A New Way to Predict Flight Delays

Coming home for thanksgiving break, I found myself stuck at the Richmond airport for 10 hours more than I had planned for. Our flight had been delayed, and I arrived in Boston at 2 in the morning instead of the original 4 PM. However, recently, researchers from Binghamton University in New York have created a revolutionary computer model that can accurately predict flight delays quickly. This model could potentially save travelers, like myself, hours of time before arriving at the airport.

The current method for predicting flight delays uses artificial neural network computer models, otherwise known as ANNs. Sina Khanmohammadi, leading the study, notes that their "proposed method is better suited to analyze datasets with categorical variables (qualitative variables such as weather or security risks instead of numerical ones) related to flight delays" (ScienceDaily). ANN models contain nodes that take in variables and predict outcomes through analyzing these variables. Through previous data, ANNs can look for patterns and are self- learning. Nevertheless, these networks can also be backfilled with data from previous flights and this can slow the process of flight delay predictions, causing delays to be reported later than desired.

This new research has created a new ANN to help airlines easily determine the relationships between input like weather or previous delays and output- the flight delays themselves. The method analyzes fourteen variables. When the team used the model to predict delays for hypothetical flights expected to land at JFK airport in New York City on January 21st, they found the model predicted delay length with "20 percent more accuracy" and took "40 percent less time" to reach those conclusions (EconomicTimes). They found that previous delays causing a chain reaction of delays were the biggest causes of late arrivals. In fact, that was one of the causes for my own delay last Tuesday. Not only will this new information be useful to fliers, but it can also help airline companies retain their customers and efficiently compensate for delayed flights.

References:
Content:
https://www.sciencedaily.com/releases/2016/11/161114103905.htm
http://economictimes.indiatimes.com/news/science/researchers-find-faster-way-to-predict-flight-delays/articleshow/55432529.cms
https://www.bupipedream.com/news/75742/auto-draft-171/

Images:
http://www.newsx.com/sites/default/files/styles/home_image/public/field/image/Researchers-find-faster-way-to-predict-flight-delays.jpg?itok=uqpIdhIG
http://image.slidesharecdn.com/final-141219125424-conversion-gate01/95/airline-flights-delay-prediction-2014-spring-data-mining-project-3-638.jpg?cb=1418993788

Insect Biobots and Drones Used to Map Disaster Areas

After a disaster, it can be dangerous for humans to enter an unknown and potentially unsafe area. This is why researchers at North Carolina State University developed the technology to use unmanned aerial vehicles, or drones, and insect biobots to enter these unknown places and inspect and map the areas. This technology would work well in areas such as a collapsed building, where gps can't be used. It can also help to locate stranded people and animals after disasters, to map out paths to reach them, and to determine how structurally safe certain paths may be compared to other ones.

The biobots these researchers have developed take the form of insects, like cockroaches. The job of the UAV's (the drones) is to contain and guide the biobots to the areas of interest. The drone hovers over the area, sending out a strong radio signal to contain the biobots. These bugbots are created by equipping cockroaches with sensors hooked up to their antennae and cerci, located on the front and back of the bug, respectively. Researchers can remotely stimulate these appendages to steer and drive the cockroaches. In this system, the biobots would be allowed to run freely through an area, with the beacon from the drone keeping the bugs in close proximity so they only map the desired area.

A specially designed algorithm takes the sensor data the biobots collect and translate it into a map of the area. The drone then changes locations, bringing along the bugbots, and the same process is repeated. The software can stitch multiple maps together, creating a comprehensive overview of the area. Co-author of the study Edgar Lobaton says that "We had previously developed proof-of-concept software that allowed us to map small areas with biobots, but this work allows us to map much larger areas and to stitch those maps together" (newatlas).

References:
Content:
http://newatlas.com/drones-cyborg-cockroaches-map-buildings/46510/
http://www.innovationtoronto.com/2016/11/using-uavs-and-insect-cyborgs-to-map-disaster-areas/
https://www.sciencedaily.com/releases/2016/11/161117104402.htm
Images:
https://images.sciencedaily.com/2016/11/161117104402_1_900x600.jpg
http://images.natureworldnews.com/data/images/full/36593/drones-and-insect-biobots-can-now-map-high-risk-disaster-areas.jpg

Cookies Are Not Just a Dessert!!

While cookies are delicious, you may have heard them in the context of computers before. Cookies are messages/ pieces of text that a web server passes to your web browser and stores on your hard disk when you visit an internet site. The web server can later go and retrieve the information, which can include content about a user's specific visit to a website (for example, items a customer has placed in a shopping cart), or content a user has volunteered about themselves or entered previously into a form (like a name, address, or credit card number). The messages stored on your machine are in small text files that include name-value pairs. The website that created the cookie is the only one that can access and read it later, and it cannot access any other information on your hard disk.

You can access and view all of the cookies stored on your computer by looking at the directory where a web browser holds this information. You can also manipulate the settings on your computer to have control over the process of websites storing name-value pairs on your computer.

The website How Stuff Works provides a good overview of how the cookie data moves:
First, when you visit any website, your web browser will contact a website's server for the specific page you are requesting. Your browser will simultaneously look on your own hard disk for a text file that the website has previously set. If it finds a cookie file, it will send this information to the server alongside the request for the page. If you have never visited a website before, you most likely will not have any cookie data stored on your computer for that site. In this case, the server will not receive any cookie data and will usually create a new ID for you, the new user, in it's database, and sends this information to your machine which stores it on your computer. The web server can alter the data it stores on your hard disk whenever you visit it's website.

Websites use cookies to remember what state your browser was in, gather information of how many people are visiting their site and what they are doing on it, to store user preferences or customize a site for a specific visitor, and more. There has been some concerns about issues with privacy and security that come with the introduction of cookies. The main issues are that some companies can sell your information to other third party companies that want to sell you similar things, making customer targeting precise. Also, some infrastructure providers, like DoubleClick, create cookies visible on multiple sites, gathering information about you from many different places and developing a detailed profile of you. These companies serve ads on so many sites, and it's scary to some people that they have the power to link these detailed profiles of the users to names and personalize the profiles.

References:
Content:
http://computer.howstuffworks.com/cookie1.htm
https://kb.iu.edu/d/agwm
https://en.wikipedia.org/wiki/HTTP_cookie

Images:
https://cldup.com/_d6DG7yyR8.png
http://www.webopedia.com/DidYouKnow/Images/051807_cookies001.jpg
https://www.grc.com/cookies/browser4.png

Secret Messages in Dance Music??

Have you ever wondered if there was a hidden message in the song you were dancing to? Well, there very well might be. A Polish man named Krysztof Szczypiorski from the Warsaw University of Technology has created a new form of cryptography. He has created an algorithm that can encode and decode secret messages in dance music. These messages are virtually undetectable by the human ear. Szczypiorski has named his program "StegIbiza." "Steg" stands for steganography, which is basically hiding hidden messages in plain sight. Audio steganography is not a new concept; throughout history notes have been used to spell out hidden messages in different ways. However, Szczypiorski's form of steganography is unique.

Szczypiorski uses variation in tempo embedded in various club dance style songs to encrypt his messages. The tempo changes are so subtle that professional musicians, when asked to listen for the message, could only detect the changes when the tempo was altered by two and three percents. The tempo changes act as a "digital morse code;" when the tempo is sped up, it represents a dot, while slowing down the tempo represents a dash. Szczypiorski's algorithm can detect the changes in tempo, decoding the message.

While this algorithm may not be revolutionary or change any lives, it is a pretty cool way to send hidden messages through music.

References:
Content:
http://blogs.discovermagazine.com/d-brief/2016/08/24/algorithm-weaves-secret-messages-into-dance-music/#.WBzhUOErKRs
http://idmmag.com/news/hidden-messages-dance-music/
http://www.pcworld.com/article/3109281/a-new-algorithm-can-hide-messages-in-your-favorite-dance-music.html

Images:
http://www.pcworld.com/article/3109281/a-new-algorithm-can-hide-messages-in-your-favorite-dance-music.html
http://blogs.discovermagazine.com/d-brief/files/2016/08/shutterstock_268477412.jpg