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DeepER tool uses deep learning to better allocate emergency services

#artificialintelligence

BEGIN ARTICLE PREVIEW: BINGHAMTON, NY — Emergencies, by their very nature, are hard to predict. When and where the next crime, fire or vehicle accident will happen is often a matter of random chance. What can be measured, however, is how long it takes for emergency services personnel to consider a particular incident to be resolved — for instance, suspects apprehended, flames extinguished or damaged cars removed from the street. New York City is among the large urban areas that maintain those kinds of statistics, and a team of researchers at Binghamton University, State University of New York has used deep-learning techniques to analyze the numbers and suggest improved public safety through re-allocation of resources. Arti Ramesh and Anand Seetharam — both assistant professors in the Department of Computer Science at the Thomas J. Watson College of Engineering and Applied Science — worked with PhD students Gissella Bejarano, MS &


Machine learning research may aid industry

#artificialintelligence

What do these topics have in common? The answer can be found in machine learning research at Binghamton University. Dana Bani-Hani, a doctoral student studying industrial and systems engineering, has spent the past few years teaching machines how to read data sets in any industry. The system she coded, called a Recursive General Regression Neural Network Oracle (R-GRNN Oracle), takes data inputs and creates prediction outputs. Classification models are not new in data science and analytics, but what Bani-Hani created goes beyond the basics.


An Algorithm that identifies Bullies on Twitter with 90% accuracy. - Analytics Jobs

#artificialintelligence

New York: Machine learning algorithms have been developed by scientists which can predict bullying and aggressors on Twitter with 90% accuracy. The study analyzed the behavioral patterns showed by abusive Twitter users as well as the differences of theirs from various other Twitter users. "Tweets of twitter users have been gathered along with their profiles, and social network-related things like who they follow, who follows them," said Jeremy Blackburn, Binghamton University. The scientists created algorithms to automatically classify 2 specific kinds of offensive online behavior, i.e. cyberbullying and cyberaggression. The algorithms could determine abusive users on Twitter with accuracy up to 90%, scientists said.


New algorithm can distinguish cyberbullies from normal Twitter users with 90% accuracy

#artificialintelligence

A team of researchers, including faculty at Binghamton University, have developed machine learning algorithms which can successfully identify bullies and aggressors on Twitter with 90 percent accuracy. Effective tools for detecting harmful actions on social media are scarce, as this type of behavior is often ambiguous in nature and/or exhibited via seemingly superficial comments and criticisms. Aiming to address this gap, a research team featuring Binghamton University computer scientist Jeremy Blackburn analyzed the behavioral patterns exhibited by abusive Twitter users and their differences from other Twitter users. "We built crawlers--programs that collect data from Twitter via variety of mechanisms," said Blackburn. "We gathered tweets of Twitter users, their profiles, as well as (social) network-related things, like who they follow and who follows them."


New algorithm can distinguish cyberbullies from normal Twitter users with 90% accuracy

#artificialintelligence

Effective tools for detecting harmful actions on social media are scarce, as this type of behavior is often ambiguous in nature and/or exhibited via seemingly superficial comments and criticisms. Aiming to address this gap, a research team featuring Binghamton University computer scientist Jeremy Blackburn analyzed the behavioral patterns exhibited by abusive Twitter users and their differences from other Twitter users. "We built crawlers -- programs that collect data from Twitter via variety of mechanisms," said Blackburn. "We gathered tweets of Twitter users, their profiles, as well as (social) network-related things, like who they follow and who follows them." The researchers then performed natural language processing and sentiment analysis on the tweets themselves, as well as a variety of social network analyses on the connections between users.


College students are the next generation of disruptors out to change the game

Mashable

One of the most obvious changes is in food. Dining halls are moving far beyond standard fare, working with students and local partners to devise healthy and diverse options. Some are incorporating the lessons of Silicon Valley by introducing on-demand and delivery services – with at least one using robots for those deliveries. Binghamton University has partnered with a local Indian restaurateur to offer authentic dishes, with a website that offers students directions to local halal and Asian grocers. The University of Coventry in the UK has brought in a truck that offers vegan food.


American Link flight simulators win Britain's top computer conservation award

ZDNet

TechWorks has won the Tony Sale Award for bringing back to life a Second World War analogue flight simulator, a 1960s-era General Aviation Trainer (GAT-1), and an all-digital Super GAT trainer from the 1980s. The three pioneering pilot trainers are available to visitors to the TechWorks museum in Binghamton in New York State. Britain's Computer Conservation Society holds a competition for the Tony Sale Award every other year to remember the man who, among other things, led the reconstruction of the Colossus computer hosted at The National Museum of Computing (TNMOC) at Bletchley Park, north of London. Also: Hitler's "unbreakable" encryption machine -- and the Bletchley Park devices which cracked the code Binghamton has been described as "the birthplace of Virtual Reality" because it is where Ed Link built the first Link flight simulator. Link's father owned a pipe organ and player piano factory, and Link -- who already knew how to fly -- thought that bouncing on an organ bellows was a bit like flying.


Why women are better at online dating

Daily Mail - Science & tech

Men are far more aggressive on online dating sites - but often'mass mail' women that are out of their league in the hope of a response, researchers have found. They say that by comparison, women tend to be more conscious of their own attractiveness to other users and approach fewer people. The study found major behavioural differences between male and female users when it comes to contacting potential partners. The researchers say men are far more aggressive on online dating sites - but often'mass mail' women that are out of their league in the hope of a response, researchers have found. Using data collected from Baihe, one of the largest dating websites in China, researchers from Binghamton University, University of Massachusetts Lowell and Northeastern University analysed the messages and how suitable each person actually was.