NAE electees, Electoral College, social media

Three INFORMS members elected to National Academy of Engineering

Three INFORMS members are among those elected to the National Academy of Engineering’s class of 2017. They include:

Arkadi Nemirovski, John Hunter Chair and Professor, H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, for “the development of efficient algorithms for large-scale convex optimization problems.”

Sridhar R. Tayur, Ford Distinguished Research Chair Professor of Operations Management, Tepper School of Business, Carnegie Mellon University, Pittsburgh, for “developing and commercializing innovative methods to optimize supply chain systems.”

Election to the National Academy of Engineering is among the highest professional distinctions accorded to an engineer. Academy membership honors those who have made outstanding contributions to “engineering research, practice or education, including, where appropriate, significant contributions to the engineering literature” and to “the pioneering of new and developing fields of technology, making major advancements in traditional fields of engineering or developing/ implementing innovative approaches to engineering education.”

Electoral College put to the math test following 2016 U.S. presidential election

While political pundits continue to rehash the respective 2016 U.S. presidential campaign, almost all of us can agree on two things: Hillary Clinton won the national popular vote by nearly three million votes, and Donald Trump won the Electoral College vote and thus the presidency.

The discrepancy caused some people to take a closer look at the Electoral College and its state-by-state, largely winner-take-all format and question whether there could be a better method for selecting the president of the United States. MIT professor Arnold Barnett and Yale University professor Ed Kaplan, both longtime members of INFORMS (Kaplan served as president of the organization in 2016), were among those with inquiring minds.

In a Dec. 16, 2016 article (“How to cure the Electoral College”) in the Los Angeles Times, Barnett and Kaplan proposed an “electoral vote equivalents” (EQV) system in which electoral votes are allocated “in direct proportion to each candidate’s share” of each state’s popular vote.” The authors argue that not only would the EQV system make every vote in every state important, but it would also increase the importance of less-populated states, which was one of the main objectives of the Founding Fathers when they created the Electoral College in the first place.

Rather than repealing the Electoral College, Barnett and Kaplan say the EQV system would strengthen it by bringing every state into play in the general election, including electorate vote-rich California, Texas and New York, which are mostly ignored during presidential campaigns today because the winners of those states are a foregone conclusion. According to the authors, the EQV system would also increase the clout of small-population states because they tend to vote more lopsidedly than the nation as a whole, which pays off when the percentage of the margin of victory within a state matters.

Would the EQV system have made a difference in this election? Yes, it would have awarded the presidency to Hillary, say the authors. But as Trump noted, if the rules of the game had been different, he would have changed his campaign strategy.

How social media data mining could shape the products of tomorrow

Researchers at Nottingham Trent University have developed a way to analyze online consumer reviews and social media to help designers create better informed products. Led by design engineering expert professor Daizhong Su, a research team used data mining techniques and produced an algorithm that identifies the most liked and disliked features of existing products, according to thousands of consumer comments on websites such as Amazon, eBay, Facebook, YouTube and online stores.

The approach – developed using big data, data mining and related Internet technologies – detects keywords using automated online searches and informs designers of the successes and flaws of any given product. “At our fingertips is an array of data which tells us the strengths and weaknesses of almost every product in the world,” Su says. “We’ve developed a way to harness this valuable information and created a powerful approach that could change the way we think about design. It has the potential to make tomorrow’s products more innovative, user-friendly, sustainable and better informed of user requirements.”

After keywords are entered, the computer program learns on its own and categorizes reviews, giving a breakdown of positive and negative comments on various products and their features. It also learns to disregard spam comments.

To test the technology, the team designed a desk lamp as a case study based on more than a thousand comments on existing designs on the market. The results showed that consumers liked desk lamps which were small, adjustable, bright but with a dimmer, that included a touch function and more. Dislikes included unstable bases, poor reliability, dullness and excessive heat. This feedback was used to set a range of specifications for a design to achieve. The final design included an on/off switch that controlled brightness, a sustainable bamboo base and LED casing, and a brushed aluminum neck with an adjustable arm.