My whole legal name is James Pate Williams, Jr. I was born in LaGrange, Georgia approximately 70 years ago. I barely graduated from LaGrange High School with low marks in June 1971. Later in June 1979, I graduated from LaGrange College with a Bachelor of Arts in Chemistry with a little over a 3 out 4 Grade Point Average (GPA). In the Spring Quarter of 1978, I taught myself how to program a Texas Instruments desktop programmable calculator and in the Summer Quarter of 1978 I taught myself Dayton BASIC (Beginner's All-purpose Symbolic Instruction Code) on LaGrange College's Data General Eclipse minicomputer. I took courses in BASIC in the Fall Quarter of 1978 and FORTRAN IV (Formula Translator IV) in the Winter Quarter of 1979. Professor Kenneth Cooper, a genius poly-scientist taught me a course in the Intel 8085 microprocessor architecture and assembly and machine language. We would hand assemble our programs and insert the resulting machine code into our crude wooden box computer which was designed and built by Professor Cooper. From 1990 to 1994 I earned a Bachelor of Science in Computer Science from LaGrange College. I had a 4 out of 4 GPA in the period 1990 to 1994. I took courses in C, COBOL, and Pascal during my BS work. After graduating from LaGrange College a second time in May 1994, I taught myself C++. In December 1995, I started using the Internet and taught myself client-server programming. I created a website in 1997 which had C and C# implementations of algorithms from the "Handbook of Applied Cryptography" by Alfred J. Menezes, et. al., and some other cryptography and number theory textbooks and treatises.
An anagram is a scrambled or jumbled word. It is a permutation of the letters in a word. There are six permutations of a three letter word such as “the” and are “the”, “teh”, “hte”, “het”, “eth”, and “eht”. The number of permutations of a word consisting of n letters is n!, for example, 4! = 4 * 3 * 2 * 1 = 4 * 3! = 24, 5! = 5 * 4! = 120, etc. I wrote a program to brute force solve anagrams using an English language dictionary consisting of 152,512 words, a hash table, and a permutation generator. The hash table is generated from the English language dictionary by the formula first character integer ASCII value squared + the second character integer ASCII value . The base hash table entry for the word “an” is 65 * 65 + 78 = 4,303. There will be collisions or words with the same hash code. In this case there is a list of words for each hash code value. The application can solve 12 character anagrams in less than one hour on my computer where 12! = 479,001,600. Some anagrams can represent more than one word so a list of potential anagrams is created. Some example executions of the C# application are illustrated below.
I very recently created a multiple precision signed integer package in C++ using the standard library and a base of 10. I then implemented two integer factoring algorithms trial division and Pollard’s Rho method. Trial division uses all the prime numbers <= 10000 and there are 1229 such primes. Due to the choice of language and the exceedingly small base the resulting application is awfully slow when compared to a similar C# application. The multiple precision signed integer package is largely based on translation of the Pascal source code found in “Prime Numbers and Computer Methods for Factorization” by Hans Riesel. The test number is 2 ^ 72 – 1 which is a Mersenne composite integer. The output large integers start with the number of base 10 digits in the number. For comparison I have included the output from my C# Big Integer factorization program as a screen shot.
Menu
0 Exit Application
1 Test of Package
2 Trial Division
3 Pollard Rho
2
n = 4722366482869645213695
Duration (min:sec.mil) = 00:08.784
n is composite, factors:
3 ^ 3 factor has 1 digits
5 factor has 1 digits
7 factor has 1 digits
13 factor has 2 digits
17 factor has 2 digits
19 factor has 2 digits
37 factor has 2 digits
73 factor has 2 digits
109 factor has 3 digits
241 factor has 3 digits
433 factor has 3 digits
Large prime 5 3 8 7 3 7
Menu
0 Exit Application
1 Test of Package
2 Trial Division
3 Pollard Rho
3
n = 4722366482869645213695
n is composite, factors:
2 2 1
1 3
1 3
4 3 5 1 5
2 1 3
4 1 2 4 1
3 2 4 1
3 1 0 9
3 4 3 3
5 3 8 7 3 7
1 3
1 3
1 3
1 5
1 7
2 1 3
2 1 7
2 1 9
2 3 7
2 7 3
3 1 0 9
3 2 4 1
3 4 3 3
5 3 8 7 3 7
Duration (min:sec.mil) = 00:02.197
I started creating computer programs the Summer Semester of 2002 at Auburn University. I took a course named “Hand Held Software Development”. The course was taught by my research advisor Associate Professor Richard O. Chapman. I created a distributed chess playing client-server Internet system for human chess players. The program was built using the Palm Pilot’s Palm OS and its C language compiler. Later in circa 2006 I built a rule based and neural network chess program for a computer to play itself and for a human observer (voyeur). The language was Java. Then in 2015 I translated and enhanced my Java program by rewriting the code in C#. Below are pictures of one game.
The description of this alphabetic letter game is very facile. Given a word make as many other words as possible using the letters of the given initial word. But first before we enumerate the game solution, we need to refresh the reader’s memory of some elementary mathematics.
The binary number system also known as the base 2 number system is used by computers to perform arithmetic. The digits in the binary number system are 0 and 1. The numbers 0 to 15 in binary using only four binary digits are where ^ is the exponentiation operator (raising a number to a power) are:
0 0000
1 0001 2 ^ 0 = 1
2 0010 2 ^ 1 = 2
3 0011 2 ^ 1 + 2 ^ 0 = 2 + 1 = 3
4 0100 2 ^ 2 = 4
5 0101 2 ^ 2 + 2 ^ 0 = 4 + 1 = 5
6 0110 2 ^ 2 + 2 ^ 1 = 4 + 2 = 6
7 0111 2 ^ 2 + 2 ^ 1 + 2 ^ 0 = 4 + 2 + 1 = 7
8 1000 2 ^ 3 = 8
9 1001 2 ^ 3 + 2 ^ 0 = 8 + 1 = 9
10 1010 2 ^ 3 + 2 ^ 1 = 8 + 2 = 10
11 1011 2 ^ 3 + 2 ^ 1 + 2 ^ 0 = 8 + 2 + 1 = 11
12 1100 2 ^ 3 + 2 ^ 2 = 8 + 4 = 12
13 1101 2 ^ 3 + 2 ^ 2 + 2 ^ 0 = 8 + 4 + 1 = 13
14 1110 2 ^ 3 + 2 ^ 2 + 2 ^ 1 = 8 + 4 + 2 = 14
15 1111 2 ^ 3 + 2 ^ 2 + 2 ^ 1 + 2 ^ 0 = 8 + 4 + 2 + 1 = 15
An algorithm to convert a base 10 (decimal) number to base 2 (binary) number is given below:
Input n a base 10 number
Output b[0], b[1], b[2], … a finite binary string representing the decimal number
Integer i = 0
Do
Integer nmod2 = n mod 2
Integer ndiv2 = n / 2
b[i] = nmod2 + ‘0’
i = i + 1
n = ndiv2
While n > 0
The b[i] will be in reverse order. For example, convert 12 from decimal to using four binary digits:
12 mod 2 = 0
12 div 2 = 6
b[0] = ‘0’
i = 1
n = 6
6 mod 2 = 0
6 div 2 = 3
b[1] = ‘0’
i = 2
n = 3
3 mod 2 = 1
3 div 2 = 1
i = 3
b[2] = ‘1’
n = 1
1 mod 2 = 1
1 div 2 = 0
b[3] = ‘1’
n = 0
So, the reversed binary string of digits is “0011”. And after reversing the string we have 12 is represented by the binary digits “1100”.
Next, we need to define a power set and its binary representation. The index power set of 4 objects which has 2 ^ 4 = 16 entries is specified in the following table:
0 0000
1 0001
2 0010
3 0011
4 0100
5 0101
6 0110
7 0111
8 1000
9 1001
10 1010
11 1011
12 1100
13 1101
14 1110
15 1111
A permutation of the set of three indices is given by the following list:
012, 021, 102, 120, 201, 210
A permutation of n objects is a list of n! = n * (n – 1) * … * 2 * 1. A permutation of 4 objects has a list of 24 – 4-digit indices list since 4! = 4 * 3 * 2 * 1 = 24 has the table:
0123, 0132, 0213, 0231, 0312, 0321,
1023, 1032, 1203, 1230, 1320, 1302,
2013, 2031, 2103, 2130, 2301, 2310,
3012, 3021, 3102, 3120, 3201, 3210
Suppose our word is “lost” then we first find the power set:
1 0001 t
2 0010 s
3 0011 st ts
4 0100 o
5 0101 ot to
6 0110 os so
7 0111 ost ots sot sto tos tso
8 1000 l
9 1001 lt tl
10 1010 ls sl
11 1011 lst lts slt stl tsl tls
12 1100 lo ol
13 1101 lot lto olt otl tlo tol
14 1110 los lso slo sol osl ols
15 1111 lost lots slot etc.
Using a dictionary of 152,512 English words my program finds 16 hits for the letters of “lost”:
Dictionary Length: 152512
Word: lost
0 l
1 lo
2 lost
3 lot
4 lots
5 ls
6 o
7 s
8 slot
9 so
10 sol
11 sot
12 st
13 t
14 to
15 ts
Total letters and/or words 16
Next, we use “tear” as our word:
Dictionary Length: 152512
Word: tear
0 a
1 are
2 art
3 at
4 ate
5 e
6 ea
7 ear
8 eat
9 era
10 et
11 eta
12 r
13 rat
14 rate
15 re
16 rt
17 rte
18 t
19 tar
20 tare
21 tea
22 tear
23 tr
Total letters and/or words 24
Finally, we use the word “company”:
Dictionary Length: 152512
Word: company
0 a
1 ac
2 am
3 amp
4 an
5 any
6 c
7 ca
8 cam
9 camp
10 campy
11 can
12 canopy
13 cap
14 capo
15 capon
16 cay
17 cm
18 co
19 com
20 coma
21 comp
22 company
23 con
24 cony
25 cop
26 copay
27 copy
28 coy
29 cyan
30 m
31 ma
32 mac
33 man
34 many
35 map
36 may
37 mayo
38 mo
39 moan
40 mop
41 mp
42 my
43 myna
44 n
45 nap
46 nay
47 nm
48 no
49 o
50 om
51 on
52 op
53 p
54 pa
55 pan
56 pay
57 pm
58 pony
59 y
60 ya
61 yam
62 yap
63 yo
64 yon
Total letters and/or words 65
The C++ program's source code is given below:
// WordToWords.cpp : This file contains the 'main' function. Program execution begins and ends there.
//
#include "pch.h"
#include <algorithm>
#include <fstream>
#include <iomanip>
#include <iostream>
#include <string>
#include <vector>
using namespace std;
vector<string> dictWords;
bool ReadDictionaryFile()
{
fstream newfile;
newfile.open("C:\\Users\\james\\source\\repos\\WordToWords\\Dictionary.txt", ios::in);
if (newfile.is_open()) {
int index = 0, length = 128;
char cstr[128];
while (newfile.getline(cstr, length)) {
string str;
str.clear();
for (int i = 0; i < (int)strlen(cstr); i++)
str.push_back(cstr[i]);
dictWords.push_back(str);
}
newfile.close();
sort(dictWords.begin(), dictWords.end());
return true;
}
else
return false;
}
string ConvertBase2(char cstr[], int n, int len)
{
int count = 0;
string str, rev;
do
{
int nMod2 = n % 2;
int nDiv2 = n / 2;
str.push_back(nMod2 + '0');
n = nDiv2;
} while (n > 0);
n = str.size();
for (int i = n; i < len; i++)
str.push_back('0');
n = str.size();
for (int i = n - 1; i >= 0; i--)
if (str[i] == '1')
rev.push_back(cstr[i]);
return rev;
}
vector<string> PowerSet(char cstr[], int len)
{
vector<int> index;
vector<string> match;
for (long ps = 0; ps <= pow(2, len); ps++)
{
string str = ConvertBase2(cstr, ps, len);
int psf = 1;
for (int i = 2; i <= len; i++)
psf *= i;
for (int i = 0; i < psf; i++)
{
if (binary_search(dictWords.begin(), dictWords.end(), str))
{
if (!binary_search(match.begin(), match.end(), str))
{
match.push_back(str);
sort(match.begin(), match.end());
}
}
next_permutation(str.begin(), str.end());
}
sort(match.begin(), match.end());
}
return match;
}
int main()
{
bool done = false;
char cstr[128];
int len;
string str;
vector<int> index;
vector<string> match;
if (!ReadDictionaryFile())
return -1;
cout << "Dictionary Length: " << dictWords.size() << endl << endl;
cout << "Word: ";
cin >> cstr;
cout << endl;
len = strlen(cstr);
if (len != 0)
{
vector<string> match = PowerSet(cstr, len);
for (int i = 0; i < match.size(); i++)
{
cout << setprecision(3) << setw(3) << i << "\t";
cout << match[i] << endl;
}
cout << endl;
cout << "Total letters and/or words " << match.size() << endl;
cout << endl;
}
}
The Rosette motion of the perihelion precession of a massive object orbiting a black hole (Schwarzschild solution Einstein’s general relativity field equations is illustrated by the graphs below for varying values of eccentricity of the ellipsoidal orbit 0.00, 0.01, 0.02, 0.03, 0.04, and 0.05. The angular momentum constant is B = 1, and the mass is M = 10.
using System;
using System.Drawing;
using System.Windows.Forms;
namespace SchwarzschildOrbit
{
public partial class GraphForm : Form
{
private double B, B2, B4, M, M2, M3, epsilon;
public GraphForm(double B, double M, double epsilon)
{
InitializeComponent();
this.B = B;
this.M = M;
this.epsilon = epsilon;
B2 = B * B;
B4 = B2 * B2;
M2 = M * M;
M3 = M * M2;
panel1.Paint += Panel1_Paint;
}
private double u0(double phi)
{
return M * (1.0 + epsilon * Math.Cos(phi)) / B2;
}
private double u1(double phi)
{
return u0(phi) + 3.0 * M3 * (1.0 + epsilon * phi * Math.Sin(phi)
+ epsilon * epsilon * (0.5 - Math.Cos(2.0 * phi) / 6.0)) / B4;
}
private double X(double r, double phi)
{
return r * Math.Cos(phi);
}
private double Y(double r, double phi)
{
return r * Math.Sin(phi);
}
private void Maximums(out double maxR, out double maxPhi,
out double XMax, out double XMin, out double YMax, out double YMin)
{
double phi = 0.0, r = 0.0, XC = 0.0, YC = 0.0;
maxPhi = 0.0;
maxR = double.MinValue;
XMax = double.MinValue;
YMax = double.MinValue;
XMin = double.MaxValue;
YMin = double.MaxValue;
while (phi <= 8.0 * Math.PI)
{
r = 1.0 / u1(phi);
if (r > maxR)
{
maxR = r;
maxPhi = phi;
}
XC = X(r, phi);
if (XC > XMax)
XMax = XC;
YC = Y(r, phi);
if (YC > YMax)
YMax = YC;
if (XC < XMin)
XMin = XC;
if (YC < YMin)
YMin = YC;
phi += 0.001;
}
}
private void Minimums(out double minR, out double minPhi,
out double XMax, out double XMin, out double YMax, out double YMin)
{
double phi = 0.0, r = 0.0, XC = 0.0, YC = 0.0;
minPhi = 0.0;
minR = double.MaxValue;
XMax = double.MinValue;
YMax = double.MinValue;
XMin = double.MaxValue;
YMin = double.MaxValue;
while (phi <= 8.0 * Math.PI)
{
r = 1.0 / u1(phi);
if (r < minR)
{
minR = r;
minPhi = phi;
}
XC = X(r, phi);
if (XC > XMax)
XMax = XC;
YC = Y(r, phi);
if (YC > YMax)
YMax = YC;
if (XC < XMin)
XMin = XC;
if (YC < YMin)
YMin = YC;
phi += 0.001;
}
}
private void Panel1_Paint(object sender, PaintEventArgs e)
{
panel1.Size = ClientSize;
int width = ClientSize.Width;
int height = ClientSize.Height;
int deltaX = width / 6;
int deltaY = height / 6;
int minX = deltaX;
int maxX = 5 * deltaX;
int minY = deltaY;
int maxY = 5 * deltaY;
double maxPhi, minPhi, maxR, minR;
double XMax, XMin, YMax, YMin;
double UMax, UMin, VMax, VMin;
Maximums(out maxR, out maxPhi, out XMax, out XMin, out YMax, out YMin);
Minimums(out minR, out minPhi, out UMax, out UMin, out VMax, out VMin);
double slopeX = (maxX - minX) / (XMax - XMin);
double slopeY = (minY - maxY) / (YMax - YMin);
double interX = minX - slopeX * XMin;
double interY = maxY - slopeY * YMin;
double chi = 0.0, eta = 0.0, phi = 0.0, r = 0.0, x, y;
Graphics g = e.Graphics;
Pen bp = new Pen(Color.Black);
SolidBrush rb = new SolidBrush(Color.Red);
g.Clip = new Region(new Rectangle(minX, minY, maxX - minX + 1, maxY - minY + 1));
for (int i = 0; i < 5; i++)
g.DrawLine(bp, (i + 1) * deltaX, minY, (i + 1) * deltaX, maxY);
for (int i = 0; i < 5; i++)
g.DrawLine(bp, minX, (i + 1) * deltaY, maxX, (i + 1) * deltaY);
while (phi <= 8.0 * Math.PI)
{
r = 1.0 / u1(phi);
x = X(r, phi);
y = Y(r, phi);
chi = slopeX * x + interX;
eta = slopeY * y + interY;
g.FillEllipse(rb, (float)chi, (float)eta, 1, 1);
phi += 0.001;
}
}
}
}
I implemented a computerized version of a game similar to the board game Boggle. Given a jumble of letters find as many words as possible. Suppose we have the jumbled letters “sldfie” then my C++ program outputs:
Now suppose the scrambled letters are “nifrsmo”:
The program uses permutations and power sets. All permutations of the set of three numbers 1, 2, and 3 are:
123 132 213 231 312 321
The total number of permutations of n objects is n! where n! = n * (n – 1) * … * 2 * 1. So we have 3! = 3 * 2 * 1 = 6 and 4! = 4 * 3 * 2 * 1 = 24.
A power set of three objects can generated by using the binary representation of all binary numbers 0 to 2 * 2 * 2 – 1 = 8 – 1 = 7.
Number of External Keys = 2 ^ 31 – 1 = 2,147,483,647 Possibilities
Number of the Internal Keys = n-Rotors (8) * 128 (# of standard ASCII characters) = 1024 Internal Keys
Beaufort Internal Cipher with 8 alphabets of 128 internal keys
The system is weak in its current configuration
Here is the 4 A, 8 A, and 12 A cases
I need to strengthen the external key length to at least 2^192 key possibilities by adding a cryptographic secure random number generator instead of a standard weak C type pseudorandom number generator. Another way of strengthening the system would be to rotate each rotor after a one character or one block use. The block length is 8 ASCII characters.