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Everything posted by khaled

  1. 1. You have to program the plug-in manager 2. it's a thread that works aside from your program, async communicates with it, to manage the use of plug-ins -- it's simply a simple thread, which is programmed to give authorization for any action related to plug-ins, it checks -- if it's valid action for current permissions, then it either give OK, or DENY 3. this is really too hard for one to program, usually security companies such as Norton and McAfee make -- their sandboxing software, there are some open-source sandbox software that you can check
  2. To have a good start, you should make the following documents: - UML diagrams (Class, Object, State-chart, flow-diagram, ..) - Component-based diagram - Structural description, using the "Script" style - Record all routines as algorithms (Numbered Steps, Flow-chart, Pseudo-code ..) .. good luck,
  3. I think that multi-dimensions are true .. and humans can perceive the universe as a 4-dimensional projection of the universe, I think that the most crazy physicist is dr.kaku, his writing are way out of mind
  4. You can find a detailed documentation, downloadable PDFs at PeerSIM:Documentation good luck,
  5. You can download it from: LibraryFind:Download And in case you don't know how to install the package manually in Linux, you can use sudo apt-get install libraryfind good luck,
  6. games for PlayStation are programmed in C++, since the PlayStation Dev Kit are in C++, XBox game are programmed in C#, using DirectX and XNA ... Computer games can be programmed even by flash, java, ..etc Good programming skills are required, but a complex game requires alot of specialized developers of different specialties from Graphics\Music\Animations to Artificial Intelligence, Game Platforms provide a Dev Kit, that you can download and use ...
  7. I'm working on a new statistical stochastic model, .. and I need to know what conferences I can submit at ? I'd like something related to\sponsored by IEEE ... -- thanks in advance
  8. If I remember right, some mathematicians such as Mersenne have a formula to generate a large prime number, Mersenne Prime: [math]M_p = 2^p - 1[/math]
  9. Wait a minute, if the crowded street where all cars move at 100 Km\h, if one bumped at the car behind it, the one behind will lose speed, and bump the one behind, the damage will be sequential ...
  10. Basically, if you and someone else move in the same speed and direction, the relative speed is 0, just like if you both are not moving at all .. if he slows down, it's like if you both were standing and went backward and bumped you, so I guess, he'd bump you at (your speed - his new speed) Km\h, which is negative, I think that if you accelerate and bump into his car with some force, will result different, if he slowed down and bumped your car in the same amount of force ...
  11. [math]KB \models \alpha[/math], where KB the Knowledge Base, and [math]\alpha[/math] is the statement that has a model with KB, So, "(A V B) Λ (¬C V ¬D V E)" ~ KB = { (A V B), (¬C V ¬D V E) } and since KB = TRUE, then (A V B) = TRUE, and (¬C V ¬D V E) = TRUE 1. TRUE, because (A V B) is TRUE in the KB 2. TRUE, because (A V B V C) = TRUE since (A V B) = TRUE in the KB, and (B Λ C Λ D --> E) = (¬B V ¬C V ¬D V E) = TRUE since (¬C V ¬D V E) = TRUE in the KB 3. Not sure, you have to revise Boolean Calculus, Wikipedia: Prepositional Calculus
  12. This is a complex topic in computer science ... Parallel systems need synchronization, the def of sync is 'equilibrium enforcement', sync differs depending on what are you synchronizing, I will give a simple examples: 1. Sync Send: The sender has to wait until, data is received 2. Sync Receive: The receiver waits until data comes 3. Sync Time: All entities reset their clocks as coordinated 4. Sync DataBases: All DataBases stop query processing, until all data are distributed to all 5. Sync Data Between N Data Storages: data on one side are generalized in other sections, shared data checked, and modified data are versioned* and data set according to priority\timestamp .. as I said before, this is a complex topic in computer science good luck,
  13. I used Bernoulli Distribution, and since Bernoulli model model doesn't seem to work with transition and order in the trial, I've worked out some new model based on Bernoulli Process, Similar to Markov Model .. Because Bernoulli, and its variations, can only tell me informations such as Probability of getting m success out of n, and such But, I'm more interested in knowing, what is the probability that in the next Trial Xi will be a success ...
  14. You see, the thing I meant that "made a powerful gravitational impulse towards its origin" .. was something worse than a black hole, but not black hole, Black holes seem like a 2-dimensional hole at some level, but this thing is a 0-dimensional hole, .. now I sound more crazy
  15. Greetings, I'm working on a model, for a 2-state random variable over discrete-time domain, and I need to know what are the well-known probability models, I know Bayesian Model, and Markov Models .. what other models are there ?
  16. I'm not good at physics, but I will talk about what I think ... my speculation about what was before the big bang: .. it might sound crazy, I just don't know,
  17. Cryptography, Keys Distribution, Hashing, and Integrity Check ... But the question that Security people fear most is: is the system designed to steal your information ? Because if it's true, then no security can work,
  18. There are software called Wipers, those software write over unused data in a harddisk, sometimes multiple passes for security
  19. [math]- 1/2 ln(x) = x^2[/math] [math]ln(x) = - 2 x^2[/math] You need to use Lambert W Function, as Shadow said .. regarding your equation have complex roots, here is the solution from Wolfram|Alpha
  20. I usually use this: [math]P(A) = (\frac{1}{number of A outcomes})^{N}[/math], which for large N leads to small numbers that are rounded as zero But, if I use this: [math]\frac{number of A outcomes}{N}[/math], this would approach zero slower Laplace smothering used logarithm and exp functions to work that problem .. I've worked on it regarding Markov Models
  21. Working on a research in Markov Models

  22. Still, I have no idea how to use this equation [math] P(A) = \lim_{N \to \infty} \frac{nummber of A outcomes}{N} [/math] isn't [math]\lim_{N \to \infty} \frac{C}{N} = \lim \frac{C}{\infty} = 0 \;\; for \;\; 0 \leq C < \infty[/math] ..?
  23. Dr. Rocket .. with all regards, neither my post nor yours is wrong So, just because I mentioned the simple situation doesn't mean it's wrong or absurd, and my definition of conditional probability is not wrong in my point of view ... So, your equation to calculate P(A) looks complex to me, can you show how to use it ?
  24. Robotics have several branches, such as Intelligent Search, Machine Learning, Neural Networks, ..etc You can work in one or more branches at that point, simply you go for it, you can find a place where you can study robotics as a Master degree, or take master degree in computer science, as usual, and then take a Ph.D in Robotics ... The mathematics skills you need for AI, basic Calculus, basic Geometry, basic Linear Algebra, good Probability & Statistics, good Boolean Algebra, good Model Theory, good Group Theory, advanced Discrete Mathematics, advanced Graph Theory, good Mathematical Logic, advanced Logic ... I'm too, also going for a Ph.D in Artificial Intelligence generally, good luck,
  25. Let me detail this, Case: What is the probability of getting 3 or more Tails when tossing a fair coin 6 times Possible Outcomes: { Head, Tail } [math]P ( Outcome_{i} ) = \frac{1}{Number of Outcomes}[/math] P(Head) = 1/2, P(Tail) = 1/2 Conditional Probability: how likely to get an outcome based on previous outcomes [math]P(Head,Head,Head) = [/math] [math]P(Head) \times P(Head|Head) \times P(Head|Head,Head) = P(Head) \times (\frac{P(Head \cap Head)}{P(Head)}) \times (\frac{P(Head \cap Head \cap Head)}{P(Head) \times P(Head)})[/math] But, to solve our case, we consider n = number of Heads in the Trials ... [math]P(n > 2) = 1 - P'(n > 2) = 1 - P(n < 3)[/math] To evaluate a simple case, we can do this, [math]P(n > 2) = 1 - P(n < 3) = 1 - (P(n=0) + P(n=1) + P(n=2))[/math] In complex cases, you have to use Probability Distribution and Mass Function
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