This document provides instructions for creating polished presentations in LaTeX. It covers topics like inserting tables, figures, and subfiles; displaying mathematics; including code listings; and adding references. The document contains examples of tables, figures, equations, algorithms, and other elements to demonstrate LaTeX features for technical presentations. It concludes by noting that the theme source code and a demo presentation are available on GitHub under a Creative Commons license.
This is the slides of the UCLA School of Engineering Matlab workshop on Matlab graphics.
Learning Matlab graphics by examples:
- In 2 hours, you will be able to create publication-quality plots.
- Starts from the basic 2D line plots to more advanced 3D plots.
- You will also learn some advanced topics like fine-tuning the appearance of your figure and the concept of handles.
- You will be able to create amazing animations: we use 2D wave equation and Lorentz attractor as examples.
I am Blake H. I am a Software Construction Assignment Expert at programminghomeworkhelp.com. I hold a PhD. in Programming, Curtin University, Australia. I have been helping students with their homework for the past 10 years. I solve assignments related to Software Construction.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Software Construction Assignments.
This is the slides of the UCLA School of Engineering Matlab workshop on Matlab graphics.
Learning Matlab graphics by examples:
- In 2 hours, you will be able to create publication-quality plots.
- Starts from the basic 2D line plots to more advanced 3D plots.
- You will also learn some advanced topics like fine-tuning the appearance of your figure and the concept of handles.
- You will be able to create amazing animations: we use 2D wave equation and Lorentz attractor as examples.
I am Blake H. I am a Software Construction Assignment Expert at programminghomeworkhelp.com. I hold a PhD. in Programming, Curtin University, Australia. I have been helping students with their homework for the past 10 years. I solve assignments related to Software Construction.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com. You can also call on +1 678 648 4277 for any assistance with Software Construction Assignments.
I am Christopher Hemmingway. I am a Computer Science Assignment Expert at programminghomeworkhelp.com. I hold a Master's in Computer Science, Princeton University, Princeton. I have been helping students with their homework for the past 10 years. I solve assignments related to Computer Science.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com.You can also call on +1 678 648 4277 for any assistance with Computer Science assignments.
How to 2D plots in Matlab. Easy steps to graph mathematical functions.
You have to define your interval of interest and consider a step in your independent vector, then you have to define your function and use an appropriate 2D built-in function.
More information and examples:
http://matrixlab-examples.com/matlab-plot-2tier.html
Ec2203 digital electronics questions anna university by www.annaunivedu.organnaunivedu
EC2203 Digital Electronics Anna University Important Questions for 3rd Semester ECE , EC2203 Digital Electronics Important Questions, 3rd Sem Question papers,
http://www.annaunivedu.org/digital-electronics-ec-2203-previous-year-question-paper-for-3rd-sem-ece-anna-univ-question/
More instructions for the lab write-up1) You are not obli.docxgilpinleeanna
More instructions for the lab write-up:
1) You are not obligated to use the 'diary' function. It was presented only for you convenience. You
should be copying and pasting your code, plots, and results into some sort of "Word" type editor that
will allow you to import graphs and such. Make sure you always include the commands to generate
what is been asked and include the outputs (from command window and plots), unless the problem
says to suppress it.
2) Edit this document: there should be no code or MATLAB commands that do not pertain to the
exercises you are presenting in your final submission. For each exercise, only the relevant code that
performs the task should be included. Do not include error messages. So once you have determined
either the command line instructions or the appropriate script file that will perform the task you are
given for the exercise, you should only include that and the associated output. Copy/paste these into
your final submission document followed by the output (including plots) that these MATLAB
instructions generate.
3) All code, output and plots for an exercise are to be grouped together. Do not put them in appendix, at
the end of the writeup, etc. In particular, put any mfiles you write BEFORE you first call them.
Each exercise, as well as the part of the exercises, is to be clearly demarked. Do not blend them all
together into some sort of composition style paper, complimentary to this: do NOT double space.
You can have spacing that makes your lab report look nice, but do not double space sections of text
as you would in a literature paper.
4) You can suppress much of the MATLAB output. If you need to create a vector, "x = 0:0.1:10" for
example, for use, there is no need to include this as output in your writeup. Just make sure you
include whatever result you are asked to show. Plots also do not have to be a full, or even half page.
They just have to be large enough that the relevant structure can be seen.
5) Before you put down any code, plots, etc. answer whatever questions that the exercise asks first.
You will follow this with the results of your work that support your answer.
SAMPLE QUESTION:
Exercise 1: Consider the function
f (x,C)=
sin(C x)
Cx
(a) Create a vector x with 100 elements from -3*pi to 3*pi. Write f as an inline or anonymous function
and generate the vectors y1 = f(x,C1), y2 = f(x,C2) and y3 = f(x,C3), where C1 = 1, C2 = 2 and
C3 = 3. Make sure you suppress the output of x and y's vectors. Plot the function f (for the three
C's above), name the axis, give a title to the plot and include a legend to identify the plots. Add a
grid to the plot.
(b) Without using inline or anonymous functions write a function+function structure m-file that does
the same job as in part (a)
SAMPLE LAB WRITEUP:
MAT 275 MATLAB LAB 1 NAME: ...
I am Christopher Hemmingway. I am a Computer Science Assignment Expert at programminghomeworkhelp.com. I hold a Master's in Computer Science, Princeton University, Princeton. I have been helping students with their homework for the past 10 years. I solve assignments related to Computer Science.
Visit programminghomeworkhelp.com or email support@programminghomeworkhelp.com.You can also call on +1 678 648 4277 for any assistance with Computer Science assignments.
How to 2D plots in Matlab. Easy steps to graph mathematical functions.
You have to define your interval of interest and consider a step in your independent vector, then you have to define your function and use an appropriate 2D built-in function.
More information and examples:
http://matrixlab-examples.com/matlab-plot-2tier.html
Ec2203 digital electronics questions anna university by www.annaunivedu.organnaunivedu
EC2203 Digital Electronics Anna University Important Questions for 3rd Semester ECE , EC2203 Digital Electronics Important Questions, 3rd Sem Question papers,
http://www.annaunivedu.org/digital-electronics-ec-2203-previous-year-question-paper-for-3rd-sem-ece-anna-univ-question/
More instructions for the lab write-up1) You are not obli.docxgilpinleeanna
More instructions for the lab write-up:
1) You are not obligated to use the 'diary' function. It was presented only for you convenience. You
should be copying and pasting your code, plots, and results into some sort of "Word" type editor that
will allow you to import graphs and such. Make sure you always include the commands to generate
what is been asked and include the outputs (from command window and plots), unless the problem
says to suppress it.
2) Edit this document: there should be no code or MATLAB commands that do not pertain to the
exercises you are presenting in your final submission. For each exercise, only the relevant code that
performs the task should be included. Do not include error messages. So once you have determined
either the command line instructions or the appropriate script file that will perform the task you are
given for the exercise, you should only include that and the associated output. Copy/paste these into
your final submission document followed by the output (including plots) that these MATLAB
instructions generate.
3) All code, output and plots for an exercise are to be grouped together. Do not put them in appendix, at
the end of the writeup, etc. In particular, put any mfiles you write BEFORE you first call them.
Each exercise, as well as the part of the exercises, is to be clearly demarked. Do not blend them all
together into some sort of composition style paper, complimentary to this: do NOT double space.
You can have spacing that makes your lab report look nice, but do not double space sections of text
as you would in a literature paper.
4) You can suppress much of the MATLAB output. If you need to create a vector, "x = 0:0.1:10" for
example, for use, there is no need to include this as output in your writeup. Just make sure you
include whatever result you are asked to show. Plots also do not have to be a full, or even half page.
They just have to be large enough that the relevant structure can be seen.
5) Before you put down any code, plots, etc. answer whatever questions that the exercise asks first.
You will follow this with the results of your work that support your answer.
SAMPLE QUESTION:
Exercise 1: Consider the function
f (x,C)=
sin(C x)
Cx
(a) Create a vector x with 100 elements from -3*pi to 3*pi. Write f as an inline or anonymous function
and generate the vectors y1 = f(x,C1), y2 = f(x,C2) and y3 = f(x,C3), where C1 = 1, C2 = 2 and
C3 = 3. Make sure you suppress the output of x and y's vectors. Plot the function f (for the three
C's above), name the axis, give a title to the plot and include a legend to identify the plots. Add a
grid to the plot.
(b) Without using inline or anonymous functions write a function+function structure m-file that does
the same job as in part (a)
SAMPLE LAB WRITEUP:
MAT 275 MATLAB LAB 1 NAME: ...
MATLAB DOCUMENTATION ON SOME OF THE MODULES
A.Generate videos in which a skeleton of a person doing the following Gestures.
1.Tilting his head to right and left
2.Tilting his hand to right and left
3.Walking
in matlab.
B. Write a MATLAB program that converts a decimal number to Roman number and vice versa.
C.Using EZ plot & anonymous functions plot the following:
· Y=Sqrt(X)
· Y= X^2
· Y=e^(-XY)
D.Take your picture and
· Show R, G, B channels along with RGB Image in same figure using sub figure.
· Convert into HSV( Hue, saturation and value) and show the H,S,V channels along with HSV image
E.Record your name pronounced by yourself. Try to display the signal(name) in a plot vs Time, using matlab.
F.Write a script to open a new figure and plot five circles, all centered at the origin and with increasing radii. Set the line width for each circle to something thick (at least 2 points), and use the colors from a 5-color jet colormap (jet).
G. NEWTON RAPHSON AND SECANT METHOD
H.Write any one of the program to do following things using file concept.
1.Create or Open a file
2. Read data from the file and write data to another file
3. Append some text to already existed file
4. Close the file
I.Write a function to perform following set operations
1.Union of A and B
2. Intersection of A and B
3. Complement of A and B
(Assume A= {1, 2, 3, 4, 5, 6}, B= {2, 4, 6})
Classification of common clustering algorithm and techniques, e.g., hierarchical clustering, distance measures, K-means, Squared error, SOFM, Clustering large databases.
Overview of basic concepts related to Data Mining: database, data model, fuzzy sets, information retrieval, data warehouse, dimensional modeling, data cubes, OLAP, machine learning.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
This chapter lays out a discussion on discrete data representation, continuous data sampling and re- construction. Fundamental differences between continuous (sampled) and discrete data are outlined. It introduces basic functions, discrete meshes and cells as means of constructing piecewise continuous approximations from sampled data. One learns about various types of datasets commonly used in the visualization practice: their advantages, limitations and constraints. This chapter gives an understanding of various trade-offs involved in the choice of a dataset for a given visualization application while focuses on efficiency of implementing the most commonly used datasets presented with cell types in d ∈ [0, 3] dimensions.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
We presented a number of fundamental methods for visualizing scalar data: color mapping, contouring, slicing, and height plots. Color mapping assigns a color as a function of the scalar value at each point of a given domain. Contouring displays all points within a given two- or three-dimensional domain that have a given scalar value. Height plots deform the scalar dataset domain in a given direction as a function of the scalar data. The main advantages of these techniques are that they produce intuitive results, easily understood by users, and they are simple to implement. However, such techniques also have s number of restrictions.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
In this chapter author discusses a number of popular visualization methods for vector datasets: vector glyphs, vector color-coding, displacement plots, stream objects, texture-based vector visualization, and the simplified representation of vector fields.
Section 6.5 presents stream objects, which use integral techniques to construct paths in vector fields. Section 6.7 discusses a number of strategies for simplified representation of vector datasets. Section 6.8 presents a number of illustrative visualization techniques for vector fields, which offer an alternative mechanism for simplified representation to the techniques discussed in Section 6.7 Chapter presents also feature detection methods, algorithm for computing separatrices on field’s topology, and top-down and bottom-up field decomposition methods.
Chapter summary and solutions to end-of-chapter exercises for "Data Visualization: Principles and Practice" book by Alexandru C. Telea
Chapter provides an overview of a number of methods for visualizing tensor data. It explains principal component analysis as a technique used to process a tensor matrix and extract from it information that can directly be used in its visualization. It forms a fundamental part of many tensor data processing and visualization algorithms. Section 7.4 shows how the results of the principal component analysis can be visualized using the simple color-mapping techniques. Next parts of the chapter explain how same data can be visualized using tensor glyphs, and streamline-like visualization techniques.
In contrast to Slicer, which is a more general framework for analyzing and visualizing 3D slice-based data volumes, the Diffusion Toolkit focuses on DT-MRI datasets, and thus offers more extensive and easier to use options for fiber tracking.
Crime Analysis based on Historical and Transportation DataValerii Klymchuk
Contains experimental results based on real crime data from an urban city. Our set of statistics reveals seasonality in crime patterns to accompany predictive machine learning models assessing the risks of crime. Moreover, this work provides a discussion on implementation, design for a prototype of cloud based crime analytics dashboard.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
2. Outline i
Introduction
Tables, figures and subfiles
Tables and Figures
Cross-references
Sub section through input command
Displaying Mathematics
Inline Mode
Display Mode
Code Listings and Using Symbols
Conclusion
1
5. This is going to be a normal paragraph in our introduction.
Some intro stuff
Observation
This is a very important piece of information.
Some other stuff ...
2
6. Blocks
Three different block environments are pre-defined and may
be styled with an optional background color.
Default
Block content.
Alert
Block content.
Example
Block content.
Default
Block content.
Alert
Block content.
Example
Block content.
3
8. To insert a figure, you can use the TeXnicecenter menus.
SP SR
VS
SP SR
VS
SP SR
VS
a) Pushed Validation b) Pulled Validation c) Delegated Validation
1
23
4
1
2
34 14 32
Figure 1: My First Figure
4
10. Multipage Xtabular table i
Table 1: Sample multipage table with repeating header
document class bibliography
style
Institute of
Electrical and
Electronics
Engineers
IEEEtran IEEEtran
6
11. Multipage Xtabular table ii
Table 1 continued
document class bibliography
style
Association for
Computing Ma-
chinery
sig-alternate plain
Lecture Notes
in Computer
Science
llncs lllncs
7
12. Multipage Xtabular table iii
Table 1 continued
document class bibliography
style
General article plain
8
13. Gant charts
2020 2021 2022
3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2
Proposal Defense
Background Study
Android Security
Code Analysis
Policy Mechanisms
Literature Review Complete
Formal Specification
Spec Document
Thesis and Paper Writing
Figure 3: My First Gantt
9
14. Some text here that wants to refer to Table 1. You can also
refer to the Figure 1. When you want to refer to a previous
section, you can use the ref command again. Section 2.
This comes from a separate file. Notice that we have this
subsection included in the Navigator.
10
15. Algorithms
Algorithm 1 My First Simple Algorithm
Require: Randomly populated array
Ensure: Sorted array
if i ≤ 0 then
2: i ← 1
else
4: if i ≥ 0 then
for j = 0 to 10 do
6: blah()
carryOutSomeProcessing()
8: end for
end if
10: end if
return i
11
16. And of course, we can refer to the algorithm using ref: See
Algorithm 1 but the good thing is we can also refer to a
specific line e.g. Line 4 or Line 7.
12
18. LATEX is extremely powerful when it comes to typesetting
mathematics. It’s one of the core strengths of this system.
There are two ways of displaying maths. One is inline and the
other is display format – in which the whole math sits on its
own set of lines.
We are going to insert a mathematics equation inline here
using a pair of $ signs: E = mc2 . As you can see, the display
(such as line spacing) does not get messed up by the
mathematics as it does with word processing softwares.
13
19. We can also display equations in their own set of lines. To do
this, we can use the equation environment.
E = mc2
(1)
As you can see, LATEX inserts the equation number
automatically. We can refer to it using the ref command just
as we referred to sections, figures and tables. (E.g.
Equation 1.) To get rid of the equation number, simply use the
star variant of the equation environment. (For this, you need
the amsmath package.)
E = mc2
14
20. Alternatively, we can use the shorthand keys [ and ]
E = mc2
LATEX has many builtin features and you can get many more
easily. Here, we’ll see some of these features:
Addition, subtraction, multiplication and division:
x + 2 − 25 × 35 ÷ 98
Superscripts and subscripts:
x2
x(i)
14
23. Greek letters:
α + β + γ∗
+ Σ + Θ + 2
Matrices and vectors. For this, you need to include the
amsmath package and then use the bmatrix or pmatrix
environment:
a
44 b
c
√
d
Accents:
ˆx
ˆı
˙x 16
24. See the Math menu in the IDE for other operations. You can
refer to “Short Math Guide for LATEX” for a lot more examples.
17
26. You might come across situations where you need to find new
symbols. For this, you can refer to the “The Comprehensive
LATEXSymbols List”.
x y
(Optional) Since this is a long command, we might want to
create a shortcut using the newcommand command in the
preamble. This also allows us to later change the symbol
without having to change the equations.
x y
18
27. LATEXCode
Listing 1: Some LATEXCode
l s t s e t {language =[ LaTeX ] tex }
l s t s e t {caption=Some LaTeX Code}
begin{ lrbox }{codebox}
begin{ l s t l i s t i n g *}[ frame= single ]{}
begin{frame}
end{frame}
end{ l s t l i s t i n g *}
end{ lrbox }
begin{frame}{LaTeX Code}
usebox{codebox}
end{frame}
19
28. C++ Code
Listing 2: Some C++ Code
for(i = 0; i < 10; i++){
// increment the pointer
*p++ = i;
}
20
30. Bar charts
1 1.5 2 2.5 3 3.5 4
10
15
20
25
Foo
Bar
lorem
ipsum
dolor
22
31. Frame footer
metropolis defines a custom beamer template to add a text
to the footer. It can be set via
setbeamertemplate{frame footer}{My custom footer}
My custom footer 23
34. Summary
Get the source of this theme and the demo presentation from
github.com/voklymchuk/latex_templates
The theme itself is licensed under a Creative Commons
Attribution-ShareAlike 4.0 International License.
cba
25
36. Backup slides
Sometimes, it is useful to add slides at the end of your
presentation to refer to during audience questions.
The best way to do this is to include the
appendixnumberbeamer package in your preamble and call
appendix before your backup slides.
metropolis will automatically turn off slide numbering and
progress bars for slides in the appendix.
37. References i
P. Erd˝os.
A selection of problems and results in combinatorics.
In Recent trends in combinatorics (Matrahaza, 1995), pages
1–6. Cambridge Univ. Press, Cambridge, 1995.
R. Graham, D. Knuth, and O. Patashnik.
Concrete mathematics.
Addison-Wesley, Reading, MA, 1989.
G. D. Greenwade.
The Comprehensive Tex Archive Network (CTAN).
TUGBoat, 14(3):342–351, 1993.
38. References ii
D. Knuth.
Two notes on notation.
Amer. Math. Monthly, 99:403–422, 1992.
H. Simpson.
Proof of the Riemann Hypothesis.
preprint (2003), available at
http://www.math.drofnats.edu/riemann.ps, 2003.