Bill owns and has operated a bicycle shop
Bill owns and has operated a bicycle shop in a major regional town since 1 July 2011. He lives 15 minutes from town on 5 hectares with his spouse. The property is on two titles. The 4 hectare block has their home and was purchased in joint names. The adjacent 1 hectare has a large shed and workshop/studio apartment that existed when the blocks were purchased and in which they lived while building the house and was purchased only in Bill’s name. Both properties were purchased at the same time, on 1 November 2009, and the home was completed and they moved in on 1 December 2010.
The annual gross turnover from the bicycle shop last year was $1,200,000 and he expects this to increase by around 10% in the current year.
Each year he arranges for the storage of bicycles purchased, if required by customers, in the shed for pick up in the week before Christmas. Generally these start to be stored from July. In addition he has stored some second hand trade-in bikes acquired mostly in February to October which he drops off at the Mens’ Shed every month. These are reconditioned by the Mens’ Shed members and donated to charity. He has undertaken these activities since July 2015.
During the current year he has undertaken an extension to the shop premises which was finished in April costing $200,000. This additional space will discontinue the need for storage away from the shop.
This assignment has two parts, both must be submitted and your submission should adopt the ILAC decision model. Ensure you note relevant legislation, case law or other supporting information as well as any additional information you may require. The report should follow the style guide below.
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POSTED ONJUNE 21, 2021
the probability distribution function of the error
where xo = (x,.0,x2.0,..,x„.o )7. is the point in which the linearization is performed normally chosen as the mean value point and of (x) = 1,2,..n are the first order partial derivatives ax,
of f (x) taken in x = . From Equation (11.12) and Equation (11.6) it is seen that the expected value of the error E[e] can be assessed by: EH= f (p.) (11.17) and its variance Var[e] can be determined by: yam = tiaM 10.2 (a./(11 ax, x ‘ ax, „, ax, ‘
Provided that the distribution functions for the random variables are known, e.g. normal distributed the probability distribution function of the error is easily assessed. It is, however, important to notice that the variance of the error as given by Equation (11.14) depends on the linearizationpoint, i.e. x. = )T .z,o
Example 1— Linear Safety Margin Consider a steel rod under pure tension loading. The rod will fail if the applied stresses on the rod cross-sectional area exceed the steel yield stress. The yield stress R of the rod and the loading stress on the rod S are assumed to be uncertain modelled by uncorrelated normal distributed variables. The mean values and the standard deviations of the yield strength and the loading are given as g„ = 350,6„ = 35 MPa and US = 200,a, = 40 MPa respectively. The limit state function describing the event of failure may be written as: g(x) = r — s whereby the safety margin M may be written as: M = R — S The mean value and standard deviation of the safety margin M arc thus: Pa = 350 — 200 =150 QM = 4352 +402 = 53.15 whereby we may calculate the reliability index as: = 5150. 2.84 53.15 Finally we have that the failure probability is determined as: Pr = 4,(-2.84) = 2.4.10′
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density function of the random variables X
Pf = Jfx(x)dx (11.3) gmo where fx (x) is the joint probability density function of the random variables X . This integral is, however, non-trivial to solve and numerical approximations are expedient. Various methods for the solution of the integral in Equation (11.3) have been proposed including numerical integration techniques, Monte Carlo simulation and asymptotic Laplace expansions. Numerical integration techniques very rapidly become inefficient for increasing dimension of the vector X and are in general irrelevant. In the following we will direct the focus on the widely applied and quite efficient FORM methods, which furthermore can be shown to be consistent with the solutions obtained by asymptotic Laplace integral expansions.
11.3 Linear Limit State Functions and Normal Distributed Variables For illustrative purposes we will first consider the case where the limit state function g(x) is a linear function of the basic random variables x . Then we may write the limit state function as:
g( x )= ao +Ea ix, (11 -I) If the basic random variables are normally distributed we furthermore have that the !meat safety margin M defined through: M = ao+ZaiX, ( 1 1 5)
1.1
is also normally distributed with mean value and variance
Pm = au +Zahux, QM =Ea;oi +E Epoi,aiaorri
(11.6)
where p, are the correlation coefficients between the variables X, and X i . Defining the failure event by Equation (11.1) we can write the probability of failure as: PF= P(g(X) 5 0) = P(M 0) (11.7) which in this simple case reduces to the evaluation of the standard normal distribution function:
P, =4)(4) (11.8) where fi the so-called reliability index (due to Cornell (1969) and Basler (1961)) is given as:
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Methods of Structural Reliability Analysis
le Lecture: Methods of Structural Reliability Analysis The aim of the present lecture is to introduce the most common techniques of structural reliability analysis, namely, First Order Reliability Methods (FORM) and Monte-Carlo simulation. First the concept of limit state equations and basic random variables is introduced. Thereafter the problem of error propagation is considered and it is shown that FORM provides a generalization of the classical solution to this problem. Different cases of limit state functions and probabilistic characteristics of basic random variables are then introduced with increasing generality. Furthermore, FORM results are related to partial safety factors used in common design codes. Subsequently, crude Monte-Carlo and Importance sampling is introduced as an alternative to FORM methods. The introduced methods of structural reliability theory provide strong tools for the calculation of failure probabilities for individual failure modes or components. On the basis of the present lecture, it is expected that the students should acquire knowledge and skills in regard to:
• What is a basic random variable and what is a limit state function? • What is the graphical interpretation of the reliability index? • What is the principle for the linearization of non-linear limit state functions? • How to transform non-normal distributed random variables into normal distributed variables? • How to consider dependent random variables? • How are FORM results related to partial safety factors? • What is the principle of Monte-Carlo simulation methods? • Why is importance sampling effective and what does it require in terms of information additional to crude Monte-Carlo methods?
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imaginary project concept proposal
1st assignment grades are not visible Nip mu 25/02/2021 12:50 AM —7 • • • To: Manjeet Kaur. . Dear Manjeet,
Thank you for your email.
You have obtained the grade of 0 marks out of 15 for your first written assessment because the assessment does not feature a specific, original, imaginary project concept proposal relating to your home or workplace but instead a general, superficial discussion of the refurbishment of a general workplace.
You have obviously misunderstood the requirements for the first assessment as explained countless times by me during the tutorial sessions.
Moreover, you have not included any headings in the main body of your assessment, nor have you discussed the subject matter in an appropriate sequence, nor have you have included any tables, graphs, or charts which, as I have mentioned numerous times during the tutorial sessions, must be included in the assessment.
Furthermore, your reference list of sources contains inaccuracies.
Kind regards,
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project failure not the failure of a business
2nd Assessment
Choose a renowned failed project. Ascertain that this is a project failure not the failure of a business. Describe the selected project and analyse the losses incurred by the project. Examine the concrete reasons for the selected project’s failure and propose alternative solutions / recommendations which are underpinned by supporting evidence. Students will be expected to utilise project management theories throughout their assignment and include diagrams, tables, charts and graphs to illustrate their answers. Please note: This assessment must be in an essay format and approximately 2,500 words in length. All students need to clear their selection of failed projects with the lecturer. Deadline for
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you are free to access resources
Dear Students, The Final Evaluation for PGP 9404 Applied Linguistics will be an exam held as an Open Book Test of 3 hours. In an open book test, you are free to access resources; however, it is strongly encouraged that students approach this test as you would a conventional examination. While you may have your notes ready to refresh your memory, without adequate study you will be unable to maximize your time.
The scheduled exam will comprise of 1 compulsory question based on second language learning theories (40 marks) and 3 essay type questions to be answered from 4 questions given (60 marks). That is, you will get to select 3 questions from 4 essay questions. You are encouraged to write a maximum of 500 to 750 words in essay type question answers. This is a general guide and you can write less or more but keep in mind it is content that is marked not length.
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address both theory and practice
The four essay questions will be based on the following areas: 1. Genre Analysis 2. Corpus Linguistics 3. Multimodality 4. Positioning in ELT contexts
Some important points to remember: 1. The questions will address both theory and practice. 2. You can incorporate in-text citations but you do not need to include a reference list. 3. You are allowed to submit a typed answer or if you have the facilities, the option of uploading a handwritten answer is available. 4. Please note that each question answered has to be uploaded separately. There will be relevant spaces in the google classroom created for uploading your answers. The time for the exam includes the time reserved for uploading your answers.
This OBT will be held on Sunday March 7th from 9.00 — 12.00am.
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variance-covariance matrix of the composite shocks
It may not he apparent at first glance, but you can obtain the *-elements in Equation (6) using a Cholesky decomposition of a variance-covariance matrix of the composite shocks. In order to do so, you need reorder the entries of II to account for a new variable ordering y’t. = (rf, pt, ay . We call this new variance-covariance matrix SY. Note that the same values occur in both matrices, they are just ordered differently (for example, Var(4) is the [1, *element in 12 and the [2, 2]-element in SY). Construct IT and print it to the command window.
The identification scheme in Equation (6) entails for the reordered variables:
Et [E 141 Et ut f Utf ]
where
wr
*
(7)
Obtain NV from a Cholesky decomposition of tif. Note that Wr holds the same elements as W. but they are in a different ordering. Hint: Use the MATLAB function chol to perform the decomposition and keep in mind that ciao]. returns an upper triagonal matrix.
Reorder the elements of INTT to obtain W. Print W to the output window.
Study the effects of one unit shocks in the idiosyncratic innovations on yt by platting impulse response functions. Proceed in the following way: To study the effects of a one unit shock in ith, set u1 = (1, 0, 0)1, and obtain the respective E 1 by means of Equation (5). Now, similar to what you already did in task 1.10, iterate the system forwards (consider s = 0, … , 10) by setting all future u = 0. Do the same for one unit shocks in ttf and ut and plot the resulting impulse response functions comprehensively. Interpret your results.
POSTED ONJUNE 21, 2021
abstract and a separate page for references
1:12 *
60%■
Instructions
The paper is to follow APA rules and guidelines.
You must have at least 5 academic sources, maximum two of which can be a textbook; the remaining must be peer reviewed articles.
The paper is to be 5000 (+/- 10%) words in length.
The paper must have a title page, and abstract and a separate page for references at the end. It is expected that the introduction comprises no more than 10% of the paper, the analysis is to be roughly 70% of the paper, and the remaining 20% to be conclusion and recommendations.
Evaluation
Individual Project Management Case Study will be marked in its entirety out of 100. The following rubric indicates the criteria students are to adhere to, and their relative weights to the assignment overall.
Activity/Competencies Demonstrated
% of Final Grade
Critical Analysis
/70
a. Depth of case analysis – in-depth analysis of case covering the deliverables
/30
b. Breadth of case analysis – issues /20 related to case questions have
II
