CELLULAR AUTOMATA RULES GENERATOR FOR MICROBIAL COMMUNITIES CALIFORNIA STATE UNIVERSITY, SAN BERNARDINO SCHOOL OF COMPUTER SCIENCE & ENGINEERING By Melissa Quintana

Microbial Community April 1999 – Removal of Microbial Life September 2003 – Regrowth

Current Research Dr. Penelope Boston Explorations of extreme environments Microbiologist – Studies Microbial Communities Courtesy of Dr. Penelope Boston

Cellular Automata = death 1 = life Total sum = 5 Rule : if total sum is 5 or less the cell state lives

Cellular Automata Dr. Schubert Samples Cellular Automata Rules Radius of three Series of 20 to represent growth over a period of time

Goal – Extract Radius Use image analysis to produce a visual representation of cellular automata specifications. for i=1:prod(size(a1)) if (a1(i)==0 & b1(i)==1) then Live(a2(i)+1)=Live(a2(i)+1)+1 elseif (a1(i) - b1(i)>0) then Die(a2(i)+1)=Die(a2(i)+1)+1 elseif (a1(i)==1 & b1(i)==1) then StableTwo(a2(i)+1)=StableTwo(a2(i) +1)+1; end

What is the radius of effect? The radius of effect of Cellular Automata Why is it important?

Goal-Estimate the Rules Estimated Rules Program Estimated Rules

What are Rules? Game of Life 1 represents a neighbor 0 represents no life Any live cell with fewer than two live neighbors dies, as if caused by under-population. <2 = Death Any live cell with more than three live neighbors dies, as if by overcrowding. >3 = Death Any live cell with two or three live neighbors lives on to the next generation. 2 or 3 = life Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction. Exactly 3 = Life

Importance of the Study Discover the rules without knowing the rules. Correlate the rules with patterns. Overall understanding of what and how much of the environmental factors contribute to the results of the growth.

Visual Identification Life Death Water Soil Biomass Weather Randomness Over-crowding Correlate the rules with the patterns with an understanding of the surrounding environmental factors. AirSediments (animals, plants)Hot and Cold Temperatures

Thesis Project Three Phases – Phase One Testing Calculations Identifying the Radius of effect – Phase Two Identifying an approximation of the Rules – Phase Three Identifying an approximation of the Rules from pictures Samples – Cellular Automata – Pictures SciLab

First Phase – Predefined Matrix Predefined Matrix A = [ ; ; ; ; ; ; ; ; ];

Calculate and Store = = = = = = =

Calculation Output Manual Verification

Program Function Cellular Automaton Was used that had specific rules assigned to it. Series of 20 to represent growth and time. Function First program was turned into a function. The function was called on every time series to produce Histogram Analysis.

Radius 1 Output Radius of effect = 1 Calculation area

Radius 2 Output Radius of effect = 2 Calculation area

Radius 3 Output Radius of effect = 3 Calculation area

Second Phase Created to compare against existing estimates from Cellular Automaton of a static image. Live Center Dead Center

Cellular Automata

Calculate and Store (1 ST Series) … = Center Cell state – Live (1) or dead (0) = =

For all Generations (2 nd Series) … = Center Cell state – Live (1) or dead (0) = =

Comparison of Selected Generations …. 20 t = 20If t == ? then … …. Vector with radius summed values Series 5 Matrix calculation ResultsSeries 6 Matrix calculation Results Vector with radius summed values …. Vector with radius cell states … A dead cell becomes alive A live cell remains alive A live cell becomes dead A dead cell Remains dead

Program Output Live State 0-1 Dead State 1-0 Stable State 1-1 Stable State 0-0

Static Versus Dynamic Live State 0-1 Stable State 1-1 Dead State 1-0 Stable State 0-0 Dynamic Stable1-13 Live14-35 Die36-45 Live Center Dead Center Static

3rd Phase – Using Pictures

Image Preparation Paint – Clip and Resize pictures – Resize according to the radius Scilab Image Processing toolbox – Converts the image into a matrix – [Apr1999]=imread('C:\program files\scilab \contrib\siptoolbox\images\April_1999_Color_W106xH103.jpg')

Thresholding = Summed value of all cells/(max cell value* radius^2) Round Value If < 0.5 Value = 0 If > 0.5 Value =

Calculate and Store This is completed for both picture matrix = Center Cell state – Live (1) or dead (0) = =

Compare …. Vector with radius summed values First Picture Matrix calculation ResultsSecond Picture Matrix calculation Results Vector with radius summed values …. Vector with radius cell states … A dead cell becomes alive A live cell remains alive A live cell becomes dead A dead cell Remains dead April 1999 September 2003

4 th Program - Output Live State 0-1 Dead State 1-0 Stable State 1-1 Stable State 0-0

Picture Rules Live State 0-1 Dead State 1-0 Stable State 0-0 Pictures Live Die17-50 Stable State 1-1

Picture Results Too long of a time period High value summed range producing life High value summed ranged producing death

Future Studies Future Research – Compare all series comparisons Missing rules – More samples What should represent a series? Long Term Goals – Correlate the rules with patterns – Aid in ongoing efforts

Test for Missing Rules Compare COMPARE

Identify an Appropriate Time Series Approximately 4 years

Goal Estimated Rules Program Estimated Rules

Visual Identification Life Death Water Soil Biomass Weather Randomness Over-crowding Correlate the rules with the patterns with an understanding of the surrounding environmental factors. AirSediments (animals, plants)Hot and Cold Temperatures

Conclusion Learning more about microbial communities and supporting other’s in their efforts will enable us to equip ourselves with knowledge to be used when the opportunity for future endeavors arise.

Committee Members Dr. Keith Schubert Dr. Richard Botting Dr. Ernesto Gomez Melissa Quintana