Parts-per-Object Count in Agricultural Images: Solving Phenotyping Problems via a Single Deep Neural Network

Solving many phenotyping problems involves not only automatic detection of objects in an image, but also counting the number of parts per object. We propose a solution in the form of a single deep network, tested for three agricultural datasets pertaining to bananas-per-bunch, spikelets-per-wheat-spike, and berries-per-grape-cluster. The suggested network incorporates object detection, object resizing, and part counting as modules in a single deep network, with several variants tested. The detection module is based on a Retina-Net architecture, whereas for the counting modules, two different architectures are examined: the first based on direct regression of the predicted count, and the other on explicit parts detection and counting. The results are promising, with the mean relative deviation between estimated and visible part count in the range of 9.2% to 11.5%. Further inference of count-based yield related statistics is considered. For banana bunches, the actual banana count (including occluded bananas) is inferred from the count of visible bananas. For spikelets-per-wheat-spike, robust estimation methods are employed to get the average spikelet count across the field, which is an effective yield estimator.

Design of Class 4 Hollow Structural Section Compression Members

This paper presents a study on the CSA S16:19, AISC 360-16, and EN 1993-1-1 approaches to determine the nominal capacity (Cn) of Class 4 hollow structural section (HSS) compression members. Class 3 limits and effective width (be) equations are compared, and the effect of member slenderness (KL/r), width-(or diameter-)to-thickness ratio, and height-to-width (or aspect) ratio on the relative Cn predictions are evaluated. For Class 4 rectangular hollow sections, CSA S16:19 is shown to under-predict Cn by up to 34% relative to AISC 360-16. A more economical, yet still safe, method to calculate be (and hence, Cn) is proposed. For Class 4 circular hollow sections (CHS), a new method to calculate Cn utilizing the “effective area method” is proposed. This new method removes the need for having an “effective yield stress method” in CSA S16 Clause 13.3.4.

Cold Forming of Al-TiB2 Composites Fabricated by SPS: A Computational Experimental Study

The mechanical response and failure of Al-TiB2 composites fabricated by Spark Plasma Sintering (SPS) were investigated. The effective flow stress at room temperature for different TiB2 particle volume fractions between 0% and 15% was determined using compression experiments on cylindrical specimens in conjunction with an iterative computational methodology. A different set of experiments on tapered specimens was used to validate the effective flow curves by comparing experimental force–displacement curves and deformation patterns to the ones obtained from the computations. Using a continuum damage mechanics approach, the experiments were also used to construct effective failure curves for each material composition. It was demonstrated that the fracture modes observed in the different experiments could be reproduced in the computations. The results show that increasing the TiB2 particle volume fraction to 10% results in an increase in material effective yield stress and a decrease in hardening. For a particle volume fraction of 15%, the effective yield stress decreases with no significant influence on the hardening slope. The ductility (workability) of the composite decreases with increasing particle volume fraction.

Reverse engineering the Milky Way

ABSTRACT The ages, metallicities, alpha-elements, and integrals of motion of globular clusters (GCs) accreted by the Milky Way from disrupted satellites remain largely unchanged over time. Here we have used these conserved properties in combination to assign 76 GCs to five progenitor satellite galaxies – one of which we dub the Koala dwarf galaxy. We fit a leaky-box chemical enrichment model to the age–metallicity distribution of GCs, deriving the effective yield and the formation epoch of each satellite. Based on scaling relations of GC counts we estimate the original halo mass, stellar mass, and mean metallicity of each satellite. The total stellar mass of the five accreted satellites contributed around 109 M⊙ in stars to the growth of the Milky Way but over 50 per cent of the Milky Way’s GC system. The five satellites formed at very early times and were likely accreted 8–11 Gyr ago, indicating rapid growth for the Milky Way in its early evolution. We suggest that at least three satellites were originally nucleated, with the remnant nucleus now a GC of the Milky Way. 11 GCs are also identified as having formed ex situ but could not be assigned to a single progenitor satellite.