Low-complexity three-dimensional discrete Hartley transform approximations for medical image compression.

The discrete Hartley transform (DHT) is a useful tool for medical image coding. The three-dimensional DHT (3D DHT) can be employed to compress medical image data, such as magnetic resonance and X-ray angiography. However, the computation of the 3D DHT involves several multiplications by irrational quantities, which require floating-point arithmetic and inherent truncation errors.

Low-Complexity Approximate Convolutional Neural Networks.

In this paper, we present an approach for minimizing the computational complexity of the trained convolutional neural networks (ConvNets). The idea is to approximate all elements of a given ConvNet and replace the original convolutional filters and parameters (pooling and bias coefficients; and activation function) with an efficient approximations capable of extreme reductions in computational complexity. Low-complexity convolution filters are obtained through a binary (zero and one) linear programming scheme based on the Frobenius norm over sets of dyadic rationals.

Low-Complexity Multidimensional DCT Approximations for High-Order Tensor Data Decorrelation.

In this paper, we introduce low-complexity multidimensional discrete cosine transform (DCT) approximations. 3D DCT approximations are formalized in terms of high-order tensor theory. The formulation is extended to higher dimensions with arbitrary lengths.

Correction: Modeling Occupancy of Hosts by Mistletoe Seeds after Accounting for Imperfect Detectability.

[This corrects the article DOI: 10.1371/journal.pone.

Modeling occupancy of hosts by mistletoe seeds after accounting for imperfect detectability.

The detection of an organism in a given site is widely used as a state variable in many metapopulation and epidemiological studies. However, failure to detect the species does not necessarily mean that it is absent. Assessing detectability is important for occupancy (presence-absence) surveys; and identifying the factors reducing detectability may help improve survey precision and efficiency.

Spatial and temporal changes in bird assemblages in forest fragments in an eastern Amazonian savannah.

We investigated the effects of forest fragmentation on bird assemblages in an Amazonian savannah landscape with forest fragments that have been isolated for more than 100 years. The study was conducted in areas surrounding the village of Alter do Chão (2°31'S, 55°00'W), Santarém, Brazil. Bird surveys and measurements of tree density were undertaken in 25 areas, with 19 plots in forest fragments of different sizes and six in an area of continuous forest.

[Information from the invoicing sector as support for decision-making: a case study at the University Hospital of the Federal University of Grande Dourados (UFGD)].

The public sector is the main financing agent of hospital admissions and the information generated constitutes the input for the hospital information network of the Unified Health System (SUS). This paper seeks to design a report template to be used for decision-making in both public and university hospitals. The theoretical approach sought inspiration in discussions about the SUS, hospital institutions, hospital information systems and decision-making.

Contributions of C and C plants to higher trophic levels in an Amazonian savanna.

We studied the energy flow from C and C plants to higher trophic levels in a central Amazonian savanna by comparing the carbon stable-isotope ratios of potential food plants to the isotope ratios of species of different consumer groups. All C plants encountered in our study area were grasses and all C plants were bushes, shrubs or vines. Differences in δC ratios among bushes (x¯ = -30.