2011-2012 Research Projects@Hunter

1. 2011-2012 Research Projects@Hunter contributed by Prof Felisa Vázquez-Abad Department of Computer Science Hunter College Felisa Vázquez-Abad

2. Our Research Mathematical Models: understanding relations and dynamics Computer Simulation: virtual reality and experimentation Optimization: decision making, management and “learning” Statistics: Analysis and computer learning Felisa Vázquez-Abad

3. On Public Transport A system for “collective taxis” Is the public bike system suitable for Manhattan?

4. How many idle taxis?How long the wait? Felisa Vázquez-Abad

5. Collective Taxis • Work done for the Paris metropolitan area (show results of Lioris, Cohen and la Fortellez). • Control algorithms: sensors, data analytics, optimization • Computer Simulations to assess impact: • Idle times statistics, passenger delays, route statistics • Pricing methods • Environmental impact • Feasibility as alternative transportation system for five boroughs of NYC? Felisa Vázquez-Abad

6. Five Boroughs of New York Reduce trajectory length travelled per public transport vehicle Provide adequate service at reasonable prices, at low cost Environmental impact Felisa Vázquez-Abad

7. Extension: Central/Mixed control model • Central operation: read current traffic conditions and schedule vehicles • Reservations: handheld devices for communication (optimal allocation) • Optimization: acceptance of clients and reservation rules based on threshold policies (sensitivity analysis) • Economic modeling: study pricing models with priorities, relationship between cost and thresholds • Intelligence: IT-driven self-awareness Felisa Vázquez-Abad

8. The Public Bikes Are they suitable for Manhattan? Felisa Vázquez-Abad

9. How it works Short distance, shared bikes Membership for residents, or daily/weekly passes for tourists Any time, anywhere, for “free” Targets healthy population, movements within city centers Environmental impact, health impact, economic impact from shared resources Felisa Vázquez-Abad

10. Improving Public Bikes • Routing and information. Software development for information panels and to keep track of data: users patterns, financial info, bike’s data, etc. • Stations. Use optimization techniques to start with a simple plan with a view to grow: use current city developments. • Availability. Use simulations to assess flow patterns for users: centrifugal, centripetal or balanced demand. Develop learning algorithms. • Redistribution problem: Optimization algorithms for redistribution: intelligent incentives? • Vandalism. Use sensors to target individual bikes and control misuse. Learning algorithm to adapt. • Pricing. Use mathematical models to decide on a pricing system. Felisa Vázquez-Abad

11. On Public Health Emergency Departments Understanding the impact of generic drugs

12. Emergency Departments Doctors/nurses allocated to areas (low and high acuity), patients are directed to areas by the triage nurses Overcrowded, long waiting causes patient deterioration Technical improvements, staff and space are expensive Fast Track: a low cost alternative Felisa Vázquez-Abad

13. Standard Emergency Department Model p3 Discharge or admitted to another ward Triage p1 LA Non-trauma p6 p7 p2 HA p8 Trauma treatment Trauma p4 p5 Felisa Vázquez-Abad

14. Fast Track Emergency Department Model p4 Discharge or admitted to another ward p7 FT Triage p1 Non-trauma p8 p2 LA p9 p3 p10 Trauma treatment Trauma HA p11 p5 p6 Felisa Vázquez-Abad

15. Research Questions Testing in real hospitals: expensive and may be misleading. Does the FT decrease patient waiting times? What is the impact on patient health? Are the costs of operation significantly different? Is it suitable to all hospitals? What are the critical conditions of arriving patients that favor the use of a FT? How should resources be diverted to FT? Active resource management (machine learning) How would it integrate with the new health care system in our country? Felisa Vázquez-Abad

16. Generic Drugs Good or evil? Felisa Vázquez-Abad

17. Reasonable, isn’t it? • Brand names: pharmaceuticals charge high cost for their product • Generics are manufactured using same active ingredients, considerably cheaper • “In the long run, you save money if you buy generics” Felisa Vázquez-Abad

18. Reasonable, isn’t it? • Brand names: pharmaceuticals charge high cost for their product • Development: extensive testing (dose, vehicle…) • Generics are manufactured using same active ingredients, considerably cheaper • “In the long run, you save money if you buy generics” Felisa Vázquez-Abad

19. Reasonable, isn’t it? • Brand names: pharmaceuticals charge high cost for their product • Development: extensive testing (dose, vehicle…) • Generics are manufactured using same active ingredients, considerably cheaper • Not tested, manufactured cheaply • “In the long run, you save money if you buy generics” Felisa Vázquez-Abad

20. Reasonable, isn’t it? • Brand names: pharmaceuticals charge high cost for their product • Development: extensive testing (dose, vehicle…) • Generics are manufactured using same active ingredients, considerably cheaper • Not tested, manufactured cheaply • “In the long run, you save money if you buy generics” • Effectiveness, economic consequences, who pays? Felisa Vázquez-Abad

21. Scientific Approach Mathematical model for the financial process involving generics and brand names Scientific evidence of effectiveness Scientific evidence of real costs Statistical studies, interviews with medical professionals, real data Incorporate the role of insurance companies Incorporate the role of government and public health Felisa Vázquez-Abad

22. SuburbanMicrofarms A Sustainable Operating System for Sustenance Felisa Vázquez-Abad

23. The Problem We had all the answers, but the questions have changed • Food production technology, 20th Century • Oil: efficient energy production, speeds process, large scale • Mathematical models and profit-driven business • The IOSS and MacDonald • 50% World population in cities • From > 45% to < 3% Americans in agriculture in 4 decades (5 million needed in 2020) • Serious health, financial and environmental problems Felisa Vázquez-Abad

24. Minimize use of non-renewable energy (harvesting energy) • Fertilizers and composting • Plot size and scalability (complexity) • Small farms (motivate young people) • Community resilience (from the soil to the table) GINGER Microfarm“El Chilhuacle” in the suburbs of Melbourne, Australia An initiative by Ari Fainchtein

25. Computer Science, Mathematics, Optimization • Don’t go back to ancient farming • Ginger: a model for an Operating System (open data source) • New data structure and communication language • Current world connected via computers • Sensor technologies, internet: new models for supply chain • Going beyond into transformational discipline (academic degrees) A New Transformational Science “Because we have a Hammer, everything looks like a nail” Felisa Vázquez-Abad

26. Other Problems The Melbourne airport fleet: how many buses should they have? Why is the price of copper cyclic? Intelligent batteries for active energy management

27. Multidisciplinary projects for joint collaboration • CUNY ideally placed to get involved in community development • Research at all levels: never too soon, never too late to be creative Thank you! Felisa Vázquez-Abad