text:
User:Egm6321.f10.team4.Yoon/Mtg38

=EGM6321 - Principles of Engineering Analysis 1, Fall 2010=

[[media: 2010_11_11_08_24_37.djvu | Mtg 38:]] Thu, 11 Nov 10

= Legendre functions: Orthogonality, odd-ness, even-ness =

[[media: 2010_11_11_08_24_37.djvu | Page 38-1]]
Now, back to the heat problem.

= Heat conduction on a sphere (cont'd) =

Spotting zero coefficients with no computation
[[media: 2010_11_10_14_40_12.djvu | Eqn(4) p.37-5:]] $$\displaystyle f(\mu) =T_0 \left( 1-\mu^2 \right)^2 $$ is an even function.

$$\displaystyle \Rightarrow A_n=0$$ for $$\displaystyle n=2k+1$$, since $$\displaystyle P_{2k+1}(\mu)$$ is an odd function.

$$\displaystyle \Rightarrow A_1=A_3=A_5=. . . =0$$

Actually, it turns out that $$\displaystyle A_n=0 \ \forall n \geqslant5$$ due to the linear independence of the family $$\displaystyle \mathcal F = \{ P_k \} $$ and orthogonality of $$\displaystyle \mathcal F$$.

$$\displaystyle P_n(x) $$ is a polynomials of order n.

$$\displaystyle P_n(x) \in \mathcal P_n$$ set of all polynomials with $$\displaystyle \underbrace{\text{order}}_{\text{degree}} \leqslant n $$.

[[media: 2010_11_11_08_24_37.djvu | Page 38-3]]
Orthogonality of $$\displaystyle \mathcal F=\{ P_k \}$$ [[media: 2010_11_10_14_40_12.djvu | Eqn(2a) p.37-4]]

[[media: 2010_11_11_08_24_37.djvu | Page 38-4]]
Consider $$\displaystyle f(\mu) = T_0(1-\mu^2)^2 = T_0 \cos^4 \theta$$.

Hence only need to evaluate $$\displaystyle A_0, A_2, A_4$$

[[media: 2010_11_11_08_24_37.djvu | Page 38-5]]
[[media: 2010_11_10_14_40_12.djvu | Eqn(1)p.37-2]]:

title: User:Egm6321.f10.team4.Yoon/Mtg38


text:
User:Egm6321.f10.team4.Yoon/Mtg40

=EGM6321 - Principles of Engineering Analysis 1, Fall 2010=

[[media: 2010_11_23_15_05_23.djvu | Mtg 40:]] Tue, 23 Nov 10

= Historical development of Legendre functions =

[[media: 2010_11_23_15_05_23.djvu | Page 40-1]]
Historical Development of $$\displaystyle \{ P_n \} $$ Plan: - Atraction of spheres - Newtonian potential in spherical coordinate - Power series => $$\displaystyle \{ P_n \} $$ - binomial theorem - 2 recurrence relations - Legendre differential equation

Legendre: Attraction of spheres

Newtonian potential: $$\displaystyle V=\frac{1}{r_{PQ}}$$ Recall: Force = grad $$\displaystyle V (\Rightarrow \frac{1}{r^2})$$ Express $$\displaystyle r_{PQ} $$ in terms of spherical coodinate of P and Q

= Generating function for Legendre polynomials =

[[media: 2010_11_23_15_05_23.djvu | Page 40-3]]
Recall

 * {| style="width:100%" border="0"

$$  \displaystyle (r_{PQ})^2 = (r_P)^2 + (r_Q)^2 - 2r_Pr_Q \cos \gamma $$     (3)
 * style="width:95%" |
 * style="width:95%" |
 *
 * }

 * style = |
 * }
 * }

Now power series of potential energy.

= Power series of potential energy =

Goal: Power series of $$\displaystyle V$$ in terms of $$\displaystyle \rho$$.

[[media: 2010_11_23_15_05_23.djvu | Page 40-4]]
King p.35:

General binomial theorem
n integers(negative, positive)

Generalize (2) to case n=r=real numbers

Note:

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/

title: User:Egm6321.f10.team4.Yoon/Mtg40


text:
User:Egm6321.f10.team4.Yoon/Mtg42

No Class

title: User:Egm6321.f10.team4.Yoon/Mtg42


text:
User:Egm6321.f10.team4.Yoon/Mtg44

=EGM6321 - Principles of Engineering Analysis 1, Fall 2010=

[[media: 2010_11_30_19_50_24.djvu | Mtg 44:]] Fri, 3 Dec 10

Step 3: Eliminate $$\displaystyle A^{\frac{3}{2}}$$
Compare [[media: 2010_11_30_14_54_10.djvu | Eqn(1) p.41.4]] and [[media: 2010_11_30_14_54_10.djvu | Eqn(6)p.41.3:]]

$$\displaystyle (\mu - \rho) \times $$ $$\displaystyle [$$ [[media: 2010_11_30_14_54_10.djvu | Eqn(6)p.41.3]] $$\displaystyle ]$$ $$\displaystyle = \rho \times$$ $$\displaystyle [$$ [[media: 2010_11_30_14_54_10.djvu | Eqn(1) p.41.4]] $$\displaystyle ]$$

$$\displaystyle \Rightarrow (\mu - \rho) \times \frac{\rho}{A^{\frac{3}{2}}} = \rho \sum^{\infty}_{n=1} P_n(\mu) n \rho^{n-1} $$

The summation index $$\displaystyle n$$ starts from $$\displaystyle 1$$ instead of $$\displaystyle 0$$ due to the presence of $$\displaystyle n$$ in the summand.

$$\displaystyle \Rightarrow (\mu - \rho) \sum_{n=1}^{\infty} P_n'(\mu) \rho^n = \rho \sum_{n=1}^{\infty} P_n(\mu) n \rho^{n-1}$$

$$\displaystyle \Rightarrow \mu \sum^{\infty}_{n=1} P_n' \rho^n - \sum^{\infty}_{n=1} P_n' \rho^{n+1} = \sum^{\infty}_{n=1} P_n n \rho^n$$

$$\displaystyle \Rightarrow \underbrace{\mu \underbrace{P_1'}_{\color{blue}{1}} \rho - \underbrace{P_1}_{\color{blue}{\mu}} \cdot 1 \cdot \rho}_{\color{red}{0}} + \sum_{n=2} [-P_{n-1}' + \mu P_n' - nP_n]\rho^n = 0 $$

$$\displaystyle \Rightarrow -P_{n-1}' + \mu P_n' - n P = 0$$

[[media: 2010_11_30_19_50_24.djvu | Page 44-2]]
RR1:

2nd recurrence relation: Derivation
[[media: 2010_11_23_15_05_23.djvu | Eqn(5) p.40-3]]:

[[media: 2010_11_30_14_54_10.djvu | Eqn(1) p.41-4]]:

[[media: 2010_11_30_19_50_24.djvu | Page 44-3]]
Want to have $$\displaystyle \rho^n$$ as common factor.

Ignore the initial terms => recurrence rel. is from factors of $$\displaystyle \rho^n $$

[[media: 2010_11_30_19_50_24.djvu | Page 44-4]]
$$\displaystyle -2\mu[P_1 \cdot 1 \cdot \rho + \sum_{n=2} P_n n \color{red}{\rho^n} \color{black}{] + [\sum_{n=2} P_{n-1}(n-1)} \color{red}{\rho^n} \color{black}{]} $$

$$\displaystyle \Rightarrow \mu P_n - P_{n-1} = P_{n+1}(n+1) - 2 \mu P_n n + P_{n-1} (n-1)$$

$$\displaystyle \Rightarrow (n+1)P_{n+1} - (2n+1)\mu P_n + n P_{n-1} = 0 $$ (RR2)

Now Legendre differential equation.

[[media: 2010_11_30_19_50_24.djvu | Page 44-5]]
$$\displaystyle \color{red}{(RR1)} \color{black}{ \Rightarrow (n+1)P_{n+1}' - (2n+1)[P_n + \mu P_n' ] + n\underbrace{(\mu P_n' - nP_n)}_{\color{blue}{P_{n-1}'}}} = 0$$

$$\displaystyle \Rightarrow (n+1) P_{n+1}' - (n+1) \mu P_n' + \underbrace{(-2n -1 -n^2)}_{\displaystyle \color{blue} -(n+1)^2} P_n = 0$$

$$\displaystyle \Rightarrow P_{n+1}' - \mu P_n' - (n+1) P_n = 0$$

Change $$\displaystyle (n+1)$$ to $$\displaystyle n$$:

$$\displaystyle \Rightarrow P_n' - \mu P_{n-1}' - n P_{n-1} = 0$$

Transform index to $$\displaystyle n$$ using (RR1) again: $$\displaystyle P_{n-1}' = \mu P_n' - n P_n$$

$$\displaystyle \Rightarrow (1-\mu^2) P_n' + n \mu P_n - n P_{n-1} = 0$$

Want to transform the index of $$\displaystyle P_{n-1}$$ in the last term to $$\displaystyle n$$.

[[media: 2010_11_30_19_50_24.djvu | Page 44-6]]
Note:

To write the 2nd term in [[media: 2010_11_30_19_50_24.djvu | Eqn(1) p.44-1]] with the factor $$\displaystyle \rho^n$$, first define the index $$\displaystyle m:=n+1$$ to have

$$\displaystyle \sum^{\infty}_{n=1} P_{n}' \rho^{n+1} = \sum^{\infty}_{m=2} P_{m-1}' \rho^{m}$$

Then change the index $$\displaystyle m$$ back to $$\displaystyle n$$ to obtain

$$\displaystyle \sum^{\infty}_{n=1} P_{n}' \rho^{n+1} = \sum^{\infty}_{n=2} P_{n-1}' \color{red}{\rho^{n}}$$

end Note

title: User:Egm6321.f10.team4.Yoon/Mtg44


text:
User:Egm6321.f10.team4.Yoon/Mtg46

 Mtg 46: Mon, 6 Dec 10

[[media: 2010_12_02_14_28_37.djvu | Page 46-1]] Other applications: Dislocation theory, Quantum mechanics, Spectral Methematics. Discrete var. : Coding theory, Probability(Queing Theory, Birth and Death) Ref: Nikitorrv et al.(1991)

Rodrigues's formula: Another way to generate $$\displaystyle \{ P_n \}$$

Other orthogonal functions: (in particular, polynomials)

[[media: 2010_12_02_14_28_37.djvu | Page 46-2]] Unified general theory of orthogonal functions Note: Also include Bessel Functions.

Def: (After some transformations) Fundermental equations of Hypergeometric type(FEHT)

Ex: Legendre differntial equation(LDE)

[[media: 2010_12_02_14_28_37.djvu | Page 46-3]]

Theorem 1: All derivatives of a FHT, which is a solution of a FEHT, is again a FHT. Def: y is a FHT, i.e., a solution of a FEHT

Theorem 2: "Self-adjoint" form

[[media: 2010_12_02_14_28_37.djvu | Page 46-4]]

Theorem 3:

[[media: 2010_12_02_14_28_37.djvu | Page 46-5]] By Theorem 2:

note: [[media: 2010_12_02_14_28_37.djvu | (1)p.46-5]] is general Rodrigues's formula with [[media: 2010_12_02_14_28_37.djvu | (1)p.46-1]] as particular case.

Canonical form of classical orthogonal polynomials

title: User:Egm6321.f10.team4.Yoon/Mtg46


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User talk:Apawan.L

Hi !! My Name is Apawan. I'm an MBA Student at Silpakorn University International College.

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User:Charyanaan

hi im Charyanaan and Supasin Group

What is SugarCRM?

SugarCRM Inc. is the 800-pound gorilla in the open-source CRM category. Founded in 2004 by John Roberts, Clint Oram and Jacob Taylor, the Sugar open-source code has been downloaded more than 3 million times. The company has received $26 million in venture financing and employs more than 100 people. More than 12,000 companies use SugarCRM including Honeywell International, Starbucks Corp., First Federal Bank and BDO Seidman LLP. SugarCRM is written in PHP and is compatible with the MySQL database. You can easily import data from another CRM solution, or even just a standard spreadsheet using the standard Comma Separated Value (CSV) format. You can import directly into the database, or use the import wizard found in the shortcut menus through out the application. If you need additional help, SugarCRM offers data migration packages to assist you with importing your data SugarCRM is an open-source CRM platform which covers the basic needs of contact, account, campaign and sales management.

It's benefits are with the selling premium cable TV subscription package on UBC shop around:

•	It is very easy to customize

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What can we offer besides SugarCRM?

JBOSS Process Engine provides a very functional platform for integration, task and process management. A single web application is created to provide a unified interface, while all the information and actions are pulled together via web services.

SCM Homework

Micros Fidelio – My-i-Inventory

MICROS Materials Control gives your business the ability to manage your entire procurement process from requisition to delivery. Whether you are operating a cafe or a group of restaurants, Materials Control will allow you to streamline inventory management processes to increase the accuracy, speed and efficiency or your ordering process.

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MyInventory was developed with those objectives in mind. The application enables managing inventories at either a single property or multiple locations, and is integrated within the browser based myMicros.

Micros- Fidelio

MICROS Materials Control would be the best SCM package for hotel as it is very popular and they are very function able easy to use and cover in all area in the hotel and restaurant inventories. Micros-Fidelio also do after training that will be needed for the Hotel’s staff that a number of staff will be involve in using Fidelio. They all so separate the program in the categories in the different pages for example one page will be for Food and Beverage inventory for Food and Beverage store, Page for Non- Food inventories for General store and Engineer Inventory Page for maintenance Area all of those reason are very convenience for store keeper receiving and end user.

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User:ActuarialStudent2.71828182

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hello world.............. i'm in.................

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title: File:Fe1.s11.mtg6.djvu


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User:EGM6341.s11.TEAM1.Yoon

= Homework mynote = Homework 1

Team Homework 1

Homework 2

Team Homework 2

Homework 3

Team Homework 3

Homework 4

Team Homework 4

=SPRING 2011 HOMEWORK TABLE=

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User:Eml5526.s11.team1.fcas

Hi team1

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Working on HW 1

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User:EGM6341.S11.team5.cavalcanti

Homeworks Table Walkthrough Mtg1 Mtg3 Mtg5 Mtg7 Mtg9 Mtg11 Mtg13 Mtg15 Mtg17 Mtg19 Mtg21 Mtg23 Mtg25 Mtg27 Mtg29 Mtg31 Mtg33 Mtg35 Mtg37 Mtg39 Mtg41 Mtg43

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title: User talk:EGM6341.S11.team5.cavalcanti


text:
User talk:EGM6341.s11.TEAM1.Yoon

 Hello EGM6341.s11.TEAM1.Yoon, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 16:50, 16 January 2011 (UTC)

Files Missing License Information
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 * File:Nm1 s11 team1 HW7 p0 fig c1.png
 * File:Nm1.s11.team1.HW3.p4.bifolium.png

MaintenanceBot (discuss • contribs) 03:45, 11 November 2013 (UTC)

title: User talk:EGM6341.s11.TEAM1.Yoon


text:
User talk:Eml5526.s11.team3.perry

 Hello Eml5526.s11.team3.perry, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 16:50, 16 January 2011 (UTC)

title: User talk:Eml5526.s11.team3.perry


text:
User:Haplology

I taught English in Japan for 5 years from 2007 to 2012.

Grammatical forms
I'm currently working on a set of templates that can be used to create nested tables that show the grammatical structure of an expression, generally a sentence. At the level of the part of speech, the template links to the definition of the word in Wiktionary and an article about the part of speech in Wikipedia. At the level of the phrase, the structure is indicated by indentation, and links are provided to WP articles about those phrases. A sentence marked up in this way displays all of the information that can be given about the sentence at the level of grammar and lexis (vocabulary).

My hope is that students can use tables like those to explore grammar on their own and lead their own studying, rather than passively being led down a syllabus, lesson by lesson, by a teacher. Rather than the learners being passive listeners to a teacher who is a "knower", I want the teacher to be at the side to help the learners be "discoverers".

An example of a nested table of grammatical forms is below.

I am adding categories to the grammatical form templates so that each time one of them is used, the resource using it is added to a category of resources employing that grammatical feature.

Useful resources

 * Template:EnglishLesson

Review
{Put these words in the correct order. -- Word 1 -- Word 2 -- Word 3 -- Word 4 -- Word 5 -- Word 6
 * type=""}

{Put these words in the correct order. - Word 1 - Word 2 - Word 3 - Word 4 - Word 5
 * type=""}

{Put these words in the correct order. -- Word 1 -- Word 2 -- Word 3 -- Word 4 -- Word 5 -- Word 6
 * type=""}

title: User:Haplology


text:
User talk:Haplology

 Hello Haplology, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 18:02, 16 January 2011 (UTC)

Avoiding name clash on the topic of apologizing.
Thanks for developing valuable learning resources on English as a second language.

I am developing a course on the general topic of apologizing based on materials I previously developed at: http://www.emotionalcompetency.com/apology.htm You have provided a learning resource on English language sentences and phrases related to apologizing at: https://en.wikiversity.org/wiki/Apologizing The name space will be better used, and the Wikiversity topology will be more clear if you can please move your specialized treatment to a specialized name space. Specifically I request moving your Apologizing resource, without redirection, to a sub-directory under the topic of English as a Second Language. Alternatively, please rename it to indicate it is specific to English as a second language. I am developing a course on the general topic of apologizing and want to name the new, general course "Apologizing". I believe this will result in a more clear topics hierarchy.

Please let me know how you would like to proceed. Thanks! --Lbeaumont (discuss • contribs) 13:04, 28 July 2018 (UTC)

title: User talk:Haplology


title: File:Nm1.s11.mtg6.djvu


text:
User:Eml5526.s11.t1.ab

Hello everyone, My name is Abhijeet, I am Pursuing MS in Solid mechanics, design and Mfg from UF.

Useful Links - Course Wiki
Eml5526 Course Wiki

Lecture Plan
Lecture Plan

Homework - Report Table
Report table

Group Page
Team 1 Page

Homework Figures
[| Homework Figures]

Homeworks
[Homework2 Page]

[Homework3 Page]

[Homework4 Page]

[Homework5 Page]

[Homework6 Page]

title: User:Eml5526.s11.t1.ab


text:
User talk:TrevorDoe

 Hello TrevorDoe, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 19:43, 16 January 2011 (UTC)

title: User talk:TrevorDoe


text:
User:Lafay~enwikiversity

I am a semiretired physician with an interest in medical education. I would like to learn more about internet resources for learners and am interested in editing some of the Wikiversity resources for medicine.

title: User:Lafay~enwikiversity


text:
User talk:Lafay~enwikiversity

 Hello Lafay, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

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 * Take a guided tour and learn to edit.
 * Visit a (kind of) random project.
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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 20:27, 16 January 2011 (UTC)

Your account will be renamed
Hello,

The developer team at Wikimedia is making some changes to how accounts work, as part of our on-going efforts to provide new and better tools for our users like cross-wiki notifications. These changes will mean you have the same account name everywhere. This will let us give you new features that will help you edit and discuss better, and allow more flexible user permissions for tools. One of the side-effects of this is that user accounts will now have to be unique across all 900 Wikimedia wikis. See the announcement for more information.

Unfortunately, your account clashes with another account also called Lafay. To make sure that both of you can use all Wikimedia projects in future, we have reserved the name Lafay~enwikiversity that only you will have. If you like it, you don't have to do anything. If you do not like it, you can pick out a different name.

Your account will still work as before, and you will be credited for all your edits made so far, but you will have to use the new account name when you log in.

Sorry for the inconvenience.

Yours, Keegan Peterzell Community Liaison, Wikimedia Foundation 23:36, 17 March 2015 (UTC)

Renamed
 This account has been renamed as part of single-user login finalisation. If you own this account you can |log in using your previous username and password for more information. If you do not like this account's new name, you can choose your own using this form after logging in: . -- Keegan (WMF) (talk) 06:14, 19 April 2015 (UTC)

title: User talk:Lafay~enwikiversity


text:
User:Eml5526.s11.team4.simko

EML 5526, Spring 2011, Team 4, Dustan Simko

= Links:=

| Course WIKI

| Team WIKI

| Google Group

=Homework:=

Homework 1

Homework 2

=References:= | Charles Cook

title: User:Eml5526.s11.team4.simko


text:
User:Guido den Broeder/Navigation

 User Talk Edits Pinboard Tools Content Resources

title: User:Guido den Broeder/Navigation


text: User:Guido den Broeder/Resources

title: User:Guido den Broeder/Resources


text: User:Guido den Broeder/Content

title: User:Guido den Broeder/Content


text:
User:Guido den Broeder/Tools

__NOINDEX__

Templates

 * User space navigation

title: User:Guido den Broeder/Tools


text:
User:Guido den Broeder/Pinboard

__NOINDEX__

Categories

 * Category:Categories
 * Category:Requests for custodial action

Schools

 * School:Game design

Wikiversity

 * Maintenance
 * Vision/2010

External

 * List of Wikimedia IRC Channels

title: User:Guido den Broeder/Pinboard


text: Psycholinguistics/Language Thought and Society


text:
SPIR608/Bibliography

This is a bibliography for SPIR608 Political Simulation and Gaming.

title: SPIR608/Bibliography


text:
User:Eml5526.s11.team01

Useful Links
Eml5526 Course Wiki

Homework
Report table

Homework #1
Homework #1

Homework #2
Homework #2

Homework #3
Homework #3

Homework #4
Homework #4

Homework #5
Homework #5

Homework #6
Homework #6

Homework #7
Homework #7

Members
James Roark

Cedric Adam

Fernando Casanova

Yu Hao

Harrison Sheffield

Abhijeet Bhalerao

Team One Facts

 * Team One and Superman once had a bet. The loser had to start wearing his underwear on the outside of his pants.
 * Team One can slam a revolving door.
 * Team One counted to infinity - twice.
 * Team One can delete the recycle bin.
 * Team One knows the last digit of pi.
 * Team One can divide by zero.

title: User:Eml5526.s11.team01


text:
User:Eml5526.s11.team01.roark

=About Me= My name is Jimmy Roark. I work for the Navy in Jacksonville, FL as a Civil Servant.

Extra credit
Test 1

Lectures
Mtg01 Mtg03 Mtg05 Mtg07 Mtg09 Mtg11 Mtg13 Mtg15 Mtg17 Mtg19 Mtg21 Mtg23 Mtg25 Mtg29 Mtg31 Mtg33 Mtg35 Mtg37 Mtg39 Mtg41

title: User:Eml5526.s11.team01.roark


text:
User:User:Eml5526.s11.team01/Hwk1

Were you looking for user:eml5526.s11.team01/Hwk1???

title: User:User:Eml5526.s11.team01/Hwk1


text:
Building

Building, in architecture, is any human-made structure used or intended for supporting or sheltering any continuous occupancy.Buildings come in a wide amount of shapes and functions, and have been adapted throughout history for a wide number of factors, from building materials available, to weather conditions, to land prices, ground conditions, specific uses and aesthetic reasons.

Buildings serve several needs of society – primarily as shelter from weather and as general living space, to provide privacy, to store belongings and to comfortably live and work. A building as a shelter represents a physical division of the human habitat (a place of comfort and safety) and the outside (a place that at times may be harsh and harmful).

History
The first shelter on Earth constructed by a relatively close ancestor to humans is believed to be built 500,000 years ago by an early ancestor of humans.

title: Building


text:
User:Eml5526.s11.team7.snook

Lecture 1

HW 2

HW 4

title: User:Eml5526.s11.team7.snook


text:
User talk:Eml5526.s11.team01

Hi, I am a account for Team 01 on FE1.Spring11

 Hello Eml5526.s11.team01, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

To get started, you may

 * Take a guided tour and learn to edit.
 * Visit a (kind of) random project.
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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 01:01, 17 January 2011 (UTC)

title: User talk:Eml5526.s11.team01


text:
User talk:Jkwchui

 Hello Jkwchui, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 01:01, 17 January 2011 (UTC)

title: User talk:Jkwchui


text:
User talk:Eml5526.s11.team01.roark

 Hello Eml5526.s11.team01.roark, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

To get started, you may

 * Take a guided tour and learn to edit.
 * Visit a (kind of) random project.
 * Browse 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.
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 * 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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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 01:01, 17 January 2011 (UTC)

Files Missing License Information
Thank you for uploading files to Wikiversity. See Media for copyright and license requirements for Wikiversity files. All files must have copyright and/or license information added to the file.

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 * File:Fe1.s11.mtg25.figure25-1.svg
 * File:Fe1.s11.mtg29.figure29-1.svg
 * File:Fe1.s11.mtg29.figure29-2.svg
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 * File:Fe1.s11.team1.hw4.fig6.1.jpg

MaintenanceBot (discuss • contribs) 03:46, 11 November 2013 (UTC)

title: User talk:Eml5526.s11.team01.roark


text:
User talk:Eml5526.s11.team7.snook

 Hello Eml5526.s11.team7.snook, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

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 * Take a guided tour and learn to edit.
 * Visit a (kind of) random project.
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 * Explore Wikiversity with the links to your left.

 * Read an introduction for teachers and find out how to write an educational resource for Wikiversity.
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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 01:01, 17 January 2011 (UTC)

title: User talk:Eml5526.s11.team7.snook


text:
User talk:Speaks3703

 Hello Speaks3703, 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. All users are expected to abide by our Privacy policy, Civility policy, and the Terms of Use while at Wikiversity.

To get started, you may

 * Take a guided tour and learn to edit.
 * Visit a (kind of) random project.
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 * Find out about research activities on Wikiversity.
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 * Read an introduction for teachers and find out how to write an educational resource for Wikiversity.
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You don't need to be an educator to edit. You only need to be bold to contribute and to experiment with the sandbox or your userpage. See you around Wikiversity! --Ottava Rima (talk) 01:01, 17 January 2011 (UTC)

title: User talk:Speaks3703


title: File:Fe1.s11.mtg7.djvu


text:
User:Beaudalion

TS

Mobile specification Homework

IPad 2

Capacity 8GB, 16GB, or 32GB flash drive

TV and video

Support for 480p and 576p component TV out

Wireless Wi-Fi (802.11b/g) Nike + iPod support built in Maps location-based service

Display 3.5-inch (diagonal) widescreen Multi-Touch display 480-by-320-pixel resolution at 163 pixels per inch

Audio Frequency response: 20Hz to 20,000Hz

IPhone 4

Capacity3

	16GB or 32GB flash drive

Display

	Retina display 	3.5-inch (diagonal) widescreen Multi-Touch display 	960-by-640-pixel resolution at 326 ppi 	800:1 contrast ratio (typical) 	500 cd/m2 max brightness (typical) 	Fingerprint-resistant oleophobic coating on front and back 	Support for display of multiple languages and characters simultaneously Camera, photos, and video 	Video recording, HD (720p) up to 30 frames per second with audio 	5-megapixel still camera 	VGA-quality photos and video at up to 30 frames per second with the front camera 	Tap to focus video or still images 	LED flash 	Photo and video geotagging Audio playback 	Frequency response: 20Hz to 20,000Hz Cellular and wireless 	GSM model: UMTS/HSDPA/HSUPA (850, 900, 1900, 2100 MHz); GSM/EDGE (850, 900, 1800, 1900 MHz) 	CDMA model: CDMA EV-DO Rev. A (800, 1900 MHz) 	802.11b/g/n Wi-Fi (802.11n 2.4GHz only) 	Bluetooth 2.1 + EDR wireless technology

Blackberry BOLD 9700 •Display: o	 Light sensitive screen o	User-selectable font size o	High-resolution 480x360 pixel color display •Wifi: o	802.11 b / g o	WPA / WPA2 Personal and Enterprise o	Cisco CCX certified o	Wi-Fi® access to BlackBerry® Enterprise Server o	Wi-Fi access to BlackBerry® Internet Bundle o	Support for UMA (carrier-dependent) •Audio & Voice o	3.5 mm stereo headset jack o	Built-in speakerphone o	M3/T3 rating for hearing aids •Memory: o	256 MB onboard memory o	2 GB media card included o	Expandable memory with support for microSD cards •Camera & video recording: o	3.2 MP camera o	2X digital zoom o	Flash o	Video recording

In my opinion, amongst the three mobiles (IPad2, IPhone4 and Blackberry bold 9700), the best mobile is IPhone 4 because IPhone4 got the best camera which is 5-megapixel while blackberry's camera is only 3.2 megapixek and it got more memory than the blackberry. Also IPhone can be used as a phone to call but IPad can’t. IPhone also smaller than IPad and thinner than blackberry so it have a very good appearance.

-

Aspire AZ3751

Operating system: Genuine Window 7 Home Premium

Processor: Intel® Core™ i5 processor (4 MB L3 cache, DDR3 1333 MHz, 73 W)

Audio: Creative® THX® TruStudio PC™, featuring TruStudio Surround, TruStudio Crystalizer, TruStudio Dialog Plus, TruStudio Smart Volume, TruStudio Speaker Embedded high-definition audio with 7.1-channel surround sound and EAX® 5.0 audio support Creative® Sound Blaster™ X-Fi Titanium sound card with EAX® 5.0 audio support S/PDIF (Sony/Philips Digital Interface) support

Chipset: Intel® H57 Express Chipset

Memory: Up to 8 GB of DDR3 1333 MHz SDRAM (dual-channel support on four DIMMs)

Display: 21.5" Full HD 1920 x 1080 pixel resolution, high brightness (300-nit), TFT LCD Integrated multi-touch screen supporting finger touch 16:9 aspect ratio 5 ms response time 16.7 million colors 1000:1 (ACM) contrast ratio

Hard drive: Serial ATA hard disk up to 1.5 TB8

Optical Drive: BD reader & SuperMulti burner SuperMulti

Card reader: Multi-in-1 card reader, supporting: MultiMediaCard™ (MMC) MMCmobile™ MMCmicro™ Reduced-Size MultiMediaCard (RS-MMC) Secure Digital™ (SD) Card xD-Picture Card™ Memory Stick™ Memory Stick Duo™ Memory Stick PRO™ Memory Stick PRO Duo™

Graphic (on-board): Intel® HD Graphics with 1.70 GB of video memory, featuring: Intel® Clear Video HD Technology, DVD upscaling MPEG-2, VC-1, AVC/H.264 decoding De-interlacing, sharpness detail, noise reduction, Film Mode detection, video scaling, panel scalar Microsoft® DirectX® 10 support Intel® Dynamic Video Memory Technology 5.0 (Intel® DVMT 5.0) support

Audio: Dolby®6-optimized surround sound system with two built-in stereo speakers Optimized Dolby® Home Theater®6 audio enhancement, featuring Dolby® Digital, Dolby® Digital Live, Dolby Pro Logic® II, Dolby® Headphone and Dolby® Virtual Speaker technologies7 High-definition audio support Built-in microphone Integrated 5 W stereo speaker system MS-Sound compatible

Communication: WLAN1, 9 802.11b/g/n Wi-Fi CERTIFIED™ WPAN1: Bluetooth® 2.1 + EDR LAN: Gigabit Ethernet

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Psycholinguistics/Parsing

What is Parsing?
Parsing is the assignment of the words in a sentence to their appropriate linguistic categories to allow understanding of what is being conveyed by the speaker. It is not simply the assignment of words to simple diagrams or categories, but also involves evaluating the meaning of a sentence according to the rules of syntax drawn by inferences made from each word in the sentence. This evaluation of meaning is what makes parsing such a complex process. When speech or text is being parsed, each word in a sentence is examined and processed to contribute to the overall meaning and understanding of the sentence as a whole.

It occurs as the language is being processed, examining both the past and present stimuli to allow understanding of future concepts. When a sentence is read, the reader decides which categories the words belong in. These categories include basic grammatical components,(such as agent, proposition, patient) that are assigned based on what is inferred. These categories are very basic, simple enough that a computer can parse them if enough grammatical rules and roles are known.

However, parsing cannot just rely on simple grammatical rules as quite often, these thematic categorical components can be assigned to multiple categories or take on multiple meanings that drastically change the meaning of a sentence. This is part of what causes parsing to be so complex as it must go past the basic grammatical understanding of a word or a sentence and apply the correct meaning to it.

Parsing allows the reader to make these decisions, based on cues obtained from the words previously read in the sentence and the conclusions that can be drawn from these words. It takes the meaning drawn from what was read previously to allow understanding of what is currently being read. This parsing continues from word to word, sentence to sentence and paragraph to paragraph.

What Causes Parsing?
Parsing is driven by four main factors. Each contribute to parsing occurring correctly, however the exact weight of each of these forces' contribution is unknown. These factors are as follows:

Thematic roles
These are critical to parsing as they allow the most basic understanding of a sentence. This initial comprehension must be made before further and deeper inferences can be parsed. As a sentence is being spoken or read, roles are assigned to every noun phrase by using role assignors such as verbs. The verbs being assigned determine which roles need to be filled in a sentence, depending on which noun phrases are used. The primary decisions in parsing are based on the lowest "cost" in the sentence system in liking roles and noun phrases together. This means that the decisions regarding assignment to categories are based on the lowest amount of rules broken. The thematic roles focus on the lexical information being presented. They rely on interpreting the words semantically in a sentence. It allows the linkage and coordination of both the semantic and discourse information as well as lexical and syntactic information (Christianson, 2001).

Semantic Features
Semantic features are associations that are directly affiliated with a particular word or idea. These associations may be conscious or subconscious. For example, a person thinks of an apple, they might also think of the color red, a worm or a tree. If a person thinks of a bird, then flying, feathers, and nest, may come to mind, as they are semantic features related to birds.

When parsing occurs of a sentence or phrase, the parser uses these semantic features of a word to draw inferences about the meaning of a sentence. This is crucial to understanding a sentence as sometimes examining thematic roles is not enough. This is especially true with common phrases or slang that doesn't always mean what the direct thematic roles suggest. An example of this would be, "Jane kicked the bucket." Parsing that sentence without knowing the correct semantic features would cause the reader to believe that Jane actually knocked over a bucket with her foot. However, knowing that this phrase is also semantically associated with dying, the reader can parse the sentence correctly.

Semantic features of sentences don't have to be so obvious however. Sometimes when a sentence is vague or could have multiple meanings, parsing relies on the associations with the words to derive the correct meaning. An example of this would be in the sentence, "Rover barked when someone entered the house." The semantic features in this sentence suggest that Rover is a dog. This is not stated in the sentence, thus Rover could be a cat, a seal or even a person. However due to these semantic features (in this case, the pronoun and the use of the word barking), the reader can correctly infer that Rover is a dog.

Knowing the overall meaning and associations in a sentence allows the cotent to be understood much faster, thus decreasing the time it takes to parse a sentence. However, sometimes errors can be made because of relying on semantics too much during parsing of a sentence, causing the wrong inferences to be drawn. An example of this is a long time riddle: "A plane crashes on the border between Canada and the United States.  Where do they bury the survivors?" The semantics associated with a plane crash and burying suggest that victims should be buried. This leads to the wrong meaning being derived and the parsing of the sentence to be incorrect. However, even with these errors, relying on the semantic features of a sentence allows parsing to be completed much more efficiently.

Probabilities
The probability of a particular meaning of a word being associated with a particular sentence directly drives parsing. When parsing is occurring, assumptions are made about the meaning of what is being parsed based on the probability of that meaning most likely to occur.

Probabilities are important when a sentence is ambiguous. For example, "Visiting relatives can be such a nuisance." If the sentence before or after that sentence was, "We hate the long drive," then it can be assumed that the primary sentence meant going to visit one's relatives rather then the relatives visiting the speaker. This assumption is based on the probability of what the speaker means. It is no more then an educated guess based on the information presented.

Syntactic Phrase Structure
This knowledge of a concrete syntactic phrase structure is critical for parsing to occur. Having a solid knowledge of the rules of grammar and an unwillingness to deviate from these rules cause errors in parsing.

Serial and Parallel Processing
There are two main types of sentence processing that take allow parsing to occur. There has been much debate in the literature regarding which of these types or even if a combination of these types is the definitive strategy for parsing. There has been no solid conclusions on this however (Gibson, 2000; Ashcraft, 2006). The two types of processing are as follows.

Serial Processing
This is when the parser commits to only one syntactic structure at a time. The reader uses one structure, then, upon finding it is inaccurate, will try another solution

Parallel Processing
This is when multiple structures are possibilities of sentence meaning are processed at once.

Chomsky's Transformational Grammar
The basis for Chomsky's theory of grammar is that words can be combined to create meaningful phrases, called phrase structure grammar. Parsing is the process of dividing this. He suggests that sentences have both a simple and a deep structure. The deep structure, which is the meaning of a sentence, is the most meaningful and abstract level of representation of a sentence. Parsing is critical to determining this deep structure. Chomsky also created the tree diagrams that serve as a visual representation for how parsing occurs. For an example of a tree diagram, you can click Here. Another example is illustrated below. Parsing uses these strategies in top down and bottom up parsing. Top down, often called conceptually driven parsing, moves from the top of the tree diagram. It is guided by higher level previous knowledge, which in turn affects the lower level processes. Bottom up processing, or data-driven parsing, is when parsing decisions are made from the bottom of the tree diagram; it is when the parsing decisions are guided by only the features of the sentence itself, driven by the knowledge that is obtained at that given time. The parser starts with the most basic elements, then moves to the more complicated (Ashcraft, 2006).

Theories of Parsing
There are two main theories for parsing of the English language.

1) Garden Path Model: Minimal Attachment

2) Constraint Satisfaction Models

Garden Path Sentences
The Garden Path model is a dominant theory in about how people are able to parse words together to interpret the meaning of statements. The title of the theory is based on a metaphor about being led down the wrong path. In regards to psycholinguistics, a person can be led down the wrong path while reading a sentence when they make inaccurate assumptions about the context of the noun phrases. The reader is not aware that they are being lead down the wrong path. At the beginning of the sentence, or the path, the reader is under the impression that they are proceeding in the right direction with the syntactic structure and making the correct assumptions as they are reading. Then suddenly, new information presented later on in the sentence causes the reader to fall down the rabbit hole. This new information causes confusion because, up until that rabbit hole, the reader assumed they were correct in their perception of the garden path. The assumption behind this theory is that the reader perceives the sentence as being set in only one context. There is a failure to perceive that there may be another context or way to interpret the sentence based on the noun phrases. The reader remains confident in their perceived judgement and assumes they are right. Garden path sentences create confusion as the reader's preconceived judgments are shattered (van Gompel et. al., 2006). There are generally three alternative ways how a person could perceive a sentence:
 * 1) Assemble a structure for just one of the possible interpretations and ignore all others (like the garden path model)
 * 2) Take into consideration all of the possible interpretations for the noun phrase at the same time
 * 3) Complete a partial analysis, with minimal commitment to one perception, waiting to make a final decision until more information is obtained.

Principles that Guide the Garden Path Model
There are two principles of the Garden Path Model which explain how incorrect assignment of roles in a sentence can create confusion.

Late Closure
This parsing error is when the new words and phrases that are creating confusion to be attached to the already open phrase (a phrase that is already being processed). An example of this type of error is: The horse raced past the barn fell (can also be written as: The horse that raced past the barn fell).

Minimal Attachment
This is when the reader uses the simplest strategy to help understand the sentence. It is a strategy of parsimony, where the simplest strategy is seen as being the most accurate, and therefore, the best. Minimal attachment causes each incoming word to be attached to the already existing structure.

Misconceptions Linger
According to the Garden Path Model, the initial mistakes in reading and interpreting the sentence affect the inferences that the reader makes about the sentence as a whole. The reader does realize that an error has occurred in the interpretation of the sentence. Research by Christianson et. al. (2001), suggests that the initial interpretation readers have at the beginning of the sentence remains consistent despite being proved wrong and causing confusion to the reader. These lingering misconceptions are a result of partial reanalysis. They are dependent on variables such as the length of ambiguous problem region, the actual plausibility (whether the sentence makes sense to the reader) and whether or not sentence is a garden path sentence.

The conclusions of this research state that the reader, instead of coming to a concrete, ideal solution, creates a "good enough" interpretation of the ambiguous sentence. This means that a reader's understanding does not focus on establishing a conclusion that fits perfectly to a sentence structure. Instead, the reader stops when they have reached a conclusion that seems to make sense with the processing and deems further processing of the sentence unnecessary (Christianson et. al., 2001).

The "Good Enough" Theory
Fernanda Ferreiand colleagues from the University of Edinburgh(2002) are a few of the primary researchers behind the "good enough" theory of parsing garden path sentences. Since 2002, there has been increased in research in support of this theory.

Research by Barton & Sandford (1993) states that processing of sentences is relatively shallow. A reader will make an assumption and fail to interpret it until further processing of that information is necessary. For example, consider the sentence, "Andrea and Amie saved $100." Generally, when a sentence such as this is ambiguous, the reader will not question or draw conclusions about it until these conclusions are demanded (Did they each save $100, or did they save $100 in total?). The reader operates under the "good enough" theory until deeper processing of the true meaning is required.

Challenges to the Garden Path Model
The Gardent Path Model is not the only model to explain Parsing. Listed below are some other models to explain how parsing may occur and other challenges to the Garden Path theory in general.

Constraint Satisfaction Model
This model states that the reader uses all of the available information at once when engaging in parsing of a sentence. This means that all lexical, syntactic, discourse and contextual information is taken into consideration simultaneously. According to this model, readers use all the information that they have, all the time. This is considered parallel processing, due to the multiple structures that are used.

Dependency Locality Theory
This theory argues that the reader prefers to attach information to local nodes rather than long distance nodes. This is based on amount of working memory required to fully understand a sentence. An increase in the amount of working memory needed to make sense of a sentence is correlated with an increased tendency for the reader to parse locally rather then to use long distance nodes. The theory of locality is crucial to this concept, stating that the cost of integrating two elements together directly depends on the distance between the two (Gibson, 2000).

Competition Model
The majority of theories are based on how people parse English. In different languages, cues may be weighted differently depending on the language in regards to how much they are relied on to parse the language in question. For example, speakers of the English language rely heavily on word order, while Hungarian speakers do not. Language processing is a series of competitions between lexical items, phonological forms and syntactic patterns. There may be other important processing items that are not considered in the Garden Path or any other model specifically because it is not used in the English language. More research has to be completed to compare other language parsing to determine if one theory can simply encompass all languages (MacWhinney & Bates, 1993).

Computers and Parsing
Although the vast majority of information presented has been regarding the natural English language, it must be noted that computers are now programmed to be able to correctly parse. First of all, lexicons are established, if the computer is parsing English, the lexicons would be the entire English dictionary. Grammar rules must then be established. When a computer encounters a sentence, it parses the sentence multiple times, creating tree diagrams until a viable meaning is found (Ashcraft, 2006). However, there is a problem with ambiguity when a computer parses sentences. Many sentences in the English language are vague and rely on either probability or context to determine the meaning of a sentence. Computers can do this, based on knowledge of previous conversations but more mistakes are made. A video describing parsing and computers can be found Here.

Resources
Ashcraft, M.H. & Klein, R.H. (2006). Cognition. Toronto: Pearson Canada. Barton, S. B., & A. J. Sanford. 1993.A case study of anomaly detection: shallow semantic processing and cohesion establishment. Memory and Cognition 21.477–8 Christianson, K., Hollingworth, A., Halliwell, J. F., & Ferreira, F. (2001). Thematic roles assigned along the garden path linger. Cognitive Psychology, 42, 368–407 Ferreira, F., & Patson, N. D. (2007). The “good enough” approach to language comprehension. Language and Linguistics Compass, 1, 71–83. Gibson, E. (2000). The dependency locality theory: A distance-based theory of linguistic complexity. In A. Marantz, Y. Miyashita, W. O'Neil, A. Marantz, Y. Miyashita, W. O'Neil (Eds.), Image, language, brain: Papers from the first mind articulation project symposium (pp. 94-126). Cambridge, MA US: The MIT Press. Retrieved from EBSCOhost. MacWhinney, B., & Bates, E. (1993). The crosslinguistic study of sentence processing. Journal of Child Language, 20, 463-471. van Gompel, R. P. G., Pickering, M. J., Pearson, J., & Jacob, G. (2006). The activation of inappropriate analyses in garden-path sentences: Evidence from structural priming. Journal of Memory and Language, 55, 335–362. http://www.psy.ed.ac.uk/people/fferreir/Fernanda/Ferreira_Patson_LLC_2007.pdf

Learning Exercise: Test Your Knowledge
Here is a video about parsing and the garden path model. You can view it HERE. Then, when you have watched it, complete the follow quiz questions about the topic of parsing and what you've learned in this chapter.

1.	List and describe the two principles of the garden path model. How do they differ?

2.	You are parsing a sentence into a tree structure in Psycholinguistics class one day. Your friend beside you gets a different answer then you do. Is it possible that you are both right? a.	How?

3. What type of sentence processing most likely occurs when a sentence is being parsed? Why?

4. The steps in the Garden Path model is a metaphor for what language component?

5. If a computer was parsing language, which of the four factors of Parsing do you think it would have the biggest problem with automating or doing as well as a human? Why?

title: Psycholinguistics/Parsing


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