Exploring Performance Bounds of Visual Place Recognition Using Extended Precision

Recent advances in image description and matching allowed significant improvements in Visual Place Recognition (VPR). The wide variety of methods proposed so far and the increase of the interest in the field have rendered the problem of evaluating VPR methods an important task. As part of the localization process, VPR is a critical stage for many robotic applications and it is expected to perform reliably in any location of the operating environment. To design more reliable and effective localization systems this letter presents a generic evaluation framework based on the new Extended Precision performance metric for VPR. The proposed framework allows assessment of the upper and lower bounds of VPR performance and finds statistically significant performance differences between VPR methods. The proposed evaluation method is used to assess several state-of-the-art techniques with a variety of imaging conditions that an autonomous navigation system commonly encounters on long term runs. The results provide new insights into the behaviour of different VPR methods under varying conditions and help to decide which technique is more appropriate to the nature of the venture or the task assigned to an autonomous robot

The influence of structure on the elastic, optical and dielectric properties of nematic phases formed from bent-core molecules

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Principal molecular axis and transition dipole moment orientations in liquid crystal systems: an assessment based on studies of guest anthraquinone dyes in a nematic host

An assessment of five different definitions of the principal molecular axis along which molecules align in a nematic liquid crystal system has been made by analysing fully atomistic molecular dynamics (MD) simulations of a set of anthraquinone dyes in the cyanobiphenyl-based nematic host mixture E7. Principal molecular axes of the dyes defined by minimum moment of inertia, minimum circumference, minimum area, maximum aspect ratio, and surface tensor models were tested, and the surface tensor model was found to give the best description. Analyses of MD simulations of E7 alone showed that the surface tensor model also gave a good description of the principal molecular axes of the host molecules, suggesting that this model may be applicable more generally. Calculated dichroic order parameters of the guest-host systems were obtained by combining the surface tensor analysis with fixed transition dipole moment (TDM) orientations from time-dependent density functional theory (TD-DFT) calculations on optimised structures of the dyes, and the trend between the dyes generally matched the trend in the experimental values. Additional analyses of the guest-host simulations identified the range of conformers explored by the flexible chromophores within the dyes, and TD-DFT calculations on corresponding model structures showed that this flexibility has a significant effect on the TDM orientations within the molecular frames. Calculated dichroic order parameters that included the effects of this flexibility gave a significantly improved match with the experimental values for the more flexible dyes. Overall, the surface tensor model has been shown to provide a rationale for the experimental alignment trends that is based on molecular shape, and molecular flexibility within the chromophores has been shown to be significant for the guest-host systems: The computational approaches reported here may be used as a general aid in the predictive design of dyes with appropriate molecular shapes and flexibilities for guest-host applications

On the Microscopic Origin of Cholesteric Pitch

We present a microscopic analysis of the instability of the nematic phase to chirality when molecular chirality is introduced perturbatively. We show that previously neglected short-range biaxial correlations play a crucial role in determining the cholesteric pitch. We propose an order parameter which quantifies the chirality of a molecule.Comment: RevTeX 3.0, 4 pages, one included eps figure. Published versio

Water demand prospects for the irrigation in São Francisco River.

Abstract: This study analyzed how the irrigation expansion in São Francisco Hydrographic Region (SFRH) would affect the water availability in four specifics physiographic regions into SFRH (Upper, Middle, sub-Middle, and Lower). The TERM-BR model was used to simulate expansion scenarios in irrigated areas aiming to verify the impact in the water use for 2025 and 2035 according to with National Water Resources Plan (PNRH), and Water Resources Plan for the São Francisco River (SFP). The simulations were carried out for areas deemed potentially suitable for irrigation based on the Ministry of National Integration report (MI). The Climatic Water Balance (CWB) was estimated for São Francisco hydrographic region (SFRH) in order to compare regional water supply and demand. Results suggest that cities located in Upper and Middle São Francisco region would present greater irrigation potential due to the water availability and the proximity to neighborhoods that also irrigate. The comparative result of the CWB and the TERM-BR model shown water availability problems in the states of Alagoas and Pernambuco in particular and cities located in São Francisco Lower.GTAP Resource #5725

Binary Neural Networks for Memory-Efficient and Effective Visual Place Recognition in Changing Environments

Visual place recognition (VPR) is a robot’s ability to determine whether a place was visited before using visual data. While conventional handcrafted methods for VPR fail under extreme environmental appearance changes, those based on convolutional neural networks (CNNs) achieve state-of-the-art performance but result in heavy runtime processes and model sizes that demand a large amount of memory. Hence, CNN-based approaches are unsuitable for resource-constrained platforms, such as small robots and drones. In this article, we take a multistep approach of decreasing the precision of model parameters, combining it with network depth reduction and fewer neurons in the classifier stage to propose a new class of highly compact models that drastically reduces the memory requirements and computational effort while maintaining state-of-the-art VPR performance. To the best of our knowledge, this is the first attempt to propose binary neural networks for solving the VPR problem effectively under changing conditions and with significantly reduced resource requirements. Our best-performing binary neural network, dubbed FloppyNet, achieves comparable VPR performance when considered against its full-precision and deeper counterparts while consuming 99% less memory and increasing the inference speed by seven times

UAV Remote Sensing for High-Throughput Phenotyping and for Yield Prediction of Miscanthus by Machine Learning Techniques

Miscanthus holds a great potential in the frame of the bioeconomy, and yield prediction can help improve Miscanthus’ logistic supply chain. Breeding programs in several countries are attempting to produce high-yielding Miscanthus hybrids better adapted to different climates and end-uses. Multispectral images acquired from unmanned aerial vehicles (UAVs) in Italy and in the UK in 2021 and 2022 were used to investigate the feasibility of high-throughput phenotyping (HTP) of novel Miscanthus hybrids for yield prediction and crop traits estimation. An intercalibration procedure was performed using simulated data from the PROSAIL model to link vegetation indices (VIs) derived from two different multispectral sensors. The random forest algorithm estimated with good accuracy yield traits (light interception, plant height, green leaf biomass, and standing biomass) using a VIs time series, and predicted yield using a peak descriptor derived from a VIs time series with 2.3 Mg DM ha−1 of the root mean square error (RMSE). The study demonstrates the potential of UAVs’ multispectral images in HTP applications and in yield prediction, providing important information needed to increase sustainable biomass production

Biofuels from perennial energy crops on buffer strips: A win-win strategy

The objective of this work was to assess the environmental performances of advanced biofuels produced from perennial energy crops (miscanthus and willow) grown in bioenergy buffer strips (BBS) and compare them with the environmental performances of alternative systems providing the same function, i.e. private mobility. The growing evidence of potentially negative environmental impacts of bioenergy pathways calls for renewed efforts in identifying win-win bioenergy pathways, thus capable of mitigating climate change without worsening other environmental impacts. An holistic approach encompassing all the relevant areas of environmental concern is thus fundamental to highlight environmental trade-offs. Therefore, in this study we follow an attributional Life Cycle Assessment approach, but our analysis includes detailed modelling of biogenic carbon pools, nutrients cycles, infrastructures’ impacts as well as the expansion of the system boundaries to include the fuel use. We find that the fragmented and linear configuration of the buffer strips does not affect significantly the GHG emissions of lignocellulosic ethanol for BBS compared to growing the crops in open field. Additionally, we find that ethanol from perennials grown in BBS has the potential to reduce several other environmental impacts associated to private mobility. Firstly, the cultivation of miscanthus and willow in BBS enables both the removal of nutrients from the environment and the removal of carbon from the atmosphere, through the creation of an additional terrestrial sink. Secondly, when compared to the use of fossil gasoline, bioethanol from BBS crops generates lower impacts on all other areas of environmental concern, such as resources depletion or air pollution. We also find that cars fuelled with bioethanol form buffer strips perform even better than electric vehicles in all the impact categories analysed except for acidification and particulate matter emissions, where battery electric vehicles running on renewables perform slightly better. We conclude that bioethanol from perennial crops grown in BBS is a good example of nature-based solution, able to reduce GHG emissions without shifting the environmental burden on other areas of environmental concern

Flexoelectricity in an oxadiazole bent-core nematic liquid crystal

We have determined experimentally the magnitude of the difference in the splay and bend flexoelectric coefficients, |e1 - e3|, of an oxadiazole bent-core liquid crystal by measuring the critical voltage for the formation of flexodomains together with their wave number. The coefficient |e1 - e3| is found to be a factor of 2-3 times higher than in most conventional calamitic nematic liquid crystals, varying from 8 pCm-1 to 20 pCm-1 across the ∼60 K - wide nematic regime. We have also calculated the individual flexoelectric coefficients e1 and e3, with the dipolar and quadrupolar contributions of the bent-core liquid crystal by combining density functional theory calculations with a molecular field approach and atomistic modelling. Interestingly, the magnitude of the bend flexoelectric coefficient is found to be rather small, in contrast to common expectations for bent-core molecules. The calculations are in excellent agreement with the experimental values, offering an insight into how molecular parameters contribute to the flexoelectric coefficients and illustrating a huge potential for the prediction of flexoelectric behaviour in bent-core liquid crystals