We propose a cascaded linear model for joint Chinese word segmentation and partof- speech tagging. With a character-based perceptron as the core, combined with realvalued features such as language models, the cascaded...
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Among syntax-based translation models, the tree-based approach, which takes as input a parse tree of the source sentence, is a promising direction being faster and simpler than its string-based counterpart. However, c...
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We consider multicast communications from a single source to multiple destinations over a network of erasure channels. Linear network coding maximizes the achievable (min-cut) rate, and a distributed code assignment c...
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We consider multicast communications from a single source to multiple destinations over a network of erasure channels. Linear network coding maximizes the achievable (min-cut) rate, and a distributed code assignment can be realized by choosing codes randomly at the intermediate nodes. It is typically assumed that the coding information (combining coefficients) at each node is included in the packet overhead, and forwarded to the destination. Instead, we assume that the network coding matrix is communicated to the destinations by appending training bits to the data bits at the source. End-to-end channel coding can then be applied to the training and data either separately, or jointly, by coding across both training and information bits. Ideally, the training overhead should balance the reliability of communicating the network matrix with the reliability of data detection. We maximize data throughput as a function of the training overhead, and show how it depends on the network size, erasure probability, number of independent messages, and field size. The combination network is used to illustrate our results, and shows under what conditions throughput is limited by training overhead.
Scheduling is one of the most well-known problems in both modern service science and service operational management. On the basis of quantum swarm evolutionary method, a new technique, immune quantum swarm optimizatio...
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Scheduling is one of the most well-known problems in both modern service science and service operational management. On the basis of quantum swarm evolutionary method, a new technique, immune quantum swarm optimization (IQSO) approach is proposed by redefining the immune operators, vaccinating operator and immune selecting operator, which has a powerful global exploration capability and its applications with permutation flowshop scheduling. The experimental results obtained from the proposed method on some benchmark instances show that it is very promising, compared to genetic algorithms and swarm intelligence methods.
We propose a robust hierarchical background subtraction technique which takes the spatial relations of neighboring pixels in a local region into account to detect objects in difficult conditions. Our algorithm combine...
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Grid computing is an active field in high-availability computing. This paper focuses on the numerical calculation of two-dimensional frequency selective surface using the finite difference time domain (FDTD) method on...
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Grid computing is an active field in high-availability computing. This paper focuses on the numerical calculation of two-dimensional frequency selective surface using the finite difference time domain (FDTD) method on grid-enabled cluster. The result of experiment shows that the evaluation via the parallel FDTD is in good agreement with the result obtained via the traditional FDTD method. The parallel FDTD algorithm is correct and reasonable, which can be extended to other periodic structure and finite exciting sources.
The problem addressed in this paper is the automatic segmentation of stroke lesions on MR multi-sequences. Lesions enhance differently depending on the MR modality and there is an obvious gain in trying to account for...
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The problem addressed in this paper is the automatic segmentation of stroke lesions on MR multi-sequences. Lesions enhance differently depending on the MR modality and there is an obvious gain in trying to account for various sources of information in a single procedure. To this aim, we propose a multimodal Markov random field model which includes all MR modalities simultaneously. The results of the multimodal method proposed are compared with those obtained with a mono-dimensional segmentation applied on each MRI sequence separately. We constructed an Atlas of blood supply territories to help clinicians in the determination of stroke subtypes and potential functional deficit.
While direct association rules are dedicated to describe the direct correlations among the items in a frequent itemset, indirect association rules are dedicated to describe the indirect correlations between the two it...
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While direct association rules are dedicated to describe the direct correlations among the items in a frequent itemset, indirect association rules are dedicated to describe the indirect correlations between the two items in a infrequent itemset. All the existing research works about indirect association rules are focused on improving the efficiency of mining algorithm for indirect association rules. Like incremental updating algorithm is important for mining association rules, incremental updating algorithm is also important for mining indirect association rules. In this paper, we put forward an incremental updating algorithm for mining indirect association rules to deal with the maintenance of discovered indirect association rules resulted from the change of the minimum support. The main idea is to re-utilize the results acquired in process with the old minimum support.
This paper describes the ECESS evaluation campaign of voice activity and voicing detection. Standard VAD classifies signal into speech and non-speech, we extend it to VAD+ so that it classifies a signal as a sequence ...
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Reliable signals are the basic prerequisite for most mobile ECG monitoring applications. Especially when signals are analyzed automatically, capable motion artifact detection algorithms are of great importance. This a...
Reliable signals are the basic prerequisite for most mobile ECG monitoring applications. Especially when signals are analyzed automatically, capable motion artifact detection algorithms are of great importance. This article presents different artifact detection algorithms for ECG systems with dry electrodes. The algorithms are based on the measurement of additional parameters that are correlated with the artifacts. We describe a mobile measurement system and the procedure used for the evaluation of these algorithms. The algorithms are assessed based upon their effect on QRS detection. The best algorithm improved sensitivity (Se) from 98.7% to 99.8% and positive predictive value (+P) from 98.3% to 99.9%, while 15% of the signal was marked as artifact. This corresponds to a decrease in false positive and false negative detected beats by 89.9%. Different metrics to evaluate the performance of an artifact detection algorithm are presented.
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