Vector arithmetic operations are performed element-wise. When adding or subtracting vectors, the result is a vector with the sum or difference of the corresponding elements. When vectors have unequal lengths, the shorter vector is recycled to match the length of the longer vector. Elements in a vector can be accessed using indices inside square brackets. A matrix is a two-dimensional collection of data arranged in rows and columns. Matrix operations like addition, subtraction, multiplication and division are performed element-wise on corresponding elements of the matrices. Elements of a matrix can be accessed and subsets can be extracted using row and column indices inside square brackets. Contour plots show 3D data on a 2D surface using contour lines, and can visualize topographic maps and
Box and whisker plot is a statistical measure to show the distribution of data. It is also called as Five Number Summary box as it consists of the median, the quartiles (lower and upper) and smallest and greatest values in distribution.
Probability distribution is a way to shape the sample data to make predictions and draw conclusions about an entire population because most improvement projects and scientific research studies are conducted with sample data rather than with data from an entire population. Probability distribution helps finding all the possible values a random variable can take between the minimum and maximum possible values
This presentation describes Booth's Algorithm of Multiplication.
It contains all four possible cases of multiplication.
Here everything is explained as simple as it can be.
No confusions about anything every term is explained properly.
A flow chart of algorithm is given and hardware implementation of Booth's Algorithm is also shown.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
CMSC 56 | Lecture 16: Equivalence of Relations & Partial Orderingallyn joy calcaben
Equivalence of Relations & Partial Ordering
CMSC 56 | Discrete Mathematical Structure for Computer Science
November 21, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
In MATLAB, a vector is created by assigning the elements of the vector to a variable. This can be done in several ways depending on the source of the information.
—Enter an explicit list of elements
—Load matrices from external data files
—Using built-in functions
—Using own functions in M-files
Box and whisker plot is a statistical measure to show the distribution of data. It is also called as Five Number Summary box as it consists of the median, the quartiles (lower and upper) and smallest and greatest values in distribution.
Probability distribution is a way to shape the sample data to make predictions and draw conclusions about an entire population because most improvement projects and scientific research studies are conducted with sample data rather than with data from an entire population. Probability distribution helps finding all the possible values a random variable can take between the minimum and maximum possible values
This presentation describes Booth's Algorithm of Multiplication.
It contains all four possible cases of multiplication.
Here everything is explained as simple as it can be.
No confusions about anything every term is explained properly.
A flow chart of algorithm is given and hardware implementation of Booth's Algorithm is also shown.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
CMSC 56 | Lecture 16: Equivalence of Relations & Partial Orderingallyn joy calcaben
Equivalence of Relations & Partial Ordering
CMSC 56 | Discrete Mathematical Structure for Computer Science
November 21, 2018
Instructor: Allyn Joy D. Calcaben
College of Arts & Sciences
University of the Philippines Visayas
In MATLAB, a vector is created by assigning the elements of the vector to a variable. This can be done in several ways depending on the source of the information.
—Enter an explicit list of elements
—Load matrices from external data files
—Using built-in functions
—Using own functions in M-files
The name MATLAB stands for MATrix LABoratory.MATLAB is a high-performance language for technical computing.
It integrates computation, visualization, and programming environment. Furthermore, MATLAB is a modern programming language environment: it has sophisticated data structures, contains built-in editing and debugging tools, and supports object-oriented programming.
These factor make MATLAB an excellent tool for teaching and research.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...
Vectormaths and Matrix in R.pptx
1. Vector Maths
Arithmetic operations of vectors are performed member-by-member, i.e., member wise.
For example, suppose we have two vectors a and b.
> a = c(1, 3, 5, 7)
> b = c(1, 2, 4, 8)
Then, if we multiply a by 5, we would get a vector with each of its members multiplied by
5.
> 5 * a
[1] 5 15 25 35
And if we add a and b together, the sum would be a vector whose members are the sum
of the corresponding members from a and b.
> a + b
[1] 2 5 9 15
Similarly for subtraction, multiplication and division, we get new vectors via memberwise
operations.
> a - b
[1] 0 1 1 -1
> a * b
[1] 1 6 20 56
> a / b
[1] 1.000 1.500 1.250 0.875
2. Recycling Rule
• If two vectors are of unequal length, the shorter
one will be recycled in order to match the longer
vector. For example, the following
vectors u and v have different lengths, and their
sum is computed by recycling values of the
shorter vector u.
• > u = c(10, 20, 30)
> v = c(1, 2, 3, 4, 5, 6, 7, 8, 9)
> u + v
[1] 11 22 33 14 25 36 17 28 39
3. Vector Index
• Vector Index
• We retrieve values in a vector by declaring an
index inside a single square
bracket "[]" operator.
• For example, the following shows how to
retrieve a vector member. Since the vector
index is 1-based, we use the index position 3 for
retrieving the third member.
• > s = c("aa", "bb", "cc", "dd", "ee")
> s[3]
[1] "cc"
4. Negative Index
• If the index is negative, it would strip the member
whose position has the same absolute value as
the negative index.
• For example, the following creates a vector slice
with the third member removed.
• > s[-3]
[1] "aa" "bb" "dd" "ee"
• Out-of-Range Index
• If an index is out-of-range, a missing value will be
reported via the symbol NA.
• > s[10]
[1] NA
5. Matrix
• A matrix is a collection of data elements
arranged in a two-dimensional rectangular
layout. The following is an example of a matrix
with 2 rows and 3 columns.
• We reproduce a memory representation of the
matrix in R with the matrix function. The data
elements must be of the same basic type.
6. • > A = matrix(
+ c(2, 4, 3, 1, 5, 7), # the data elements
+ nrow=2, # number of rows
+ ncol=3, # number of columns
+ byrow = T
• A # print the matrix
[,1] [,2] [,3]
[1,] 2 4 3
[2,] 1 5 7RUE) # fill matrix by rows
7. • An element at the mth row, nth column of A can be
accessed by the expression A[m, n].
• > A[2, 3] # element at 2nd row, 3rd column
[1] 7
• The entire mth row A can be extracted as A[m, ].
• > A[2, ] # the 2nd row
[1] 1 5 7
• Similarly, the entire nth column A can be extracted as A[
,n].
• > A[ ,3] # the 3rd column
[1] 3 7
• We can also extract more than one rows or columns at a
time.
• > A[ ,c(1,3)] # the 1st and 3rd columns
[,1] [,2]
[1,] 2 3
[2,] 1 7
8. Matrix Addition & Subtraction
• # Create two 2x3 matrices.
• matrix1 <- matrix(c(3, 9, -1, 4, 2, 6), nrow = 2)
print(matrix1)
• matrix2 <- matrix(c(5, 2, 0, 9, 3, 4), nrow = 2)
print(matrix2)
• # Add the matrices.
• result <- matrix1 + matrix2
• cat("Result of addition","n")
• print(result)
• # Subtract the matrices
• result <- matrix1 - matrix2
• cat("Result of subtraction","n") print(result)
10. • # Divide the matrices
• result <- matrix1 / matrix2
• cat("Result of division","n")
• print(result)
11. Matrix Access
• Create a Matrix
• x<-1:12
• Print(x)
• Mat<-matrix(x,3,4)
• Access third row of an existing matrix
• Mat[3,]
• Second column
• Mat[,2]
• Access second and third column
• Mat[,2,3]
12. Contour plot
• Contour plots are used to show 3-
dimensional data on a 2-dimensional surface.
The most common example of a contour plot
is a topographical map, which shows latitude
and longitude on the y and x axis, and
elevation overlaid with contours. Colours can
also be used on the map surface to further
highlight the contours
13. • Create a matrix, mat which is 9 rows and 9 columns with
all values are 1
• Mat<-matrix(1,9,9)
• Print(mat)
• Replace a value of 3rd row 3rd column
• Mat[3,3]<-0
• Contour(mat)
• Create a 3D perspective plot with persp(). It provides 3D
wireframe plot
• Persp(mat)
• R includes some pre defined data sets
• Volcano, which is 3D map dormant of New Zealand
• Contour(volcano)
• Heat map
• Image(volcano)