Answer:
A. Low prices and enormous product availability.
Explanation:
This is a chain of retail stores or a retail outlet that sells different kinds of goods or products that in a way that seems cheap and affordable to consumers. They also look and facilitate quick form of buying and selling. Their main goal stands primarily on cheap, fast enormous sales of the product.
They possibly can create a compelling shopping experience. In a bid to do that, they need to compress instant gratification, unique assortments and a reasonable showroom experience that aids social lifestyles.
Answer:
$961.54
Explanation:
To calculate the real price of the TV you would have to determine the present value of the TV's price. The future price of the TV is $1,000 and your discount rate is 4% annual (the same as your bank), so the present value of the TV =
present value = future value / (1 + rate) = $1,000 / 1.04 = $961.54
This excess should be credited to Budgetary Fund Balance Unassigned.
<h3>
What is Fund Balance?</h3>
Any specific fund's fund balance is basically what is left over after the fund's assets are used to pay its liabilities. Both the reserved and unreserved portions of the fund balance must be disclosed.
<h3>What is Unassigned Fund Balance?</h3>
The term "unassigned fund balance" refers to the balance that remains after non-spendable, restricted, committed, and assigned funds have been deducted from the total amount. It contains all spendable monies that are not included in the other classes. That's not a very simple explanation.
Therefore, perhaps the simplest approach to considering the unassigned fund balance is the amount of money available to stop a cash flow problem.
Therefore, in a town's general fund operating budget for the year, the number of its estimated revenues exceeded the number of its appropriations. This excess should be credited to Budgetary Fund Balance Unassigned.
For more information on Budgetary Funds, refer to the link:
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In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product. Optimization of process parameters is one of the ways to achieve desired quality of a part.
In addition to prototyping, Powder Bed Fusion (PBF) AM processes have lately been more widely used to manufacture end-use parts. These changes lead to necessity of higher requirements to quality of a final product.
Optimization of process parameters is one of the ways to achieve desired quality of a part. Finite Element Method (FEM) and machine learning techniques are applied to evaluate and optimize AM process parameters. While FEM requires specific information, Powder Bed Fusion Machine Learning is based on big amounts of data. This paper provides a conceptual framework on combination of mathematical modelling and Machine Learning to avoid these issues.
Learn more about Powder Bed Fusion here
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