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Partial Functional Dependency Indicates that if A and B are attributes of a table , B is partially dependent on A if there is some attribute that can be removed from A and yet the dependency still holds. Say for Ex, consider the following functional dependency that exists in the Tbl_Staff table: StaffID,Name -------> BranchID BranchID is functionally dependent on a subset of A (StaffID,Name), namely StaffID. Source :http://www.mahipalreddy.com/dbdesign/dbqa.htm

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Q: What is Partial function?

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The lagrange function, commonly denoted L is the lagrangian of a system. Usually it is the kinetic energy - potential energy (in the case of a particle in a conservative potential). The lagrange equation is the equation that converts a given lagrangian into a system of equations of motion. It is d/dt(\partial L/\partial qdot)-\partial L/\partial q.

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Differentials can be used to approximate a nonlinear function as a linear function. They can be used as a "factory" to quickly find partial derivatives. They can be used to test if a function is smooth.

Partial differential equations are mathematical equations that involve two or more independent variables, an unknown function, and partial derivatives of the unknown function. Even the explanation is confusing! If, however, anyone chooses to learn about PDE there are classes offered at any institution of higher learning.

Partial in mathematics can refer to:Partial derivatives (derivative of a function with respect to a specific variable, others being held constant)A partial functionPartial can also refer to the regular English usage (referring to an isolated part of the whole).

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It releases a juice called saliva which lubricates the food and aids in partial digestion of starch.

Say you have a function of a single variable, f(x). Then there is no ambiguity about what you are taking the derivative with respect to (it is always with respect to x). But what if I have a function of a few variables, f(x,y,z)? Now, I can take the derivative with respect to x, y, or z. These are "partial" derivatives, because we are only interested in how the function varies w.r.t. a single variable, assuming that the other variables are independent and "frozen". e.g., Question: how does f vary with respect to y? Answer: (partial f/partial y) Now, what if our function again depends on a few variables, but these variables themselves depend on time: x(t), y(t), z(t) --> f(x(t),y(t),z(t))? Again, we might ask how f varies w.r.t. one of the variables x,y,z, in which case we would use partial derivatives. If we ask how f varies with respect to t, we would do the following: df/dt = (partial f/partial x)*dx/dt + (partial f/partial y)*dy/dt + (partial f/partial z)*dz/dt df/dt is known as the "total" derivative, which essentially uses the chain rule to drop the assumption that the other variables are "frozen" while taking the derivative. This framework is especially useful in physical problems where I might want to consider spatial variations of a function (partial derivatives), as well as the total variation in time (total derivative).

The divergence of the function is generally a cross product of partial derivatives and the vector field of F. Mathematically, the formula is: div(F) = ∂P/∂x i + ∂Q/∂y j + ∂R/∂z k where: F = Pi + Qj + Rk has the continuous partial derivatives.

A partial derivative is the derivative of a function of more than one variable with respect to only one variable. When taking a partial derivative, the other variables are treated as constants. For example, the partial derivative of the function f(x,y)=2x2 + 3xy + y2 with respect to x is:?f/?x = 4x + 3yhere we can see that y terms have been treated as constants when differentiating.The partial derivative of f(x,y) with respect to y is:?f/?y = 3x + 2yand here, x terms have been treated as constants.

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in case of partial differentiation , suppose a z is a function of x and y so in partial differentiation of z w.r.t x all other variables except x are considered to be constant but on the contrary in differentiation process they are not considered as constant unless stated .

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