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In this paper, a novel spatial error concealment (EC) algorithm is proposed. Under the sequential recovery framework, pixels in missing blocks are successively reconstructed based on adaptive linear predictor. The predictor automatically tunes its order and support shape according to local contexts. The predictor order and support shape are determined using Bayesian information criterion, which is...
Context Management Framework (CMF) for Ubiquitous Health (U-Health) Systems should be able to continuously gather raw data from observed entities to characterize their current situation (context). However, the death of battery-dependent sensors reduce their ability for detecting the context, which directly affects the availability of context-aware u-health services. This paper proposes the use of...
On-board data compression is a critical task that has to be carried out with restricted computational resources for remote sensing applications. This paper proposes an improved algorithm for onboard lossless compression of hyperspectral images, which combines low encoding complexity and high-performance. This algorithm is based on hybrid prediction. In the proposed work, the decorrelation stage reinforces...
MODIS data is increasingly important for oceanographic, terrestrial, and atmospheric science observation. Because of the high data rate, the loss less data compression becomes vital for MODIS data transmission and storage. In this paper we present a new approach for loss less compression of MODIS data based on the maximum spanning tree and 3D context prediction. First we determine the prediction sequence...
In this paper, we analyze the correlation between wavelet coefficients. In order to use both inter-band and intra-band correlation, we build context prediction model for significance and refinement bits. Combining with sign bit prediction model of JPEG2000, we propose a lossless image compression algorithm. Compression experimental results show that our algorithm outperforms both JPEG2000 and JPEG-LS...
By using the remote functions of a modern IT service management system infrastructure, it is possible to analyze huge amounts of log file data from complex technical equipment. This enables a service provider to predict failures of connected equipment before they happen. The problem most providers face in this context is finding "a needle in a haystack" - the obtained amount of data turns...
This paper studies the ramp up behaviour of recommender systems that incorporate spatial relationships. Two previously proposed algorithms are compared regarding their recommendation quality in situations with only little data available. Additionally a third algorithm is proposed which can be used to improve recommendation quality during the ramp-upphase. It uses approaches from item-based recommender...
Several operations of Web-based applications are optimized with respect to the set of resources that will receive the majority of requests in the near future, namely the hot set. Unfortunately, the existing algorithms for the hot set identification do not work well for the emerging social network applications, that are characterized by quite novel features with respect to the traditional Web: highly...
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