Virtual Reality (VR) can cause an unprecedented immersion and feeling of presence yet a lot of users experience motion sickness when moving through a virtual environment. Rollercoaster rides are popular in Virtual Reality but have to be well designed to limit the amount of nausea the user may feel. This paper describes a novel framework to get automated ratings on motion sickness using Neural Networks. An application that lets users create rollercoasters directly in VR, share them with other users and ride and rate them is used to gather real-time data related to the in-game behaviour of the player, the track itself and users' ratings based on a Simulator Sickness Questionnaire (SSQ) integrated into the application. Machine learning architectures based on deep neural networks are trained using this data aiming to predict motion sickness levels. While this paper focuses on rollercoasters this framework could help to rate any VR application on motion sickness and intensity that involves camera movement. A new well defined dataset is provided in this paper and the performance of the proposed architectures are evaluated in a comparative study.

Fake news detection is a critical yet challenging problem in Natural Language Processing (NLP). The rapid rise of social networking platforms has not only yielded a vast increase in information accessibility but has also accelerated the spread of fake news. Given the massive amount of Web content, automatic fake news detection is a practical NLP problem required by all online content providers. This paper presents a survey on fake news detection. Our survey introduces the challenges of automatic fake news detection. We systematically review the datasets and NLP solutions that have been developed for this task. We also discuss the limits of these datasets and problem formulations, our insights, and recommended solutions.

Netflix has finally arrived on Sky Q, allowing the two companies to team up for what they say is the ultimate on demand package. The partnership will allow people to watch Netflix shows like any other box set on their Sky box. But it will also be fully integrated, meaning that new series will appear as recommendations on the homepage. And the two subscriptions will be tied together, too, allowing people to pay for their Netflix subscription through their Sky bill and tie the two offerings together for cheaper than they would be separately. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

Move aside, Chanel No. 5. Scientists have now created a scent that's even older than the iconic perfume, even if it has only just wafted into human nostrils for the first time in more than 100 years. That's because the piney, earthy perfume derives its fragrance compounds from a Hawaiian hibiscus flower that vanished from the dry-land forests of Maui in the early 1910s. Researchers at Ginkgo Bioworks, one of the largest synthetic-biology companies in world, succeeded in resurrecting the smell by expressing the genes needed for making the defunct flower's pungent aroma molecules in microbes. Ginkgo unveiled--and demoed--the new perfume at the company's inaugural annual meeting in Boston last week. It's like "Jurassic Park, but for perfume," says Ginkgo's creative director, Christina Agapakis.

Last summer, the actor Jay Duplass found himself in the middle of a lush forest in Washington state, his body struggling under the weight of a giant space-helmet. The actor was filming scenes for the sci-fi drama Prospect, in which he plays a planet-scavenger hoping to get rich. Duplass' otherworldly get-up--like nearly all of the film's costume and props--had been designed and hand-made by a team of earthbound artists. But while his beat-up headgear looked cool, wearing it was "a goddamn nightmare," the actor says. Those helmets are not designed to be worn all day, or walked around in.

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The same story also disclosed allegations of sexual misconduct of other executives, including Richard DeVaul, a director at the same Google-affiliated lab that created far-flung projects such as self-driving cars and internet-beaming balloons. DeVaul had remained at the "X'' lab after allegations of sexual misconduct surfaced about him a few years ago, but he resigned Tuesday without severance, Google confirmed Wednesday.

Your face gets wonkier as you age, research suggests. Scientists have found the structure of your facial features deviate by 0.06mm with each decade of life. Researchers at Mount Auburn Hospital, Massachusetts, used three-dimensional digital imaging techniques to make the conclusion. The changes were subtle but significant, especially in the lower two-thirds of the face - from the eyebrows to nose and from the nose to chin. Dr Helena Taylor performed detailed scans of 191 volunteers who ranged in age from four months to 88 years.

Fake news are nowadays an issue of pressing concern, given their recent rise as a potential threat to high-quality journalism and well-informed public discourse. The Fake News Challenge (FNC-1) was organized in 2017 to encourage the development of machine learning-based classification systems for stance detection (i.e., for identifying whether a particular news article agrees, disagrees, discusses, or is unrelated to a particular news headline), thus helping in the detection and analysis of possible instances of fake news. This article presents a new approach to tackle this stance detection problem, based on the combination of string similarity features with a deep neural architecture that leverages ideas previously advanced in the context of learning efficient text representations, document classification, and natural language inference. Specifically, we use bi-directional Recurrent Neural Networks, together with max-pooling over the temporal/sequential dimension and neural attention, for representing (i) the headline, (ii) the first two sentences of the news article, and (iii) the entire news article. These representations are then combined/compared, complemented with similarity features inspired on other FNC-1 approaches, and passed to a final layer that predicts the stance of the article towards the headline. We also explore the use of external sources of information, specifically large datasets of sentence pairs originally proposed for training and evaluating natural language inference methods, in order to pre-train specific components of the neural network architecture (e.g., the RNNs used for encoding sentences). The obtained results attest to the effectiveness of the proposed ideas and show that our model, particularly when considering pre-training and the combination of neural representations together with similarity features, slightly outperforms the previous state-of-the-art.

ABSTRACT The recent success of raw audio waveform synthesis models like WaveNet motivates a new approach for music synthesis, in which the entire process -- creating audio samples from a score and instrument information -- is modeled using generative neural networks. This paper describes a neural music synthesis model with flexible timbre controls, which consists of a recurrent neural network conditioned on a learned instrument embedding followed by a WaveNet vocoder. The learned embedding space successfully captures the diverse variations in timbres within a large dataset and enables timbre control and morphing by interpolating between instruments in the embedding space. The synthesis quality is evaluated both numerically and perceptually, and an interactive web demo is presented. Index Terms-- Music Synthesis, Timbre Embedding, WaveNet 1. INTRODUCTION Musical synthesis, most commonly, is the process of generating musical audio with given control parameters such as instrument type and note sequences over time.