I bet this one goes thru a much
shorter model cycle than the previous iteration, not 7 but 5 years.
Not exact matches
Swirling about him are
Model 3 production issues, three investigations between two federal organizations, and a near never - ending
cycle of new, grander ideas and plans that often buoy the stock in the
short term, while threatening to further sap the company of much - needed cash down the line.
The physics of stellar interiors are input into the computer
model and the entire star's life
cycle is simulated in a
short time.
It was
short to be able to put a six - year
cycle plan together, to work out what you're going to do with the brand, to work out what the business
model looks like and then to go fund it, it was tight.
A
short production run, complex manufacturing processes and a rushed development
cycle meant that some
models experienced a few issues, which are worth taking note of.
And it came quite quickly as well, considering the ninth - gen
model only ran a total of four years — a very
short life
cycle for a car as raved about as the Accord.
In that sense all analysis of stock market based on historical metrics do nt make much sense since composition of stocks is entirely different in different era and as more capital efficient business
model evolve and their time to market
cycle shrinks stocks likely to command higher valuations and suddenly lower valuations during
short period of time like already happening for many technology companies and as influence of technology on overall cost structure of companies increases (for example: robotics replace many of employees cost etc) valuation matrix of most companies likely to get affected dynamically in
short duration of time than in the past.
My opinion is that they're able to reuse several assets from SSB4, which used HD
models after all, and that's how they're going to have achieved it in such a
short development
cycle.
For Kiefer, Khlebnikov's 317 - year
cycle is useful in that it allows him to depict these broken 20th - century vessels in the light of naval engagements, long sea journeys, shipping losses and the battles of the past - in
short, to acknowledge both the human and the historical scale of past events, and their place in our larger
models of the world.
The methodology and analysis that followed are therefore useful guidelines for regional monitoring programs which suggest that
short, regular profiling of different eco-regions supplemented by fine - scale meteorological
modelling can be sufficient to characterize the regional dynamics of the carbon
cycle.
I would have liked to see mention of uncertainty that inherent in examining
short term data, whether the end points used introduces an element of bias, whether the «pause» is on a much higher plateau of warming than in the past, whether decadel
cycles in ocean heat displacement may have interacted with the the known minimum levels of solar activity (not
modelled) to cause this «pause».
The HCS tilt angle
model depends only on the solar
cycle phase and describes the cyclic behaviour of the HCS tilt angle, reflecting its asymmetric shape, with
short length and fast ascending phase in contrast to the gradual descending phase.
Firstly, even with man - made global warming taken into account, because of the
short - term noise due to the internal variability in the climate system, climate
models predict that there will be decades where natural
cycles dampen the man - made warming trend.
The emission data were converted to concentration data, using a selected simple carbon -
cycle climate
model for well - mixed greenhouse gases and an atmospheric chemistry
model for reactive
short - lived substances.
Second, using measured atmospheric CO2 concentrations
short circuits two layers of
modeling which themselves are major sources of uncertainty, namely, estimating global emissions and, then, estimating the atmospheric CO2 concentrations (based on complex
models of the global carbon
cycle).