Genetic algorithm for sequencing in midex model non-permutation flowshops using constrained buffers

Este trabajo presenta un Algoritmo Genético (GA) del problema de secuenciar unidades en una línea de producción. Se tiene en cuenta la posibilidad de cambiar la secuencia de piezas mediante estaciones con acceso a un almacén intermedio o centralizado. El acceso al almacén además está restringido, debido al tamaño de las piezas.AbstractThis paper presents a Genetic Algorithm (GA) for the problem of sequencing in a mixed model non-permutation flowshop. Resequencingis permitted where stations have access to intermittent or centralized resequencing buffers. The access to a buffer is restricted by the number of available buffer places and the physical size of the products.

Spatial predictions of land-use transitions and associated threats to biodiversity: the case of forest regrowth in mountain grasslands

Question Can we predict where forest regrowth caused by abandonment of agricultural activities is likely to occur? Can we assess how it may conflict with grassland diversity hotspots? Location Western Swiss Alps (4003210m a.s.l.). Methods We used statistical models to predict the location of land abandonment by farmers that is followed by forest regrowth in semi-natural grasslands of the Western Swiss Alps. Six modelling methods (GAM, GBM, GLM, RF, MDA, MARS) allowing binomial distribution were tested on two successive transitions occurring between three time periods. Models were calibrated using data on land-use change occurring between 1979 and 1992 as response, and environmental, accessibility and socio-economic variables as predictors, and these were validated for their capacity to predict the changes observed from 1992 to 2004. Projected probabilities of land-use change from an ensemble forecast of the six models were combined with a model of plant species richness based on a field inventory, allowing identification of critical grassland areas for the preservation of biodiversity. Results Models calibrated over the first land-use transition period predicted the second transition with reasonable accuracy. Forest regrowth occurs where cultivation costs are high and yield potential is low, i.e. on steeper slopes and at higher elevations. Overlaying species richness with land-use change predictions, we identified priority areas for the management and conservation of biodiversity at intermediate elevations. Conclusions Combining land-use change and biodiversity projections, we propose applied management measures for targeted/identified locations to limit the loss of biodiversity that could otherwise occur through loss of open habitats. The same approach could be applied to other types of land-use changes occurring in other ecosystems.

Cross-scale analysis of the region effect on vascular plant species diversity in southern and northern European mountain ranges.

Background: The divergent glacial histories of southern and northern Europe affect present-day species diversity at coarse-grained scales in these two regions, but do these effects also penetrate to the more fine-grained scales of local communities?Methodology/Principal Findings: We carried out a cross-scale analysis to address this question for vascular plants in two mountain regions, the Alps in southern Europe and the Scandes in northern Europe, using environmentally paired vegetation plots in the two regions (n = 403 in each region) to quantify four diversity components: (i) total number of species occurring in a region (total gamma-diversity), (ii) number of species that could occur in a target plot after environmental filtering (habitat-specific gamma-diversity), (iii) pair-wise species compositional turnover between plots (plot-to-plot beta-diversity) and (iv) number of species present per plot (plot gamma-diversity). We found strong region effects on total gamma-diversity, habitat-specific gamma-diversity and plot-to-plot beta-diversity, with a greater diversity in the Alps even towards distances smaller than 50 m between plots. In contrast, there was a slightly greater plot alpha-diversity in the Scandes, but with a tendency towards contrasting region effects on high and low soil-acidity plots.Conclusions/Significance: We conclude that there are strong regional differences between coarse-grained (landscape- to regional-scale) diversity components of the flora in the Alps and the Scandes mountain ranges,but that these differences do not necessarily penetrate to the finest-grained (plot-scale) diversity component, at least not on acidic soils. Because different processes can lead to a similar pattern, we discuss the consistency of our results with Quaternary history and other divergent features between the two regions such as habitat connectivity, selection for vagility and environmental differences not accounted for in our analyses

Settlement evolution, field systems and sedimentary processes in a Mediterranean mid-mountain (Montseny Massif, Catalunya)

This paper presents the first results of a current research project about human – environmental interactions in the Montseny Massif. Our work sets out to integrate two research lines in the studied area: - Archaeological and archaeo-morphological surveys in a lower part of the mountains in order to characterize the evolution of the settlements and field systems. - The geological and geomorphological characterization of the slope and terrace deposits in relation with field systems and archaeological data. First results point out the intensive occupation of these inland areas during the Iberian and the Roman periods. Post-Roman sediments show different processes of erosion.

Characterization and management of rockslide hazard at Turtle Mountain, Alberta, Canada

In 1903, more than 30 million m3 of rock fell from the east slopes of Turtle Mountain in Alberta, Canada, causing a rock avalanche that killed about 70 people in the town of Frank. The Alberta Government, in response to continuing instabilities at the crest of the mountain, established a sophisticated field laboratory where state-of-the-art monitoring techniques have been installed and tested as part of an early-warning system. In this chapter, we provide an overview of the causes, trigger, and extreme mobility of the landslide. We then present new data relevant to the characterization and detection of the present-day instabilities on Turtle Mountain. Fourteen potential instabilities have been identified through field mapping and remote sensing. Lastly, we provide a detailed review of the different in-situ and remote monitoring systems that have been installed on the mountain. The implications of the new data for the future stability of Turtle Mountain and related landslide runout, and for monitoring strategies and risk management, are discussed.

Continent wide response of mountain vegetation to climate change

Climate impact studies have indicated ecological fingerprints of recent global warming across a wide range of habitats. Whereas these studies have shown responses from various local case studies, a coherent large-scale account on temperature-driven changes of biotic communities has been lacking. Here we use 867 vegetation samples above the treeline from 60 summit sites in all major European mountain systems to show that ongoing climate change gradually transforms mountain plant communities. We provide evidence that the more cold-adapted species decline and the more warm-adapted species increase, a process described here as thermophilisation. At the scale of individual mountains this general trend may not be apparent, but at the¦larger, continental scale we observed a significantly higher abundance of thermophilic species in 2008, compared with 2001. Thermophilisation of mountain plant communities mirrors the degree of recent warming and is more pronounced in areas where the temperature increase has been higher. In view of the projected climate change the observed transformation suggests a progressive decline of cold mountain habitats and their biota.

Kumar's algorithm for solving Toeplitz systems of equations over finite fields

Adaptació de l'algorisme de Kumar per resoldre sistemes d'equacions amb matrius de Toeplitz sobre els reals a cossos finits en un temps 0 (n log n).

Implementation of the Rijndael-AES algorithm on a Sage-Math worksheet

La principal motivació d'aquest treball ha estat implementar l'algoritme Rijndael-AES en un full Sage-math, paquet de software matemàtic de lliure distribució i en actual desenvolupament, aprofitant les seves eines i funcionalitats integrades.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Flow resistance equations for mountain rivers

Three models of flow resistance (a Keulegan-type logarithmic law and two models developed for large-scale roughness conditions: the full logarithmic law and a model based on an inflectional velocity profile) were calibrated, validated and compared using an extensive database (N = 1,533) from rivers and flumes, representative of a wide hydraulic and geomorphologic range in the field of gravel-bed and mountain channels. It is preferable to apply the model based on an inflectional velocity profile in the relative submergence (y/d90) interval between 0.5 and 15, while the full logarithmic law is preferable for values below 0.5. For high relative submergence, above 15, either the logarithmic law or the full logarithmic law can be applied. The models fitted to the coarser percentiles are preferable to those fitted to the median diameter, owing to the higher explanatory power achieved by setting a model, the smaller difference in the goodness-of-fit between the different models and the lower influence of the origin of the data (river or flume).

In search for better pharmacological prophylaxis for acute mountain sickness: looking in other directions.

Despite decades of research, the exact pathogenic mechanisms underlying acute mountain sickness (AMS) are still poorly understood. This fact frustrates the search for novel pharmacological prophylaxis for AMS. The prevailing view is that AMS results from an insufficient physiological response to hypoxia and that prophylaxis should aim at stimulating the response. Starting off from the opposite hypothesis that AMS may be caused by an initial excessive response to hypoxia, we suggest that directly or indirectly blunting-specific parts of the response might provide promising research alternatives. This reasoning is based on the observations that (i) humans, once acclimatized, can climb Mt Everest experiencing arterial partial oxygen pressures (PaO2 ) as low as 25 mmHg without AMS symptoms; (ii) paradoxically, AMS usually develops at much higher PaO2 levels; and (iii) several biomarkers, suggesting initial activation of specific pathways at such PaO2 , are correlated with AMS. Apart from looking for substances that stimulate certain hypoxia triggered effects, such as the ventilatory response to hypoxia, we suggest to also investigate pharmacological means aiming at blunting certain other specific hypoxia-activated pathways, or stimulating their agonists, in the quest for better pharmacological prophylaxis for AMS.

A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.