Deep convolutional neural network for mill feed size characterization

Knowing the characteristics of the feed ore size is an important consideration for operations and control of a run-of-mine ore milling circuit. Large feed ore variations are important to detect as they require intervention, whether it be manual by the operator or by an automatic controller. A deep convolutional neural network is used in this work to classify the feed ore images into one of four classes. A VGG16 architecture is used and the classifier is trained making use of transfer learning.The National Research Foundation of South Africahttps://www.journals.elsevier.com/ifac-papersonlineam2020Electrical, Electronic and Computer Engineerin

Estimating ore particle size distribution using a deep convolutional neural network

In this work the ore particle size distribution is estimated from an input image of the ore. The normalized weight of ore in each of 10 size classes is reported with good accuracy. A deep convolutional neural network, making use of the VGG16 architecture, is deployed for this task. The goal of using this method is to achieve accurate results without the need for rigorous parameter selection, as is needed with traditional computer vision approaches to this problem. The feed ore particle size distribution has an impact on the performance and control of minerals processing operations. When the ore size distribution undergoes significant changes, operational intervention is usually required (either by the operator or by an automatic controller).The National Research Foundation of South Africahttps://www.journals.elsevier.com/ifac-papersonlinepm2021Electrical, Electronic and Computer Engineerin

Feed size distribution feedforward control for a grinding mill circuit

This paper proposes a method to measure and reject disturbances caused by changes in the ore distribution of the feed to a grinding mill circuit. A computer vision system is presented to measure the fraction of rocks in the feed, using only basic equipment and algorithms. A feedforward controller is designed to reject the measured feed size disturbance within the mill before causing further disturbances downstream. The feedforward controller is implemented in simulation to control a nonlinear mill model, and is compared to conventional feedback control. The allowable plant-model mismatch and practicality of feedforward control for industrial applications are investigated. It was found that feedforward control has a noticeable advantage over feedback control if well tuned. The most significant disturbance is the efficiency of the mill to break ore into fine material. Since this is not currently measured in real-time, it limits the performance of a feedforward controller in practice.https://www.journals.elsevier.com/ifac-papersonlinepm2020Electrical, Electronic and Computer Engineerin

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century