressure are reported.

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Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.

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The problem of intrusion detection and location identification in the presence of clutter is considered for a hexagonal sensor-node geometry. It is noted that in any practical application,for a given fixed intruder or clutter location, only a small number of neighboring sensor nodes will register a significant reading. Thus sensing may be regarded as a local phenomenon and performance is strongly dependent on the local geometry of the sensor nodes. We focus on the case when the sensor nodes form a hexagonal lattice. The optimality of the hexagonal lattice with respect to density of packing and covering and largeness of the kissing number suggest that this is the best possible arrangement from a sensor network viewpoint. The results presented here are clearly relevant when the particular sensing application permits a deterministic placement of sensors. The results also serve as a performance benchmark for the case of a random deployment of sensors. A novel feature of our analysis of the hexagonal sensor grid is a signal-space viewpoint which sheds light on achievable performance.Under this viewpoint, the problem of intruder detection is reduced to one of determining in a distributed manner, the optimal decision boundary that separates the signal spaces SI and SC associated to intruder and clutter respectively. Given the difficulty of implementing the optimal detector, we present a low-complexity distributive algorithm under which the surfaces SI and SC are separated by a wellchosen hyperplane. The algorithm is designed to be efficient in terms of communication cost by minimizing the expected number of bits transmitted by a sensor.

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We consider the problem of distributed joint source-channel coding of correlated Gaussian sources over a Gaussian Multiple Access Channel (MAC). There may be side information at the encoders and/or at the decoder. First we specialize a general result in [16] to obtain sufficient conditions for reliable transmission over a Gaussian MAC. This system does not satisfy the source channel separation. Thus, next we study and compare three joint source channel coding schemes available in literature.