Author Archives: Greg Ginley

P4 – Conceptual Weaves

https://uc.box.com/s/u3mpcv00e3so5wmsp8zifqjhby4qh115

 

 

 

 

https://uc.box.com/s/yasqx4z7nrielk6dpa7mnf3ub2ooj49l

P1 – Urban Mobility Manifesto

P1 – URBAN MOBILITY INVOLVING THE MOBILE PHONE

Working document of Research organized by Article used

Define MOBILE:

-able to move or be moved freely or easily.

-relating to mobile phones, handheld computers, and similar technology.

“What makes mobility complex is that it is full of interactions. Interactions between pedestrians, between cars, between buses, between trains, between vehicles and infrastructure.” (Gershenson)

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Works Used

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https://www.ridester.com/how-much-do-uber-drivers-make/

 

-Uber claims to give drivers an advertised rate of 25 dollars per hour but is this true?

-Between 2010 and 2014 the number of drivers with operating ridesharing apps rose by 69% and in 2015 it rose 63%.  

I now question Uber’s $25 per hour claims of drivers pulling in six figures a year, so I decided to do some personal digging.

-After asking around, our team found that more often than not, the earnings these drivers pull in fall well below their expectations, and there seems to be a bit of confusion as to how much Uber drivers get paid.

-A survey was conducted to find of the actual wage of drivers

-The 2014 data allowed us to see that the median was 90,766 a year.

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Gershenson, Carlos. “Improving Urban Mobility by Understanding Its Complexity.

https://arxiv.org/ftp/arxiv/papers/1603/1603.04267.pdf

 

-Technology advances in the world of city advances

-A computer engineer explores the the concept of utilizing his skills of simulations and scientific methods to develop recommendations to create a smarter city

-The interactions on our commutes is what makes the modern city a challenge

-”These interactions make it difficult to separate the components of a complex system. Traditional scientific and engineering methods rely on separability, and thus we need to use novel approaches. If we cannot study components individually, we need to model at the same time two levels of abstraction: the component level and the system level. “

-Predictability is limited in these complex systems

-Information is produced by interactions

-we will be more efficient if we build adaptive systems that can adjust to the current situation at the same scale as it changes.

-Factors that affect urban mobility

  • transportation requirements (living far from workplace or school)
  • schedule distribution (if everyone has to be at the same place at the same time, the demand concentrates during rush hours)
  • quantity (of passengers, vehicles)
  • capacity (of public transport, infrastructure)
  • technology (efficiency of infrastructure)
  • planning and regulation (to avoid undesired situations, although they must be enforced)
  • social contagion (if owning a private vehicle is seen as a sign of “success”)
  • human behavior (of passengers and drivers) We have most control of, MOOD

-Gershenson goes into how we do what we can get away with and for a commute to work we are more in favor of our individual needs

-Technology like cameras are put into place to punish bad behavior of drivers

-In other cases, policies are simply not understood by the public, making it difficult to achieve their adoption. If citizens are aware of the benefit their actions will have, they shall be more inclined to adopt a specific regulation.

 

His Solutions in my own words:

    • Adaptations over Prediction: We have to adapt our urban solutions to laws and changes that succeed based on previous fails. Our past record of events are our teacher for the future, so instead of making predictions off graphs, we should solve the problem and then analyze to see if it was successful

 

  • Regulate interactions: Efficiency can be achieved by limiting the interactions between components of the urban system. When a driver stops at a red light an interaction has initiated with the driver and the color of the stop light. This is overcome in some circumstances with the “roundabout,” bridges, or underground highways. These solutions are much more complex but because the technology is available they are considered efficient for their location. For example, traveling through downtown Cincinnati and into Newport would take many hours without the complex highway paths strategically organized to limit interactions between drivers.
  • Use Sensors: A driver or pedestrian should be able to unknowingly benefit from our technology. Sensors and cameras can be erected to yield drivers and pedestrians data via their phones or onboard entertainment panels. Imagine driving or walking and getting updates on your route due to a subscription and thus saving time and taking other routes. Human radio and news teams do this but a computer could virtually do the job quicker.

 

 

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http://blog.indeed.com/2017/07/27/the-unstoppable-rise-of-mobile-job-search/

Mobile Jobs

 

The Unstoppable Rise of Mobile Job Search: What Employers Need to Know

 

77% of adults in the United States own a smartphone, while the numbers climb as high as 92% in the 18-29 age range.

  • Millennials – 78% used mobile devices to find jobs as of  2016
    • 3/4ths of my peers used their phone while I’m sure others used a computer
  • Gen Xers – 73% searching for work on mobile devices.
  • Baby Boomers – have seen the highest increase in mobile job search among the three generations, with around 57.2% of Boomers active in 2016, up from just 51.2% in 2014.
    • I believe that the Baby Boomers are adapting to the Phone-Era and overcoming the learning curve to benefit from today’s technology.
  • Companies that do not list their careers and positions on Amobile form are reducing their probability of hiring talent.
  • Job seekers in Korea, Taiwan, and Japan take the top spots for using mobile devices to find jobs, with more than 80% of job searches originating from mobile devices in each country.
  • More than half of the total job searches originate from mobile phones

Highest job searches of fields on mobile phones

  • 80.28% – Maintenance
  • 79.79% – construction and extraction
  • 57.13% – business and legal jobs
  • 52.55% – architecture and engineering
  • 45.28% – computer and mathematical

France and Poland are the only exceptions in countries that search for jobs on a desktop and not a mobile phone.

 


 

 

 

P2 – Bus Stops and Lines

 Frequency Chart                                           Formal Map                                         Go Metro Lines info