Answer:
look up the assignment number. its in the left side of the screen. its what i did when i had problems.
Explanation:
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:
<h2>True Most Especially in the field of Automotive Engineering</h2>
Explanation:
Normally, before the introduction of vehicle diagnostics when a vehicle, mostly automobile/car break down, one could be the vehicle mechanic would only suspect one or two related faults based on the present working condition of the car, the mechanic would perform some trial and error before he could fix the car.
But in recent times, the introduction of vehicle diagnostics devices and software has changed the order as vehicles can be connected to a computer that will scan and tell what the problem is before a possible fix.
Answer:
The shaft work generated per kilogram is 
Explanation:
Given:
Temperature 
K
Initial Pressure 
MPa
Final pressure 
MPa
From the table superheated,
and 
Work done by shaft is,
But here efficiency is 0.56,
So work generated per kg is,
Work = 
Work = 
Therefore, the shaft work generated per kilogram is
Answer:
A) attached below
B) Geostatic vertical effective stress ( бv )
= 119.33 KN/m^2
Geostatic horizontal effective stress ( бn )
= 59.66 KN/m^2
C) attached below
Explanation:
attached below is a detailed solution
A) attached below
B) Determine the geostatic vertical effective stress and the geostatic horizontal effective stress at point A
Geostatic vertical effective stress ( бv )
= 119.33 KN/m^2
Geostatic horizontal effective stress ( бn )
= 59.66 KN/m^2
C) attached below
