Inverse pointer unboxing

Virtual machines (VM) for dynamic programming languages store a combination of 64-bit data types in each 64-bit register. A motivation to store multiple variables in a single register is speed, since access to variables within a register is much faster than access to variables stored within RAM. Current approaches of storing multiple 64-bit values in a single 64-bit register result in undesirable effects such as higher register pressure, increased garbage collection burden, excessive boxing/unboxing steps, etc. Most current approaches cannot distinguish a sufficient number of values in 64 bits, as much is hidden behind 64-bit pointers to RAM. This in turn affects performance of the VM. This disclosure makes use of the floating-point specification to store variables of type double, integer, boolean, etc. in non-canonical pointer space, alongside the pointers themselves. In this manner, more variables are packed in a single register, thereby improving performance of virtual machines

De-ossifying the Internet Transport Layer : A Survey and Future Perspectives

ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers for their useful suggestions and comments.Peer reviewedPublisher PD

Oilseed rape and pollinators: the impact of variety on resource availability and pollination resilience

Mass-flowering crops help support the nutritional demands of insect pollinators in agricultural environments. With an estimated 70% of crops experiencing increased yields through animal pollination, recent declines in pollinator abundance and diversity have severe consequences to global food production. Oilseed rape (Brassica napus) is the most abundant oilseed crop in Europe and experiences enhanced yield from insect pollination. Subject to intensive commercial breeding programmes, growers face continuous annual variety selection, with new varieties offering increased yields and more favourable agronomic characteristics. At a critical time for pollinators, little is known about the effects that variety selection may have on resource provisioning. This thesis examines the impact of pollination on oilseed rape and the inter-dependence between pollinators and growers, with an emphasis on variety type and the breeding systems used to produce them. The value of oilseed rape to the insect community was studied. Insect visitor surveys were undertaken in fields of conventional and hybrid varieties of oilseed rape, comparing the abundance and species composition between the field centre and crop edge, adjacent to semi-natural habitat. Overall, insects were more abundant and diverse at the edge of the crop than the field centre. While conventionally recognised pollinators (e.g. bees) were scarce during flowering, bumblebees were most abundant, particularly in the crop centre, whereas solitary bees favoured the crop edge. However, Diptera abundance was high, suggesting that their contribution to oilseed rape pollination in Scotland is more significant than that of bees. Conversely, the contribution of insect pollination to oilseed rape yield was estimated through pollinator exclusion experiments. Insect pollination increased seed set by 23% and seed weight per pod by 29%. Evidence of resource allocation was found, where plants with flowers subject to pollen limitation redirected resources to other parts of the plant. Increased pollinator abundance did not have a positive effect on the proportional contribution of pollinators for any of the yield metrics measured. To measure the effect of pollination on plant development and reproduction, glasshouse experiments, comparing wind- and insect-simulated pollination against a control were undertaken. The addition of supplementary pollination had significant effects on vegetative and reproductive metrics. Both wind- and insect-simulated pollination produced shorter plants, a reduced flowering period and the number of flowers produced per plant. Although plants receiving supplementary pollination produced lighter individual seeds, they produced a greater number of seeds per pod. In combination with increased fruit set, this resulted in a greater overall seed weight per plant. The prediction of floral resource availability (i.e. nectar and pollen) using oilseed rape agronomic characteristics was also investigated. Multiple regression analysis and predictive modelling were used to conclude that agronomic traits influence nectar sugar content and pollen quantity in oilseed rape. Contrary to the expectation that developing varieties with desirable traits for growers may come at a cost to floral resources, the opposite was found. Varieties with a higher tolerance to stressful environmental factors, particularly those found during winter, offered more nectar sugar per flower. The opposite was found for pollen, where early maturity, a desired trait for growers, had a negative effect on pollen quantity. Statistical analysis also highlighted the influence of short-term climatic changes on the sugar content of nectar. Conclusions indicate that the inter-relationship between oilseed rape and pollinators is complex but has the potential to be mutually beneficial. The floral rewards offered by oilseed rape attract a plethora of insect pollinators during a period of resource scarcity. In return, pollinators have a significant effect on plant development and seed production. Furthermore, by making considered varietal choices, oilseed rape growers can increase the potential to financially benefit from this mutualistic relationship by exploiting this valuable ecosystem service

The Dynamics of Learning in some Digital Networks

This thesis is concerned with a study of learning in feedback networks of adaptive logic circuits. Random networks have been studied by various researchers, but previous work has not considered the adaptation mechanisms in dynamic logic networks which result from exposure to a non-random environment. Starting with a consideration of some limitations of a single-layer static network, the concept of a dynamic net (i.e. one with feedback connections) is introduced. The behaviour of the system is described in terms of its cycling activity in state space, and the effect of training on the state structure is considered. Subsequent experimental investigations consider unsupervised learning in the net where early evidence of a clustering effect is seen. This effect is found to be more pronounced when constraints are applied to the system in the sense that controlling gates are included in the feedback path. The nature and definition of memory and perception in such nets, and the response of the net to sequences of inputs is also presented and discussed. In conclusion, a simple probabilistic analysis is developed so as to provide a basis for a general understanding of dynamic networks of this kind

Face recognition using the Moving Window Classifier

The Moving Window Classifier (MWC) has previously been proposed as an efficient scheme for text recognition applications. In this paper, the potential of the MWC algorithm in face recognition is investigated. To maintain the memory requirements of the classifier within acceptable practical limits, the concept of bit-plane encoding is utilized. The experimental results reported show very encouraging performance for both the schemes

Acquisition scenario analysis for face recognition at a distance

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-17289-2_44Proceedings of 6th International Symposium, ISVC 2010, Las Vegas, NV, (USA)An experimental analysis of three acquisition scenarios for face recognition at a distance is reported, namely: close, medium, and far distance between camera and query face, the three of them considering templates enrolled in controlled conditions. These three representative scenarios are studied using data from the NIST Multiple Biometric Grand Challenge, as the first step in order to understand the main variability factors that affect face recognition at a distance based on realistic yet workable and widely available data. The scenario analysis is conducted quantitatively in two ways. First, we analyze the information content in segmented faces in the different scenarios. Second, we analyze the performance across scenarios of three matchers, one commercial, and two other standard approaches using popular features (PCA and DCT) and matchers (SVM and GMM). The results show to what extent the acquisition setup impacts on the verification performance of face recognition at a distance.This work has been partially supported by projects Bio-Challenge (TEC2009-11186), Contexts (S2009/TIC-1485), TeraSense (CSD2008-00068) and "Cátedra UAM-Telefónica"

Implementation of boolean neural networks on parallel computers

This paper analyses the parallel implementation using networks of transputers of a neural structure belonging to a particular class of neural architectures known as GSN neural networks. These architectures, belonging to the general clasa of RAM-based networks and composed 01 digitally specified processing nodes, have been implemented using different processing topologies, and performance in relatíon to both training and testing efficiency in a practical pattern recognition task has been evaluated.Eje: Redes Neuronales. Algoritmos genéticosRed de Universidades con Carreras en Informática (RedUNCI

Bayesian Hierarchical Regression on Clearance Rates in the Presence of Lag and Tail Phases with an Application to Malaria Parasites

We present a principled technique for estimating the effect of covariates on malaria parasite clearance rates in the presence of “lag” and “tail” phases through the use of a Bayesian hierarchical linear model. The hierarchical approach enables us to appropriately incorporate the uncertainty in both estimating clearance rates in patients and assessing the potential impact of covariates on these rates into the posterior intervals generated for the parameters associated with each covariate. Furthermore, it permits us to incorporate information about individuals for whom there exists only one observation time before censoring, which alleviates a systematic bias affecting inference when these individuals are excluded. We use a changepoint model to account for both lag and tail phases, and hence base our estimation of the parasite clearance rate only on observations within the decay phase. The Bayesian approach allows us to treat the delineation between lag, decay, and tail phases within an individual\u27s clearance profile as themselves being random variables, thus taking into account the additional uncertainty of boundaries between phases. We compare our method to existing methodology used in the antimalarial research community through a simulation study and show that it possesses desirable frequentist properties for conducting inference. We use our methodology to measure the impact of several covariates on Plasmodium falciparum clearance rate data collected in 2009 and 2010. Though our method was developed with this application in mind, it can be easily applied to any biological system exhibiting these hindrances to estimation

Automatic Handwriting Feature Extraction, Analysis and Visualization in the Context of Digital Palaeography

Digital palaeography is an emerging research area which aims to introduce digital image processing techniques into palaeographic analysis for the purpose of providing objective quantitative measurements. This paper explores the use of a fully automated handwriting feature extraction, visualization, and analysis system for digital palaeography which bridges the gap between traditional and digital palaeography in terms of the deployment of feature extraction techniques and handwriting metrics. We propose the application of a set of features, more closely related to conventional palaeographic assesment metrics than those commonly adopted in automatic writer identification. These features are emprically tested on two datasets in order to assess their effectiveness for automatic writer identification and aid attribution of individual handwriting characteristics in historical manuscripts. Finally, we introduce tools to support visualization of the extracted features in a comparative way, showing how they can best be exploited in the implementation of a content-based image retrieval (CBIR) system for digital archiving. Read More: http://www.worldscientific.com/doi/abs/10.1142/S021800141653001