Printing actual solutions for the coin exchange problem

As I teach myself dynamic programming, I have learned about the coin exchange problems. Specially this site: provides great insight about it. Specifically, the following implementation of a tabulated-DP-based solution for this problems is presented as follows:

def count(S, m, n ):     # If n is 0 then there is 1     # solution (do not include any coin)     if (n == 0):         return 1     # If n is less than 0 then no     # solution exists     if (n < 0):         return 0;     # If there are no coins and n     # is greater than 0, then no     # solution exist     if (m <=0 and n >= 1):         return 0     # count is sum of solutions (i)     # including S[m-1] (ii) excluding S[m-1]     return count( S, m - 1, n ) + count( S, m, n-S[m-1] ); 

However, this only counts the number possibles solutions.

Question: How can I actually save these solutions for post-processing?

Previous research: In this very helpful video: they explain how to use an array of parent pointers, to generate the actual solutions, however, I am having issues with implementing this approach with the previous tabulated solution. Any hint?

Which one is the Leading Coin Market Capital Alternatives?

As my point of view,US Coin Market is the best one. This provides real-time coin prices, crypto market cap information, and comprehensive charts for well over 2,000 coins across more than 110 exchanges. The service boasts a portfolio features, an ICO list, as well as sections dedicated to news, guides, exchanges, and upcoming events.

A very neat feature of US Coin Market is represented by the fact that users can quickly access a summary of a coin’s features, the latest news related to that specific cryptocurrency, and a dedicated selection of how-to guides.

Probability of X being a trick coin (heads every time) after heads is flipped k amount of times

A magician has 24 fair coins, and 1 trick coin that flips heads every time.

Someone robs the magician of one of his coins, and flips it $ k$ times to check if it’s the trick coin.

A) What is the probability that the coin the robber has is the trick coin, given that it flips heads all $ k$ times?

B) What is the smallest number of times they need to flip the coin to believe there is at least a 90% chance they have the trick coin, given that it flips heads on each of the flips?

Here is my approach:

Let $ T$ be the probability that the robber has the trick coin

Let $ H$ be the probability the robber flips a heads k times in a row

$ Pr(T) = 1/25$

$ Pr(H|T) = 1$

$ Pr(T’) = 24/25$

$ Pr(H|T’) = 1/2$ when $ k=1$ , $ 1/4$ when $ k=2$ , $ 1/8$ when $ k=3$ … etc

$ Pr(T|H) = (1 * 1/2) / (1 * 1/2 + Pr(H|T’) * 24/25) = 1/13, 1/7, 1/4,…$ etc

So the Pr(T|H) answer changes for every k, do I answer with the formula? How can I answer A? How do I make a probability distribution when k can be infinite?

Also is B 8 flips? Since when k = 8, Pr(T|H) = 1/256.

Thanks for any help.

Are there any blockchain’s that has a built in tumbler or coin shuffling technology built into their code?

I know dash has some kind of mixing technology in their blockchain using their master nodes, but are there any other blockchains that has a built in coinjoin or coin shuffling technology built into their code? I know Monero uses ring signatures, but I’m more interested in just coinjoin or coin shuffling technology that is in blockchains. I know it might not be 100% private.

n coin balancing problem

Rank weights of coins with a balance scale

I want to generalized above problem into $ n$ coins.


using balance scale, sort $ n$ coins in order.

Slightly more generalizing the above post, [In that post, they didn’t consider equal weight case] Let’s consider, when we balance scale, there are three possibilities. [Let a,b the two coins, then a=b, a>b, a

Making trees for $ n=5$ , I obtain the number of weighting is 7.

And by the similar computation [with more effort] I figure out for $ n=6$ , 10 is enough.

How about its generalization to $ n$ ?

At this moment I have no idea how to generalize for $ n$ .

In searching internet, I found one particular arXiv,
1409.0250, but in there analysis is not matched even in $ n=5$ . [For example, I thought the section 4 of that paper is the same case with mine, but it seems not…]

How do different implementations of the Bitcoin Cash client know which type of coin they’re processing?

TL;DR: Where in this code does the SV client figure out that it’s not processing an ABC blockchain?

This image prompted my question.

There are a couple different mutually incompatible (I am assuming anyway) implementations of the Bitcoin Cash cryptocurrency client software…

  1. Bitcoin Cash ABC
  2. Bitcon Cash SV

My question assumes that each implementation processes their respective transactions using similar but mutually-incompatible blockchain processing rules.

Is it normal to run a Bitcoin Cash SV client implementation in a Bitcoin Cash ABC network? And vise versa? How, then, does one implementation know that the network it is running in, is (in)compatible with its particular processing rules?

Is it safe to handle a denarian coin indirectly?

I’m currently a new player in a campaign which does have a Denarian in it and has OOC had jokes made about my PC being tricked into touching one of their coins, which has made me curious and want to ask:

Is there anything in the setting on if it’s safe to touch a denarian coin indirectly?

Such as if the character is wearing gloves, or were to try pick it up with something like tweezers/tongs- would that result in any infestation and count as “touched/picked up” or be perfectly okay for someone to do since it’s not direct skin to metal?

Selling a 2011 Casasious S2 BITCOIN BRASS COIN?

Im selling from 2011 Casasious S2 Bitcoin!

Let me know if you guys are interested.

Starting BID: 1.5 Bitcoin Buy it now: 2 Bitcoin

I’m auctioning it here:

if you guys want to bid there.

Or JUST PM directly ( i don’t know if you can here) if you want to buy it now!

I can’t upload pics here. but there are links on that bitcointalk.

Thank you!

A coin is flipped 14 times. How many different outcomes have at most 10 heads?

I followed the pattern here but it still resulted in my problem being incorrect. How many outcomes of a coin being flipped 12 times have exactly 4 heads?

(1 pt) A coin is tossed 14 times. d) How many different outcomes have at most 10 heads?

I did 2^14-(14!/14!+14!/13!+14!/12!+14!/11!), which translates to how many flips have at least 4 tails.

Why isn’t this working?

A coin, having probability p of landing heads and probability of q=(1-p) of landing on heads.

A coin, having probability p of landing heads and probability of q=(1-p) of landing on heads. It is continuously flipped until at least one head and one tail have been flipped.

This is not part of a homework assignment. I am studying for a final and don’t understand the professors solutions.

a.) Find the expected number of flips needed.

Since this is clearly geometric, I would think the solution would be:

E(N)=$ \Sigma_{i=0}^{n}ip^{n-1}q+\Sigma_{i=0}^{n}iq^{n-1}p=\frac{1}{q}+\frac{1}{p}$ .

However, I am completely wrong. The answer is

E(N)=$ p(1+\frac{1}{q})+q(1+\frac{1}{p})$

I am not entirely sure why we have an added 1 and a factored p,q. Could someone carefully explain why it makes sense that this is the right answer?