In the classical database management systems (DBMS) setting, a query Q is evaluated against a database D. However, it has come to the attention of the database community the necessity to also include ontological reasoning and description logics (DLs) along with standard database techniques (Calvanese et al. 2007). As such, the ontological database management systems (ODBMS) has arised. In ODBMS, the classical database is enhanced with an ontology (Baader et al. 2016) in the form of logical assertions that generate new intensional knowledge. An expressive form of such logical assertions is the so-called tuplegenerating dependencies (TGDs), i.e., Horn rules extended by allowing existential quantifiers to appear in the rule heads (Cabibbo 1998; Patel-Schneider and Horrocks 2007; Calì, Gottlob, and Lukasiewicz 2009). Queries are evaluated against a database D and set of TGDs Σ (i.e., D Σ) rather than just D, as in the classical setting. Since for a given database D, a set Σ of TGDs, and a conjunctive query Q, the problem of determining if D Σ Q, i.e., the conjunctive query answering (CQ-Ans) problem, is undecidable in general (Beeri and Vardi 1981; Baget et al. 2011; Rosati 2011; Calì, Gottlob, and Pieris 2012; Calì, Gottlob, and Kifer 2013), a major research effort has been put forth to identifying syntactic conditions on TGDs for which CQ-Ans is decidable.

Just over fifty years ago, a French journalist, Jean-Jacques Servan-Schreiber, published his book, Le Défi Américain (aka The American Challenge, 1967). It presented the United States and Europe as engaged in a silent economic war. In that war, he wrote, Europe was being completely outclassed on all fronts in dealing with the Third Industrial Revolution (electronics, information technology, and automation). The invading industrial armies of the day--1960s giants such as General Motors and IBM--were becoming dominant in Europe because of stronger and more flexible management techniques, technological tools, and research capacity. The book became an international hit, selling an unprecedented 600,000 copies in France alone.

Theresa May will pledge millions of pounds of government funding to develop artificial intelligence able to transform outcomes through early diagnosis of cancer and chronic disease. In a speech in Mansfield on Monday that is being billed as the first of a series on industrial strategy, May will say: "Late diagnosis of otherwise treatable illnesses is one of the biggest causes of avoidable deaths. "The development of smart technologies to analyse great quantities of data quickly and with a higher degree of accuracy than is possible by human beings, opens up a whole new field of medical research and gives us a new weapon in our armoury in the fight against disease." May wants industry and charities to work with the NHS to develop algorithms that can use patient data and lifestyle information to warn GPs when a patient should be referred to an oncologist or another specialist. The plans envisage at least 50,000 people being diagnosed at an early stage of prostate, ovarian, lung or bowel ...

He leads the High Level Group on Industrial Technologies, which on 24 April released a report called Re-finding industry – Defining Innovation to make recommendations on EU research and innovation priorities for industry in the next funding programme. Your report says that AI should be designated as a key enabling technology in the next funding programme, which means it is classed as a priority policy area. What does this mean in practice? 'Artificial intelligence is something relatively new and a field of strong competition, not only in the world, but also in Europe. It is therefore essential to find a common way ahead to encourage our research.

The diagnosis of cancer and other diseases in the UK can be transformed by using artificial intelligence, Theresa May is to say. The NHS and technology companies should use AI as a "new weapon" in research, the PM will urge in a speech later. Experts say it can be used to help prevent 22,000 cancer deaths a year by 2033 while aiding the fight against heart disease, diabetes and dementia. High-skilled science jobs will also be created, Mrs May is to pledge. Speaking in Macclesfield, Mrs May will say: "Late diagnosis of otherwise treatable illnesses is one of the biggest causes of avoidable deaths. "And the development of smart technologies to analyse great quantities of data quickly and with a higher degree of accuracy than is possible by human beings opens up a whole new field of medical research." The prime minister wants to see computer algorithms sifting through patients' medical records, genetic data and lifestyle habits to spot cancer. BBC health and science correspondent James Gallagher says Mrs May's plans do chime with excitement within medical science about the potential of using data and AI. But our correspondent added there are many challenges ahead including creating the right infrastructure within the health service, separating hype and genuine innovation and ensuring the public's highly personal data is used responsibly. Cancer Research UK says halving the number of lung, bowel, prostate and ovarian cancers diagnosed at an advanced stage could prevent thousands of deaths a year. Sir Harpal Kumar, chief executive officer of Cancer Research, described the government's plans as pioneering but added: "We need to ensure we have the right infrastructure, embedded in our health system, to make this possible." Simon Gillespie, chief executive at the British Heart Foundation, said: "Using artificial intelligence to analyse MRI scans could spot early signs of heart disease which may be missed by current techniques.

Are You an Ecologist or Conservationist Interested in Learning GIS and Machine Learning in R? Then this course is for you! I will take you on an adventure into the amazing of field Machine Learning and GIS for ecological modelling. You will learn how to implement species distribution modelling/map suitable habitats for species in R. My name is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience in analyzing real life spatial data from different sources and producing publications for international peer reviewed journals.

Helsinki University in Finland has launched a course on artificial intelligence -- one that's completely free and open to everyone around the world. Unlike Carnegie Mellon's new undergrad degree in AI, which the institution created to train future experts in the field, Helsinki's offering is more of a beginner course for those who want to know more about it. A lot of tech giants like Google now have divisions working on artificial intelligence projects, and even whole non-tech industries already depend on AI for various tasks. But as Janina Fagerlund from the university's project partner (tech strategy firm Reaktor) said, people might not know that their lives are already affected by AI every day. Fagerlund mentioned the use of AI in the food industry to sort produce and other items at facilities as an example.

Machine-learning algorithms accomplish tasks by training on a set of data, rather than being programmed by humans. Armed with the knowledge of what worked before, the system instructs the implant to stimulate users' brains to interrupt a seizure at its onset. The innovation is part of a larger phenomenon that has big implications for how we identify and treat disease: the introduction of artificial intelligence to consumer and clinical electronics. As machines learn from at times millions of humans, doctors are gaining the ability to better identify disease and even predict it before it becomes catastrophic. As in every other area of human endeavor, the introduction of AI to medicine comes with challenges.

A data-harvesting competition that offered football fans the chance to win £50m is at the centre of new questions about pro-Brexit campaigning before the 2016 EU referendum. Last week the select committee for digital, culture, media and sport released a letter Facebook sent to the Electoral Commission in which it said that two campaigns, Vote Leave and BeLeave, used three sets of data to target audiences, noting that they covered "the exact same audiences". The two campaign groups are under investigation over whether there was collusion and coordination during the referendum campaign, circumventing spending limits. Under British electoral law, it is illegal for campaigns to work together in any way unless they declare their spending jointly, which Vote Leave and BeLeave did not. Both organisations deny any collusion.

When Prince Harry and Meghan Markle say "I do" at their royal wedding, online viewers tuning into the Sky News stream will not have to guess the names of international celebrities and British nobility in attendance. Instead, the U.K. broadcaster will use artificial intelligence to identify famous guests as they make their grand entrances at St. George's Chapel at Windsor Castle -- displaying the invitees' names and details about how they are connected to the royal couple. Dubbed "Who's Who Live," Sky News announced the livestream service last week in partnership with Amazon.com and several data and engineering firms. As the 600 guests enter the chapel, Sky News will highlight notable attendees using Amazon Rekognition, a cloud-based technology that can recognize and compare faces in images and video using artificial intelligence. Along with identifying the wedding guests, the livestream service will also show facts about them, Sky News said, using captions and on-screen graphics through the company's app.