336 research outputs found

    A Differential Feedback Scheme Exploiting the Temporal and Spectral Correlation

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    Channel state information (CSI) provided by limited feedback channel can be utilized to increase the system throughput. However, in multiple input multiple output (MIMO) systems, the signaling overhead realizing this CSI feedback can be quite large, while the capacity of the uplink feedback channel is typically limited. Hence, it is crucial to reduce the amount of feedback bits. Prior work on limited feedback compression commonly adopted the block fading channel model where only temporal or spectral correlation in wireless channel is considered. In this paper, we propose a differential feedback scheme with full use of the temporal and spectral correlations to reduce the feedback load. Then, the minimal differential feedback rate over MIMO doubly selective fading channel is investigated. Finally, the analysis is verified by simulations

    Feasibility study on lengthening the high-voltage cable section and reducing the number of cable joints via alternative bonding methods

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    The mesosphere is perhaps the least explored region in the atmosphere with very few methods of observing. This thesis will primarily be exploring a new technique for measuring the distribution of kinetic energy in the mesosphere across a wide range of spatial and temporal scales. The method being used relies on correlation functions between pairs of meteor measurements. These measurements are made using a network of specular meteor radars located in Northern Norway. This network produced 32 million meteor measurements over a 2 year period. The correlation function estimation method has been previously used on a smaller data set, but has so far not been used for a longer data set and at high latitudes. The main advantage of the new technique is that by studying the second order statistics of the wind field, we can obtain significantly better temporal and spatial resolution than before. Such a large data set allows for great resolution for both spatial and temporal correlation functions. By using temporal correlation functions and the kinetic energy spectrum, different atmospheric wave phenomena can be studied. These include diurnal and semi diurnal tides. The horizontal and vertical correlation functions will be used to verify that the kinetic energy follows a power law, as theoretically expected by the Kolmogorov theory for turbulence. This was done by using a second order structure function applied to correlation functions. The temporal and horizontal correlation functions were used to study the summer-winter variation in kinetic energy, some variation in the temporal domain is the impact from large scale waves as well as in the power spectra were there is a steeper power law slope during the winter. As for the horizontal domain there are differences in kinetic energy in the zonal and meridional direction for both large and small scale waves. The dataset in this thesis a lot more can be found out about the mesosphere, in this thesis only a few of the possibilities are explored. The results are in agreement with earlier work, confirming the results obtained by the earlier study

    Application of Big Data Technology in Product Quality and Safety Risk Information Monitoring

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    Product quality and safety risk monitoring with “risk management” as the core thought has been gradually introduced into the market supervision system. This paper discusses the application method of risk information collection and analysis in product quality risk monitoring through the application practice of big data technology in quality monitoring. Through the emotional analysis and judgment of the arti_x005fcle, the quality risk signal is intelligently excavated to provide technical means and monitoring methods for product quality risk monitoring

    A differential Feedback Scheme Exploiting the Temporal and Spectral Correlation

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    International audienceChannel state information (CSI) provided by limited feedback channel can be utilized to increase the system throughput. However, in multiple input multiple output (MIMO) systems, the signaling overhead realizing this CSI feedback can be quite large, while the capacity of the uplink feedback channel is typically limited. Hence, it is crucial to reduce the amount of feedback bits. Prior work on limited feedback compression commonly adopted the block fading channel model where only temporal or spectral correlation in wireless channel is considered. In this paper, we propose a differential feedback scheme with full use of the temporal and spectral correlations to reduce the feedback load. Then, the minimal differential feedback rate over MIMO time-frequency (or doubly) selective fading channel is investigated. Finally, the analysis is verified by simulation results

    Pursuer Assignment and Control Strategies in Multi-Agent Pursuit-Evasion Under Uncertainties.

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    We consider a pursuit-evasion problem with a heterogeneous team of multiple pursuers and multiple evaders. Although both the pursuers and the evaders are aware of each others' control and assignment strategies, they do not have exact information about the other type of agents' location or action. Using only noisy on-board sensors the pursuers (or evaders) make probabilistic estimation of positions of the evaders (or pursuers). Each type of agent use Markov localization to update the probability distribution of the other type. A search-based control strategy is developed for the pursuers that intrinsically takes the probability distribution of the evaders into account. Pursuers are assigned using an assignment algorithm that takes redundancy (i.e., an excess in the number of pursuers than the number of evaders) into account, such that the total or maximum estimated time to capture the evaders is minimized. In this respect we assume the pursuers to have clear advantage over the evaders. However, the objective of this work is to use assignment strategies that minimize the capture time. This assignment strategy is based on a modified Hungarian algorithm as well as a novel algorithm for determining assignment of redundant pursuers. The evaders, in order to effectively avoid the pursuers, predict the assignment based on their probabilistic knowledge of the pursuers and use a control strategy to actively move away from those pursues. Our experimental evaluation shows that the redundant assignment algorithm performs better than an alternative nearest-neighbor based assignment algorithm

    Estimation of Vegetation Latent Heat Flux over Three Forest Sites in ChinaFLUX using Satellite Microwave Vegetation Water Content Index

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    Latent heat flux (LE) and the corresponding water vapor lost from the Earth's surface to the atmosphere, which is called Evapotranspiration (ET), is one of the key processes in the water cycle and energy balance of the global climate system. Satellite remote sensing is the only feasible technique to estimate LE over a large-scale region. While most of the previous satellite LE methods are based on the optical vegetation index (VI), here we propose a microwave-VI (EDVI) based LE algorithm which can work for both day and night time, and under clear or non-raining conditions. This algorithm is totally driven by multiple-sensor satellite products of vegetation water content index, solar radiation, and cloud properties, with some aid from a reanalysis dataset. The satellite inputs and the performance of this algorithm are validated with in situ measurements at three ChinaFLUX forest sites. Our results show that the selected satellite observations can indeed serve as the inputs for the purpose of estimating ET. The instantaneous estimations of LE (LEcal) from this algorithm show strong positive temporal correlations with the in situ measured LE (LEobs) with the correlation coefficients (R) of 0.56-0.88 in the study years. The mean bias is kept within 16.0% (23.0W/m2) across the three sites. At the monthly scale, the correlations between the retrieval and the in situ measurements are further improved to an R of 0.84-0.95 and the bias is less than 14.3%. The validation results also indicate that EDVI-based LE method can produce stable LEcal under different cloudy skies with good accuracy. Being independent of any in situ measurements as inputs, this algorithm shows great potential for estimating ET under both clear and cloudy skies on a global scale for climate study

    An Updated Review of Atmospheric Mercury

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    The atmosphere is a key component of the biogeochemical cycle of mercury, acting as a reservoir, transport mechanism, and facilitator of chemical reactions. The chemical and physical behavior of atmospheric mercury determines how, when, and where emitted mercury pollution impacts ecosystems. In this review, we provide current information about what is known and what remains uncertain regarding mercury in the atmosphere. We discuss new ambient, laboratory, and theoretical information about the chemistry of mercury in various atmospheric media. We review what is known about mercury in and on solid- and liquid-phase aerosols. We present recent findings related to wet and dry deposition and spatial and temporal trends in atmospheric mercury concentrations. We also review atmospheric measurement methods that are in wide use and those that are currently under development
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