Site and query scheduling policies in multicomputer databasesystems

We study run-time issues, such as site allocation and query scheduling policies, in executing read-only queries in a hierarchical, distributed memory, multicomputer system. The particular architecture considered is based on the hypercube interconnection. The data are stored in a base cube, which is controlled by a control cube and host node hierarchy. Input query trees are transformed into operation sequence trees, and the operation sequences become the units of scheduling. These sequences are scheduled dynamically at run-time. Algorithms for dynamic site allocation are provided. Several query scheduling policies that support interquery concurrency are also studied. Average query completion times and initiation delays are obtained for the various policies using simulations     

Partial indexing for nonuniform data distributions in relationalDBMS's

It is well known that the effectiveness of relational database systems is greatly dependent on the efficiency of the data access strategies. For this reason, much work has been devoted to the development of new access techniques, supported by adequate access structures such as the B⁺trees. The effectiveness of the B ⁺tree also depends on the data distribution characteristics; in particular, poor performance results when the data show strong key value distribution unbalancing. The aim of this paper is to present the partial index: a new access structure that is useful in such cases of unbalancing, as an alternative to the B⁺tree unclustered indexes. The access structures are built in the physical design phase, and at execution (or compilation) time, the optimizer chooses the most efficient access path. Thus, integration of the partial indexing technique in the design and in the optimization process are also described     

Evaluation of a parallel branch-and-bound algorithm on a class ofmultiprocessors

We propose and evaluate a parallel “decomposite best-first” search branch-and-bound algorithm (dbs) for MIN-based multiprocessor systems. We start with a new probabilistic model to estimate the number of evaluated nodes for a serial best-first search branch-and-bound algorithm. This analysis is used in predicting the parallel algorithm speed-up. The proposed algorithm initially decomposes a problem into N subproblems, where N is the number of processors available in a multiprocessor. Afterwards, each processor executes the serial best-first search to find a local feasible solution. Local solutions are broadcasted through the network to compute the final solution. A conflict-free mapping scheme, known as the step-by-step spread, is used for subproblem distribution on the MIN. A speedup expression for the parallel algorithm is then derived using the serial best-first search node evaluation model. Our analysis considers both computation and communication overheads for providing realistic speed-up. Communication modeling is also extended for the parallel global best-first search technique. All the analytical results are validated via simulation. For large systems, when communication overhead is taken into consideration, it is observed that the parallel decomposite best-first search algorithm provides better speed-up compared to other reported schemes     

Comments on “Can backpropagation error surface not have localminima?”

in the above paper Yu (IEEE Trans. Neural Networks, vol.3, no.6, p.1019-21 (1992)) claims to prove that local minima do not exist in the error surface of backpropagation networks being trained on data with t distinct input patterns when the network is capable of exactly representing arbitrary mappings on t input patterns. The commenter points out that the proof presented is flawed, so that the resulting claims remain unproved. In reply, Yu points out that the undesired phenomenon that was sited can be avoided by simply imposing the arbitrary mapping capacity of the network on lemma 1 in the article.     

Hierarchical models for analysis and recognition of handwritten characters

Different hierarchical models in pattern analysis and recognition are proposed, based on occurrence probability of patterns. As an important application of recognizing handprinted characters, three typical kinds of hierarchical models such asM _89-89,M _89-36 andM _36-36 have been presented, accompanied by the computer algorithms for computing recognition rates of pattern parts. Moreover, a comparative study of their recognition rates has been conducted theoretically; and numerical experiments have been carried out to verify the analytical conclusions made. Various hierarchical models deliberated in this paper can provide users more or better choices of pattern models in practical application, and lead to a uniform computational scheme (or code). The recognition rates of parts can be improved remarkably by a suitable hierarchical model. For the modelM _89-36 in which case some of the Canadian standard handprinted characters have multiple occurrence probabilities, the total mean recognition rates of the given sample may reach 120% of that by the model proposed by Li et al., and 156% of that obtained from the subjective experiments reported by Suen.     

First break refraction event picking using fuzzy logic systems

First break picking is a pattern recognition problem in seismic signal processing, one that requires much human effort and is difficult to automate. The authors' goal is to reduce the manual effort in the picking process and accurately perform the picking. Feedforward neural network first break pickers have been developed using backpropagation training algorithms applied either to an encoded version of the raw data or to derived seismic attributes which are extracted from the raw data. The authors summarize a study in which they applied a backpropagation fuzzy logic system (BPFLS) to first break picking. The authors use derived seismic attributes as features, and take lateral variations into account by using the distance to a piecewise linear guiding function as a new feature. Experimental results indicate that the BPFLS achieves about the same picking accuracy as a feedforward neural network that is also trained using a backpropagation algorithm; however, the BPFLS is trained in a much shorter time, because there is a systematic way in which the initial parameters of the BPFLS can be chosen, versus the random way in which the weights of the neural network are chosen     

Effects of citrate on the different phases of calcium oxalate crystallization

Urinary citrate appears to be an important factor in the crystallization process of calcium oxalate and calcium phosphate. The urinary excretion of citrate was found to be significantly lower in patients with calcium oxalate stone disease as compared with normal subjects, and about 30 per cent of the calcium stone formers can be considered as hypocitraturic. The lowest excretion of citrate was recorded in urine collected during the night. Citrate has significant effects on supersaturation with respect to both calcium oxalate and calcium phosphate, it also inhibits the growth of these crystals. In addition, citrate appears to be capable of inhibiting the aggregation of crystals composed of calcium oxalate, brushite, and hydroxyapatite. The heterogenous growth of calcium oxalate on calcium phosphate is also counteracted by citrate. As a consequence of the crucial role of citrate in these processes, stone prevention with alkaline citrate has become an attractive form of treatment in patients with recurrent stone formation. Single evening dose administration of sodium potassium citrate resulted in an of sodium potassium citrate resulted in an increased excretion of citrate, reduced levels of the calcium/citrate ratio as well as supersaturation with respect to calcium oxalate and a decreased rate of stone formation. However, conflicting results of stone preventive treatment with alkaline citrate have been reported by different groups, and long-term follow-up of patients treated in a randomized way is necessary to definitely assess the efficacy of alkaline citrate.     

Two cell-wall-associated aminopeptidases from Lactobacillus helveticus and the purification and characterization of APII from strain ITGL1

Lactobacillus helveticus ITGL1 is able to hydrolyse many amino-acyl and dipeptidyl-p-nitroanilides. Analysis of heat inactivation kinetics, metal ion and protease inhibitor effects, and the subcellular location of aminopeptidase activities in both the parental strain and mutants deficient in lysyl-p-nitroanilide hydrolysis, led to the characterization of two cell-wall-associated aminopeptidases, APII and APIV. APII, which catalysed L-lysine p-nitroanilide hydrolysis, was purified about 28-fold to homogeneity from cell-wall extracts of L. helveticus ITGL1 and characterized. The purified enzyme appeared to be monomeric, with a molecular mass of 97 kDa. Aminopeptidase activity was greatest at pH 6.5 and 50 degrees C. APII was completely inhibited by bestatin, chelating agents such as EDTA or 1,10-phenanthroline and the divalent cations Zn2+ and Cu2+. The activity of the EDTA-treated enzyme was restored by Co2+, Ca2+ or Mn2+. Although APII was able to degrade several dipeptides and tripeptides with hydrophobic N-terminal amino acid (Leu, Ala), it was inactive on peptides containing Pro or Gly, and may thus contribute to the development of cheese flavour by processing bitter peptides.     

Analytical formulae for calculating stresses in unidirectional/cross-ply unbalanced laminates

A multilayer theory has been developed for unidirectional/cross-ply unbalanced laminates subjected to surface shear tractions, using the assumption of plane strain. The analytical solution for the stress field in the laminate is obtained and it is shown that the stresses in each layer are in good agreement with the results of a three-dimensional finite element analysis. Approximate formulae for the analytical stresses are also derived for a laminate subjected to an offset distributed force at one end. The accuracy of this solution is shown by comparison with a three-dimensional finite element analysis.