Look Up In My Bag Say More Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Mashable @Home Trending Now Mashable Selects Top creators, ranked Gift Ideas For Everyone On Your List Creator Playbook AI at School Safety Net All Series Jimmy Kimmel responds to Trump calling him a'loser' Sam Haysom is the General Assignment Editor, UK, for Mashable. He covers entertainment and online culture, and writes horror fiction in his spare time. Rosie O'Donnell calls out'Mango Mussolini' Trump on'Kimmel' Jimmy Kimmel calls out Fox's reaction to a'joke' from him versus one from Trump Jimmy Kimmel responds to Anthropic researcher saying'AI could kill us all by the end of the decade' Jimmy Kimmel recaps Trump's summer with a montage of the weirdest things he's said Jimmy Kimmel has incurred the wrath of the president once again, this time after comments he made about a recent Trump rally with empty seats. In the clip above the host plays footage of the president moaning about his remarks before calling him a loser. Of all the many things I said about him last week - of all the many moronic and criminal words and deeds I detailed - that's what bothers him?

Mashable Selects Mashable's Best: E-readers, robovacs, laptops, earbuds, smart home and more Creator Playbook Look Up Back to School Say More Trending Now Good Connection: Uplifting stories for a digital age Switch Off Mashable Voices Safety Net Versus All Series Could there be a better metaphor for this presidency?' Sam Haysom is the General Assignment Editor, UK, for Mashable. He covers entertainment and online culture, and writes horror fiction in his spare time. Rosie O'Donnell calls out'Mango Mussolini' Trump on'Kimmel' 'Daily Show' recaps all the excuses Republicans are making not to attend Trump's convention Jimmy Kimmel has the perfect joke to sum up Trump's Iran deal Jimmy Kimmel recaps Trump's summer with a montage of the weirdest things he's said Trump held a midterm convention in Texas on Wednesday, and attendance levels were already looking a bit shaky based on the number of Republicans making excuses about why they wouldn't be able to go. Could there be a better metaphor for this presidency than him bragging about the size of his crowd to a bunch of empty seats? When does the kid come out and inform the emperor that he has no clothes?

There are many entities that disseminate in the physical space - information, gossip, mood, innovation etc. Personal spaces are also entities that disperse and interplay. In this work we study the emergence of configurations formed by participants when choosing a place to sit in a rectangular auditorium. Based on experimental questionnaire data we design several models and assess their relevancy to a real time-lapse footage of lecture hall being filled up. The main focus is to compare the evolution of entropy of occupied seat configurations in time. Even though the process of choosing a seat is complex and could depend on various properties of participants or environment, some of the developed models can capture at least basic essence of the real processes. After introducing the problem of seat selection and related results in close research areas, we introduce preliminary collected data and build models of seat selection based on them. We compare the resulting models to the real observational data and discuss areas of future research directions.

It's been 15 years since a degenerative eye disease forced Erich Manser to stop driving. Today, he commutes to his job as an accessibility consultant via commuter trains and city buses, but he has trouble locating empty seats sometimes and must ask strangers for guidance. A step toward solving Manser's predicament could arrive as soon as next year. Manser's employer, IBM, and an independent carmaker called Local Motors are developing a self-driving, electric shuttle bus that combines artificial intelligence, augmented reality, and smartphone apps to serve people with vision, hearing, physical, and cognitive disabilities. The buses, dubbed "Olli," are designed to transport people around neighborhoods at speeds below 35 miles per hour and will be sold to cities, counties, airports, companies, and universities.

School choice programs are implemented to give students/parents an opportunity to choose the public school the students attend. Controlled school choice programs need to provide choices for students/parents while maintaining distributional constraints on the composition of students, typically in terms of socioeconomic status. Previous works show that setting soft-bounds, which flexibly change the priorities of students based on their types, is more appropriate than setting hard-bounds, which strictly limit the number of accepted students for each type. We consider a case where soft-bounds are imposed and one student can belong to multiple types, e.g., financially-distressed and minority types. We first show that when we apply a model that is a straightforward extension of an existing model for disjoint types, there is a chance that no stable matching exists. Thus we propose an alternative model and an alternative stability definition, where a school has reserved seats for each type. We show that a stable matching is guaranteed to exist in this model and develop a mechanism called Deferred Acceptance for Overlapping Types (DA-OT). The DA-OT mechanism is strategy-proof and obtains the student-optimal matching within all stable matchings. Furthermore, we introduce an extended model that can handle both type-specific ceilings and floors and propose a extended mechanism DA-OT* to handle the extended model. Computer simulation results illustrate that DA-OT outperforms an artificial cap mechanism where we set a hard-bound for each type in each school. DA-OT* can achieve stability in the extended model without sacrificing students welfare.

School choice programs are implemented to give students/parents an opportunity to choose the public school the students attend. Controlled school choice programs need to provide choices for students/parents while maintaining distributional constraints on the balance on the composition of students, typically in terms of socioeconomic status. Previous works show that setting soft-bounds, which flexibly change the priorities of students based on their types, is more appropriate than setting hard-bounds, which strictly limit the number of accepted students for each type. We consider a case where soft-bounds are imposed and one student can belong to multiple types, e.g., ``financially-distressed'' and ``minority'' types. We first show that when we apply a model that is a straightforward extension of an existing model for disjoint types, there is a chance that no stable matching exists. Thus, we propose an alternative model and an alternative stability definition, where a school has reserved seats for each type. We show that a stable matching is guaranteed to exist in this model, and develop a mechanism called Deferred Acceptance for Overlapping Types (DA-OT). The DA-OT mechanism is strategy-proof and obtains the student-optimal matching within all stable matchings. Computer simulation results illustrate that the DA-OT outperforms an artificial cap mechanism, where the number of seats for each type is fixed.