In this paper, we present a visual emulator of the emotions seen in characters in stories. This system is based on a simplified view of the cognitive structure of emotions proposed by Ortony, Clore and Collins (OCC Model). The goal of this paper is to provide a visual platform that allows us to observe changes in the characters' different emotions, and the intricate interrelationships between: 1) each character's emotions, 2) their affective relationships and actions, 3) The events that take place in the development of a plot, and 4) the objects of desire that make up the emotional map of any story. This tool was tested on stories with a contrasting variety of emotional and affective environments: Othello, Twilight, and Harry Potter, behaving sensibly and in keeping with the atmosphere in which the characters were immersed.

As shown in Example 11.20, we compile our dense sentiment classifier with a line of code that should already be familiar from recent chapters, except that--because we have a single output neuron within a binary classifier--we use binary_crossentropy cost in place of the categorical_crossentropy cost we used for our multiclass MNIST classifiers.

"Slaughterbots" directed by Stewart Sugg In a dystopian world a new form of A.I. weaponry has been created. All these drone bots need is a profile: age, sex, fitness, uniform, and ethnicity. Take out your entire enemy virtually risk free. Just characterize him, release the swarm, and rest easy. The 7 minute film opens with a Silicon Valley CEO-type delivering a product presentation to a live audience a la Steve Jobs.

Hattie, nicknamed'Tinder Granny' by the press, explains why she's quitting the popular dating app on WETV's'Extreme Love.' At age 83, Hattie is no longer on the prowl for one-night stands. The grandmother of three, famously nicknamed "Tinder Granny" by the press for her voracious appetite of younger men and love of swiping right to prospective suitors, is the subject of WETV's reality show "Extreme Love," which explores how traditional ideas of love are reimagined across the country. She previously appeared in the 2012 documentary "Extreme Cougar Wives." "I never considered what I do to be extreme," Hattie told Fox News.

The second generation of Google's smallest smart speaker gets a new name, more eco-friendly, a little smarter and more bass. The £49 Nest Mini replaces the Google Home Mini as part of a revamped and renamed line of Google smart home products under the Nest brand, pushing its predecessor to a clearance price of only £19. From the outside you would be hard pushed to see what has changed. The Nest Mini sticks with the same pincushion design with a fabric top and nonslip rubber pad on the bottom. The top contains three far-field microphones and is touch sensitive.

Warner Bros. has unveiled a wild new plan to use Cinelytic's AI technology to streamline the process of getting movies greenlit, Engadget reports. The aim is to make the process quicker and easier for executives, but it could influence which films actually make it onto the big screen. While the AI system won't have the final say on whether a movie goes into production or not, it will determine a project's financial risk. The system will analyze revenue potential, evaluate the value of a film's stars, and find an optimal release date. The move was reportedly reached in order to reduce "low-value, repetitive tasks" usually carried about by executives.

In recent years, Markov logic networks (MLNs) have been proposed as a potentially useful paradigm for music signal analysis. Because all hidden Markov models can be reformulated as MLNs, the latter can provide an all-encompassing framework that reuses and extends previous work in the field. However, just because it is theoretically possible to reformulate previous work as MLNs, does not mean that it is advantageous. In this paper, we analyse some proposed examples of MLNs for musical analysis and consider their practical disadvantages when compared to formulating the same musical dependence relationships as (dynamic) Bayesian networks. We argue that a number of practical hurdles such as the lack of support for sequences and for arbitrary continuous probability distributions make MLNs less than ideal for the proposed musical applications, both in terms of easy of formulation and computational requirements due to their required inference algorithms. These conclusions are not specific to music, but apply to other fields as well, especially when sequential data with continuous observations is involved. Finally, we show that the ideas underlying the proposed examples can be expressed perfectly well in the more commonly used framework of (dynamic) Bayesian networks.

Whether enjoying the lucid prose of a favorite author or slogging through some other writer's cumbersome, heavy-set prattle (full of parentheses, em dashes, compound adjectives, and Oxford commas), readers will notice stylistic signatures not only in word choice and grammar, but also in punctuation itself. Indeed, visual sequences of punctuation from different authors produce marvelously different (and visually striking) sequences. Punctuation is a largely overlooked stylistic feature in "stylometry", the quantitative analysis of written text. In this paper, we examine punctuation sequences in a corpus of literary documents and ask the following questions: Are the properties of such sequences a distinctive feature of different authors? Is it possible to distinguish literary genres based on their punctuation sequences? Do the punctuation styles of authors evolve over time? Are we on to something interesting in trying to do stylometry without words, or are we full of sound and fury (signifying nothing)?

In the fall of 2015, celebrated visual effects whiz Pablo Helman was in Taiwan celebrating Thanksgiving with Martin Scorsese. The 24-year veteran of Industrial Light & Magic, the company founded by George Lucas at the onset of the Star Wars franchise, was midway through production on the director's Jesuit missionary saga, Silence, for which Helman had to digitally re-create the enormity of St. Paul's College of Macau. But over holiday dinner, Scorsese began pitching Helman on a different film entirely. It was another adaption, this one based on I Heard You Paint Houses, Charles Brandt's biography of mob hit man and supposed Jimmy Hoffa murderer Frank Sheeran. Much like Silence, the story was expansive, though instead of spanning geography (Portugal to Japan), the movie would stretch across years (approximately seven decades).