Compared with traditional magnetic disks, flash memory has many advantages and has been used as external storage media for a wide spectrum of electronic devices (such as PDA, MP3, digital camera and mobile phone). As ...
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Compared with traditional magnetic disks, flash memory has many advantages and has been used as external storage media for a wide spectrum of electronic devices (such as PDA, MP3, digital camera and mobile phone). As the capacity increases and price drops, it looks like a perfect alternative for magnetic disks. However, due to hardware limitations of flash memory, techniques including storage subsystem and indexing originally designed for magnetic disks can not run smoothly in a flash memory without any modification. In this paper we explore problems of indexing flash-resided data and present a new dynamical hash index for flash memory in two schemas. The analysis and experimental results validate the efficiency of our design.
Nowadays more and more people like to publish their comments on a product on the Web. Mining such unstructured data (product reviews) is exciting hot and challenging research and application topic. In this paper, we f...
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Nowadays more and more people like to publish their comments on a product on the Web. Mining such unstructured data (product reviews) is exciting hot and challenging research and application topic. In this paper, we focus on mining product reviews written in Chinese. We aim at extract the structural information from Chinese product reviews. By structural information, we mean product features and corresponding opinion words expressed in each review text. There are already some works done for reviews written in English, but less in Chinese. In this paper, we propose an effective method to extract candidate features and some effective pruning rules to prune the features. Also, we introduce a pattern extraction and matching step to improve our results. The experiment results show our approach is very effective, and has a good recall and precision.
To meet more and more complex recommendation needs, it is quite important to implement hybrid recommendations for mobile commerce. In this paper, we propose a design for open hybrid recommendation systems in mobile co...
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To meet more and more complex recommendation needs, it is quite important to implement hybrid recommendations for mobile commerce. In this paper, we propose a design for open hybrid recommendation systems in mobile commerce, which could integrate multiple recommendation algorithms together to improve recommendation performance. First, three solutions for an open hybrid recommendation approach are discussed in detail, which are generic customer profile, weighted hybrid recommendation algorithm, and mobile device profile creation. After that, we give out a multi-agent architecture design to make the three solutions work together. Finally a prototype system based on our proposed architecture is implemented to demonstrate the feasibility of our design and evaluate the performance of the proposed open hybrid recommendation system.
A new nonlinear compensation technique to capacitor pressure sensor (CPS) based on least square support vector regression (LSSVR) is proposed. In this technique, LSSVR is used as an inverse model of the CPS; therefore...
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A new nonlinear compensation technique to capacitor pressure sensor (CPS) based on least square support vector regression (LSSVR) is proposed. In this technique, LSSVR is used as an inverse model of the CPS; therefore, the proposed technique can automatically compensate the effect of the associated non-linearity to estimate the applied pressure. Furthermore, the flexibility of the proposed technique effectively compensates any variation of the CPS's output occurring due to change in environmental temperature. The results of actual CPS compensation experiment indicate that this LSSVR approach is a useful alternative to the existing ones. This technique would be useful for other types of sensors such as thermocouples, flow sensors, magnetometer etc., possessing similar nonlinear response characteristics. The presented method has a potential future in the field of instrumentation and measurement.
In this paper, we discuss the energy efficient multicast problem for discrete power levels in ad hoc sensor wireless networks. The problem of our concern is: given n nodes and each node v has l(v) transmission power l...
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In this paper, we discuss the energy efficient multicast problem for discrete power levels in ad hoc sensor wireless networks. The problem of our concern is: given n nodes and each node v has l(v) transmission power levels and a multicast request (s, D), how to find a multicast tree rooted at s and spanning all destinations in D such that the total energy cost of the multicast tree is minimized. This problem is NP-hard. We propose a NWM_DST algorithm which has a theoretical guaranteed approximation performance ratio, and two efficient heuristics MNJT and g-D-MIP for multicast tree problem. Simulation results have shown efficiency of our proposed algorithms.
In this paper, two criteria used to evaluate the randomness of encryption stream are turned into two objectives of Multi-objective Evolutionary Algorithm (MOEA), and a new sequence encryption producing method based on...
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In this paper, two criteria used to evaluate the randomness of encryption stream are turned into two objectives of Multi-objective Evolutionary Algorithm (MOEA), and a new sequence encryption producing method based on MOEA was proposed (called MOEASEP). Because MOEASEP was based on the randomness of evolutionary operators and the features of MOEA, the encryption streams produced by MOEASEP had good merits of high randomness, chaos and long period, which had also been demonstrated in the experiments.
To solve the problems of real-time on-line measurements of freezing point of diesel fuel, a novel method of soft sensor with near-infrared (NIR) spectrometry was proposed based on the integration of both principal com...
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To solve the problems of real-time on-line measurements of freezing point of diesel fuel, a novel method of soft sensor with near-infrared (NIR) spectrometry was proposed based on the integration of both principal component analysis (PCA) and least squares support vector machines (LS-SVM). In this method, the PCA was incorporated into the model, which not only solved the linear correlation of the input, but also simplified the LS-SVM structure and improved the training speed. Then, the soft sensor model for freezing point was established using LS-SVM regression algorithm. The model performance has been tested and the results show that the propose method is superior to the soft sensor model based on BP neural network or PCA+SVM. So it can satisfy the demand of the on-lines measurement of freezing point.
The edit distance between two given strings X and Y is the minimum number of edit operations that transform X into Y. In ordinary course, string editing is based on character insert, delete, and substitute operations....
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The edit distance between two given strings X and Y is the minimum number of edit operations that transform X into Y. In ordinary course, string editing is based on character insert, delete, and substitute operations. It has been suggested that extending this model with block edits would be useful in applications such as DNA sequence comparison and sentence similarity computation. However, the existing algorithms have generally focused on the normalized edit distance, and seldom of them consider the block swap operations at a higher level. In this paper, we introduce an extended edit distance algorithm which permits insertions, deletions, and substitutions at character level, and also permits block swap operations. Experimental results on randomly generated strings verify the algorithm's rationality and efficiency. The main contribution of this paper is that we present an algorithm to compute the lowest edit cost for string transformation with block swap in polynomial time, and propose a breaking points selection algorithm to improve the computation speed.
The land use pattern and evolution have the characteristics of multi-dimension, complication and integration, so that the traditional models based on Euclid geometry and single fractal dimension shows great limitation...
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The land use pattern and evolution have the characteristics of multi-dimension, complication and integration, so that the traditional models based on Euclid geometry and single fractal dimension shows great limitations in describing the process and pattern of urban land use structure. Therefore, a compositive fractal model, which comprised of three fractal dimensions such as the boundary dimension, the radial dimension as well as the information entropy dimension, were developed. Subsequently, an example of application research is experimented in the Ezhou town through remote sensing imagines in 1992 and 2002. It makes a conclusion that the compositive fractal model can effectively analyze the complexity, centrality and equilibrium of land use.
Ant Colony Algorithm and Genetic Algorithm (GA), two bionic-inspired optimization algorithms, have great potentials to solve the combination optimization problems, respectively used in solving traveling salesman probl...
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ISBN:
(纸本)9780769533162
Ant Colony Algorithm and Genetic Algorithm (GA), two bionic-inspired optimization algorithms, have great potentials to solve the combination optimization problems, respectively used in solving traveling salesman problem, but there are some shortcomings if only one of them is used to solve TSP. Performance comparative analysis have been done by using ACA and GA respectively in solving TSP in this paper. The experiments show the advantages and disadvantages used only ACA or GA, we can overcome the shortcomings if GA and ACA are combined to solve TSP and get faster convergent speed and more accurate results compared with only using ACA or GA.
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