Efficient unbalanced merge-sort

Sorting algorithms based on successive merging of ordered subsequences are widely used, due to their efficiency and to their intrinsically parallelizable structure. Among them, the merge-sort algorithm emerges indisputably as the most prominent method. In this paper we present a variant of merge-sort that proceeds through arbitrary merges between pairs of quasi-ordered subsequences, no matter which their size may be. We provide a detailed analysis, showing that a set of n elements can be sorted by performing at most n⌊logn⌋ key comparisons. Our method has the same optimal asymptotic time and space complexity as compared to previous known unbalanced merge-sort algorithms, but experimental results show that it behaves significantly better in practice.     

Antioxidant power quantification of decoction and cold infusions of Hibiscus sabdariffa flowers

In this paper the overall antioxidant power, expressed as Briggs–Rauscher antioxidant index, of decoction or cold infusions of dried Hibiscus sabdariffa flowers was determined at 25 and 37 °C, to compare the scavenger ability of the beverages at either room or physiological temperature. Total polyphenol contents and the absorbance of anthocyanin pigments were also determined, and the trend with the overall antioxidant capability is considered. Combined photometric and pH-metric titrations were acquired to obtain information on the colour-total acidity relationship of the product. The results show that the decoction preparation protocol provides karkadè with the highest nutritional value and that the polyphenol content can account for the antioxidant capability of H. sabdariffa-based beverages. Moreover, a quantitative relationship between acid–base and redox chemistry was found. The H. sabdariffa-based drinks can be considered as protective beverages and a regular consumption of karkadè might be proposed to ensure protection against free radicals.     

A test generation program for sequential circuits

This article presents an automatic test pattern generation system based on both algebraic and topological techniques. Circuit partitioning, testability measures, 9-valued functions, pruning heuristics, and interactive fault simulation are employed to increase the performance of a modified version of the sequential D-Algorithm. Test generation results for someIscas'89 circuits are presented.Enrico Macii is also with Politecnico di Torino, Dip. di Automatica e Informatica, Torino, Italy 10129.     

Variance decomposition-based sensitivity analysis via neural networks

This paper illustrates a method for efficiently performing multiparametric sensitivity analyses of the reliability model of a given system. These analyses are of great importance for the identification of critical components in highly hazardous plants, such as the nuclear or chemical ones, thus providing significant insights for their risk-based design and management. The technique used to quantify the importance of a component parameter with respect to the system model is based on a classical decomposition of the variance. When the model of the system is realistically complicated (e.g. by aging, stand-by, maintenance, etc.), its analytical evaluation soon becomes impractical and one is better off resorting to Monte Carlo simulation techniques which, however, could be computationally burdensome. Therefore, since the variance decomposition method requires a large number of system evaluations, each one to be performed by Monte Carlo, the need arises for possibly substituting the Monte Carlo simulation model with a fast, approximated, algorithm. Here we investigate an approach which makes use of neural networks appropriately trained on the results of a Monte Carlo system reliability/availability evaluation to quickly provide with reasonable approximation, the values of the quantities of interest for the sensitivity analyses. The work was a joint effort between the Department of Nuclear Engineering of the Polytechnic of Milan, Italy, and the Institute for Systems, Informatics and Safety, Nuclear Safety Unit of the Joint Research Centre in Ispra, Italy which sponsored the project.     

Methodology for estimating saving of primary energy with membrane operations in industrial processes

Membrane separation processes can realize significant savings of direct energy (e.g., oil, gas, coal) and indirect energy (intrinsically contained in the materials recovered and/or recycled). The methodology of the energy analysis in various industrial cycles is described, and the benefits of these operations, based principally on electrical energy consumption, are evaluated using the definition of “substitution coefficient” (primary energy saved vs. 1 kWh of electrical energy consumed). The industrial sectors where this methodology has been applied are: textile (recycle of water, dyes and chemicals); polymer manufacturing (recycle of caprolactame and water); the tanning industry (recycle of sulfides and protein recovery), the dairy industry (saving of thermal energy and recovery of fat substances); and tomato and orange juice concentration (saving of thermal energy). The analyses show very interesting values for the substitution coefficients confirming the convenience of membrane operations from an energetic viewpoint.     

Multiscale Analysis of Stock Index Return Volatility

We present a study where wavelet approximation techniques and some relatedcomputational algorithms are applied to non-stationary high frequencyfinancial timesseries. Wavelets represent a novel instrument as far as concernedapplications in the finance setting, but have a great relevance in manydomains, from physics to statistics. Thus, while one goal of the paper isto compare the numerical performance of global and local function optimizers,another goal is to try to show that ad hoc wavelet-based functiondictionaries are very useful for financial modeling through signaldecomposition and approximation. Detecting the latent dependence featureswhich are typically found in high frequency financial returns is particularlyimportant for the scope of proposing models which are able to achievereliable results in parameter estimation and pointwise function prediction.We show that by pre-processing data with wavelet dictionaries we effectivelyaccount for hidden periodic components, whose discovery allows to attain andimprove the feature extraction power. We refer to sparse approximationthrough the Matching Pursuit algorithm, thus handling the negative effects ofcovariance non-stationarity at very high frequencies.     

Carrier phase synchronization for GMSK signals

Several carrier phase recovery schemes for Gaussian minimum shift keying (GMSK) modulated signals are derived and analysed in terms of squaring loss and acquisition time. Two bandwidths are considered for the GMSK signal: BT_b=0.5 and 0.25, following the recommendations of the Consultative Committee for Space Data Systems. Pre‐encoding is assumed to remove the inherent differential encoding of the GMSK modulations. The carrier phase recovery schemes are derived from the approximate expression of the GMSK signal as an OQPSK signal or as the superposition of two OQPSK signals maximum a posteriori/maximum likelihood phase estimation is considered, with perfect clock reference; both non‐data‐aided and decision–directed schemes are analysed. Moreover, in the case of GMSK with BT_b=0.25, an equalizer is also included in the synchronizer loop to remove inter‐symbol interference. High and low signal to noise ratio (SNR) approximations are considered to simplify the structure of the synchronizers. It is shown that, for the considered BT_b values, the complex synchronizers initially derived do not provide any improvements over their simplified versions; the introduction of the equalizer for GMSK with BT_b=0.25 leads to a better performance. Moreover, it is shown that GMSK with BT_b=0.5 has a better performance than unfiltered OQPSK, which is better than GMSK with BT_b=0.25. The SNR values above which the high SNR approximation turns out to be convenient with respect to the low SNR approximation are also given. Copyright © 2002 John Wiley & Sons, Ltd.     

Impact of interpretation on associative freedom.

70 hrs from the psychoanalytic case of Mrs. C, covering the full course of treatment, were scored for associative freedom, number of interventions, and a variety of clinical phenomena (e.g., clarifications, interpretations, different forms of resistance, transference manifestations). Associative freedom significantly increased over the course of treatment and was significantly related to the number of analyst interventions per hour. The relationship was particularly strong in the latter stages of treatment. Three specific types of interventions were found to increase associative freedom in the latter stages of treatment. The effect of each type was found to influence both the session containing the interpretation and the next 3 sessions. This carryover effect was specific to the latter stages of the analysis. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A model to design and optimize multi-energy systems in buildings at the design concept stage

Increasing interest is currently being addressed to multi-energy systems in buildings. These systems integrate different energy sources, at least one of which is renewable, in order to cover the thermal and electrical loads of a building. Since the design and operation of such systems are very complicated for many reasons (e.g. the intermittent nature of the renewable sources, the highly interlinked system layouts), it is of the foremost importance to provide tools to help select the best system configuration and energy sources mix.A modelling approach to multi-energy systems in buildings, based on the energy hub concept is presented in this work. This approach allows the coupling between the energy demand and the energy supply in a building to be modelled in a synthetic way. The model was customised to be used at the concept stage of the building design, either as a system simulation tool or as a system selection tool. If the prices and the characteristics of the energy converters and of the energy-wares are known, it is possible, with a certain set of constraints, to determine the configuration that minimises the initial investment costs, the use of non-renewable sources or the life-cycle costs. This approach makes it possible to avoid the simulation and ranking of a set of different system configurations, and also permits the study of the behaviour of such systems in an open configuration and not as individual systems. An application of the methodology to a case study is provided.