Re: i hate to S.T.A.N. you but.....

[Guest guest]

Hahaha! Great!

GG

>

> in 1975 at my junior high they got all the students in the auditorium (this

> is before the days of the cafetorium!) and the dept head of the math dept

> told all of us that " the whole world is going to the metric system in 1980 "

and

> if we don't learn it " we all will be garbagemen "

>

> give 'em 2.54cm and they will take 1.609km "

>

> jim davis

>

>

>

> >

> > Subject: Re: UMMM hasn't this been done?

> > To: " Texas EMS L " <texasems-l@yahoogrotexasem>

> > Date: Wednesday, June 18, 2008, 12:58 AM

> > Ugh computers will solve all our problems and by 2000 we

> > will live in a paperless society. Explains why I buy paper

> > by the pallet load at my office!

> >

> > LNM from Baku, AZ

> > - UMMM hasn't this been done?

> >

> > ScienceDaily (Jun. 17, 2008) — Every extra second it

> > takes an ambulance to get to its destination can mean life

> > or death. But how, besides driving faster, can ambulances

> > get emergency services to people in need as efficiently as

> > possible, every day? It's a classic operations research

> > question that three Cornell researchers are tackling in

> > groundbreaking ways.

> >

> > A National Science Foundation grant of almost $300,000 is

> > allowing associate professor of operations research Shane

> > , assistant professor of operations research

> > Huseyin Topaloglu and applied mathematics Ph.D. student

> > Mateo Restrepo to work on this problem. They are seeking to

> > perfect a computer program that estimates how best to spread

> > ambulances across a municipality to get maximum coverage at

> > all times.

> >

> > The researchers are working on a computerized approach to

> > take such available information as historical trends of

> > types and incidences of calls, geographical layout and

> > real-time locations of ambulances to figure out where

> > ambulance bases should be, and where ambulances should be

> > sent once finished with a call.

> >

> > The whole process is not unlike the puzzle game Tetris,

> > Restrepo said. The easy part is knowing what an ideal

> > system should look like. The hard part is anticipating

> > various outcomes in a limited period of time, like the

> > falling blocks in the video game.

> > Using their program, the researchers are recommending

> > that ambulance organizations break the traditional setup of

> > assigning ambulance crews to various bases and sending them

> > back to their assigned locations once finished with a call.

> >

> > Going back to base isn't necessarily the best option

> > for maximum efficiency, say the operations researchers. It

> > might be better to redeploy an idle ambulance to where

> > coverage is lacking, even though no calls have yet been

> > placed there.

> > " If everyone is constantly going back to the base

> > assigned, they're ignoring what's going on in real

> > time in the system, " explained. The concept

> > is easy enough, but the solution is tricky, especially

> > because of the enormous amount of uncertainty involved.

> >

> > The field of operations research that deals with making

> > decisions over time in the face of uncertainty is called

> > dynamic programming, in which Topaloglu is an expert. The

> > key is coming up with what's called a value function, a

> > mathematical construction that estimates the impact of a

> > current decision on the future evolution of the system. In

> > this case, it's the impact of current ambulance

> > locations on the number of future calls that are served on

> > time.

> > " When you're trying to make a decision, you have

> > to select the locations of your ambulances so the

> > performance predicted by the value function is as good as

> > possible, " Topaloglu explained. " But it turns out

> > that computing that function is very difficult, especially

> > if you're talking about the scale of the problem

> > we're trying to solve. "

> >

> > has more than 10 years of experience working on

> > such problems, using a technique called simulation

> > optimization, which is modeling different scenarios of what

> > could happen in any given industrial system.

> >

> > He and a colleague have already commercialized an earlier

> > generation of emergency medical system planning, which now

> > forms the basis for the technology used by the New Zealand

> > ambulance company Optima.

> >

> >

> > The comments contained in this correspondence are the sole

> > responsibility of the author. They do not necessarily

> > reflect the thoughts, feelings, or opinions of my employer,

> > or any other group or organization that I may be, am

> > perceived to be, have been or will be involved with in the

> > future. They are my own comments, submitted freely and they

> > are worth exactly what you paid for them.

> >

> >

> >

[Guest guest]

in 1975 at my junior high they got all the students in the auditorium (this is

before the days of the cafetorium!) and the dept head of the math dept told all

of us that " the whole world is going to the metric system in 1980 " and if we

don't learn it " we all will be garbagemen "

give 'em 2.54cm and they will take 1.609km "

jim davis

>

> Subject: Re: UMMM hasn't this been done?

> To: " Texas EMS L " <texasems-l >

> Date: Wednesday, June 18, 2008, 12:58 AM

> Ugh computers will solve all our problems and by 2000 we

> will live in a paperless society. Explains why I buy paper

> by the pallet load at my office!

>

> LNM from Baku, AZ

> - UMMM hasn't this been done?

>

> ScienceDaily (Jun. 17, 2008) — Every extra second it

> takes an ambulance to get to its destination can mean life

> or death. But how, besides driving faster, can ambulances

> get emergency services to people in need as efficiently as

> possible, every day? It's a classic operations research

> question that three Cornell researchers are tackling in

> groundbreaking ways.

>

> A National Science Foundation grant of almost $300,000 is

> allowing associate professor of operations research Shane

> , assistant professor of operations research

> Huseyin Topaloglu and applied mathematics Ph.D. student

> Mateo Restrepo to work on this problem. They are seeking to

> perfect a computer program that estimates how best to spread

> ambulances across a municipality to get maximum coverage at

> all times.

>

> The researchers are working on a computerized approach to

> take such available information as historical trends of

> types and incidences of calls, geographical layout and

> real-time locations of ambulances to figure out where

> ambulance bases should be, and where ambulances should be

> sent once finished with a call.

>

> The whole process is not unlike the puzzle game Tetris,

> Restrepo said. The easy part is knowing what an ideal

> system should look like. The hard part is anticipating

> various outcomes in a limited period of time, like the

> falling blocks in the video game.

> Using their program, the researchers are recommending

> that ambulance organizations break the traditional setup of

> assigning ambulance crews to various bases and sending them

> back to their assigned locations once finished with a call.

>

> Going back to base isn't necessarily the best option

> for maximum efficiency, say the operations researchers. It

> might be better to redeploy an idle ambulance to where

> coverage is lacking, even though no calls have yet been

> placed there.

> " If everyone is constantly going back to the base

> assigned, they're ignoring what's going on in real

> time in the system, " explained. The concept

> is easy enough, but the solution is tricky, especially

> because of the enormous amount of uncertainty involved.

>

> The field of operations research that deals with making

> decisions over time in the face of uncertainty is called

> dynamic programming, in which Topaloglu is an expert. The

> key is coming up with what's called a value function, a

> mathematical construction that estimates the impact of a

> current decision on the future evolution of the system. In

> this case, it's the impact of current ambulance

> locations on the number of future calls that are served on

> time.

> " When you're trying to make a decision, you have

> to select the locations of your ambulances so the

> performance predicted by the value function is as good as

> possible, " Topaloglu explained. " But it turns out

> that computing that function is very difficult, especially

> if you're talking about the scale of the problem

> we're trying to solve. "

>

> has more than 10 years of experience working on

> such problems, using a technique called simulation

> optimization, which is modeling different scenarios of what

> could happen in any given industrial system.

>

> He and a colleague have already commercialized an earlier

> generation of emergency medical system planning, which now

> forms the basis for the technology used by the New Zealand

> ambulance company Optima.

>

>

> The comments contained in this correspondence are the sole

> responsibility of the author. They do not necessarily

> reflect the thoughts, feelings, or opinions of my employer,

> or any other group or organization that I may be, am

> perceived to be, have been or will be involved with in the

> future. They are my own comments, submitted freely and they

> are worth exactly what you paid for them.

>

>

>

[Guest guest]

True re metrics I too heard that and while I was taught the system in grade

school and JR high I like most paid no attention. That's hurt me as a 43 year

old fire protection consultant who refers to a " deuce and a half " to the blank

stare of my students until I refer to the 70 mm line. So here I am in Asia with

cheat sheets and converters galore.

LNM from Baku, AZ

Sent via BlackBerry by AT & T

UMMM hasn't this been done?

> >

> > ScienceDaily (Jun. 17, 2008) — Every extra second it

> > takes an ambulance to get to its destination can mean life

> > or death. But how, besides driving faster, can ambulances

> > get emergency services to people in need as efficiently as

> > possible, every day? It's a classic operations research

> > question that three Cornell researchers are tackling in

> > groundbreaking ways.

> >

> > A National Science Foundation grant of almost $300,000 is

> > allowing associate professor of operations research Shane

> > , assistant professor of operations research

> > Huseyin Topaloglu and applied mathematics Ph.D. student

> > Mateo Restrepo to work on this problem. They are seeking to

> > perfect a computer program that estimates how best to spread

> > ambulances across a municipality to get maximum coverage at

> > all times.

> >

> > The researchers are working on a computerized approach to

> > take such available information as historical trends of

> > types and incidences of calls, geographical layout and

> > real-time locations of ambulances to figure out where

> > ambulance bases should be, and where ambulances should be

> > sent once finished with a call.

> >

> > The whole process is not unlike the puzzle game Tetris,

> > Restrepo said. The easy part is knowing what an ideal

> > system should look like. The hard part is anticipating

> > various outcomes in a limited period of time, like the

> > falling blocks in the video game.

> > Using their program, the researchers are recommending

> > that ambulance organizations break the traditional setup of

> > assigning ambulance crews to various bases and sending them

> > back to their assigned locations once finished with a call.

> >

> > Going back to base isn't necessarily the best option

> > for maximum efficiency, say the operations researchers. It

> > might be better to redeploy an idle ambulance to where

> > coverage is lacking, even though no calls have yet been

> > placed there.

> > " If everyone is constantly going back to the base

> > assigned, they're ignoring what's going on in real

> > time in the system, " explained. The concept

> > is easy enough, but the solution is tricky, especially

> > because of the enormous amount of uncertainty involved.

> >

> > The field of operations research that deals with making

> > decisions over time in the face of uncertainty is called

> > dynamic programming, in which Topaloglu is an expert. The

> > key is coming up with what's called a value function, a

> > mathematical construction that estimates the impact of a

> > current decision on the future evolution of the system. In

> > this case, it's the impact of current ambulance

> > locations on the number of future calls that are served on

> > time.

> > " When you're trying to make a decision, you have

> > to select the locations of your ambulances so the

> > performance predicted by the value function is as good as

> > possible, " Topaloglu explained. " But it turns out

> > that computing that function is very difficult, especially

> > if you're talking about the scale of the problem

> > we're trying to solve. "

> >

> > has more than 10 years of experience working on

> > such problems, using a technique called simulation

> > optimization, which is modeling different scenarios of what

> > could happen in any given industrial system.

> >

> > He and a colleague have already commercialized an earlier

> > generation of emergency medical system planning, which now

> > forms the basis for the technology used by the New Zealand

> > ambulance company Optima.

> >

> >

> > The comments contained in this correspondence are the sole

> > responsibility of the author. They do not necessarily

> > reflect the thoughts, feelings, or opinions of my employer,

> > or any other group or organization that I may be, am

> > perceived to be, have been or will be involved with in the

> > future. They are my own comments, submitted freely and they

> > are worth exactly what you paid for them.

> >

> >

> >