Answer:
COMMON ENGINEERING DOCUMENTS
Inspection or trip reports.
Research, laboratory, and field reports.
Specifications.
Proposals.
Progress reports.
ect...
Explanation:
Answer:
= -0.303 KW
Explanation:
This is the case of unsteady flow process because properties are changing with time.
From first law of thermodynamics for unsteady flow process
Given that tank is insulated so
and no mass is leaving so
Mass conservation 
is the initial and final mass in the system respectively.
Initially tank is evacuated so 
We know that for air 
,
So now putting values
= -0.303 KW
Features of Multidimensional scaling(MDS) from scratch is described below.
Explanation:
Multidimensional scaling (MDS) is a way to reduce the dimensionality of data to visualize it. We basically want to project our (likely highly dimensional) data into a lower dimensional space and preserve the distances between points.
If we have some highly complex data that we project into some lower N dimensions, we will assign each point from our data a coordinate in this lower dimensional space, and the idea is that these N dimensional coordinates are ordered based on their ability to capture variance in the data. Since we can only visualize things in 2D, this is why it is common to assess your MDS based on plotting the first and second dimension of the output.
If you look at the output of an MDS algorithm, which will be points in 2D or 3D space, the distances represent similarity. So very close points = very similar, and points farther away from one another = less similar.
Working of MDS
The input to the MDS algorithm is our proximity matrix. There are two kinds of classical MDS that we could use: Classical (metric) MDS is for data that has metric properties, like actual distances from a map or calculated from a vector
.Nonmetric MDS is for more ordinal data (such as human-provided similarity ratings) for which we can say a 1 is more similar than a 2, but there is no defined (metric) distance between the values of 1 and 2.
Uses
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset. MDS is used to translate "information about the pairwise 'distances' among a set of n objects or individuals" into a configuration of n points mapped into an abstract Cartesian space.
Answer:
2.65 MPa
Explanation:
To find the normal stress (σ) in the wall of the basketball we need to use the following equation:
<u>Where:</u>
p: is the gage pressure = 108 kPa
r: is the inner radius of the ball
t: is the thickness = 3 mm
Hence, we need to find r, as follows:
<u>Where:</u>
d: is the outer diameter = 300 mm
Now, we can find the normal stress (σ) in the wall of the basketball:
Therefore, the normal stress is 2.65 MPa.
I hope it helps you!
