OpenLLM-France/wikimedia huggingface dataset:
# Security IT/Forgery

Most server in clearnet give register on own page. Usually it's nick, e-mail and password. Hoverer on most popular website's how Facebook or Amazon or simply eBay or other site servies eg. Internet domains required more information - this latest even SSL or activate phone. What do, if not want give personal information? Simply not give? Yes! Give fake information about us in internet it very important step in anonymity. In article use for this purpose some services:
* Fake Name Generator - can almost all
* Receive SMS - create temporary telephone number (it's phrase to search)
* BigHugeLabs - create fake picture ID.

## Fake Name generator

harder termins:
* Phone - Here just random numbers, if site required activate from telephone, must use some server with receive SMS.
* e-mail - site can do temporary mail for generated ID. Something some site can blocked this address (name server after sign @ - eg. Twitter have white list)
# Security IT
## Introduce

* The Art of War from Sun Tzu
* Open Source
* Open Hardware

## Hardware

* List of open-source hardware projects
* Bulding PC

## Software

* OpenBIOS
* Running - disk encryption
* First line of defense - Operating Systems
* Check the authenticity of software

## Internet

* How to Protect your Internet Anonymity and Privacy
* Methods blocks
** Bypass censorship
** Bypass firewalls
* Panic
* NAT

## Suplements

* Sumpletent A: LiveCD
* Suplement B: Fake identity

## See also

* Steganography
# SI521 "Open Educational Resources at the University of Michigan" Open Textbook/Class Materials/February 5 Assignment

No reviews assigned this week. Read/view materials and come prepared to discuss, and to ask visiting lecturer questions.
# SI521 "Open Educational Resources at the University of Michigan" Open Textbook/Class Materials/wiki contributions

1. Everyone is required to do at least one 8-page chapter.
2. The "project" work can be: a) expanding your required 8 page chapter into a 16 page single topic chapter; b) another (different topic) 8 page chapter; c) an 8 page research paper on a topic we agree on; or, d) dScribing
3. Teaming is left open; you can do it if you like in the construction of chapters. If you team with someone, the chapter length is the sum of each individual's contribution - so a team of two would result in a 16 page chapter, a team of 3 in a 24 page chapter. I'd prefer, in order to get a number of chapters off the ground, that everyone do one by themselves. But I'm going to consider that as a simple recommendation, not a requirement. I could see someone doing a 16 page chapter by themselves, or doing an 8 page chapter by themselves and teaming with another person on a 16 page chapter, each contributing 8 pages to the team-written chapter, or teaming with the same or different people on two chapters, contributing 8 pages to each chapter.
4. Everyone will be reviewing two chapters done by someone else. This will result in overall comments useful to the authors as they progress in their writing, and specific suggestions, corrections or additions to the chapters under construction. The chapters you review can be chosen by you (with no more than 2 people reviewing any one chapter) or can be assigned by me, whichever you prefer. You'll see what chapters other are working on by Feb 12, and can start making your choices then.
# SI521 "Open Educational Resources at the University of Michigan" Open Textbook/Commons

The idea of shared resources, or resources that are not owned by anyone in particular, rather by everyone, is a starting point for a description of a "commons." Many of our ideas about a commons are related to the idea of a "tragedy of the commons" pioneered by Garrett Hardin ("The Tragedy of the Commons", Science 13, 1968. ). The idea was originally applied to environmental resources, but has since been extended to any potential resource that is not exclusively privately owned--including broadcast frequencies and intellectual property. Other ideas come from analyses that have been done in economics concerning public goods, their definition and characteristics (ref). Recent developments surrounding the production of open source software and peer production processes have revitalized discussions of the commons and feed into the debate surrounding open resources. James Boyle talks about the "Commons of the Mind" at .
Some things to consider for this chapter include: – what it is, how it works, public domain vs a copyrighted domain, how digital objects change the nature of the Commons, conceptions of the Commons over the years. bush did 9/11
# Simulation with AnyLogic/Agent-Based Modeling/Step 1. Creating a new model

Step 1. Creating a New Model
First, we will create a new model.
Create a new model
* Click the New Model toolbar button. The New Model dialog box is displayed.
* Specify the name of the model. In the Model Name edit box, type Bass Diffusion Agent Based.
* Specify the location where you want to store your model file. Browse for the existing folder using the Browse buton, or type the name of the folder you want to create in the Location edit box.
* Click Next. This will open the next page of the New Model wizard. Here you can choose, whether you want to start creating a new model from scratch, or to use a model template as a starting point in model development. Since we want to explain you the whole process of creating an agent based model in details, we will not use a template, but will create our model from scratch.
* Click Finish to complete the process.
New model is created. It already has one active object class called Main and experiment called Simulation.
Active objects are the main building blocks of AnyLogic model. They can be used to model very diverse objects of the real world.
In the center of the workspace you will see the graphical editor. It shows the diagram of the Main class. By default it does not contain any elements.
To the left of the graphical editor you can see the Project view. The Project view provides access to AnyLogic models currently opened in the workspace. The workspace tree provides easy navigation throughout the models.
On the right side of the workspace you can see the Palette view, and at the bottom - the Properties view. The Palette view simplifies the process of drawing diagrams, providing the list of model elements grouped by categories in a number of stencils.
The Properties view is used to view and modify the properties of a currently selected model item(s). When you select something – e.g., in the Project view or in a graphical editor – the Properties view displays the properties of the selection.
When working with a model, do not forget to save it by clicking Save .
# Simulation with AnyLogic/Agent-Based Modeling/Step 10. Adding agent animations

Step 10. Adding Agent Animations
Now we will create a simple animation of our model to visualize the process. We want to draw agents on our presentation. Agents will be displayed relative to the coordinates they have in the modeled environment.Product adopters and potential adopters will be shown with the shapes of different colors.
Draw a shape depicting a person
* Open the Person class diagram by double-clicking the Person item in the Project view.
* Zoom the diagram in, say to 400% scale.
* Drag the diagram a little bit down and to the right with the right mouse button pressed.
* Draw the agent shape like shown in the following figure:
* Draw it using a curve. Therefore, choose the Curve element from the Presentation stencil of the Palette view (this stencil contains shapes and controls you can add on your presentation) and successively click at each curve point on the diagram and finally double-click to finish drawing.
* Place the shape right in the upper left corner in the point (0,0) (the coordinates of the mouse cursor are shown in the status bar):
* Zoom the diagram out.
* Click on the agent shape and open the Dynamic properties of the shape. In the Fill Color property, type statechart.isStateActive(PotentialAdopter) ? royalBlue : red The expression checks, whether the person is a potential adopter (the PotentialAdopter state of the agent's statechart is active). Adopters will be displayed with red points, potential adopters – with blue ones.
Modify the model to set up agent animations properly
* Open the Main class diagram by double-clicking the Main item in the Project view.
* Select the people object in the graphical editor. On the General page of its Properties view, click the Create Presentation button. You will see the agent shape appeared in the upper left corner.
* Drag this shape down to the place shown in the following figure: The point where we place our shape will be the upper left corner of the agent's environment area. Agents with (0,0) coordinates will be placed there.
* Select the environment object.
* Open the Advanced' tab of the environments Properties view. Define the dimensions of the space our agents populate. Set up Width 650 and Height 300.
We have finished creating the animation. Run the model and watch the dynamics on the network.
# Simulation with AnyLogic/Agent-Based Modeling/Step 11. Making people contacts distance-based

Step 11. Making People Contacts Distance-Based
Now people are located randomly in 650x300 miles square area. Let people only contact if they are not more than 25 miles away.
Set up the environment properties
* Open the Main class diagram by double-clicking the Main item in the Project view.
* Select the environment object.
* Open the Advanced' tab of the environments Properties view.
* Change the Network type to Distance based and modify the Connection range: 25.
Modify the agent's statechart
* Open the Person class diagram by double-clicking the Person item in the Project view.
* Click on the internal transition of the Adopter state.
* Modify the transition's Action. Substitute the existing string for the following: send (“Buy!”, RANDOM_CONNECTED); People will now contact only with their neighbors.
Now we will modify our animation a little bit to visualize the network of contacts.
Draw a line to depict people contacts
* Open the Person class diagram.
* Draw a line like shown in the figure below. Choose the Line element from the Presentation page of the Palette view. Then click in the graphical editor at the point (0,0) to place the start point of the line and finally click aside where you want to draw the end point.
* Open the Dynamic' tab of the lines Properties view and modify some dynamic properties of the line.
* In the Replication field, type: getConnectionsNumber, (you can use code completion assist when typing). Here we specify the number of contact lines for the agent. We need to draw a line for each connection of this agent. For that, we call the getConnectionsNumber function, returning the number of agents currently connected to this one in our network.
* Define line's location on the animation: In the dX field, type: getConnectedAgent(index).getX - getX In the dY field, type: getConnectedAgent(index).getY - getY Here we place the end point of each line to the point with the coordinates of the corresponding connected agent. Connected agents are alternately accessed using the getConnectedAgent(index) function. Now those people who contact with each other will be shown on our presentation connected with lines.
We have finished creating the animation. Run the model and watch the dynamics on the network.
# Simulation with AnyLogic/Agent-Based Modeling/Step 2. Creating agents

Step 2. Creating Agents
The first thing you do when creating agent-based model is create agents. Agent is the basic building block of the agent-based model. Agent-based model consists of multiple agents and their environment. Every agent is given a set of rules according to which it interacts with other agents; this interaction then generates the overall system behavior. In this model agents are people.
To create agents in AnyLogic, you define the agent’s internal structure using the active object class, and then create the required number of class instances, each one representing the individual agent.
Create new active object class for an agent
* In the Project view, right-click the model item, and choose New|Active Object Class… from the popup menu.
* The New Active Object Class dialog box is displayed.
* Specify the name of the new active object class. Type Person in the Name field.
* Click Finish. The Person class diagram is opened automatically.
* Once you have created some new element, it becomes selected and its properties are displayed in the Properties view. You can adjust element properties here as your model requires. Please note that Properties view is context-sensitive view and it displays the properties of the currently selected element of the model. To adjust properties at a later time, first select the element (by clicking on the element in the graphical editor or in the Project view) and then modify the properties you want.
* On the General page of the Properties view, select the Agent check box. This makes this active object class an agent.
You have successfully created the class that will define the agent’s internal structure. Now it’s a time to add agents into the model. To place agents into the model environment, you should encapsulate the object that models agent (Person) into the class that models environment (Main).
Place agents into the environment
* Open the Main class diagram by double-clicking the Main item in the Project view.
* Drag the Person class from the Project view onto the diagram of the Main class.
* On the General page of the Properties view, type the object’s Name: people.
* Specify the number of agents you want to have in your model. In the Replication edit box, specify the number of objects: 1000. The specified number of class instances will be automatically created, each one representing the individual agent.
We have created the required number of agents. Now we will model the adoption of the product influenced by advertisement.
# Simulation with AnyLogic/Agent-Based Modeling
## Bass Diffusion. Agent Based Model

AnyLogic supports different modeling techniques. This tutorial covers the agent-based modeling approach, successfully applied in a wide range of fields such as ecology, sociology, economics, traffic simulation, and many others. Agent-based modeling is used to model markets (agent is a potential customer), competition and supply chains (agent is a company), population (agent is a family, a citizen, or a voter), etc. Agent-based models allow getting an insight into the general behavior of the system assuming the behavior of its elements, without having any global knowledge about the system.
AnyLogic is the only simulation tool, which allows creating flexible models with agents, interacting with each other and their environment. AnyLogic supports all known ways of specifying the agent behavior – statecharts, synchronous and asynchronous event scheduling.
This tutorial will briefly take you through the process of constructing a simulation model using AnyLogic. It is intended to introduce you to AnyLogic interface and many of its main features. We will create a simple illustrative example—the product life cycle model, used for forecasting sales of new products. The first steps will take you through the process of construction of the classic Bass diffusion model. The model describes a product diffusion process. Potential adopters of a product are influenced into buying the product by advertising and by word of mouth from adopters – those who have already purchased the new product. Adoption of a new product driven by word of mouth is likewise an epidemic. Potential adopters come into contact with adopters through social interactions. A fraction of these contacts results in the purchase of the new product. The advertising causes a constant fraction of the potential adopter population to adopt each time period.
Then we will expand our model by considering some details and introducing you to some advanced features of AnyLogic useful in agent-based modeling.
Note that there are several reference files available for this model representing the milestones of the editing. You can use reference files if you experience any difficulties creating a model and you would like to compare your model with the reference file. You can use Welcome Page to open those examples. Welcome Page appears automatically when you open AnyLogic. It can be opened whenever you like from AnyLogic menu: Help|Welcome.
You can also run this model online.
* Step 1. Creating a new model
* Step 2. Creating agents
* Step 3. Adding Adoption from Advertisement
* Step 4. Counting the product adopters
* Step 5. Adding charts
* Step 6. Configuring simulation
* Step 7. Running the model
* Step 8. Adding adoption from word of mouth
* Step 9. Adding the Product Consumption Logic
* Step 10. Adding agent animations
* Step 11. Making people contacts distance-based
# Quantum Mechanics/Mass, Momentum and Energy

The mass, momentum and energy are related by E=P$^2$/2m where P is the momentum, m is mass of the particle. The difference in the quantum mechanics is that energy cannot be continuous for a particle. Even the great aspect is that energy of quantum particle can have a minimum value but cannot be zero.
# Quantum Mechanics/Quarks and Leptons

All fermionic-based matter is divided into two broad categories: hadrons and leptons.
All the hadrons are composed of quarks, whereas leptons are material particles not containing quarks. Furthermore, leptons are believed to be point-like fundamental particles.
Quarks come in 6 different types:
| Generation | Charge = -1/3 | Charge = +2/3 |
| 1st | d (down) | u (up) |
| 2nd | s (strange) | c (charm) |
| 3rd | t (truth=top) | b (beauty=bottom) |
The quarks are never seen in isolation but always bound together in pairs or triplets, to form protons, neutrons, and many other particles. The up and down quarks form the protons and neutrons that we are familiar with: a proton is a bound state of 2 up quarks and 1 down quark, whilst a neutron is a bound state of 1 up quark and 2 down quarks.
| particle | quark composition |
| $p$ (proton) | $uud$ |
| $n$ (neutron) | $udd$ |
| $\Lambda$ (lambda barion) | $uds$ |
| $\pi ^{+}$ (charged pion) | $u{\bar {d}}$ |
| $\pi ^{-}$ (charged pion) | $d{\bar {u}}$ |
Leptons also come in 6 different varieties:
| Generation | Charge = -1 | Charge = 0 |
| 1st | $e$ (electron) | $\nu _{e}$ (the electron's neutrino) |
| 2nd | $\mu$ (muon) | $\nu _{\mu }$ (the muon's neutrino) |
| 3rd | $\tau$ (tau) | $\nu _{\tau }$ (the tau's neutrino) |
Until recent years it was thought the neutrino was a massless particle but it has since been found that neutrinos can "oscillate" (change) between different types. This is only possible if they have mass, albeit a very small mass in the case of the electron neutrino.
# Quantum Mechanics/The Hydrogen Atom
## The Hydrogen Atom
### Introduction

By now you're probably familiar with the Bohr model of the atom, which was a great help in classifying the position of fundamental atomic specta lines. However, Bohr lucked out in more ways than one. The hydrogen atom turns out to be one of the few systems in Quantum Mechanics that we are able to solve almost precisely. This has made it tremendously useful as a model for other Quantum Mechanical systems, and as a model for the behavior of atoms themselves.

### Fundamentals

We can assume that the hydrogen atom is governed by the Coulomb potential, namely:
$V(r)=-{\frac {e^{2}}{4\pi \epsilon _{0}}}{\frac {1}{r}}$
such that, $H\Psi =-{\frac {\hbar ^{2}}{2m}}{\frac {d^{2}\Psi }{dx^{2}}}-{\frac {e^{2}}{4\pi \epsilon _{0}}}{\frac {1}{r}}$
Obviously, simply by inspection, we can see that the Hydrogen Atom is a spherical system. Hence it makes more sense to deal with the Hydrogen atom in spherical coordinates. One should remember at this point that, via Separation of variables, you can obtain the solution to the spherical Laplacian in three-dimensional space:
$\nabla ^{2}f={1 \over r^{2}}{\partial \over \partial r}\left(r^{2}{\partial f \over \partial r}\right)+{1 \over r^{2}\sin \theta }{\partial \over \partial \theta }\left(\sin \theta {\partial f \over \partial \theta }\right)+{1 \over r^{2}\sin ^{2}\theta }{\partial ^{2}f \over \partial \phi ^{2}}$
the solutions to this function when we use separation of variables inside a Hamiltonian gives us two different functions, the Radial Wave functions (not useful now, but good to know):
$A\cdot J_{l}\left(Z_{nl}{\frac {r}{a}}\right)$
where $J_{l}$ are the spherical Bessel functions of type l, and $Z_{nl}$ are the zeroes of said Bessel functions.
The other component, the angular component are the Spherical harmonics which are explored in detail on Wikipedia.

### Calculations

Essentially, we're ahead of the game at this point. We already know the answers. The hydrogen wave function will have to involve the spherical solutions to the Laplacian and will be related to both the angular and radial components. This is most fortunate; for us to attempt to solve the Laplacian while doing the hydrogen atom would be difficult. However, we have some tasks left. The situation must be normalized, and we must deal with the fact that our potential has a pesky r dependence.

### Results

We end up with the results that you knew we were going to. We can write down the hydrogen wave equation as:
$\Psi _{nlm}(r,\phi ,\theta )=R_{nl}(r)Y_{m}^{l}(\theta ,\phi )$
where $Y_{m}^{l}(\theta ,\phi )$ are the spherical harmonics.
# Quantum Mechanics/Quantum Scattering
## Stationary scattering wave

The (elastic) scattering stationary state (azimuthally symmetric) is described by a wave-function with the following asymptotic,
    $\psi ({\vec {r}}){\underset {r\to \infty }{\longrightarrow }}e^{i{\vec {k}}{\vec {r}}}+f(\theta ){\frac {e^{ikr}}{r}}\;,$         (1)
where $e^{i{\vec {k}}{\vec {r}}}$ is the incident plane wave of projectiles with momentum ${\vec {k}}$, $f(\theta ){\frac {e^{ikr}}{r}}$ is the scattered spherical wave, and $f(\theta )$ is the scattering amplitude.

## Cross-section

Consider a detector with the window $d\Omega$ positioned at the angle $\theta$ at the distance $r$ from the scattering center. The count rate of the detector, $dN/dt$, is given by the radial flux density of particles, $j_{r}$ through the detector window,
    ${\frac {dN}{dt}}=j_{r}r^{2}d\Omega \,.$
The radial flux from the stationary wave (1) is given as
    $j_{r}={\frac {\hbar }{2mi}}\left(\psi ^{*}{\frac {\partial \psi }{\partial r}}-{\frac {\partial \psi ^{*}}{\partial r}}\psi \right)=|f(\theta )|^{2}{\frac {1}{r^{2}}}{\frac {\hbar k}{m}}\,.$         (2)
The cross-section $d\sigma$ is defined as the count rate of the detector divided by the flux density of the incident beam,
    $d\sigma ={\frac {1}{|j_{i}|}}{\frac {dN}{dt}}\,.$         (3)