Combining intensional with extensional query evaluation in tuple independent probabilistic databases

In this paper, we prove that a query plan is safe in tuple independent probabilistic databases if and only if its every answer tuple is tree structured in probabilistic graphical models. We classify hierarchical queries into core and non-core hierarchical queries and show that the existing methods can only generate safe plans for core hierarchical queries. Inspired by the bucket elimination framework, we give the sufficient and necessary conditions for the answer relation of every candidate sub-query to be used as a base relation. Finally, the proposed algorithm generates safe plans for extensional query evaluation on non-boolean hierarchical queries and invokes the SPROUT algorithm [24] for intensional query evaluation on boolean queries. A case study on the TPC-H benchmark reveals that the safe plans of Q7 and Q8 can be evaluated efficiently. Furthermore, extensive experiments show that safe plans generated by the proposed algorithm scale well.     

An approximate duplicate elimination in RFID data streams

The RFID technology has been applied to a wide range of areas since it does not require contact in detecting RFID tags. However, due to the multiple readings in many cases in detecting an RFID tag and the deployment of multiple readers, RFID data contains many duplicates. Since RFID data is generated in a streaming fashion, it is difficult to remove duplicates in one pass with limited memory. We propose one pass approximate methods based on Bloom Filters using a small amount of memory. We first devise Time Bloom Filters as a simple extension to Bloom Filters. We then propose Time Interval Bloom Filters to reduce errors. Time Interval Bloom Filters need more space than Time Bloom Filters. We propose a method to reduce space for Time Interval Bloom Filters. Since Time Bloom Filters and Time Interval Bloom Filters are based on Bloom Filters, they do not produce false negative errors. Experimental results show that our approaches can effectively remove duplicates in RFID data streams in one pass with a small amount of memory.     

Corrected upper bounds for free-cut elimination

Free-cut elimination allows cut elimination to be carried out in the presence of non-logical axioms. Formulas in a proof are anchored provided they originate in a non-logical axiom or non-logical inference. This paper corrects and strengthens earlier upper bounds on the size of free-cut elimination. The correction requires that the notion of a free cut be modified so that a cut formula is anchored provided that all of its introductions are anchored, instead of only requiring that one of its introductions is anchored. With the correction, the originally proved size upper bounds remain unchanged. These results also apply to partial cut elimination. We also apply these bounds to elimination of cuts in propositional logic.If the non-logical inferences are closed under cut and infer only atomic formulas, then all cuts can be eliminated. This extends earlier results of Takeuti and of Negri and von Plato.     

Image reconstruction from in-line Fresnel holograms by using coherent background elimination

Image reconstruction from in-line Fresnel holograms by eliminating a coherent background is studied by computer simulation. The coherent background is calculated by averaging an intensity of a recorded hologram. The quality of the reconstructed image is measured by using a ratio of peak signal to noise. In comparison with the conventional reconstruction method, the results show that the background elimination can improve significantly the quality of the reconstructed images. The text was submitted by the authors in English.     

Efficient Sequence Alignment with Side-Constraints by Cluster Tree Elimination

Aligning DNA and protein sequences is a core technique in molecular biology. Often, it is desirable to include partial prior knowledge and conditions in an alignment. Going beyond prior work, we aim at the integration of such side constraints in free combination into alignment algorithms. The most common and successful technique for efficient alignment algorithms is dynamic programming (DP). However, a weakness of DP is that one cannot include additional constraints without specifically tailoring a new DP algorithm. Here, we discuss a declarative approach that is based on constraint techniques and show how it can be extended by formulating additional knowledge as constraints. We take special care to obtain the efficiency of DP for sequence alignment. This is achieved by careful modeling and applying proper solving strategies. Finally, we apply our method to the scanning for RNA motifs in large sequences. This case study demonstrates how the new approach can be used in real biological problems. A prototypic implementation of the method is available at .     

Fraction-free matrix factors: new forms for LU and QR factors

Gaussian elimination and LU factoring have been greatly studied from the algorithmic point of view, but much less from the point view of the best output format. In this paper, we give new output formats for fraction free LU factoring and for QR factoring. The formats and the algorithms used to obtain them are valid for any matrix system in which the entries are taken from an integral domain, not just for integer matrix systems. After discussing the new output format of LU factoring, the complexity analysis for the fraction free algorithm and fraction free output is given. Our new output format contains smaller entries than previously suggested forms, and it avoids the gcd computations required by some other partially fraction free computations. As applications of our fraction free algorithm and format, we demonstrate how to construct a fraction free QR factorization and how to solve linear systems within a given domain.     

计算对称带状矩阵特征值问题的并行二分／多分法

文中提出了在分布式环境下并行求解对称带状矩阵特征值问题的并行二分．多分法及其改进,该算法利用变形高斯消去法计算对称带状矩阵的Sturm序列,并利用Rayleigh商迭代对二分／多分法加以改进,在算法的并行执行过程中,各处理机间不需通信,特别适用在分布式环境下的并行计算,最后给出了数值实验结果。     

An Efficient Output-Size Sensitive Parallel Algorithm for Hidden-Surface Removal for Terrains

We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log ⁴ n) steps on the CREW PRAM model with a work bound of O((n+k) \polylog ( n)) where n and k are the input and output sizes, respectively. In order to achieve the work bound we use a number of techniques, among which our use of persistent data structures is somewhat novel in the context of parallel algorithms. Received July 29, 1998; revised October 5, 1999.     

Elimination of Boolean variables for probabilistic coherence

 In this paper we deal with the computational complexity problem of checking the coherence of a partial probability assessment (called CPA). The CPA problem, like its analogous PSAT, is NP-complete so we look for an heuristic procedure to make tractable reasonable instances of the problem. Starting from the characteristic feature of de Finetti's approach (i.e. the explicit distinction between the probabilistic assessment and the logical relations among the sentences) we introduce several rules for a sequential “elimination” of Boolean variables from the domain of the assessment. The procedure resembles the well-known Davis-Putnam rules for the satisfiability, however we have, as a drawback, the introduction of constraints (among real variables) whose satisfiability must be checked. In simple examples we test the efficiency of the procedure respect to the “traditional” approach of solving a linear system with a huge coefficient matrix built from the atoms generated by the domain of the assessment.