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University of Florida/Eml4500/f08/Matlab Summary

3. Matrix Operations, Array operations
If sizes of matrices are incompatible with the operator, and error message is shown. The matrix division operators required extra attention. If A is an invertible square matrix and b is a compatible column, resp. row, vector, then

x=A\b is the solution of A*x=b and resp.,

x=b/A is the solution of x*A=b

Array Operations

The matrix operators of addition and subtraction will work for arrays but the other operators will not. The matix operators can be used to operate entry-wise by placing a period in front of the operator.

4. Statements, expressions, variables
MATLAB is an expression language where exspression are comprised of operators, functions,and variable names. Expressions are evaluated into matrices and stored as such. Statements are generally terminated with a carriage return but can be continued onto the next line. Also statements can be terminated with a semicolon or period, which suppresses printing of the statement but still carries out the operation. MATLAB is case sensitive. Runaway displays or computation can be halted with CTRL-C.

Saving a session

All variable are lsot when MATLAB is close. Using the save command saves the variables to a .mat file which can later be retrieved with the load command.

5. Matrix building functions
Some functions in matlab will accomplish predetermined convinient tasks for you.

Here is an example of the of a 5-by-5 matrix(B) created from an original 3-by-3 matrix(A):

disp('5. Matrix Building Function.')

A=[1 2 3;4 5 6;7 8 9]

B = [A,zeros(3,2);zeros(2,3),eye(2)]

The result in MatLab is:

5. Matrix Building Function.

A =

 * 1    2     3
 * 4    5     6
 * 7    8     9

B =

 * 1    2     3     0     0
 * 4    5     6     0     0
 * 7    8     9     0     0
 * 0    0     0     1     0
 * 0    0     0     0     1

6. For, while, if and relations
For

For a given n, the statement

x=[]; for i=1:n, x=[x,i^2],end

will produce a certain n-vector and the statement

x=[]; for i=n:-1:1, x=[x,i^2], end

will produce the same vector in reverse order.

The for statement permits any matrix to be used instead of 1:n.

While

The general form of a while loop is

while relation

statements

end

The statements will be repeated as long as the relation remains true. For example, for a number a, the following will compute the smallest non-negative integer n such that 2^n>a:

n=0;

while 2^n < a

n = n + 1;

end

n

If

The general for of an if statement is

if relations

statements

end

The statement will only be executed if the relation is true. The if function can be branched using the elseif and else functions. For example:

if n < 0

parity = 0;

elseif rem(n,2) == 0

parity = 2;

else

parity = 1;

end


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User:Eml4500.f08.jamama.adam

matrix building

Matlab Homework 2

Homework 2

Homework 3

Homework 4

Homework 5

Homework 6

Homework 7

title: User:Eml4500.f08.jamama.adam


text:
User:Eml4500.f08.jamama.justin/Mat

Accessing Matlab
 * On most systems one can enter Matlab with the command matlab, although on other systems you can access it through a menu or just by clicking an icon.

Entering Matricies
 * Matlab mainly works with a rectangular numerical matrix. All variables represent matrices.

Imaginary numbers can also be entered, using the units i or j.

 * Large amounts of data can easily be loaded using the command load data.ext, where .ext could be any extension. The best files to use are ASCII files.
 * To just create matrices one can just use some of the built in functions.

Individual parts of matrices can be referenced simply by their address. so A(2,3) will select the entry in matrix A, row 2, column 3.

TRY IT!

Matrix operations, array operations

 * If the sizes of the matrices your trying to operations on do not coincide with one another an error message will appear, that is unless one of the matrices is a scalar (a 1X1 matrix). A scalar can be used on any size matrix.
 * Also, the division operators are related to one another. Right division is defined in terms of left division by b/A = (A'\b')'.

Matrix operations, array operations

 Array Operations Although addition and subtraction only operate entry-wise, the other operations are matrix operations. Entry-wise will operate on each of the individual elements, while matrix operations operate on the matrices as a whole.

Matrix operations, array operations

TRY IT

Statements, expressions, and variables; saving a session
 * Matlab statements are usually in the simple form of expressions, which are typically composed of operators functions and variable names. When an expression is evaluated it is turned into a matrix with a variable as its name.  If no variable is assigned, a variable ans is created to store that particular matrix.
 * Statements end by pressing enter. They can be continued by putting three or more periods then pressing enter, or can simply be put on one line (but they must be separated by comas or semi-colons).
 * Putting a semicolon at the end of a line makes it so the operation is still done, yet it is not immediately printed.
 * Matlab is case sensitive; A is different than a.
 * The command Who will list all current variables.
 * The command clear can be used before a variable to just delete that one, or used on its own to delete all variables.
 * The permanent variable epsilon (eps) rounds to about 10^-16 on most machines which can be used for converging iterative processes.
 * To stop an unwanted computation without leaving matlab press CTRL-C.

Saving a Session One can hit the save button to store a session as a diskfile with the extension .mat. You can then re-enter Matlab later and use the load function to restore the former workspace.

Matlab Homework Assignment Code

title: User:Eml4500.f08.jamama.justin/Mat


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text:
User talk:Eml4500.f08.jamama.adam

 Hello Eml4500.f08.jamama.adam, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

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And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 23:10, 11 September 2008 (UTC)

title: User talk:Eml4500.f08.jamama.adam


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User talk:Eml4500.f08.jamama.chris

 Hello Eml4500.f08.jamama.chris, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

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 * Chat with other Wikiversitans on #wikiversity-en.

And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 23:10, 11 September 2008 (UTC)

title: User talk:Eml4500.f08.jamama.chris


text:
User:Eml4500.f08.gravy.jad

HW1

HW1Matlab

HW1MatlabTeamGravy

HW1NotesTeamGravy

REDOHW1LectureNotes+MatlabTeamGravy

condistation of old and new HW1

HW2

HW2NotesJAD

HW2NotesGravy

REDOHW2NotesGravy

condistation of old and new HW2

HW3

HW3NotesJAD

HW3NotesGravy

REDOHW3NotesGravy

HW4

HW4NotesJAD

HW4NotesGravy

HW5

HW5NotesJAD

HW5NotesGravy

HW6

HW6NotesJAD

HW6NotesGravy

HW7

HW7NotesJAD

HW7NotesGravy

title: User:Eml4500.f08.gravy.jad


text:
Portal:Social entrepreneurship/community mobilisation

The purpose of this page is to highlight issues around participation so that the community of educators and students can grow stronger.

Please indicate any difficulties you may have had and any suggestions for improving community engagement.

If you have time, lend a hand with developing a survey/questionnaire to probe reasons for the low level of participation:
 * Draft Survey.

=Ideas for community mobilisation=

 * Raise awareness of OER - via the OER Handbook for Educators and with some pro-active communication etc..
 * Organize the entire course, have a core team to take care of planning and to look after other aspects of course. Invite experts to take care of particular topic, experts are usually self motivated. Some kind of certification and credits be given to the co learners, so that there is a motivation to complete the course and activities on time. Collaborations with NGOs and not for profit organizations,as well as individual entrepreneurs, who want to contribute some time and be the mentors will also help. I am available for any assistance.User:Prof._Vivek_Sharma

=Time=

Not having enough on top of other work.

 * Our aim should be to make this wiki a time saver.
 * Best done with some collaboration and consensus on structure and content (including tools and other resources).

Timing of Activities
When is a good time for curriculum development and participation in general?

 * For UNW (and probably other universities) the beginning of the year is best - when new projects are planned - a much more suitable time to participate.

=See Also=

 * Process Improvement
 * Issue Tracker


text:
User talk:Eml4500.f08.gravy.jad

 Hello Eml4500.f08.gravy.jad, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

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 * Visit a (kind of) random random project.
 * Browse everything on Wikiversity, or visit a portal corresponding to your educational level: pre-school, primary, secondary, tertiary, non-formal education.
 * Find out about research activities on Wikiversity.

 * Read an introduction for teachers and find out how to write an educational resource for Wikiversity.
 * Give feedback about your initial observations
 * Discuss Wikiversity issues or ask questions at the colloquium.
 * Chat with other Wikiversitans on #wikiversity-en.

And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 23:18, 11 September 2008 (UTC)

title: User talk:Eml4500.f08.gravy.jad


text: File:MatlProp.JPG

title: File:MatlProp.JPG


text:
User talk:Eml4500.f08.Lulz.fisher

 Hello Eml4500.f08.Lulz.fisher, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

 * Take a guided tour and learn to edit.
 * Visit a (kind of) random random project.
 * Browse everything on Wikiversity, or visit a portal corresponding to your educational level: pre-school, primary, secondary, tertiary, non-formal education.
 * Find out about research activities on Wikiversity.

 * Read an introduction for teachers and find out how to write an educational resource for Wikiversity.
 * Give feedback about your initial observations
 * Discuss Wikiversity issues or ask questions at the colloquium.
 * Chat with other Wikiversitans on #wikiversity-en.

And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 23:38, 11 September 2008 (UTC)

title: User talk:Eml4500.f08.Lulz.fisher


text:
User:Eml4500.f08.jamama.adam/matlabtutorial

5. Matris Building FunctionLink title

Some functions in matlab will accomplish predetermined convinient tasks for you.

Here is an example of the of a 5-by-5 matrix(B) created from an original 3-by-3 matrix(A):

disp('5. Matrix Building Function.')

A=[1 2 3;4 5 6;7 8 9]

B = [A,zeros(3,2);zeros(2,3),eye(2)]

The result in MatLab is:

5. Matrix Building Function.

A =

 * 1    2     3
 * 4    5     6
 * 7    8     9

B =

 * 1    2     3     0     0
 * 4    5     6     0     0
 * 7    8     9     0     0
 * 0    0     0     1     0
 * 0    0     0     0     1

6. For, while, if, - and relations.Link title

Examples of the use of "for", "while" and "if" in MatLab:


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text:
User:Eml4500.f08.team.allen.oca/hw1

13. Text strings, error messages, input.

Text strings are entered into MATLAB surrounded by single quotes. The following assigns variable s with a string:

s = ‘This is a test’

The function disp is used to display a text string. Using the above text string as an example,

disp(‘This is a test’) or disp(s)

The function error is used to display a string just like disp, but will also abort the running M-file where it was called from.

A method of taking in data from a user from inside an m-file is the function input as seen in the following example.

iter = input(‘Enter the number of iterations: ‘);

Here the user is prompted by the string asking for a number. After the user enters the number and presses the Return key, the number entered is stored in iter.

14. Managing M-files

On systems that support only one process at a time, to avoid MATLAB exiting while working with a local editor, proceed the system commands normally used to enter a local program or action with !. For example,

!ed rotate.m

will open a local editor to work on rotate.m. After closing the editor, MATLAB will be found to be just as you left it. This is not a concern on most Unix or Windows systems as they support multiple programs running simultaneously.

Many debugging tools are available for M-files. They can be accessed by typing help dtype.

Directory and File commands with strings as operators:

pwd returns the current working directory

cd 'newdirectory' changes directory to that of newdirectory

dir or ls lists all files in working directory

what lists only M-files in working directory

delete 'filename' deletes a file in the working directory

type 'filename' can be used to print an M-file to the screen.

Along with the current working directory, a directory called MATLAB found in the users root directory will also be accessed when the user requests an M-file. The command path returns all file directories MATLAB searches when looking for an M-file. See help path on how directories can be added to the aforementioned list.

15. Comparing efficiency of algorithms: flops, tic and toc.

The number of flops used and time spent processing an algorithm are good indicators of the efficacy of the algorithm.

The command flops(0) resets the current count of flops to zero and should be placed just before the start of the algorithm to be watched. After the algorithm has finished, the command flops returns the number of operations that took place.

The commands tic and toc operate a stopwatch timer which measures the number of seconds between the two command calls. Placing tic before and toc after an algorithm will return how many seconds the algorithm took to complete.

16. Output format.

Although all computations in MATLAB are performed in double precision, the format of the displayed output can be controlled by the following commands.

format short 		fixed point with a 4 decimal places (default)

format long 		fixed point with 14 decimal places

format short e 	       scientific notation with 4 decimal places

format long e 		scientific notation with 15 decimal places

format rat 		approximation by ratio of small integers

format hex 		hexadecimal format

format bank 		fixed dollars and cents

format + 		+, -, bank

Once invoked, the chosen format remains in effect until changed.

Other commands include: format compact		 suppresses blank lines to display more information format loose		 returns to un-compacted format

17. Hardcopy.

The command diary filename creates a file called filename in the working directory to record all activity in the MATLAB command window. The command diary off stops the recording and actually places the recording into the file.

18. Graphics.

The command plot(x,y) displays an x-y plot in a separate window of the elements x vs the elements y. For example, the following produces a graph of sinusoid:  x = -4:0.01:4; y = sin(x); plot(x,y)

In MATLAB there can be multiple graph windows open, but only one can be current at a time. To place a plot in a new graph window, use the command figure. To create a graph window with a specific number (one that is not already in current use) one can type figure(16) for a figure window of number 16. The command gcf will return the number of the current graph window.

MATLAB supplies a function fplot to easily and efficiently plot the graph of a function. For example, to plot the graph of the function above, one can first define the function in an M-file called say, expnormal.m containing

'''Function y = expnormal(x) y = exp(-x.^2);'''

Then the command  fplot(‘exnormal’, [-1.5,1.5])

will produce the graph.

The following commands can be used to format the graph and take a string as an argument:

title 		graph title

xlabel 		x-axis label

ylabel 		y-axis label

gtext		 place text on the graph using mouse

text 		position text at specified coordinates

For further details on how to use the above commands, type help text at the command prompt.

The command grid will place grid lines on the current graph.

By default the axes are auto-scaled. The axis command can be used to to modify the axes and what follow are some features of the axis command:

axis([xmin, xmax, ymin, ymax])	set axis scaling to prescribed limits

axis (axis)				freezes scaling for subsequent graphs

axis 					auto returns to auto-scaling

v = axis 				returns vector v showing current scaling

axis square 				same scale on both axes

axis equal 				same scale and tic marks on both axes

axis off 				turns off axis scaling and tic marks

axis on				 turns on axis scaling and tic marks

The axis command should be given after the plot command.

One method to display multiple plots on a single graph is to define an independent domain and a number of dependent functions. Then the following command will place the plots in a single graph:

plot(x,y1,x,y2,x,y3)

Another method is to hold the current graphics screen so that subsequent plots are superimposed onto it. The axes may be rescaled, however. Entering hold off releases the “hold.”

To override the default line types on a plot the plot command can be called with additional arguments, for example:

plot(x,y1,’--‘, x, y2, ‘r:’, x, y3, ‘y+’)

Where the first graph will be represented by a dashed line, the second by a red dotted line and the third by a yellow cross symbol at every node. Acceptable line type and color arguments are:

Line types: solid (-), dashed (--), dotted (:), dashdot (-.)

Mark types: point (.), plus (+), star (*), circle (o), x-mart (x)

Colors: yellow (y), magenta (m), cyan (c), red (r), green (g), blue (b), white (w), black (k)

The command subplot is used to partition the screen so that several small plots can be placed in one figure. See help subplot.

Other specialized 2-D functions:

Polar, bar, hist, quiver, compass, feather, rose, stairs, fill

title: User:Eml4500.f08.team.allen.oca/hw1


text:
User:EML4500.f08.Ateam.Miller/homework1

Trusses are structural systems consisting of long slender members. The members are arranged so that they are loaded axially and do not experience bending or shear forces. For more information on trusses, please refer to the Truss article on Wikipedia.

Global Picture

Before trusses are analyzed with the Matrix Method or any other method, it is important to develop a standardized system for labeling and drawing the systems. First, the truss system is drawn and the components are labeled. Global nodes are labeled with a number circumscribed in a circle and elements are labeled with a number circumscribed in a triangle.

Global Free Body Diagram

The next step in the process is to draw the global free body diagram (FBD). The global FBD is a diagram of the whole structure that shows the applied forces, as well as the reaction forces. The FBD includes known and reactionary forces represented by arrows. The reaction forces are labeled Rna, where a denotes the direction of the force in reference to the global coordinate system and n represents the global node number. For example, R1X represents the reaction force R applied along the X axis at node 1.

Element Free Body Diagrams

After the global FBD is created, an element FBD must be created. The element FBD is a diagram of each element of the whole structure that includes known, reaction, and internal forces applied to that element. The elemental diagram is labeled with the element number as stated above. Each node of the element is labeled with its global node number as stated above, as well as a local node number that is a number circumscribed in a square. Each internal force of the element is labeled fi(e), where i is the force number and e is the element number. Force numbers are assigned first by local node number and then orientation related to the coordinate system. For example, a force f1(1) is the first degree of freedom (DOF) in element one.

Force-Displacement Relation

The next "big step" in applying the matrix method to a truss problem is to develop a relation between the applied force and the resulting displacement. The deformation of an elastic truss member can be modeled as the deformation of a spring. Therefore, mass-spring relations will be examined.

Spring with One End Constrained

First, consider a one dimensional spring with one end fixed. The force-displacement relation for this system is represented by the equation $$f=kd$$, where f is the force, d is the displacement, and k is the spring constant that it a property of the spring. This relation shows that there is linear relationship between the applied load and the resulting displacement.

Spring with Both Ends Free

Another spring system to consider is a one dimensional spring with both ends free. This system has two degrees of freedom so there is a system of two equations that govern the relationship between the applied force and the resulting displacement. Consider the spring system shown in the figure. Force 1, F1, acts at node 1, causing a displacement, d1 and force 2 acts at node 2, resulting in a displacement d2. The equations of motion for this system are developed for two cases. For the first case, consider an observer sitting on node 1. The resulting equation of motion is $$f_2 = k(d_2-d_1)$$. The second case is when an observer sits on node 2, resulting in the equation $$f_1 = k(d_1-d_2)$$. Therefore, the resulting force-displacement relation for this system is represented by the system of equations below.

$$\begin{bmatrix} F_1 \\ F_2 \\ \end{bmatrix} $$ = $$\begin{bmatrix} k & -k \\ -k & k \\ \end{bmatrix} $$ $$\begin{bmatrix} d_1 \\ d_2 \\ \end{bmatrix} $$

title: User:EML4500.f08.Ateam.Miller/homework1


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text:
User:Eml4500.f08.gravy.jad/Matlab

5. Matrix Building Functions

Some commonly used functions in Matlab consists of:

For example, by saying zeros(m,n) produces an mxn matrix containing zeros. By saying zeros(n) produces an nxn matrix containing zeros. By saying zeros(A) while A is an existing matrix, it produces a matrix size A containing zeros.

6. For, if, while -and relations

For, if and while are different types of loops used in Matlab.

for:

-The "for" loop produces a vector of size "n" for a given function "x"

-saying, i=n:-1:1, will write the vector backwards

-There can be double nested "for" loops (two or more for loops in the same loop. This will produce an mxn matrix.

-A matrix can be used instead of "n" and it will assume to compute the matrix

while:

-The "while" function is a loop that will continue to loop until the condition statement becomes false

if:

-The"if" function is a single loop that will only enter the loop if the primary condition is met

-it is a single loop

Relations

Some common relational operators used in Matlab consists of:

logical operators are as follows:

In addition, any true/false relations appear as a scalar number 1/0.

title: User:Eml4500.f08.gravy.jad/Matlab


text:
University of Florida/Eml4500/f08.FEABBQ/HW1/Notes/admin

1- Class info:
 * Syllabus:

Instructor :
 * Dr. L. Vu-Quoc
 * Tel: 392-6227
 * E-mail:vu-quoc@ufl.edu
 * Office: NEB 135 (New Engineering Building)
 * Classroom: FLG 270
 * Class time: MWF, period 8 (3:00pm - 3:50pm)
 * Office hours: MWF, period 9 (4:05pm - 4:55pm)
 * web site: WWW.mae.ufl.edu/~vql

TAs:
 * 1) Nicolas Vigroux
 * Office: NEB 109, Tue, periods 3 and 4 (9:35am - 11:30am)
 * Tel: 846-3027
 * E-mail: nvigroux@ufl.edu

 * 2) Sung-Uk Zhang
 * Office: NEB 109,Thu, periods 6 and 7 (12:50pm - 13:40pm)
 * Tel: 392-3347
 * E-mail: zsunguk@ufl.edu

Exams Schedule:
 * 1) There are no scheduled make-up exams
 * 2) All exams are closed books, closed notes
 * 3) with a 4.25"x5.5" (half a letter-size paper) formula sheet allowed (handwritten)
 * 4) calculators can solve systems of linear simultaneous equations
 * 5) NOT allowed are laptops and any hand-held devices

Exam Dates:
 * 1) Exam 1: Wed, 24 Sep 2008
 * 2) Exam 2: Wed, 22 Oct 2008
 * 3) Exam 3: Wed, 03 Dec 2008

 * The grading will be 23% for every exam and 31% for the homework and projects.

Class Website

 * to log on the class website:
 * 1) www.mae.ufl.edu/~vql
 * 2) Teaching
 * 3) Course website
 * 4) EMl4500
 * 5) Pass Word is: (fall08.wiki)


text:
User:NCMnMe

becca {| cellpadding="10" cellspacing="5" style="width: 100%; background-color: inherit; margin-left: auto; margin-right: auto"
 * style="width: 50%; background-color: LemonChiffon; border: 1px solid Gray; vertical-align: top; -moz-border-radius-topleft: 8px; -moz-border-radius-bottomleft: 8px; -moz-border-radius-topright: 8px; -moz-border-radius-bottomright: 8px;" |

About me

 * Name
 * Becca

 * External Links

 * Location

 * School

 * Why I want to learn filmmaking.
 * it's what the cool kids are doing

 * Contact

 * }

 * NCMnMe has completed the following assignments in the course on Basic filmmaking (pre-production) for narrative motion pictures.

 * [[Image:Blancovinkjeup.png|16px]] Formatting the Script [[Image:Nuvola apps package wordprocessing.png|28px]]
 * [[Image:Blancovinkje.png|16px]] Pop Quiz - What is the first shot? [[Image:Crystal Clear app clock.svg|24px]]
 * [[Image:Blancovinkje.png|16px]] Creating the thumbnail storyboards [[Image:Crystal Clear app gimp.png|24px]]
 * [[Image:Blancovinkje.png|16px]] Quick Exercise - Over-the-shoulder shot [[Image:Applications-accessories.svg|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Creating the 3D storyboards [[Image:Crystal Clear app Login Manager.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] A simple DVD-Video Editing Workshop [[Image:Crystal Clear device cdwriter unmount.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Learning about camera lenses [[Image:Crystal Clear app camera.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Record the dialog for the animatic [[Image:Crystal Clear app krec.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Intro to narrative filmmaking [[Image:Clapboard-Small.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Draw the movie poster for "Star Wars" [[Image:Crystal Clear app kcoloredit.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Understanding dailies [[Image:Clapboard-Small.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Create a matte painting [[Image:Crystal Clear app kcoloredit.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Understanding editing [[Image:Clapboard-Small.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Pop Quiz - Creating the moods (film scoring) [[Image:Crystal Clear app clock.svg|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Understanding "L-Cuts" [[Image:Clapboard-Small.png|24px]]
 * [[Image:Blancovinkjeemptysmall.png|16px]] Create the animatic [[Image:Clapboard-Small.png|28px]]

 October 1, 2008 -- NCMnMe has formatted the script with free demo of Final Draft. You can download it at.

 October 1, 2008 -- NCMnMe has created a thumbnail storyboard.

 October 1, 2008 -- NCMnMe has created a wide angle over-the-shoulder shot and a telephoto over-the-shoulder shot.

 October 1, 2008 -- NCMnMe has created a 3D Storyboard

title: User:NCMnMe


text:
User:Eml4500.f08.team.foskey.ckf/HW1c

 Example Problem

Using the methods explained earlier, we will now look at an example problem, and solve it using the finite element method.

Data

Element Lengths

L(1) = 4

L(2) = 2

Young’s Moduli

E(1) = 3

E(2) = 5

Cross Sectional Areas

A(1) = 1

A(2) = 2

Inclination Angles

θ(1) = 30°

θ(2) = 45°

Solving The Problem

Using the previously explained methodology, we create a free body diagram for the Global Picture. The internal forces and displacements are labeled using the established conventions.

The variables are then placed into the force displacement relation equation. The global system has six degrees of freedom (displacements) and six internal forces. Thus the equation contains a (6x1) global force matrix, a (6x6) global stiffness matrix, and a (6x1) global displacement matrix.

Global Force-Displacement relationship

title: User:Eml4500.f08.team.foskey.ckf/HW1c


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User:Eml4500.f08.gravy.jad/Matlab2

 Summery of Matlab tutorial by Kermit Sigmon

Accessing MATLAB
After MATLAB is installed to the computer, it may be accessed either by clicking on a icon on the desktop, or if that icon was not created, by selecting the icon in the start menu. An alternate method to access MATLAB is to enter it into the system command which can also be found in the start menu

For convenience, MATLAB, as well as the local editor should both remain open in separate windows for any computer system that allows for multiple processes. Any questions in this area should be directed towards the computer manufacturer.

Entering Matrices
Matrices are the method by which MATLAB represents all variables. Single variables or interpreted as a 1 x 1 matrix, with no indicated direction. This is also known as a scalar quantity. A vector is represented by any matrix consisting of one column, or one row. All matrices are two dimensional and must consist of numerical values.

There are multiple methods by which to introduce a matrix into MATLAB including loading the matrix from a disk or file, inserting the matrix manually, or using a matrix that has been generated by another mathematical equation. The following two statements are examples of the correct syntax to generate a 3 x 3 matrix:

A = [1 2 3; 4 5 6; 7 8 9]

A= [

1 2 3 4 5 6 7 8 9]

The first example separates the values by spaces and the rows by semi-colons while the second separates the rows by lines.

To indicate an exponent, values must be entered in without spaces (i.e. 2.34e-5) for proper syntax. MATLAB also has the ability to interpret imaginary numbers using i and j. These values are also entered without spaces (i.e. 3+4i). If the values of i and j are assigned prior to their use as an imaginary value, a new value can be used by first setting it equal to the square root of negative one.

If a matrix is too long and tedious to enter manually it should be entered via an ASCII file from the local editor to avoid possible error from input. To load files in MATLAB, use the load command followed by the name of the file.

For example: load filename.ext If a user wishes to experiment with matrices of random numbers the rand, magic, and hilb functions provide a solution. The rand function creates a matrix of randomly generated numbers for a matrix with the same number of rows as columns. The magic function creates a magic square matrix. This is a particular type of matrix where the rows, columns, and diagonals have a common sum. The hilb function creates a Hilbert matrix.

Matrix and Array Operations
MATLAB has a variety of operations available including addition (+), subtraction (-), multiplication (*), power (^), conjugate transpose (‘), left division (\), and right division (/) all of which can be applied to both scalars and vectors. Order of operations applies.

Statements Expressions and Variables
Matlab uses operators, functions and variable names (which are case-sensitive) to complete tasks. When an operation has been completed the results are displayed in matrix form, unless the line ends in a semicolon. The semicolon will suppress the output but the operation will still be carried out. To stop matlab mid operation hit CTRL and C, or CTRL and break.

The workspace saves all variables and their values. The command “who” or “whos” will displace the variables in the workspace. To clear a variable the command is “clear” followed by the variable name, if the variable name is omitted then all variables will be cleared.

Saving a Session
To save the variables from the workspace the command is “save”. Save will write the variable in a file called matlab.mat. To load the saved session the command is “load”.

Matrix Building Functions
Some commonly used functions in Matlab consists of:

For example, by saying zeros(m,n) produces an mxn matrix containing zeros. By saying zeros(n) produces an nxn matrix containing zeros. By saying zeros(A) while A is an existing matrix, it produces a matrix size A containing zeros.

For, if, while -and relations
For, if and while are different types of loops used in Matlab.

for:

-The "for" loop produces a vector of size "n" for a given function "x"

-saying, i=n:-1:1, will write the vector backwards

-There can be double nested "for" loops (two or more for loops in the same loop. This will produce an mxn matrix.

-A matrix can be used instead of "n" and it will assume to compute the matrix

while:

-The "while" function is a loop that will continue to loop until the condition statement becomes false

if:

-The"if" function is a single loop that will only enter the loop if the primary condition is met

-it is a single loop

Relations

Some common relational operators used in Matlab consists of:

logical operators are as follows:

In addition, any true/false relations appear as a scalar number 1/0.

Scalar Functions
There are some functions in MATLAB that were designed and created for scalar functions. These functions can still operate element-wise on matrices. Some common examples are sin, cos, tan, asin, acos, atan, exp, log, ln, rem (remainder), abs (absolute value), sqrt (square root)

Vector Functions
Unlike scalar functions, vector functions are, as their name hints, used on vectors (i.e. matrices or size m x n). These functions when used yield answers which are also in vector form. Some common examples of vector functions are max (max value), min (min value), sort (sort values), median, mean, std (standard deviation), sum, prod (product)

Matrix Functions
As mentioned above, matrices are used as a representation of variables in MATLAB. This is what makes the program such a useful tool. Some common examples of matrix functions are eig (eigenvalues), chol (choleski factorization), inv (inverse), hess (hessenberg form), det (determinant)

Command line editing and recall
- editing is easy -> backspace or delete to the right or left of the cursor

- commands: Ctl-a, Ctl-e, Ctl-d, Ctl-k for Unix or PC systems

- the cursor can be moved up or down to recall any previous line, therefore one can move the cursors up, down, left, right and recall and/or edit anything on the page

Submatrices and colon notation
-matlab uses vectors and submatrices, often generated by "colon notation"

- "colon notation" and subscripting is used to manipulate data sets

- ex: A(1:4,3) = matrix A, column 3, elements 1 through 4

A(:,3) = matrix A, column 3, all elements

A(:,[2 4]) = matrix A, column 2 and 4, all elements

M-Files
M-files M-files are are stored files usually ending with the “.m” extension. They allow MATLAB to run an entire preprogrammed series of commands. They effectivly make up the backbone of MATLAB, and most work is usually done to create or edit these files. There are two main types of m-files: script files and function files.

Script Files Script files are a type of m-file that contains a sequence or normal MATLAB commands. They are normally used for the creation and mataince of large variables, such as matrices. The varibable created in a script file are global. To call a script file, simply enter a command into MATLAB that is the name of the script file with the “.m” extension left off. For example, if the file is named “example1.m” than typing in the command “example1” will cause the script file to run.

Function Files Function files are the true brains behind MATLAB. They allow for the creation of any type of function programmable, which greatly extends the cabalities of MATLAB. Function files, unlike script files, default to creating local variables. However they can be declared global if the need arises. A function files starts with the line “function variable=execute(a,b)”. The word “function” tells MATLAb that the following is a function. “variable” is the output argument, and the name can be changed to be more descriptive. “execute(a,b)” is the name of the function (execute) and the variables that need to be passed into the function (a,b). The list of variables (a,b), called the input arguments, can be expanded or deleted to fit the need of the function. Function files, like all m-files, are able to use and call other files within them, allowing for a greater range of programming options.

An example of a function file is shown below. Remember that the “%” symbol allows for comments without affecting any code. MATLAB ignores all statements after the % symbol.

function a=randint(m,n) %RANDINT Randomly generated integral matrix. %       randint(m,n) returns an m-by-n matrix with entries

%      between 0 and 9 a=floor(10*rand(m,n))

Putting the command “z=randint(3,6)” into MATLAB will return a 3-by-6 matrix variable named “z”. The great advantage to function files is the ability to expand and create huge programs. This allows for the creation of many smaller function, similar to the randint(a,b) created before, to be combined into a large file that can be programmed to do thousands of different things. Also, there is the ability to combine self-made functions with some of MATLAB’s built-in functions, much like the built in function “rand(x,y)” was used above.

A useful command to find out a list of all the functions that MATLAB has access to, a combination of built-in and user programmed functions, can be seen by typing the command “type functionname”.

Text strings, error messages, input
To enter a text string in MATLAB, use single quotes: s = 'This is a test' This will assign the text string ‘This is a test’ to the variable s.

To display a text string, use the function disp: disp('this message is hereby displayed');

To display an error message, use the function error: error('Sorry, the matrix must be symmetric'); This also will exit the M-file upon execution.

To prompt the user for input data, use the function input: iter = input('Enter the number of iterations: '); This will display ‘Enter the number of iterations’ and pause execution while the user inputs the data which is then data assigned to the variable iter.

Managing M-files
To keep MATLAB active while editing a file in order to avoid losing all variables, use the !-feature by inserting a ! before any system command: >> !ed rotate.m This will let you edit rotate.m using the local editor without exiting MATLAB.

See help dbtype and references given there for more concerning debbugging tools.

The following commands will duplicate system commands without the use of a !:

M-files must be in an accessible directory. Storing personal M-files in a subdirectory named Matlab in one’s home directory should work. For further information see the discussion of MATLABPATH in the User's Guide.

Comparing efficiency of algorithms: flops, tic, toc
There are two measure of algorithm efficiency: floating point operations (flops) performed and the elapsed time (tic and toc).

The MATLAB function flops keeps a running total of the flops performed.

To reset the flops count to 0, use the command fops(0), not flops=0. Do this at the beginning of the code, and then use the command fops at the end to get the fops count of the algorithm: fops (0); x=A\b; fops

The MATLAB functions tic and toc give the elapsed time between the two commands: tic; x=A\b; toc

However, on timesharing machines, elapsed time is not as reliable as flops at determining algorithm efficiency because the rate of execution is dependent on how busy the computer is at the time.

Output format
To control the format of the displayed output, use the following commands:

Once invoked, the chosen format remains in effect until changed.

To suppress most blank lines, use the command format compact. To reverse the format compact command, use format loose. These are independent of the other format commands.

Hard copy
Saving input from the command window to an alterable and printable file can be done using the command diary. To start recording the command is “diary” then the file name. If you don’t give a file name the default file name is diary. To end recording the command is “diary off”.

Planer plots
The command for plot is “plot (x,y)” with x and y being the variables to be plotted. An interval and mesh size can be set by “variable name= lower limit: mesh size: upper limit”.

“fplot (‘function file’,[lower limit, upper limit])” is the command to graph functions. Function file is a m-file that contains the function to be graphed.

Only one figure is active at a time but you can switch between the figures using “figure(n)” where n is the figure number wanted. “gcf” command gives the active figure’s number.

Multiple plots on one graph can be made using “plot(x, y1,x,y2,…)”Other ways are, declaring a matrix of functions like U=[function1, function2 ] and using plot(x,U). Or using the “hold” command to freeze the current plot and all plots after will be placed on the same plot. To unfreeze the plots, the command is  “hold off”.

3-D line plots
To create 3-d plots the command is “plot3(x,y,z)”.

3-D mesh and surface plots
To create 3-D wire mesh surface plots the command is “mesh(z)” and three dimensional faceted surface plots “surf(z)”where z is a matrix of points in the z direction.

To plot a function over a rectangle use first the command “[x,y]=meshgrid(xx,yy)” where xx and yy are matrices of the sides of the rectangle. x and y result in matrices whose columns equal xx and yy respectably. Next the command mesh is used with z= exp(-x.^2-y.^2)

The color of the shadings can be changed using the command “shading” followed by the setting. The settings are faceted, interp ( for interpolated), and flat. The color profile is changed using the command “colormap” followed by the color. The color codes are hsv, hot, cool, jet, pink, copper, flag, gray, and   bone.

Labeling the figure
The commands Title, xlabel, ylabel and zlabel, can be used to label the figure. An example is Title(‘Title name’).

gtext(‘The Spot’), command places text where on the figure the mouse is clicked, while the text command places the text at coordinates.

Axis scaling
The following commands are used to change the scaling on the axis.

axis([x lower limit, x upper limit, y lower limit, y upper limit ]), to set scaling.

axis(axis), freezes scaling for subsequent graphs.

axis auto, resets the scale to the default.

Variable= axis, the variable will be set to the current scaling.

axis square, makes the same scale for both axes.

axis equal, make the same scale and tic marks for both axes.

axis off, turns off scaling and tic marks axis on turns them on.

Line types
To change the line type, mark type and color use the tables below. The syntax is Plot(x,y,’color line type mark type’) so Plot(x,y,’b:*’) is a blue dotted line with star markers.

'''

Graphics hard copy
The command “print” will send the current graphic to the default printer. The command “print ” then the file name will save and overwrite the graphic to a file, but ”print -append” then the file name will add the graphic to the end  of a file.

To save a graphic that is not the current one, the command is “print –deps –f#” then the filename and # the figure number.

Sparse Matrix Computations
There are two storage modes in Matlab for a matrix: full and sparse. Full mode stores everything, while sparse only stores nonzero numbers. The default is to store elements of a matrix in full mode. In full mode, the zero elements are taken into account during calculations. Sparse mode will remove these zero elements during calculations, thus reducing time spent performing them. It saves time, but still outputs the same numbers.

Matrices can be converted between sparse and full fairly easily. The command “S=sparse(F)” will convert the full matrix, F, to a sparse matrix, S. It can then be converted back from sparse to full using the command "F=full(S)”. Usually though, if a sparse matrix is desired, it will be created directly rather than by converting from a full matrix. There are sparse analogs to many full matrices. The functions speye, sparse, spones, and sprandn are sparse analogs to the full functions eye, zeros, ones and randn respectively.

When performing calculations using both full and sparse matrices, the storage mode of the output will vary. If calculations are performed on only sparse functions, the output will be sparse. If calculations are performed only on full functions, the output will be full. However, if calculations are performed using both full and sparse functions, the output will always come out as full unless the user specifically states otherwise.

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text:
MATLAB Tutorial: Part1

Finite Element Analysis

MatLab Tutorial Summary/Explanation

MatLab is developed by the MathWorks Company. Below is their link for further information outside the scope of the document below.

About MatLab: MatLab is a matrix-based enginering computation program that is user-interactive. By using matrices to enter and solve complex equations, MatLab can do in a fraction of the time it would take older programming languages to do. When dealing with finite element analysis, depending on the number of nodes, there can be numerous partial differential equations that need to be solved.

Starting Matlab: MatLab can be started 2 ways. The first is using the command window and typing run/matlab. The second is through the start menu >> programs >> matlab.

Matrices: MatLab works solely with matrices to handle all computations. These matrices can range in size from 1 by 1 all the way up to thousands of elements. Entering a matrix into matlab is easy and is done with the following notation: A = [1 2 3; 4 5 6; 7 8 9] This creates a 3 by 3 matrix with the values shown and a new row started after each semi-colon. Additionally, matrices do not have to be entered with just real numbers. Complex numbers (i) can also be entered into matrices. For example: A = [1+3i; 2-4i; 3]

When it comes to large matrices, it may be very time consuming to enter in all the matrix values by hand. In such a case, the values can be read in from an ASCII file. As long as the file has a rectangular matrix in it, simply type: >> load numbers.ext This will load the matrix in the file numbers into the workspace.

Matrix Operations: MatLab uses the same basic mathematical operators plus a few additional ones. Below are the operators: * + addition * - subtraction * * multiplication * / right division * \ left division * ^ power * ` conjugate The left division operator is special in that it allows for division of matrices that are not square. If you use the right division operator, MatLab will give an error saying that the matrices are not square.

Statements, Expressions, and Variables:

Matlab is an expression language meaning the user types an expression, usually composed of variables, functions, and operators, and Matlab interprets it and performs the expression. After the expression is evaluated, the output is put into a matrix. If no matrix name is specified by the user, matlab puts the result in a matrix called ans. Normally after each expression is evaluated, Matlab outputs the result of the expression. To supress(hold) the output, put a semi-colon at the end of the expression. Variables can have virtually any name you choose, as long as it is not a reserved variable or function name. Matlab is case sensitive but has no restriction on variable name length. Some Helpful Commands: * whos - displays a list of variables currently in the workspace Also, there are come commands that can be used to help the user build matrices Matrix Building Commands: * eye - identity matrix * zeros - matrix of zeros * ones - matrix of ones Each of the commands needs to be followed by the following notation: (# of rows, # on columns) Example: zeros(3,3) yeilds a square 3 by 3 matrix of zeros.

Loops:

Loops are used to repeat a series of operations until a certain condition is met. Below are the two types of loops that are used frequently in Matlab.

For:

For loops execute continually once a condition is met up until the condition is no longer met.

While:

While loops are similar to for loops except for while loops are guaranteed to execute at least once. It will exectue the statement, then check it against the while statement. If it is true, it will run back through the loop. If it is false, it will exit the loop. '''In addition to loops, one can have an operation performed only IF a condition is met. That type of operator is an if statement. Below is an example of an IF statement.'''

NOTE: All code was taken from my previous homework assignments in Numerical Methods

Relations:

The relational operators are used to compare the value of a variable to another variable or to a constant value. Below are some common relational operators: * == equal * ~= not equal * < less than * > greater than * >= greater than or equal to    * <= less than or equal to     * & and * | or    * ~ not

Relational operators are always used in for, while,and if statements to see when to execute, or stop executing expressions within the loop.

Scalar Functions:

Certain matlab functions operate on scalar numbers and when applied to a matrix, they act on 1 matrix element at a time. Some scalar Matlab functions are listed below: sin, cos, tan, asin, acos, atan exp, log, rem, abs, sqrt, sin, round, floor, ceil

Vector Functions:

Vector functions act on a vector matrix column by column to produce a row matrix as the solution. These functions can only be used when the matrix is larger than 1 by 1. Below are some examples of vector functions: max, min, sort, sum, prod, median, mean, std, any, all

Command Line Editing:

The command line in Matlab is denoted by 2 arrows (>>). The command line is the line that the user uses to type in commands. To keep the user from having to re-enter previously used commands, Matlab allows the user to scroll through the old commands used during the session by hitting the up-arrow and down-arrow keys.

Also, it is important to remember that instead of entering a series of commands by hand every time, create an m-file to execute. This will save loads of time and needless typing.

M-Files

M-files are special Matlab files that have a .m extension. These files contain a series of statements that can be exectued at one time, thus saving the user time from having to exectue expressions 1 at a time. There are two types of m-files, script files and function files.

Script files contain a series of normal Matlab scripts. They are traditionally used to enter large amounts of data into matrices. Any variable or matrix is global, meaning the parameter can be used in any other portion of the workspace.

Function files are a type of m-file that allow users to essentially create new Matlab functions. The functions can be specific to a particuar problem that the user is working on.

Text Strings

You can assign text strings to variables by using single quotes around the text to be entered into the variable. Additionally, text can be displayed to the screen using the disp function. The error function also outputs a message to the screen but also aborts the code in an m-file when it is executed. Below are examples of the 2 functions: disp('Hello World') error('Warning!!!')

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User:Eml4500.f08.Lulz.Layton.Eric/Homework 1

Part 11: Submatrices and colon notation
This section of the primer discusses more advanced matrix manipulation techniques.

 >> 0.2:0.2:1.2
 * The first example shows the use of non-integral increments and boundaries in matrix declaration:

ans =

0.2000   0.4000    0.6000    0.8000    1.0000    1.2000 >> 5:-1:1

ans =

5    4     3     2     1  >> x = [0.0:0.1:2.0]';
 * The next example employs a table of  values to demonstrate matrix generation from a set of vectors:

>> y = sin(x);

>> [x y]

ans =

0        0

0.1000   0.0998

0.2000   0.1987

0.3000   0.2955

0.4000   0.3894

0.5000   0.4794

0.6000   0.5646

0.7000   0.6442

0.8000   0.7174

0.9000   0.7833

1.0000   0.8415

1.1000   0.8912

1.2000   0.9320

1.3000   0.9636

1.4000   0.9854

1.5000   0.9975

1.6000   0.9996

1.7000   0.9917

1.8000   0.9738

1.9000   0.9463

2.0000   0.9093  >> A = rand(5)
 * The following set of examples display the various uses of the colon operator in MATLAB:

A =

0.8147   0.0975    0.1576    0.1419    0.6557

0.9058   0.2785    0.9706    0.4218    0.0357

0.1270   0.5469    0.9572    0.9157    0.8491

0.9134   0.9575    0.4854    0.7922    0.9340

0.6324   0.9649    0.8003    0.9595    0.6787

>> B = rand(5)

B =

0.7577   0.7060    0.8235    0.4387    0.4898

0.7431   0.0318    0.6948    0.3816    0.4456

0.3922   0.2769    0.3171    0.7655    0.6463

0.6555   0.0462    0.9502    0.7952    0.7094

0.1712   0.0971    0.0344    0.1869    0.7547 >> A(1:4,3)

ans =

0.1576

0.9706

0.9572

0.4854 >> A(:,3)

ans =

0.1576

0.9706

0.9572

0.4854

0.8003 >> A(1:4,:)

ans =

0.8147   0.0975    0.1576    0.1419    0.6557

0.9058   0.2785    0.9706    0.4218    0.0357

0.1270   0.5469    0.9572    0.9157    0.8491

0.9134   0.9575    0.4854    0.7922    0.9340 >> A(:,[2 4])

ans =

0.0975   0.1419

0.2785   0.4218

0.5469   0.9157

0.9575   0.7922

0.9649   0.9595 >> A(:,[2 4 5]) = B(:,1:3)

A =

0.8147   0.7577    0.1576    0.7060    0.8235

0.9058   0.7431    0.9706    0.0318    0.6948

0.1270   0.3922    0.9572    0.2769    0.3171

0.9134   0.6555    0.4854    0.0462    0.9502

0.6324   0.1712    0.8003    0.0971    0.0344 >> A(:,[2,4]) = A(:,[2,4])*[1 2;3 4]

A =

0.8147   0.5232    0.1576    0.7626    0.6557

0.9058   1.5438    0.9706    2.2440    0.0357

0.1270   3.2941    0.9572    4.7567    0.8491

0.9134   3.3341    0.4854    5.0838    0.9340

0.6324   3.8434    0.8003    5.7677    0.6787  >> x = A(:,1)
 * The final set of examples for this section explores reordering of vectors using both colon notation and the  and   commands.

x =

0.8147

0.9058

0.1270

0.9134

0.6324 >> x = x(5:-1:1)

x =

0.6324

0.9134

0.1270

0.9058

0.8147 >> y = fliplr(x)

y =

0.6324

0.9134

0.1270

0.9058

0.8147 > y = flipud(x')

y =

0.6324   0.9134    0.1270    0.9058    0.8147

Part 12: M-files: script files, function files
This section of the primer discusses MATLAB's M-file system for executing command sequences. MATLAB handles two types of M-files: scripts and functions.

 First, the MATLAB code saved as : A = [
 * The first example shows the use of a simple script for creating a matrix:

1234

5678

];

And then the execution of the script to create the matrix:

>> data

>> A

A =

1234

5678

 First, the MATLAB code saved as the function : function a = randint(m,n,a,b)
 * The next example employs a function to generate a n-by-m matrix of random numbers from 0 to 9:

%RANDINT Randomly generated integral matrix.

%   randint(m,n) returns and m-by-n such matrix with entries

%   between 0 and 9.

%   rand(m,n,a,b) return entries between integers a and b.

if nargin < 3, a = 0; b = 9; end

a = floor((b-a+1)*rand(m,n)) + a;

And the calling of the function to generate a 4-by-5 matrix: >> z = randint(4,5)

z =

2    1     5     5     5

6    4     2     6     1

6    9     7     8     1

1    3     2     9     2

 First, the MATLAB code saved as : function [mean, stdev] = stat(x)
 * The next function highlights the capability to have multiple outputs:

% STAT Mean and standard deviation

%   For a vector x, stat(x) returns the mean of x;

%   [mean, stdev] = stat(x) both the mean and standard deviation.

%   For a matrix x, stat(x) acts columnwise.

[m n] = size(x);

if m == 1

m = n; % handle case of a row vector

end

mean = sum(x)/m;

stdev = sqrt(sum(x.^2)/m - mean.^2); Next, two function calls are made to. The first displays the aforementioned multiple outputs: >> [xm, xd] = stat(x)

xm =

0.6786

xd =

0.2938 And the second displays a single output (no square bracket required): >> xm = stat(x)

xm =

0.6786 Lastly, the  command is used to display the header for  : >> help stat

STAT Mean and standard deviation

For a vector x, stat(x) returns the mean of x;

[mean, stdev] = stat(x) both the mean and standard deviation.

For a matrix x, stat(x) acts columnwise.
 * The last function examples highlight the use of the  command to pass functions to other functions:

First, the MATLAB code for the function, which finds the zero of a passed function via bisection method: function [b, steps] = bisect(fun, x, tol)

%BISECT Zero of a function of one variable via the bisection method

%   bisect(fun,x) returns a zero of the function. fun is a string

%   containing the name of a real-valued MATLAB function of a

%   single real variable; ordinarily functions are defined in

%   M-files. x is a starting guess. The value returned is near

%   a point where fun changes sign. For example,

%   bisect('sin',3) is pi. Note the quotes around sin.

%

%   An optimal third input argument sets a tolerance for the

%   relative accuracy of the result. The default is eps.

%   An optional section output argument gives a matrix containing a

%   trace of the steps; the rots are of form [c f(c)].

% Initialization

if nargin < 3, tol = eps; end

trace = (nargout == 2);

if x ~= 0, dx = x/20; else, dx = 1/20; end

a = x - dx; fa = feval(fun,a);

b = x + dx; fb = feval(fun,b);

% Find change of sign.

while (fa > 0) == (fb > 0)

dx = 2.0*dx;

a = x - dx; fa = feval(fun,a);

if (fa > 0) ~= (fb > 0), break, end

b = x + dx; fb = feval(fun,b);

end

if trace, steps = [a fa; b fb]; end

%Main loop

while abs(b - a) > 2.0*tol*max(abs(b),1.0)

c = a + .5*(b-a); fc = feval(fun,c);

if trace, steps = [steps; [c fc]]; end

if (fb > 0) == (fc > 0)

b = c; fb = fc;

else

a = c; fa = fc;

end

end

And the function call to find the zero of the sin function near x = 2: >> bisect('sin',2)

ans =

3.1416  >> type eig
 * Finally, the primer notes the usefulness of the  command to identify the nature of functions:

'eig' is a built-in function. >> type vander

function A = vander(v)

%VANDER Vandermonde matrix.

%  A = VANDER(V) returns the Vandermonde matrix whose columns

%  are powers of the vector V, that is A(i,j) = v(i)^(n-j).

%

%  Class support for input V:

%     float: double, single

%  Copyright 1984-2004 The MathWorks, Inc.

%  $Revision: 5.9.4.1 $  $Date: 2004/07/05 17:01:29 $

n = length(v);

v = v;

A = ones(n,class(v));

for j = n-1:-1:1

A(:,j) = v.*A(:,j+1);

end >> type rank

function r = rank(A,tol)

%RANK  Matrix rank.

%  RANK(A) provides an estimate of the number of linearly

%  independent rows or columns of a matrix A.

%  RANK(A,tol) is the number of singular values of A

%  that are larger than tol.

%  RANK(A) uses the default tol = max(size(A)) * eps(norm(A)).

%

%  Class support for input A:

%     float: double, single

%  Copyright 1984-2004 The MathWorks, Inc.

%  $Revision: 5.11.4.3 $  $Date: 2004/08/20 19:50:33 $

s = svd(A);

if nargin==1

tol = max(size(A)') * eps(max(s));

end

r = sum(s > tol);

Part 13: Text strings, error messages, input
This section of the primer discusses the various methods of handling text in MATLAB.

 >> s = 'This is a test'
 * The first example shows the necessity of single quotes for defining a simple text string:

s =

This is a test  >> disp('this message is hereby displayed')
 * The next example features use of the  and   commands:

this message is hereby displayed >> error('Sorry, the matrix must be symmetric')

??? Sorry, the matrix must be symmetric Note that when the  command is used, the resulting output is displayed in red.  >> iter = input('Enter the number of iterations:  ')
 * The final example features text-based input:

Enter the number of iterations:  12

iter =

12


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User:EML4500.f08.A-team.VandenBerg/August 25, 2008

Syllabus Overview:

Course website: (website)

Then Click on:

* teaching * my course website * Fall 2008 – Finite Element Analysis and Design

Office: NEB 135

Office Hours: MWF 9th Period

Exam Schedule:

Book: (Blackish in color) Finite Element Analysis with Mathematica and Matlab Computations and Practical Applications: Fundamental Concepts

Grading: HW + Project + Class Participation + Bonuses = 31%

Peer Evaluations: wikiHW:fall08.wiki


text:
User:Eml4500.f08.echo.marshall.cwd

PRACTICE PAGE

TEAM ECHO

TEAM ECHO

title: User:Eml4500.f08.echo.marshall.cwd


title: User:Eml4500.f08.gravy.jad/Notes1


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User talk:EML4500.f08.jamama.megan

 Hello EML4500.f08.jamama.megan, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

 * Take a guided tour and learn to edit.
 * Visit a (kind of) random random project.
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 * Find out about research activities on Wikiversity.

 * Read an introduction for teachers and find out how to write an educational resource for Wikiversity.
 * Give feedback about your initial observations
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 * Chat with other Wikiversitans on #wikiversity-en.

And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 02:55, 12 September 2008 (UTC)

title: User talk:EML4500.f08.jamama.megan


text:
User:Eml4500.f08.gravy.sms

HW 1

HW 2

HW 3

HW 4

HW 5

HW 6

HW 7

title: User:Eml4500.f08.gravy.sms


text:
University of Florida/Egm4200c/f08.carbon

Course Information

Course Website: www.mae.ufl.edu/~vql → "teaching" → "my course website" → "EGM 4200C Aerospace Structures" EGM 4200c Course website

Password: fall08.wiki

Office: 135 NEB - MWF 9th (office hours)

Course Content

The Finite Element Method (FEM) makes solving partial differential equations (PDEs) convenient. This is integral to the study of Aerospace Structures, or its structural components.

The emphasis of the course will be to understand structural mechanics, formulate problems, judge solution correctness, and avoid ad-hoc structural analysis methods.

The plan of the course is to maintain confidentiality while using large-scale peer-to-peer domains including Wikiversity and MIT's OpenCourseWare in addition to the textbook. The course will examine the method of work instead of other approaches such as e-learning and the old approach to EML4500 (10% HW and 30% x 3 for each exam). This format allows students to be introduced to MediaWiki and stimulate collaboration with other students, teams, the professor, and the class as a whole.

There are several relevant time zones important to us (UTC, EDT, and EST). HW will be turned in according to the UTC time to maintain consistency with the Wikipedia time stamp format.

HW shortcuts should be created by attaching the URL from the archived version by going to "History" → click on the date to open archived version → copy this address to submit.

Announcements
HOMEWORK 1 IS DUE ON FRIDAY! Eas4200c.f08.carbon.clausen 20:48, 10 September 2008 (UTC)

Members

 * User:Eas4200c.f08.carbon.booth
 * User:Eas4200c.f08.carbon.clausen
 * User:Eas4200c.f08.carbon.guidry
 * User:Eas4200c.f08.carbon.orear
 * User:Eas4200c.f08.carbon.w

Homework

 * Homework 1: User:Eas4200c.f08.carbon.orear


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User:Eas4200c.f08.gator.edwards/Problem 1.1

Problem 1.1
 Team gator, you need to register user "Eas4200c.f08.gator.edards" so that this wiki page can be preserved. I also moved the figure up so that it does not block the link to "show" your first collapsible table. Eml4500.f08 12:52, 18 September 2008 (UTC)

Problem 1.1 is taken from the textbook Mechanics of Aircraft Structures by C.T.Sun, copyright 2006.

Find the optimum ratio of $$b/a$$ to maximize the load carrying ability of the beam. Assume $$M=T$$ and $$\displaystyle \sigma_{allowable}=2\displaystyle \tau_{allowable}$$.

The question is asking for the optimal cross section carrying the maximum bending moment and maximum torque.

Since the cross section walls are very thin, assume shear stress distribution in the thin walls of the beam are distributed uniformly. This results in the equation $$\displaystyle \tau=\frac{T}{2abt}$$.

Case 1: Assume $$\displaystyle \sigma$$ (bending moment stress) reaches $$\displaystyle \sigma_{allowable}$$ first. Verify $$\displaystyle \tau \le 2\displaystyle \tau$$.

From Mechanics of Materials, the normal stress caused by a bending moment is $$\displaystyle \sigma=\frac{Mz}{I}$$


text:
User talk:Eas4200c.f08.spars.lee

 Hello Eas4200c.f08.spars.lee, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

 * Take a guided tour and learn to edit.
 * Visit a (kind of) random random project.
 * Browse everything on Wikiversity, or visit a portal corresponding to your educational level: pre-school, primary, secondary, tertiary, non-formal education.
 * Find out about research activities on Wikiversity.

 * Read an introduction for teachers and find out how to write an educational resource for Wikiversity.
 * Give feedback about your initial observations
 * Discuss Wikiversity issues or ask questions at the colloquium.
 * Chat with other Wikiversitans on #wikiversity-en.

And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 04:01, 12 September 2008 (UTC)

title: User talk:Eas4200c.f08.spars.lee


text:
User talk:Eml4500.f08.gravy.sms

 Hello Eml4500.f08.gravy.sms, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

 * Take a guided tour and learn to edit.
 * Visit a (kind of) random random project.
 * Browse everything on Wikiversity, or visit a portal corresponding to your educational level: pre-school, primary, secondary, tertiary, non-formal education.
 * Find out about research activities on Wikiversity.

 * Read an introduction for teachers and find out how to write an educational resource for Wikiversity.
 * Give feedback about your initial observations
 * Discuss Wikiversity issues or ask questions at the colloquium.
 * Chat with other Wikiversitans on #wikiversity-en.

And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 04:02, 12 September 2008 (UTC)

title: User talk:Eml4500.f08.gravy.sms


title: File:Hw1.jpg


text:
User:Eml4500.f08.gravy.jad/Matlab1

5. Matrix Building Functions

Some commonly used functions in Matlab consists of:

For example, by saying zeros(m,n) produces an mxn matrix containing zeros. By saying zeros(n) produces an nxn matrix containing zeros. By saying zeros(A) while A is an existing matrix, it produces a matrix size A containing zeros.

6. For, if, while -and relations

For, if and while are different types of loops used in Matlab.

for:

-The "for" loop produces a vector of size "n" for a given function "x"

-saying, i=n:-1:1, will write the vector backwards

-There can be double nested "for" loops (two or more for loops in the same loop. This will produce an mxn matrix.

-A matrix can be used instead of "n" and it will assume to compute the matrix

while:

-The "while" function is a loop that will continue to loop until the condition statement becomes false

if:

-The"if" function is a single loop that will only enter the loop if the primary condition is met

-it is a single loop

Relations

Some common relational operators used in Matlab consists of:

logical operators are as follows:

In addition, any true/false relations appear as a scalar number 1/0.

10. Command line editing and recall

- editing is easy -> backspace or delete to the right or left of the cursor

- commands: Ctl-a, Ctl-e, Ctl-d, Ctl-k for Unix or PC systems

- the cursor can be moved up or down to recall any previous line, therefore one can move the cursors up, down, left, right and recall and/or edit anything on the page

11. Submatrices and colon notation

-matlab uses vectors and submatrices, often generated by "colon notation"

- "colon notation" and subscripting is used to manipulate data sets

- ex: A(1:4,3) = matrix A, column 3, elements 1 through 4

A(:,3) = matrix A, column 3, all elements

A(:,[2 4]) = matrix A, column 2 and 4, all elements

title: User:Eml4500.f08.gravy.jad/Matlab1


text:
University of Florida/Eml4500/f08.qwiki/Lecture 5

 Read:  Chapter 4 Chapter 1: Big Picture
 * 1.1 Discritization (1.1.1 Plane truss elem)
 * 1.2 Assembly of elem. eqs. Ex. 1.4: Five-bar truss
 * 1.4 Elem Soln and model validity (1.4.1 Plane truss elem)

Steps to solve simple truss system described on 9/3

1. Global:  The displacement dofs are partitioned into: 1)a known part,e.g.(fixed dofs, constraints) 2)an unknown part: solve using FEA

The same for global forces: 1) known part 2) unknown part

2. Element picture:
 * Element dofs
 * Element forces

3. Global FD relation:
 * Element stiffness matrices in global coordinates
 * Element force matrices in global coordinates
 * Assembly of element stiffness matrix and element force matrix into global FD relation k nxn d nx1= F nx1

4. Elimination:  The elimination of known dofs to reduce the global FD rel. (stiffness matrix non-singular => invertible)

m = number of unknown displacement dofs

n = number of all displacement dofs
 * m < n

d = k-1 F

5. Compute Element Forces

6. Compute Reactions

 Example:

 * L(1)=4    L(2)=2 (Length)
 * E(1)=3 E(2)=5 (Young's Modulus)
 * A(1)=1 A(2)=2 (Area)


text:
Talk:Visual Basic/Functions and Subroutines

Why don't you give an example that passes an array as a parameter?

How to do a premature return, i.e. why does the following not work

Sub foo(x as Integer) if (x = 1) then return            '// how to exit foo??? end if End sub


text:
User:EAS4200C.F08.WIKI.A

=Mechanics of Aircraft Structures=

This wiki page is dedicated to the course EAS4200C: Mechanics of Aircraft Structures taught at the University of Florida. Class notes and homework problems will be posted for students of the class and world.

=Team Wiki Members=

Christopher Pergola

Christopher Fontana

Jeff Huenink

Braden Barnes

Eric Viale

Michale Rolle

=Homework=

/HW

/Homework

/Homework3

/Homework4

/Homework5

/Homework6

/Homework7

=My Contribution=

/My Contribution: HW

/My Contribution: 2

/My Contribution: 3

/My Contribution: 4

/My Contribution: 5

/My Contribution: 6

/My Contribution: 6.1

/My Contribution: 7

=Matlab Certification=

I, the undersigned, certify that I can read, understand, and write matlab codes, and can thus contribute effectively to my team.

Eric Viale Eas4200c.f08.wiki.c 18:10, 7 November 2008 (UTC) Braden Barnes Eas4200c.f08.wiki.b 19:48, 7 November 2008 (UTC) Christopher Pergola EAS4200C.F08.WIKI.A 20:07, 7 November 2008 (UTC) Christopher Fontana Eas4200c.f08.WIKI.E 18:35, 30 November 2008 (UTC) Michael Rolle Eas4200c.f08.wiki.d 21:36, 7 November 2008 (UTC)

Jeff Huenink Eas4200c.f08.wiki.f 15:27, 10 November 2008 (UTC)

title: User:EAS4200C.F08.WIKI.A


text:
Talk:Subspecialties of Nursing and Advanced Practice

Running head: THEORIES

Theories Lee E. Scott California State University, Fresno

Theories Nursing 221 1.	Briefly (1-2 sentences) identify the key ideas or characteristics of each of the four historical eras of development in the field of nursing. a.      The curriculum era:  This addresses the question of specific courses, standard study that nursing students need to reach their goals. This evolved nursing education from the hospitals into the universities. b.     The research era:  This is specialized education, knowledge development in research courses towards advanced higher education on a graduate level. The emphasis is arriving at the understanding of the scientific world with the research path to new nursing knowledge. c.      The graduate education era: Master’s degree and doctoral programs in nursing evolved to meet society’s need for nurses with specialized education. Also, it is necessary for research and graduate education increasing the studying of research and conceptual theories development.

d.     The theory era:  It is the natural development of the research and graduate education eras. Also, emphasis is increased knowledge research; theories put together producing nursing science. 2.	Briefly (1-2 sentences), in your own words, define the following: a.      Nursing philosophy is furthering the areas of human science through the analysis of reasoning and logical argument. It is a historical and traditional source for the practice to guide nurses in their work. b.     Conceptual model gives nursing its starting point (reference), and guides to look, and translates the evidence of interest to the profession of nursing care. c.      Nursing theory is collecting data, describe, explain, and predict nursing practice. It brings together an organized structure, and various nursing theories that are abstract, but points to conceptual aspect of nursing practice. d.     Middle range nursing theory is a clearer focus, and direct compared to the abstract grand theory. It much more concrete, and falls in the middle of nursing theory. Middle range theory gets into the specifics of nursing action within the nursing theory they evolved. 3.	Identify 3 benefits to studying and implementing nursing theory. , prediction It guides nursing practice, education, research, analyze, and critical thinking skills. 4.	Briefly differentiate between rationalism and empiricism. Rationalism stresses priori reasoning for advance knowledge. This is knowledge coming from reasoning based on theory-then-research strategy. If it does not meet the theoretical tests, then the theory is discarded. Reason is the source of its concepts. Empiricism is based on the idea of sensory experience coming within inductive reasoning. Its method is based on the idea of a collection of facts to form a generalization which is research-then-theory strategy. If we do not have a source of knowledge, then experience is only source of ideas. 5.	Give an example of each of the following (do not use the book example): a.      Concrete concept       textbook, tree, flowers, thing, objects, people b.     Abstract concept        human body, mass, temperature c.      Discrete concept        gender, ethnic, background, religion, d.     Continuous concept   blood pressure, pain, spiritual, 6.	Choose a concept that you might use as a research variable. Provide a theoretical and an operational definition for your variable. a.      Concept:   The research variable would using Dorothea Orem’s  theory which is a self care theory in maximizing the patient's level of self care used in developing nursing courses, and is operational in the VA Hospital System. Self-care deficit theory is focused with evaluating the self-care agent’s ability to meet therapeutic self-care demand. b.     Theoretical definition: Orem’s theory focus of nursing is on the identification of the patient’s self-care requisites. Orem defines the person or persons as the self-care agent (SCA). The goal is to involve deliberate actions to promote health, and well-being. Self-care deficit theory (SCDT) goes with the nursing process as a way of building nursing systems to compensate for the self-care deficit. c.  Operational definition:   How to apply this theory is to set goals that are measurable. Self-care, according Orem is the practice of all the activities that the patient tries to accomplish and perform on his or her behalf in maintaining life, health, and well-being on a satisfactory level.


title: File:Flyght1.gif


text:
Subspecialties of Nursing and Advanced Practice

Running head: THEORIES QUIZ

Theories Quiz Lee E. Scott California State University, Fresno

Theories Quiz Theory Quiz – Nursing 221 1.	Briefly (1-2 sentences) identify the key ideas or characteristics of each of the four historical eras of development in the field of nursing. a.      The curriculum era:  This addresses the question of specific courses, standard study that nursing students need to reach their goals. This evolved nursing education from the hospitals into the universities. b.     The research era:  This is specialized education, knowledge development in research courses towards advanced higher education on a graduate level. The emphasis is arriving at the understanding of the scientific world with the research path to new nursing knowledge. c.      The graduate education era: Master’s degree and doctoral programs in nursing evolved to meet society’s need for nurses with specialized education. Also, it is necessary for research and graduate education increasing the studying of research and conceptual theories development.

d.     The theory era:  It is the natural development of the research and graduate education eras. Also, emphasis is increased knowledge research; theories put together producing nursing science. 2.	Briefly (1-2 sentences), in your own words, define the following: a.      Nursing philosophy is furthering the areas of human science through the analysis of reasoning and logical argument. It is a historical and traditional source for the practice to guide nurses in their work. b.     Conceptual model gives nursing its starting point (reference), and guides to look, and translates the evidence of interest to the profession of nursing care. c.      Nursing theory is collecting data, describe, explain, and predict nursing practice. It brings together an organized structure, and various nursing theories that are abstract, but points to conceptual aspect of nursing practice. d.     Middle range nursing theory is a clearer focus, and direct compared to the abstract grand theory. It much more concrete, and falls in the middle of nursing theory. Middle range theory gets into the specifics of nursing action within the nursing theory they evolved. 3.	Identify 3 benefits to studying and implementing nursing theory. , prediction It guides nursing practice, education, research, analyze, and critical thinking skills. 4.	Briefly differentiate between rationalism and empiricism. Rationalism stresses priori reasoning for advance knowledge. This is knowledge coming from reasoning based on theory-then-research strategy. If it does not meet the theoretical tests, then the theory is discarded. Reason is the source of its concepts. Empiricism is based on the idea of sensory experience coming within inductive reasoning. Its method is based on the idea of a collection of facts to form a generalization which is research-then-theory strategy. If we do not have a source of knowledge, then experience is only source of ideas. 5.	Give an example of each of the following (do not use the book example): a.      Concrete concept       textbook, tree, flowers, thing, objects, people b.     Abstract concept        human body, mass, temperature c.      Discrete concept        gender, ethnic, background, religion, d.     Continuous concept   blood pressure, pain, spiritual, 6.	Choose a concept that you might use as a research variable. Provide a theoretical and an operational definition for your variable. a.      Concept:   The research variable would using Dorothea Orem’s  theory which is a self care theory in maximizing the patient's level of self care used in developing nursing courses, and is operational in the VA Hospital System. Self-care deficit theory is focused with evaluating the self-care agent’s ability to meet therapeutic self-care demand. b.     Theoretical definition: Orem’s theory focus of nursing is on the identification of the patient’s self-care requisites. Orem defines the person or persons as the self-care agent (SCA). The goal is to involve deliberate actions to promote health, and well-being. Self-care deficit theory (SCDT) goes with the nursing process as a way of building nursing systems to compensate for the self-care deficit. c.  Operational definition:   How to apply this theory is to set goals that are measurable. Self-care, according Orem is the practice of all the activities that the patient tries to accomplish and perform on his or her behalf in maintaining life, health, and well-being on a satisfactory level.


text:
Psychological resilience

This learning resource is for introducing and explaining the concept of psychological resilience and for researchers to discuss investigations of resilience.

Theory
The notion of resilience derives from the physiological stress literature and the coping literature.

Resilience is one's ability to “bounce back” (Smith et al., 2008 ).

The etymology is from the Latin word resile which translates to bounce or spring back (Oxford Dictionary, 2004). This definition views resilience as a process of returning to normal function after a stressful event.

Reslience can be differentiated from “thriving”, which involves decreased reactivity to stressors, quicker recovery from subsequent stressors and/or a higher maintained level of functioning (Carver, 1998; O’Leary & Ickovics, 1995).

Resilience has been related to other positive personal traits such as hardiness, mental toughness and self-efficacy. Hardiness is defined as a combination of commitment, control and challenge, managed by turning a stressful circumstance into an opportunity for growth (Kobasa, 1979; Maddi, 2002). Mental toughness is defined as disciplined thinking and a response to pressure that allows the individual to stay relaxed, calm and energised (Clough, Earle, & Sewell, 2002; Loehr, 1986). Self-efficacy develops via mastering experiences through perseverance and overcoming obstacles with sustained efforts (Carr, 2004). This leads to knowledge of one’s own boundaries and limitations (Bandura, 1997). These characteristics contribute to and are supported by resilience (Bonanno, 2004), however, are not included in the definition of resilience as they cloud its simplicity and clarity (Smith et al., 2008 ).

Measurement
There are a variety of options for measuring the resiliency of an individual, a family, a classroom, a school, community or organisation.

This article reviews 19 resilience instruments (4 of which are refinements of earlier instruments):
 * Windle, G., Bennett, Noyes, J. (2011). A methodological review of resilience measurement scales, Health and Quality of Life Outcomes, 9(8). doi: 10.1186/1477-7525-9-8

It suggests that the best psychometric ratings exist for:
 * Connor-Davidson Resilience Scale (CD-RISC; 5 factors, 25 items; Connor & Davidson, 2003)
 * Connor-Davidson Resilience Scale - Short (CD-RISC; 1 factor, 10 items; Connor & Davidson, 2003)
 * Resilience Scale for Adults (RSA; 6 factors, 33 items; Friborg et al., 2005 )
 * Brief Resilience Scale (BRS; 1 factor, 6 items; Smith et al., 2008 )

Copyrighted, no-cost

 * Connor-Davidson Resilience Scale (CD-RISC; 5 factors, 25 items; Connor & Davidson, 2003)
 * Connor-Davidson Resilience Scale - Short (CD-RISC; 1 factor, 10 items; Connor & Davidson, 2003)
 * Bharathiar University Resilience Scale (BURS; 30 items; Annalakshmi, 2009)

Proprietary, at-cost measure

 * Resilience Scale (Wagnild & Young, 1993)
 * Resiliency Initiatives - versions for:
 * 8 - 12 years
 * 13 - 18 years
 * 19 years and up

Indicators of resilience

 * 1) Use mind-calming and restorative activities.
 * 2) Continually undertake challenges to experience and learn new things.
 * 3) View future with optimism and hope.
 * 4) Emphasise positive (optimistic) thinking over negative (pessimistic) thinking
 * 5) Persist in pursuit of important goals.
 * 6) Choose actions consistent with deeply held values
 * 7) Experience a sense of purpose in life.

Resilience quiz
True or false?
 * 1) One's level of resilience is fixed - it cannot be changed. (False)
 * 2) Resilient people do not experience stress. (False)
 * 3) Resilient tends to increase with age. (True)
 * 4) Adversity improves resilience. (Neither true or false - it can go either way - adversity can increase or decrease resilience. And, whilst a healthy experience of resilience can be a very effective way to enhance resilience, there are also other ways to improve resilience.)

title: Psychological resilience


text:
User talk:Eas4200c.f08.vqcrew.c

 Hello Eas4200c.f08.vqcrew.c, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

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title: User talk:Eas4200c.f08.vqcrew.c


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User talk:Eas4200c.f08.ZYX.barnard

 Hello Eas4200c.f08.ZYX.barnard, and welcome to Wikiversity! If you need help, feel free to visit my talk page, or contact us and ask questions. After you leave a comment on a talk page, remember to sign and date; it helps everyone follow the threads of the discussion. The signature icon in the edit window makes it simple. To get started, you may

 * Take a guided tour and learn to edit.
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And don't forget to explore Wikiversity with the links to your left. Be bold to contribute and to experiment with the sandbox or your userpage, and see you around Wikiversity! --JWSchmidt 06:25, 12 September 2008 (UTC)

title: User talk:Eas4200c.f08.ZYX.barnard


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Talk:Learning from conflict and incivility/Salmon of Doubt

I appreciate reading your thoughts here, as it helps me to understand your own particular reflection on the situation. The Jade Knight 06:57, 12 September 2008 (UTC)