Rapid preconditioning of data for accelerating convex hull algorithms

Given a dataset of two-dimensional points in the plane with integer coordinates, the method proposed reduces a set of n points down to a set of s points s ≤ n, such that the convex hull on the set of s points is the same as the convex hull of the original set of n points. The method is O(n). It helps any convex hull algorithm run faster. The empirical analysis of a practical case shows a percentage reduction in points of over 98%, that is reflected as a faster computation with a speedup factor of at least 4.

Distributed parallelization of greedy Mobile Network Optimization algorithms

The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.

Asynchronous distributed parallelization of mobile network optimization algorithms

It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.

Efficiency of evolutionary algorithms in water network pipe sizing

The pipe sizing of water networks via evolutionary algorithms is of great interest because it allows the selection of alternative economical solutions that meet a set of design requirements. However, available evolutionary methods are numerous, and methodologies to compare the performance of these methods beyond obtaining a minimal solution for a given problem are currently lacking. A methodology to compare algorithms based on an efficiency rate (E) is presented here and applied to the pipe-sizing problem of four medium-sized benchmark networks (Hanoi, New York Tunnel, GoYang and R-9 Joao Pessoa). E numerically determines the performance of a given algorithm while also considering the quality of the obtained solution and the required computational effort. From the wide range of available evolutionary algorithms, four algorithms were selected to implement the methodology: a PseudoGenetic Algorithm (PGA), Particle Swarm Optimization (PSO), a Harmony Search and a modified Shuffled Frog Leaping Algorithm (SFLA). After more than 500,000 simulations, a statistical analysis was performed based on the specific parameters each algorithm requires to operate, and finally, E was analyzed for each network and algorithm. The efficiency measure indicated that PGA is the most efficient algorithm for problems of greater complexity and that HS is the most efficient algorithm for less complex problems. However, the main contribution of this work is that the proposed efficiency ratio provides a neutral strategy to compare optimization algorithms and may be useful in the future to select the most appropriate algorithm for different types of optimization problems.

Selecting algorithms for Earth observation of climate within the European Space Agency Climate Change initiative: introduction to a special issue

This special issue is focused on the assessment of algorithms for the observation of Earth’s climate from environ- mental satellites. Climate data records derived by remote sensing are increasingly a key source of insight into the workings of and changes in Earth’s climate system. Producers of data sets must devote considerable effort and expertise to maximise the true climate signals in their products and minimise effects of data processing choices and changing sensors. A key choice is the selection of algorithm(s) for classification and/or retrieval of the climate variable. Within the European Space Agency Climate Change Initiative, science teams undertook systematic assessment of algorithms for a range of essential climate variables. The papers in the special issue report some of these exercises (for ocean colour, aerosol, ozone, greenhouse gases, clouds, soil moisture, sea surface temper- ature and glaciers). The contributions show that assessment exercises must be designed with care, considering issues such as the relative importance of different aspects of data quality (accuracy, precision, stability, sensitivity, coverage, etc.), the availability and degree of independence of validation data and the limitations of validation in characterising some important aspects of data (such as long-term stability or spatial coherence). As well as re- quiring a significant investment of expertise and effort, systematic comparisons are found to be highly valuable. They reveal the relative strengths and weaknesses of different algorithmic approaches under different observa- tional contexts, and help ensure that scientific conclusions drawn from climate data records are not influenced by observational artifacts, but are robust.

Environmental controls on the distribution and diversity of lentic Chironomidae (Insecta: Diptera) across an altitudinal gradient in tropical South America

To predict the response of aquatic ecosystems to future global climate change, data on the ecology and distribution of keystone groups in freshwater ecosystems are needed. In contrast to mid- and high-latitude zones, such data are scarce across tropical South America (Neotropics). We present the distribution and diversity of chironomid species using surface sediments of 59 lakes from the Andes to the Amazon (0.1–17°S and 64–78°W) within the Neotropics. We assess the spatial variation in community assemblages and identify the key variables influencing the distributional patterns. The relationships between environmental variables (pH, conductivity, depth, and sediment organic content), climatic data, and chironomid assemblages were assessed using multivariate statistics (detrended correspondence analysis and canonical correspondence analysis). Climatic parameters (temperature and precipitation) were most significant in describing the variance in chironomid assemblages. Temperature and precipitation are both predicted to change under future climate change scenarios in the tropical Andes. Our findings suggest taxa of Orthocladiinae, which show a preference to cold high-elevation oligotrophic lakes, will likely see range contraction under future anthropogenic-induced climate change. Taxa abundant in areas of high precipitation, such as Micropsectra and Phaenopsectra, will likely become restricted to the inner tropical Andes, as the outer tropical Andes become drier. The sensitivity of chironomids to climate parameters makes them important bio-indicators of regional climate change in the Neotropics. Furthermore, the distribution of chironomid taxa presented here is a vital first step toward providing urgently needed autecological data for interpreting fossil chironomid records of past ecological and climate change from the tropical Andes.

Zero attracting recursive least squares algorithms

The l1-norm sparsity constraint is a widely used technique for constructing sparse models. In this contribution, two zero-attracting recursive least squares algorithms, referred to as ZA-RLS-I and ZA-RLS-II, are derived by employing the l1-norm of parameter vector constraint to facilitate the model sparsity. In order to achieve a closed-form solution, the l1-norm of the parameter vector is approximated by an adaptively weighted l2-norm, in which the weighting factors are set as the inversion of the associated l1-norm of parameter estimates that are readily available in the adaptive learning environment. ZA-RLS-II is computationally more efficient than ZA-RLS-I by exploiting the known results from linear algebra as well as the sparsity of the system. The proposed algorithms are proven to converge, and adaptive sparse channel estimation is used to demonstrate the effectiveness of the proposed approach.

Medial contact and smaller plantar loads characterize individuals with Patellofemoral Pain Syndrome during stair descent

Objectives: To investigate plantar pressure distribution in individuals with and without Patellofemoral Pain Syndrome during the Support phase of stair descent. Design: Observational case-control study. Participants: 30 Young adults With Patellofemoral Pain Syndrome and 44 matched controls. Main outcome measures: Contact area, peak pressure and pressure-time integral (Novel Pedar-X system) were evaluated in six plantar areas (medial, central and lateral rearfoot: midfoot; medial and lateral forefoot) during stair descent. Results: Contact area was greater in the Patellofemoral Pain Syndrome Group at medial rearfoot (p = 0.019) and midfoot (p < 0.001). Subjects with Patellofemoral pain Syndrome presented smaller peak pressures (p < 0.001). Conclusion: The pattern of plantar pressure distribution during stair descent in Patellofemoral Pain Syndrome Subjects was different from controls. This seems to be related to greater medial rearfoot and midfoot Support. Smaller plantar loads found in Patellofemoral Pain Syndrome subjects during stair descent reveal a more Cautious motor pattern in a challenging task. (C) 2009 Elsevier Ltd. All rights reserved.

Integrated marine gravity field in the Brazilian coast from altimeter-derived sea surface gradient and shipborne gravity

Sea surface gradients derived from the Geosat and ERS-1 satellite altimetry geodetic missions were integrated with marine gravity data from the National Geophysical Data Center and Brazilian national surveys. Using the least squares collocation method, models of free-air gravity anomaly and geoid height were calculated for the coast of Brazil with a resolution of 2` x 2`. The integration of satellite and shipborne data showed better statistical results in regions near the coast than using satellite data only, suggesting an improvement when compared to the state-of-the-art global gravity models. Furthermore, these results were obtained with considerably less input information than was used by those reference models. The least squares collocation presented a very low content of high-frequency noise in the predicted gravity anomalies. This may be considered essential to improve the high resolution representation of the gravity field in regions of ocean-continent transition. (C) 2010 Elsevier Ltd. All rights reserved.

Germination rate and sporeling development of Chondracanthus chamissoi (Rhodophyta, Gigartinales) varies along a latitudinal gradient on the coast of Chile

Chondracanthus chamissoi (C. Agardh) Kutzing is an economically important red seaweed with an extended latitudinal distribution along the south-east Pacific. Here we report on the seasonal in vitro germination of carpospores and tetraspores from four populations distributed from 27 to 41 degrees S on the Chilean coast. Our results show that both types of spores exhibited a different physiological behavior related to the geographic origin of the specimens. Germination occurred throughout the year for both spore types in the four populations. However, for the northern locations (Calderilla, La Herradura and Puerto Aldea) germination was higher in spring, while for the southern location (Lechagua), germination was higher in summer. The growth rate of carposporelings and tetrasporelings varied seasonally in ail locations studied, with higher growth in spring. Among all, carposporelings from Lechagua specimens reached the highest growth rates (9.3 +/- 0.2% d(-1)). However, spores from Herradura and P. Aldea had a good germination and SGR in all seasons and would be good candidates to start spores-based cultivation of this valuable resource in Chile. (C) 2009 Elsevier B.V. All rights reserved

Seed dispersal and predation in the endemic Atlantic rainforest palm Astrocaryum aculeatissimum across a gradient of seed disperser abundance

Tropical forests have been subject to intense hunting of medium and large frugivores that are important in dispersing large-seeded species. It has been hypothesized that in areas with extinction or low abundance of medium and large-bodied animals the density of small rodents may increase. Therefore, this increment in the density of small rodents may compensate for the absence or low abundance of medium and large frugivores on seed removal and seed dispersal. Here, we fill up this gap in the literature by determining if seed removal, seed dispersal, and seed predation by small rodents (spiny rats, Trinomys inheringi and squirrels, Sciurus ingrami) are maintained in defaunated areas. We accessed seed removal, seed dispersal, seed predation, and seedling recruitment of an endemic Atlantic rainforest palm, Astrocaryum aculeatissimum, in a gradient of abundance of agoutis. We found that seed removal, scatter hoarding, and seed predation increase with the abundance of agoutis. In contrast, the proportion of dispersed but non-cached seeds decreased with the abundance of agoutis. We did not find any effect of the abundance of agoutis on seed dispersal distance, but we did find a positive trend on the density of seedlings. We concluded that small rodents do not compensate the low abundance of agoutis on seed removal, scatter hoarding, and seed predation of this palm tree. Moreover, areas in which agoutis are already extinct did not present any seed removal or scatter hoarding, not even by small rodents. This study emphasizes both the importance of agoutis in dispersing seeds of A. aculeatissimum and the collapse in seed dispersal of this palm in areas where agoutis are already extinct.

Decomposition in tropical forests: a pan-tropical study of the effects of litter type, litter placement and mesofaunal exclusion across a precipitation gradient

1. Litter decomposition recycles nutrients and causes large fluxes of carbon dioxide into the atmosphere. It is typically assumed that climate, litter quality and decomposer communities determine litter decay rates, yet few comparative studies have examined their relative contributions in tropical forests. 2. We used a short-term litterbag experiment to quantify the effects of litter quality, placement and mesofaunal exclusion on decomposition in 23 tropical forests in 14 countries. Annual precipitation varied among sites (760-5797 mm). At each site, two standard substrates (Raphia farinifera and Laurus nobilis) were decomposed in fine- and coarse-mesh litterbags both above and below ground for approximately 1 year. 3. Decomposition was rapid, with >95% mass loss within a year at most sites. Litter quality, placement and mesofaunal exclusion all independently affected decomposition, but the magnitude depended upon site. Both the average decomposition rate at each site and the ratio of above- to below-ground decay increased linearly with annual precipitation, explaining 60-65% of among-site variation. Excluding mesofauna had the largest impact on decomposition, reducing decomposition rates by half on average, but the magnitude of decrease was largely independent of climate. This suggests that the decomposer community might play an important role in explaining patterns of decomposition among sites. Which litter type decomposed fastest varied by site, but was not related to climate. 4. Synthesis. A key goal of ecology is to identify general patterns across ecological communities, as well as relevant site-specific details to understand local dynamics. Our pan-tropical study shows that certain aspects of decomposition, including average decomposition rates and the ratio of above- to below-ground decomposition are highly correlated with a simple climatic index: mean annual precipitation. However, we found no relationship between precipitation and effects of mesofaunal exclusion or litter type, suggesting that site-specific details may also be required to understand how these factors affect decomposition at local scales.

The genetic effects of Late Quaternary climatic changes over a tropical latitudinal gradient: diversification of an Atlantic Forest passerine

The increase in biodiversity from high to low latitudes is a widely recognized biogeographical pattern. According to the latitudinal gradient hypothesis (LGH), this pattern was shaped by differential effects of Late Quaternary climatic changes across a latitudinal gradient. Here, we evaluate the effects of climatic changes across a tropical latitudinal gradient and its implications to diversification of an Atlantic Forest (AF) endemic passerine. We studied the intraspecific diversification and historical demography of Sclerurus scansor, based on mitochondrial (ND2, ND3 and cytb) and nuclear (FIB7) gene sequences. Phylogenetic analyses recovered three well-supported clades associated with distinct latitudinal zones. Coalescent-based methods were applied to estimate divergence times and changes in effective population sizes. Estimates of divergence times indicate that intraspecific diversification took place during Middle-Late Pleistocene. Distinct demographic scenarios were identified, with the southern lineage exhibiting a clear signature of demographic expansion, while the central one remained more stable. The northern lineage, contrasting with LGH predictions, exhibited a clear sign of a recent bottleneck. Our results suggest that different AF regions reacted distinctly, even in opposite ways, under the same climatic period, producing simultaneously favourable scenarios for isolation and contact among populations.

A hybrid approach to learn with imbalanced classes using evolutionary algorithms

There is an increasing interest in the application of Evolutionary Algorithms (EAs) to induce classification rules. This hybrid approach can benefit areas where classical methods for rule induction have not been very successful. One example is the induction of classification rules in imbalanced domains. Imbalanced data occur when one or more classes heavily outnumber other classes. Frequently, classical machine learning (ML) classifiers are not able to learn in the presence of imbalanced data sets, inducing classification models that always predict the most numerous classes. In this work, we propose a novel hybrid approach to deal with this problem. We create several balanced data sets with all minority class cases and a random sample of majority class cases. These balanced data sets are fed to classical ML systems that produce rule sets. The rule sets are combined creating a pool of rules and an EA is used to build a classifier from this pool of rules. This hybrid approach has some advantages over undersampling, since it reduces the amount of discarded information, and some advantages over oversampling, since it avoids overfitting. The proposed approach was experimentally analysed and the experimental results show an improvement in the classification performance measured as the area under the receiver operating characteristics (ROC) curve.