Collaborating Authors

Metals & Mining

WA to spend AU$1 million to divert 1,000 tonnes of e-waste per year


Western Australia has announced it will invest AU$1 million into nine initiatives that are aimed at reducing e-waste. The AU$1 million investment will come out of the state's AU$16.7 million New Industries Fund, and is expected to divert approximately 1,000 tonnes of e-waste annually from landfill. "The selected projects will support the recovery of high value material, while diverting materials which may have presented risks to human health and the environment if not disposed of appropriately," Environment Minister Stephen Dawson added. Among the grant recipients are Curtin University, the Commonwealth Scientific and Industrial Research Organisation (CSIRO), and Epichem, which are all set to receive AU$200,000 apiece for their respective projects. Curtin University will use the funds to create a mini plant for recycling and metal recovery from printed circuit boards and integrated circuits; CSIRO will develop "innovative biotechnology" for extracting precious and base metals from e-waste; and Epichem has agreed to test whether oxidative hydrothermal dissolution can break down e-waste to produce a range of useful chemicals.

#326: Deep Sea Mining, with Benjamin Pietro Filardo


In this episode, Abate follows up with Benjamin Pietro Filardo, founder of Pliant Energy Systems and NACROM, the North American Consortium for Responsible Ocean Mining. Pietro discusses the current proposed solutions for deep sea mining which are environmentally destructive, and he offers an alternative solution using swarm robots which could mine the depths of the ocean while creating minimal disturbance to this mysterious habitat. Benjamin "Pietro" Filardo After several years in the architectural profession, Pietro founded Pliant Energy Systems to explore renewable energy concepts he first pondered while earning his first degree in marine biology and oceanography. With funding from four federal agencies he has broadened the application of these concepts into marine propulsion and a highly novel robotics platform.

The deep sea discoveries of 2020 are stunning


This spring, in a canyon over 2,000 feet beneath the Indian Ocean surface, a robot happened upon a fantastical, coiled creature. This siphonophore, found laying like loosely piled rope on the seabed, might be the longest animal ever discovered. The discovery, made by scientists aboard the R/V Falkor, a vessel operated by the marine research organization the Schmidt Ocean Institute, was one of many unique sightings in, or newly published research about, the deep sea this year. The worst pandemic in a century may have canceled many marine expeditions, but discoveries in the ocean deep -- abetted by robotic explorers -- continued apace in 2020. Marine scientists candidly admit humanity has "barely scratched the surface" of what transpires in the ocean's "twilight zone," a place extending some 660 to 3,300 feet below the surface.

Women in Robotics Update: Robin Murphy, Ayanna Howard


Robin Murphy (featured in 2013), is the Raytheon Professor of Computer Science and Engineering in Texas A & M and Director of the non-profit Humanitarian Robotics and AI Laboratory, (formerly known as Center for Robot-Assisted Search and Rescue (CRASAR). She is a distinguished Disaster Roboticist pioneering the advancement of AI and mobile robotics in unstructured and extreme environments. At CRASAR, she has been actively supplying her rescue robot since 9/11 in 2001 and has now participated in more than 30 disasters which include building collapses, earthquakes, floods, hurricanes, marine mass casualty events, nuclear accidents, tsunamis, underground mine explosions, and volcanic eruptions, in five different countries. And she has developed and taught classes in robotics for emergency response and public safety for over 1,000 members of 30 agencies from seven countries.

Sundance joins Digital Catapult's Machine Intelligence Garage AI/ML incubator


Sundance Multiprocessor Technology has joined Digital Catapult's Machine Intelligence Garage business incubator, in a move that will help to deepen its expertise in the deployment of AI (artificial intelligence) and ML (machine learning) techniques across a diverse range of embedded systems applications. In addition to Sundance's embedded platforms optimised for running deep learning algorithms used for performing autonomous navigation and other computer vision applications, these companies are working on a range of applications that include video analytics for improved livestock welfare management, solutions for reducing greenhouse emissions, interactive podcasting and neural networking. Digital Catapult is the UK's advanced digital technology innovation centre and connects start-up and scaleup companies with large businesses, investors, government and public organisations, and research and academia. Its Machine Intelligence Garage aims to provide support in the AI/ML arena as well as provide access to the compute-intensive power needed by these enterprises to develop and test their models. It is delivered as part of London's CAP-AI project and is part funded through the European Regional Development Fund. "We started the Machine Intelligence Garage to address the challenges the UK's promising early stage AI and ML companies face, accelerating their growth and helping them realise their true potential by providing access to high-level computational power, relevant expertise, mentoring and networking opportunities," said Jeremy Silver, CEO of Digital Catapult.

Towards Coinductive Models for Natural Language Understanding. Bringing together Deep Learning and Deep Semantics Artificial Intelligence

This article contains a proposal to add coinduction to the computational apparatus of natural language understanding. This, we argue, will provide a basis for more realistic, computationally sound, and scalable models of natural language dialogue, syntax and semantics. Given that the bottom up, inductively constructed, semantic and syntactic structures are brittle, and seemingly incapable of adequately representing the meaning of longer sentences or realistic dialogues, natural language understanding is in need of a new foundation. Coinduction, which uses top down constraints, has been successfully used in the design of operating systems and programming languages. Moreover, implicitly it has been present in text mining, machine translation, and in some attempts to model intensionality and modalities, which provides evidence that it works. This article shows high level formalizations of some of such uses. Since coinduction and induction can coexist, they can provide a common language and a conceptual model for research in natural language understanding. In particular, such an opportunity seems to be emerging in research on compositionality. This article shows several examples of the joint appearance of induction and coinduction in natural language processing. We argue that the known individual limitations of induction and coinduction can be overcome in empirical settings by a combination of the the two methods. We see an open problem in providing a theory of their joint use.

Over a Decade of Social Opinion Mining Artificial Intelligence

Social media popularity and importance is on the increase, due to people using it for various types of social interaction across multiple channels. This social interaction by online users includes submission of feedback, opinions and recommendations about various individuals, entities, topics, and events. This systematic review focuses on the evolving research area of Social Opinion Mining, tasked with the identification of multiple opinion dimensions, such as subjectivity, sentiment polarity, emotion, affect, sarcasm and irony, from user-generated content represented across multiple social media platforms and in various media formats, like text, image, video and audio. Therefore, through Social Opinion Mining, natural language can be understood in terms of the different opinion dimensions, as expressed by humans. This contributes towards the evolution of Artificial Intelligence, which in turn helps the advancement of several real-world use cases, such as customer service and decision making. A thorough systematic review was carried out on Social Opinion Mining research which totals 485 studies and spans a period of twelve years between 2007 and 2018. The in-depth analysis focuses on the social media platforms, techniques, social datasets, language, modality, tools and technologies, natural language processing tasks and other aspects derived from the published studies. Such multi-source information fusion plays a fundamental role in mining of people's social opinions from social media platforms. These can be utilised in many application areas, ranging from marketing, advertising and sales for product/service management, and in multiple domains and industries, such as politics, technology, finance, healthcare, sports and government. Future research directions are presented, whereas further research and development has the potential of leaving a wider academic and societal impact.

Spectroscopy and Chemometrics News Weekly #47, 2020


NIR Calibration-Model Services Spectroscopy and Chemometrics News Weekly 46, 2020 NIRS NIR Spectroscopy MachineLearning Spectrometer Spectrometric Analytical Chemistry foodindustry Analysis Lab Laboratories Laboratory Software IoT Sensors QA QC Testing Quality LINK Get the Spectroscopy and Chemometrics News Weekly in real time on Twitter @ CalibModel and follow us. Near-Infrared Spectroscopy (NIRS) "Near infrared absorption spectroscopy for the quantification of unsulfated alcohol in sodium lauryl ether sulfate" LINK "Estimation of Organic Carbon in Anthropogenic Soil by VIS-NIR Spectroscopy: Effect of Variable Selection" LINK "Near infrared spectroscopy (NIRS) based high-throughput online assay for key cell wall features that determine sugarcane bagasse digestibility") LINK "Authentication of barley-finished beef using visible and near infrared spectroscopy (Vis-NIRS) and different discrimination approaches" LINK "Energetic Distribution of States in Irradiated Low-Density ...

Windfall Geotek (TSXV: WIN)


Windfall Geotek (formerly Albert Mining) is a Canadian corporation offering a proven and industry-leading digital platform leveraging Artificial Intelligence (AI) technologies to significantly improve outcomes in the exploration, development, operations and financing of geologically focused projects. Principal markets encompass the global resource mining industry including virtually all forms of mineralization including oil and gas exploration. Recent advances have led to the detection of water sources and aquifers especially in drought regions, and of anti-personnel landmines and related deadly legacy hazards in conflict zones. Our applied machine learning technology offers a revolutionary approach to geologic discovery and a markedly positive economic impact on operational efficiencies. Since 2004 our Company has added value to over 30 client discoveries and more than 80 target generation projects around the globe.

Predictive AI Provides Update on Sales Process and Pipeline


Predictiv AI Inc. (TSX VENTURE: PAI) (OTC: INOTF) (FRANKFURT: 71TA) ("Predictiv AI" or the "Company"),, a software and solutions provider in the artificial intelligence and industrial IoT markets, is pleased to provide a sales update on ThermalPass, Predictiv AI is delivering units, against five initial orders, over the next 45 days. The initial customer base consists of a wide cross-section of businesses and organizations which include a convention center, a hospital, a mining company, two manufacturing plants and a leading industrial conglomerate. The internal sales and marketing team has also built an extensive pipeline since ThermalPass' commercial launch 30 days ago. In addition, the Company has entered into seven strategic reseller contracts with established sales channels in Canada, the United States and Europe.