Concrete example of Vertex Cover to Subset Sum reduction

In Computational Intractability, we often come across a need to reduce Vertex Cover (VC) problem to a Subset Sum problem, mostly to prove Subset Sum is NP-Complete. I also see a reduction in the line of – A graph G has VC of size k if and only if there is a subset S that sums exactly to t. However, not able to find out (understand) exactly what is this t. I think providing a concrete example will help many like me. Request any one to provide a concrete graph with |VC| 3 or something manageable, and then show exact value of t i.e. what would be the exact instance of subset sum problem. Finally, explaining/clearly mentioning elements of S would be of great help.

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by: mainurbd
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Category: Art & Design
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How much of the system is secure boot going to cover?

Background: We’re developing for a Debian 9.8 system, but the space in which we are operating is dominated by embedded devices.

according to wikipedia, secure boot can “secure the boot process by preventing the loading of drivers or OS loaders that are not signed with an acceptable digital signature”. I take this to mean that kernel-level code is protected, but that user-level code is not.

I am having some terminology confusion with my boss, who is under the impression that Secure Boot can protect the entire operating system. I believe that Secure Boot can secure the entire system only when the computer-in-question is an embedded device (you will never receive software updates, therefore you can group all the executable stuff together and sign that). If the device is your typical PC, secure boot cannot practically keep it secure (your PC is getting software updates all the time, meaning that an executable block would be changing all the time, meaning that you’d have to recalculate/re-sign the entire block with each update).

Am I right, or is he? Is there an easy way to extend the protections of Secure Boot to our custom user-level software? Is there something similar to secure boot that I should be looking at to secure user-level software?

Determining minimal cover of a relation

I am having trouble understanding why a certain set of functional dependencies is not minimal. We have a relation R(A,B,C,D,E,F,G) with the following dependencies F:

1. A->CDE 2. B->FG 3. AB->CDEFG 

Minimal cover of F is just dependency 1 and 2. It is intuitive that attributes CDEFG are already determined by A and B separately. Hence, no new attribute is determined by union of AB. Is there an exact rule that determines that such dependency (union of AB->CDEFG) is redundant?

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