Diagonalizing properties of the discrete cosine transforms

Since its introduction in 1974 by Ahmed et al., the discrete cosine transform (DCT) has become a significant tool in many areas of digital signal processing, especially in signal compression. There exist eight types of discrete cosine transforms (DCTs). We obtain the eight types of DCTs as the complete orthonormal set of eigenvectors generated by a general form of matrices in the same way as the discrete Fourier transform (DFT) can be obtained as the eigenvectors of an arbitrary circulant matrix. These matrices can be decomposed as the sum of a symmetric Toeplitz matrix plus a Hankel or close to Hankel matrix scaled by some constant factors. We also show that all the previously proposed generating matrices for the DCTs are simply particular cases of these general matrix forms. Using these matrices, we obtain, for each DCT, a class of stationary processes verifying certain conditions with respect to which the corresponding DCT has a good asymptotic behavior in the sense that it approaches Karhunen-Loeve transform performance as the block size N tends to infinity. As a particular result, we prove that the eight types of DCTs are asymptotically optimal for all finite-order Markov processes. We finally study the decorrelating power of the DCTs, obtaining expressions that show the decorrelating behavior of each DCT with respect to any stationary processes     

Scalability and robustness of parallel hyperheuristics applied to a multiobjectivised frequency assignment problem

The Frequency Assignment Problem (fap) is one of the key issues in the design of Global System for Mobile Communications (gsm) networks. The formulation of the fap used here focuses on aspects that are relevant to real gsm networks. In this paper, we adapt a parallel model to tackle a multiobjectivised version of the fap. It is a hybrid model which combines an island-based model and a hyperheuristic. The main aim of this paper is to design a strategy that facilitates the application of the current best-behaved algorithm. Specifically, our goal is to decrease the user effort required to set its parameters. At the same time, the usage of such an algorithm in parallel environments was enabled. As a result, the time required to attain high-quality solutions was decreased. We also conduct a robustness analysis of this parallel model. In this analysis we study the relationship between the migration stage of the parallel model and the quality of the resulting solutions. In addition, we also carry out a scalability study of the parallel model. In this case, we analyse the impact that the migration stage has on the scalability of the entire parallel model. Computational results with several real network instances have validated our proposed approach. The best-known frequency plans for two real-world network instances are improved with this strategy.     

An empirical analysis of ontology-based query expansion for learning resource searches using MERLOT and the Gene ontology

This paper proposes an expansion of queries based on formal domain ontologies in the context of the search for learning resources in repositories. The expansion process uses the relation types that are represented in these models; common ontological relations, and ontological relations specific to domain and traditional terminology relations, typical of thesauri. The tests were conducted using Gene ontology as the knowledge base and MERLOT is used as the test repository. The results of this study case indicate that, at similar levels of precision, expanded queries improve levels of novelty and coverage compared to the original query (without expansion), i.e. expanded queries allow the user to retrieve relevant objects, which might not be obtained without expansion.     

Androgens Upregulate Pathogen-Induced Placental Innate Immune Response

Group B Streptococcus (GBS) is a leading cause of placental infection, termed chorioamnionitis. Chorioamnionitis is associated with an increased risk of neurobehavioral impairments, such as autism spectrum disorders, which are more prominent in males than in female offspring. In a pre-clinical model of chorioamnionitis, a greater inflammatory response was observed in placenta associated with male rather than female fetuses, correlating with the severity of subsequent neurobehavioral impairments. The reason for this sex difference is not understood. Our hypothesis is that androgens upregulate the placental innate immune response in male fetuses. Lewis dams were injected daily from gestational day (G) 18 to 21 with corn oil (vehicle) or an androgen receptor antagonist (flutamide). On G 19, dams were injected with saline (control) or GBS. Maternal, fetal sera and placentas were collected for protein assays and in situ analyses. Our results showed that while flutamide alone had no effect, a decrease in placental concentration of pro-inflammatory cytokines and infiltration of polymorphonuclear cells was observed in flutamide/infected compared to vehicle/infected groups. These results show that androgens upregulate the placental innate immune response and thus may contribute to the skewed sex ratio towards males observed in several developmental impairments resulting from perinatal infection/inflammation.     

Policies to improve the local impact from hydrocarbon extraction: Observations on West Africa and possible lessons for Central Asia

The paper offers specific inputs to the debate on local content promotion in the oil industries of West Africa and Central Asia. To this end, we document the international experience with local content promotion to derive best practices in the field. We then use a case study approach to devise a simple analytical framework for rationalizing the selection of viable sectors for local content promotion, in an attempt to make operational one of the best practice principles (efficiency) developed before. By proposing specific rules regarding the acceptability of a project, the analysis seeks to add rigor and address distortions on localization outcomes from rent-seeking. The emphasis is not on supporting efforts to “pick winners” and subsidize them through a range of by and large discredited instruments. Rather, the paper focuses on the specific public inputs the government would have to provide to support an otherwise market-driven process.     

Sediment Pulse Behaviour Following Dam Removal in Gravel‐Bed Rivers

As dams approach the end of their useful life, there is need to predict where and how accumulated sediment will move following dam removal to estimate and mitigate the impacts of this process on aquatic habitat and infrastructure. Flume studies suggest that sediment pulses disperse in place for most dams, but it is hypothesized that certain conditions (e.g., low Froude number, fine pulse grain size, small pulse sizes, and large peak discharge) may characterize pulses that translate downstream. However, quantitative analyses of sediment pulse behavior have not been widely conducted in field settings. We thus analyzed bathymetric data from four field sites in Oregon to investigate the reliability of flume‐derived hypotheses (1) whether dispersion or translation dominates across a range of dam removal physiographies using multiple methods of evaluation and (2) if Froude number, pulse material grain size, relative pulse size, and discharge can predict reservoir sediment movement mode. Results indicated that dispersion generally dominated pulse behavior in the field setting, with some limited evidence of translational movement in individual years. The Froude number appeared to be the most reliable for anticipating pulse behavior. Further work is needed to link generalized sediment pulse behavior to sediment mobilization and transport processes. Copyright © 2016 John Wiley & Sons, Ltd.     

Improved Voice Activity Detection Using Contextual Multiple Hypothesis Testing for Robust Speech Recognition

This paper shows an improved statistical test for voice activity detection in noise adverse environments. The method is based on a revised contextual likelihood ratio test (LRT) defined over a multiple observation window. The motivations for revising the original multiple observation LRT (MO-LRT) are found in its artificially added hangover mechanism that exhibits an incorrect behavior under different signal-to-noise ratio (SNR) conditions. The new approach defines a maximum a posteriori (MAP) statistical test in which all the global hypotheses on the multiple observation window containing up to one speech-to-nonspeech or nonspeech-to-speech transitions are considered. Thus, the implicit hangover mechanism artificially added by the original method was not found in the revised method so its design can be further improved. With these and other innovations, the proposed method showed a higher speech/nonspeech discrimination accuracy over a wide range of SNR conditions when compared to the original MO-LRT voice activity detector (VAD). Experiments conducted on the AURORA databases and tasks showed that the revised method yields significant improvements in speech recognition performance over standardized VADs such as ITU T G.729 and ETSI AMR for discontinuous voice transmission and the ETSI AFE for distributed speech recognition (DSR), as well as over recently reported methods.     

Optimisation of a multi-objective two-dimensional strip packing problem based on evolutionary algorithms

This paper considers a real-world two-dimensional strip packing problem involving specific machinery constraints and actual cutting production industry requirements. To adapt the problem to a wider range of machinery characteristics, the design objective considers the minimisation of material length and the total number of cuts for guillotinable-type patterns. The number of cuts required for the cutting process is crucial for the life of the industrial machines and is an important aspect in determining the cost and efficiency of the cutting operation. In this paper we propose the application of evolutionary algorithms to address the multi-objective problem, for which numerous approaches to its single-objective formulation exist, but for which multi-objective approaches are almost non-existent. The multi-objective evolutionary algorithms applied provide a set of solutions offering a range of trade-offs between the two objectives from which clients can choose according to their needs. By considering both the length and number of cuts, they derive solutions with wastage levels similar to most previous approximations which just seek to optimise the overall length.     

Effect of kaolin nanofiller and processing conditions on the structure,morphology, and biofilm development of polylactic acid

The effect of high energy ball milling, HEBM, and the presence of kaolin on the structure, morphology, and biofilm development of polylactic acid, PLA, were studied. Biofilm development was evaluated in terms of structural and/or morphological variations so as the sole presence of kaolin. Composites based on PLA filled with kaolin were prepared by HEBM followed by hot pressing to obtain films. Structure was studied by X‐ray diffraction and Fourier transformed infrared spectroscopy whereas morphology was inspected by scanning electron microscopy and atomic force microscopy. To study biofilm development on the surface of these materials, Pseudomonas fluorescens B52 were used. The shear forces from the milling process favor kaolin dispersion within the PLA. Longer milling times and cryogenic conditions improve clay dispersion. Subsequent hot pressing process enhances the most ordered structure of PLA (α‐phase) which is also favored with previous milling at longer times and under cryogenic conditions. Changes in P. fluorescens biofilm development are mainly due to modifications of surface properties induced by structural variations, being the most ordered structures those which better support bacterial adhesion and proliferation. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42676.