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Linux-0.11 Kernel Memory Management get_free_page () function analysis

/**author:davidlin*date:2014-11-11pm*email: [email protected] or [email protected]*world:the City of SZ, in China*ver:000.000.001*history:editor time do1) Linpeng 2014-11-11 created this file!2)*/Linux-0.11 Memory Management module is more difficult to understand in the source code part, now the author's personal understanding publishedFirst hair Linux-0.11 kernel memory management get_free_page () function analysisHave time to write other functions or files:)/** Get Physical Address of first (a

Distance calculation method summary

: (3) Two n-dimensional vectors A (X11, X12 ,..., X1n) and B (X21, x22 ,..., Euclidean distance between x2n: It can also be expressed as a vector operation: (4) Calculation of Euclidean distance using Matlab MATLAB distance calculation mainly uses the pdist function. If X is a matrix of m x N, pdist (x) treats each row of m in the X matrix as an n-dimensional vector, and then calculates the distance between these M vectors. Example:

Similarity measurement in Machine Learning

, X12 ,..., X1n) and B (X21, x22 ,..., Euclidean distance between x2n: It can also be expressed as a vector operation: (4) Calculation of Euclidean distance using Matlab MATLAB distance calculation mainly uses the pdist function. If X is a matrix of m x N, pdist (x) treats each row of m in the X matrix as an n-dimensional vector, and then calculates the distance between these M vectors. Example: Calculate the Euclidean distance between vectors (),

Similarity measurement of vectors

) in three-dimensional space:(3) Euclidean distance between two n-dimensional vector A (x11,x12,..., x1n) and B (x21,x22,..., x2n):It can also be expressed in the form of a vector operation:(4) Matlab calculates Euclidean distanceMATLAB calculates distances primarily using the Pdist function. If X is a matrix of MXN, then Pdist (x) takes each row of the X matrix M as an n-dimensional vector and calculates the distance between the M vectors 22.Example:

Distance measurement in machine learning

) Euclidean distance between two n-dimensional vector A (x11,x12,..., x1n) and B (x21,x22,..., x2n):It can also be expressed in the form of a vector operation:(4) Matlab calculates Euclidean distanceMATLAB calculates distances primarily using the Pdist function. If X is a matrix of MXN, then Pdist (x) takes each row of the X matrix M as an n-dimensional vector and calculates the distance between the M vectors 22.Example: Euclidean distance between com

Similarity measurement in machine learning

,Z2) in three-dimensional space:(3) Euclidean distance between two n-dimensional vector A (x11,x12,..., x1n) and B (x21,x22,..., x2n):It can also be expressed in the form of a vector operation:(4) Matlab calculates Euclidean distanceMATLAB calculates distances primarily using the Pdist function. If X is a matrix of MXN, then Pdist (x) takes each row of the X matrix M as an n-dimensional vector and calculates the distance between the M vectors 22.Examp

Optimization NFR one--mssql Hello Buffer overflow_php Tutorial

alarm, we can properly analyze it. 3. Detection of NFR We first open the signature library published by NFR MSSQL.FP (or can also be viewed in the AI's package) to see the NFR attack signature for this vulnerability: ..... Variable definition, etc... ... Sqlserv_schema = library_schema:new (1, ["Time", "IP", "int", "IP", "int", "str"], Scope ()); Sqlserv_rec = Recorder ("Bin/list%c", "Sqlserv_schema"); Hello_sig = "\x12\x

"Reprint" The similarity measure in machine learning, method summary Comparison

-dimensional plane:(2) Euclidean distance between two points a (X1,Y1,Z1) and B (X2,Y2,Z2) in three-dimensional space:(3) Euclidean distance between two n-dimensional vector A (x11,x12,..., x1n) and B (x21,x22,..., x2n):It can also be expressed in the form of a vector operation:(4) Matlab calculates Euclidean distanceMATLAB calculates distances primarily using the Pdist function. If X is a matrix of MXN, then Pdist (x) takes each row of the X matrix M

Shellcode Getting Started (win)

esi, [edx + 0x3c]; Lea ESI, [edx + esi]; mov esi, [esi + 0x78]; Lea ESI, [edx + esi]; mov edi, [esi + 0x1c]; Lea EDI, [edx + edi]; MOV[EBP-0X04], EDI; mov

Coinitialize Analysis 1

Everyone knows that to use COM components in a program, you must first call coinitialize. This function is mainly used to initialize the com runtime environment. But does the function scope take the thread as the unit or the process as the unit? Maybe you have figured out the answer through the test program. That's right, it's a thread. Today, we will go into a bit more detail and confirm our ideas by analyzing the specific implementation of coinitialize. Let's take a look at coinitialize compil

Making cross-platform Shellcode

]; Lea ESI, [edx + esi]; mov esi, [esi + 0x78]; Lea ESI, [edx + esi]; mov edi, [esi + 0x1c]; Lea EDI, [edx + edi]; MOV[EBP-0X04], EDI; mov edi

K Nearest Neighbor algorithm

Nearest Neighbor Model feature space is generally n-dimensional real vector space, the distance can be used to make European distance, but also can be other distances, since pulled to the distance, the following is to elaborate on what the distance measurement of the representation, right when extended.1. Euclidean distance , the most common distance representation between two points or multipoint, also known as Euclid's metric, is defined in Euclidean space, such as the distance between points

Machine Learning Similarity Metrics

Transferred from: http://www.cnblogs.com/heaad/archive/2011/03/08/1977733.htmlThe use of learningThis article directory:1. Euclidean distance2. Manhattan Distance3. Chebyshev distance4. Minkowski distance5. Standardized Euclidean distance6. Markov distance7. Angle cosine8. Hamming distance9. Jaccard Distance Jaccard similarity coefficient10. Correlation coefficient related distance11. Information Entropy1. Euclidean distance (Euclidean Distance)Euclidean distance is one of the easiest distance

Machine learning in various distances __ machine learning

(X1,Y1,Z1) and B (X2,Y2,Z2) in three-dimensional space: (3) The Euclidean distance between two n-dimensional vector A (x11,x12,..., x1n) and B (x21,x22,..., x2n): You can also use the form represented as a vector operation: (4) Calculation of Euclidean distance by matlab MATLAB calculation distance mainly uses pdist function. If X is a matrix of MXN, then Pdist (x) takes each row of the X-matrix M Row as an n-dimensional vector, and then calculat

Program loading and Execution (iii)--"x86 assembly language: From the actual mode to the protection mode" Reading notes 23

Loading and execution of programs (iii)--reading notes 23And then the last time the content said.load_relocate_programthe explanation of the process is not over yet, so create a stack segment descriptor and reposition symbol table.Allocating stack space and creating a stack segment descriptor462 ; Creating a program stack segment descriptor463 movecx,[edi+0x0c]; 4KB magnification464 movEbx0x000fffff465 SubEbx,ecxTo get

function calling convention

__stdcall __cdecl __fastcall vc6.0:int __stdcall/__cdecl/__fastcall Add (int x, int y){return x+y;}void Main (){Add (2,3);}1.__stdcall:1:int __stdcall Add (int x, int y)2: {00401020 Push EBP00401021 mov Ebp,esp00401023 Sub esp,40h00401026 push EBX00401027 push ESI00401028 Push EDI00401029 Lea edi,[ebp-40h]0040102C mov ecx,10h00401031 mov eax,0cccccccch00401036 Rep stos dword ptr [edi]3:return X

Python's pulp linear programming introduction and examples

C 190 200 230 asked How to allocate water supply to the reservoir, the company can make the most profit. 2 solving problems Ideasto minimize the cost of diversion management, the profit is the highest .Set : Reservoir i to the cell J Water Supply , the total Diversion management fee is ZThe target function is: z = 160.0*x11 + 130.0*x12 + 220.0*x13 + 170.0*x14 + 140.0*x21 + 130.0*x22 + 190.0*x23 + 150.0*x2

Optimization NFR one--mssql Hello Buffer overflow_php Foundation

good analysis of the. 3. Detection of NFR We first open the NFR release of the signature library MSSQL.FP (or can also be viewed in the AI package) to see the NFR's attack signature for this vulnerability: ..... Variable definition, etc... ... Sqlserv_schema = library_schema:new (1, ["Time", "IP", "int", "IP", "int", "str"], Scope ()); Sqlserv_rec = Recorder ("Bin/list%c", "Sqlserv_schema"); Hello_sig = "\x12\x01\x00\x34\x00\x00\x00\x00\x00\x00

Krypton0.5 main program shelling

is filled, the cmp [Addr] And 0xff will be used to determine whether to check the encryption option for processing. There is Magic JUMP, but the Shell API address has been redirected, and the Patch code needs to be restored.>The code is not optimized, and there is no time to optimize it. There are too many records to analyze the main program.The Patch code is as follows:Code:00B60000 60 pushad00B60001 9C pushfd00B60002 BE 00104000 mov esi, 0x401000 Code segment Addr00B60007 BF 00404000 mov

[Analysis] summarizes three methods of using heap overflow in windows.

at the various flags. Let's take a look at the key points in rtlfreeheap. Key Aspect 1001b: 77fcc829 8a4605 mov Al, [ESI + 05] // ESI points to the start address of the buf2 8-byte management structure, namely, the Al flag001b: 77fcc82c a801 test Al, 01 // whether the flag value contains heap_entry_busy001b: 77fcc82e 0f84a40e0000 JZ 77fcd6d8 // skip if not included. Skip here001b: 77fcc834 f6c207 test DL, 07001b: 77fcc837 0f859b0e0000 jnz 77fcd6d8001b: 77fcc83d 807e0440 CMP byte PTR [ESI + 04],

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