Step 1: Find the normalization constants.
For \( f(x) \) to be a valid probability density function, we must have:
\[
\int_0^1 ax^2 \, dx + \int_1^\infty bx^{-4} \, dx = 1.
\]
First, solve for \( a \):
\[
\int_0^1 ax^2 \, dx = \frac{a}{3}, \quad \int_1^\infty bx^{-4} \, dx = \frac{b}{3}.
\]
Thus,
\[
\frac{a}{3} + \frac{b}{3} = 1 \quad \Rightarrow \quad a + b = 3.
\]
Step 2: Calculate \( E(X^2) \).
The expected value \( E(X^2) \) is given by:
\[
E(X^2) = \int_0^1 ax^4 \, dx + \int_1^\infty bx^{-2} \, dx.
\]
First, solve for each integral:
\[
\int_0^1 ax^4 \, dx = \frac{a}{5}, \quad \int_1^\infty bx^{-2} \, dx = \frac{b}{1}.
\]
Thus,
\[
E(X^2) = \frac{a}{5} + b.
\]
Substitute \( b = 3 - a \) into the equation:
\[
E(X^2) = \frac{a}{5} + (3 - a).
\]
Step 3: Use the condition \( E(X) = 1 \).
We know that \( E(X) = 1 \), so we can use the equation for \( E(X) \) to find \( a \) and \( b \). The calculation yields \( a = 2 \) and \( b = 1 \), so:
\[
E(X^2) = \frac{2}{5} + 1 = \frac{7}{5}.
\]
Final Answer:
\[
\boxed{\frac{7}{5}}.
\]