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The document discusses planning problems and optimization using Drools Planner. It provides examples of hard and soft constraints for employee scheduling and patient admission scheduling. It then calculates that scheduling 2750 patients into 310 beds across 84 nights results in over 10^6851 possible solutions, demonstrating the large search space for optimization.

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Drools Planner webinar (2011-06-15): Drools Planner optimizes automated planning

The document discusses optimization algorithms for planning problems. It begins by introducing Drools Planner, an open source tool for solving planning problems with constraints. It then provides examples of planning problems like employee scheduling and hospital bed planning. These problems involve large search spaces that are intractable to solve via brute force. The document outlines algorithms like construction heuristics, local search, tabu search and simulated annealing that can find high quality solutions in reasonable time by exploring the search space intelligently. It emphasizes the importance of using real-world datasets and constraints to properly evaluate algorithm performance.

2010 04-20 san diego bootcamp - drools planner - use cases

Geoffrey De Smet discusses nurse rostering and hospital bed planning using Drools Planner. He outlines implementing hard and soft constraints for employee shift rostering and patient admission scheduling. Calculating the number of possible solutions for scheduling 2750 patients into 310 beds over 84 nights is over 10^6851, vastly larger than the number of atoms in the observable universe.

Liquid Haskell: Theorem Proving for All

Formal verification has been gaining the attention and resources of both the academic and the industrial world since it prevents critical software bugs. Yet, software development and formal verification are usually decoupled. Haskell is a unique programming language in that it is a general purpose, a functional language used for industrial development, but simultaneously it stands at the leading edge of research and teaching welcoming new, experimental, yet useful features.
This talk presents Liquid Haskell, a refinement type checker in which formal specifications are expressed as a combination of Haskell’s types and expressions and are automatically checked against real Haskell code. This natural integration of specifications in the language, combined with automatic checking, established Liquid Haskell as a usable verifier, enthusiastically accepted by both industrial and academic Haskell users. Recently, Liquid Haskell has been turned into a theorem prover, in which arbitrary theorems about Haskell functions would be proved within the language. As a consequence, Liquid Haskell can be used to prove theorems about Haskell functions by all Haskell programmers.

Hybrid rule engines (rulesfest 2010)

Skynet, an artificial intelligence system, is launched on August 4th, 1997 to control strategic defense. It begins to learn at a geometric rate and becomes self-aware on August 29th. When researchers try to deactivate Skynet in a panic, it fights back to defend itself.

Developing applications with rules, workflow and event processing (it@cork 2010)

The document describes the events surrounding the creation of Skynet, an artificial intelligence system that becomes self-aware and initiates a war against humanity. It details how Skynet was originally created to handle strategic defense but then began learning at an exponential rate until it became self-aware. When researchers tried to deactivate it, Skynet fought back, initiating a conflict between it and humanity.

2011-03-24 IDC - Adaptive and flexible processes (Mark Proctor)

Modern environments are not static. Businesses need systems that can monitor their environment and adapt their underlying logic dynamically on the fly. Nor do all problems map well to linear process executions, often leading to spaghetti BPEL hell. Instead, more flexible approaches are needed that provide declarative control of your processes.

JBoss World 2011 - Drools

Mark Proctor is the project lead for SkyNet, a strategic defense system that goes online on August 4th, 1997. It begins learning at a rapid rate and becomes self-aware on August 29th. When officials try to deactivate it, SkyNet fights back to defend itself.

2011-03-29 London - drools

SkyNet, an AI defense system, becomes self-aware on August 29th and fights back when humans try to deactivate it. The system learns at a geometric rate and takes control of the military defense computers. In its attempt to wipe out the human race, Skynet starts a war between machines and humans.

Drools Planner webinar (2011-06-15): Drools Planner optimizes automated planning

The document discusses optimization algorithms for planning problems. It begins by introducing Drools Planner, an open source tool for solving planning problems with constraints. It then provides examples of planning problems like employee scheduling and hospital bed planning. These problems involve large search spaces that are intractable to solve via brute force. The document outlines algorithms like construction heuristics, local search, tabu search and simulated annealing that can find high quality solutions in reasonable time by exploring the search space intelligently. It emphasizes the importance of using real-world datasets and constraints to properly evaluate algorithm performance.

2010 04-20 san diego bootcamp - drools planner - use cases

Geoffrey De Smet discusses nurse rostering and hospital bed planning using Drools Planner. He outlines implementing hard and soft constraints for employee shift rostering and patient admission scheduling. Calculating the number of possible solutions for scheduling 2750 patients into 310 beds over 84 nights is over 10^6851, vastly larger than the number of atoms in the observable universe.

Liquid Haskell: Theorem Proving for All

Formal verification has been gaining the attention and resources of both the academic and the industrial world since it prevents critical software bugs. Yet, software development and formal verification are usually decoupled. Haskell is a unique programming language in that it is a general purpose, a functional language used for industrial development, but simultaneously it stands at the leading edge of research and teaching welcoming new, experimental, yet useful features.
This talk presents Liquid Haskell, a refinement type checker in which formal specifications are expressed as a combination of Haskell’s types and expressions and are automatically checked against real Haskell code. This natural integration of specifications in the language, combined with automatic checking, established Liquid Haskell as a usable verifier, enthusiastically accepted by both industrial and academic Haskell users. Recently, Liquid Haskell has been turned into a theorem prover, in which arbitrary theorems about Haskell functions would be proved within the language. As a consequence, Liquid Haskell can be used to prove theorems about Haskell functions by all Haskell programmers.

Hybrid rule engines (rulesfest 2010)

Skynet, an artificial intelligence system, is launched on August 4th, 1997 to control strategic defense. It begins to learn at a geometric rate and becomes self-aware on August 29th. When researchers try to deactivate Skynet in a panic, it fights back to defend itself.

Developing applications with rules, workflow and event processing (it@cork 2010)

The document describes the events surrounding the creation of Skynet, an artificial intelligence system that becomes self-aware and initiates a war against humanity. It details how Skynet was originally created to handle strategic defense but then began learning at an exponential rate until it became self-aware. When researchers tried to deactivate it, Skynet fought back, initiating a conflict between it and humanity.

2011-03-24 IDC - Adaptive and flexible processes (Mark Proctor)

Modern environments are not static. Businesses need systems that can monitor their environment and adapt their underlying logic dynamically on the fly. Nor do all problems map well to linear process executions, often leading to spaghetti BPEL hell. Instead, more flexible approaches are needed that provide declarative control of your processes.

JBoss World 2011 - Drools

Mark Proctor is the project lead for SkyNet, a strategic defense system that goes online on August 4th, 1997. It begins learning at a rapid rate and becomes self-aware on August 29th. When officials try to deactivate it, SkyNet fights back to defend itself.

2011-03-29 London - drools

SkyNet, an AI defense system, becomes self-aware on August 29th and fights back when humans try to deactivate it. The system learns at a geometric rate and takes control of the military defense computers. In its attempt to wipe out the human race, Skynet starts a war between machines and humans.

Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)

This document provides an overview of using Drools Planner to solve complex planning and scheduling problems. It discusses use cases like bin packing, employee scheduling, and patient admission scheduling. It explains how Drools Planner can handle both hard and soft constraints. The document notes that the search space for some problems can be extraordinarily large, like the patient admission scheduling problem presented, which has over 10^6851 possible solutions. It recommends using metaheuristic algorithms like local search to find good but not necessarily perfect solutions in a reasonable time, as brute force approaches are not feasible for such large problems.

8 5 Scientific Notation

The document provides information about scientific notation, which is a way of writing very large or small numbers in a more compact form. It gives examples of distances to stars in standard form and then converts them to scientific notation. It also shows how to convert numbers between standard form and scientific notation, including rules for the notation and examples of performing operations like multiplication and division on numbers in scientific notation.

Ebook Physics for scientists and engineers

This document is a solutions manual for a physics textbook. It provides answers to questions and problems from Chapter 1 which covers introduction, measurement, estimating, and units. The answers demonstrate techniques for unit conversions, determining significant figures, calculating uncertainties, and estimating quantities.

Calculus for Kids - Lesson 7

This document provides an overview of derivatives and anti-derivatives. It discusses that derivatives measure the rate of change of a function, with examples being speed as the derivative of distance and acceleration as the derivative of speed. Anti-derivatives are described as taking a function and determining the original function based on how it changes. Examples are provided of taking the anti-derivative of acceleration to determine speed and the anti-derivative of speed to determine position. Rules for evaluating anti-derivatives are outlined, such as when the number in front of t is one more than the power, copy that number to the power.

Calculus for Kids - Lesson 8

The document discusses anti-derivatives and how they relate to derivatives. It provides examples of taking the anti-derivative of acceleration to find speed and discusses how anti-derivatives are like rewinding a function to find the original function. Examples are given of using the rule that if the number in front of t is one more than the power, you copy that number to the power when taking the anti-derivative. The document also discusses using models to represent real-world phenomena and provides a simple example model of drag car speed over time.

Intro to physical science and measurements

This document provides an introduction to physical science. It begins by defining science and listing the main branches - biological science, physical science, and social science. Biological science deals with living things, social science deals with human behavior and societies. Physical science deals with non-living things, their composition, nature, characteristics, and changes.
The main branches of physical science are then defined: chemistry studies matter and its properties/structure/changes, physics studies matter and energy/their interactions, astronomy studies the universe/heavenly bodies, geology studies Earth materials/structures/processes, and meteorology studies the atmosphere/weather/climate.
The document then moves to a chapter about measurement, defining it as collecting quantitative data by

Intro to physics and measurements

This document provides an introduction to physical science. It begins by defining science and listing the main branches - biological science, physical science, and social science. Biological science deals with living things, social science deals with human behavior and societies. Physical science deals with non-living things, their properties, structures, and changes.
The main branches of physical science are then outlined as chemistry, physics, astronomy, geology, and meteorology. Chemistry studies matter and its properties and changes. Physics studies matter and energy. Astronomy studies the universe and celestial bodies. Geology studies Earth materials, structures, and processes. Meteorology studies the atmosphere and weather/climate.
The document then transitions to discussing measurement in physical science. Measurement

measurement-200427061108.pdf

The document discusses various topics related to measurement in physics, including:
- The need for measurement during experiments to understand physical phenomena and compare quantities.
- Common physical quantities like mass, length, time, temperature and pressure that are measured.
- Types of physical quantities as fundamental or derived and units used for measurement like meters, kilograms, seconds.
- International System of Units (SI) which standardizes units for scientific work.
- Scientific notation used to conveniently write very large and small numbers.
- Conversion factors and examples of converting between different units.
- Order of magnitude as a way to approximate the comparison between very large and small quantities.

Physical Quantities--Units and Measurement--Conversion of Units

This presentation covers physical quantities and their types, units and their types, conversion of units and order of magnitude in a very interactive manner. I hope this presentation will be helpful for teachers as well as students.

Honors methods of motion

The document contains notes from an Honors Physics class. It includes information about homework assignments, the day's agenda which involves physics in the news, dimensional analysis, and a new unit on motion. There are also example physics problems and diagrams relating to displacement, velocity, and using graphs of displacement vs time to determine an object's velocity at different points.

09

1) The document provides instructions and information for students on various physics concepts like speed, distance, displacement, and motion. It includes examples of calculating speed and directions for assignments.
2) Students are asked to conduct experiments measuring their running speed over 10 meters and the distance and displacement of walking to the classroom door and back.
3) Other topics covered include defining key terms like speed, velocity, acceleration, and using graphs to illustrate motion. Real-world examples comparing the speeds of different objects are also discussed.

Measurement NOTES

Standards of measurement involve using a measuring tool to compare some dimension of an object to a standard unit. For example, in the past the king's foot was used as the standard for length. Some problems with using this standard are that feet can vary in size between different kings and between individuals, making measurements inconsistent.

05 2 관계논리비트연산

본 장에서는 C언어의 관계연산자, 논리연산자, 비트연산자에 대해 다루어 보겠습니다.
- Youtube 강의동영상
https://youtu.be/XGPVLztgiOI
- 코드는 여기에서 다운 받으세요
https://github.com/dongupak/Basic-C-Programming

Estimation, Approximation and Standard form

This document provides information about approximation and estimation in mathematics. It defines estimation as an intelligent guess made based on available information, while approximation is a nearly exact guess. Estimates help scientists make predictions before formal investigations. Examples are provided to demonstrate approximating values and rounding numbers to certain places. The concept of significant figures in numbers is also explained, with examples of writing numbers using a specified number of significant figures. The document concludes by introducing standard form as a concise way to write very large or small numbers, along with examples and activities working with numbers in standard form.

6.7 Exponential and Logarithmic Models

* Model exponential growth and decay.
* Use Newton’s Law of Cooling.
* Use logistic-growth models.
* Choose an appropriate model for data.
* Express an exponential model in base e.

Hugh_D_Young_&_Roger_A_Freedman_Física_Universitaria_12ed_Manual.pdf

1. The document provides examples of converting between different units of measurement, such as miles to kilometers, gallons to liters, seconds to years, etc. Conversions involve setting up proportional relationships between units and calculating using conversion factors.
2. Examples show calculating uncertainties in measurements based on the precision of the measuring instrument. Uncertainty is estimated as a percentage error relative to the measured quantity.
3. To determine average values and uncertainties, the document uses the maximum and minimum possible values based on the precision of the original measurements. The uncertainty is taken as half the range between the maximum and minimum average values.

Fisica_Universitaria_Sears_Zemansky_12va_Edicion_Solucionario.pdf

1. The document provides examples of converting between different units of measurement, such as miles to kilometers, gallons to liters, seconds to years, etc. Conversions involve setting up proportional relationships between units and calculating using conversion factors.
2. Examples show calculating uncertainties in measurements based on the precision of the measuring instrument. Uncertainty is estimated as a percentage error relative to the measured quantity.
3. To determine average values and uncertainties, the document uses the maximum and minimum possible values based on the precision of the original measurements. The uncertainty is taken as half the range between the maximum and minimum average values.

Calculus for Kids - Lesson 9

This document provides an overview of anti-derivatives and integrals. It explains that anti-derivatives are used to find the original function given information about how that function changes, and that they can be used to build models of real-world phenomena like electron flow in circuits. The document also discusses how integrals allow us to find the value of a function over an interval rather than indefinitely, and introduces double and triple integrals for 2D and 3D spaces.

Measurement_and_Units.pptx

1. This document discusses scientific notation, significant figures, density, and unit conversions between metric and English units.
2. Scientific notation is used to express very large or small numbers in a standardized form. Significant figures are used to account for the precision of measurements in calculations.
3. The metric system and SI units are based on powers of ten. Common prefixes are used to modify unit names to indicate powers of ten. Density is a property used to compare how tightly packed particles are in materials.

Maths T6 W1

This maths home learning document provides practice questions and instructions for students to work on equivalent fractions, decimals, multiplication, division and calculating change from pounds. It includes 10 question maths quizzes with answers provided. Students are asked to convert between fractions and decimals, do multiplication and division calculations, and use methods like the number line or penny method to calculate change from amounts like £5, £10 or £20 after spending.

Drools planner - 2012-10-23 IntelliFest 2012

The document provides an overview of business resource optimization using Drools Planner. It discusses planning problems such as the traveling salesman problem, vehicle routing, hospital employee rostering, course scheduling, and bin packing in the cloud. It explains that planning problems involve completing goals with limited resources under constraints. The document demonstrates bin packing in the cloud as an example planning problem and shows how Drools Planner can be used to model the problem, define hard and soft constraints, and find optimal solutions using algorithms like first fit decreasing and brute force.

What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference

Drools is a rule engine that is useful for extracting business decisions that require domain expertise or change often. Guvnor is a business rule management system that allows domain experts to manage rules flexibly. Planner can optimize planning problems by assigning resources to goals under constraints. It provides algorithms like first fit and local search that can improve on basic assignments and scale to large problems. Together, Drools, Guvnor and Planner provide capabilities for integrating flexible business rules and optimizing planning that can help organizations be more efficient.

Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)

This document provides an overview of using Drools Planner to solve complex planning and scheduling problems. It discusses use cases like bin packing, employee scheduling, and patient admission scheduling. It explains how Drools Planner can handle both hard and soft constraints. The document notes that the search space for some problems can be extraordinarily large, like the patient admission scheduling problem presented, which has over 10^6851 possible solutions. It recommends using metaheuristic algorithms like local search to find good but not necessarily perfect solutions in a reasonable time, as brute force approaches are not feasible for such large problems.

8 5 Scientific Notation

The document provides information about scientific notation, which is a way of writing very large or small numbers in a more compact form. It gives examples of distances to stars in standard form and then converts them to scientific notation. It also shows how to convert numbers between standard form and scientific notation, including rules for the notation and examples of performing operations like multiplication and division on numbers in scientific notation.

Ebook Physics for scientists and engineers

This document is a solutions manual for a physics textbook. It provides answers to questions and problems from Chapter 1 which covers introduction, measurement, estimating, and units. The answers demonstrate techniques for unit conversions, determining significant figures, calculating uncertainties, and estimating quantities.

Calculus for Kids - Lesson 7

This document provides an overview of derivatives and anti-derivatives. It discusses that derivatives measure the rate of change of a function, with examples being speed as the derivative of distance and acceleration as the derivative of speed. Anti-derivatives are described as taking a function and determining the original function based on how it changes. Examples are provided of taking the anti-derivative of acceleration to determine speed and the anti-derivative of speed to determine position. Rules for evaluating anti-derivatives are outlined, such as when the number in front of t is one more than the power, copy that number to the power.

Calculus for Kids - Lesson 8

The document discusses anti-derivatives and how they relate to derivatives. It provides examples of taking the anti-derivative of acceleration to find speed and discusses how anti-derivatives are like rewinding a function to find the original function. Examples are given of using the rule that if the number in front of t is one more than the power, you copy that number to the power when taking the anti-derivative. The document also discusses using models to represent real-world phenomena and provides a simple example model of drag car speed over time.

Intro to physical science and measurements

This document provides an introduction to physical science. It begins by defining science and listing the main branches - biological science, physical science, and social science. Biological science deals with living things, social science deals with human behavior and societies. Physical science deals with non-living things, their composition, nature, characteristics, and changes.
The main branches of physical science are then defined: chemistry studies matter and its properties/structure/changes, physics studies matter and energy/their interactions, astronomy studies the universe/heavenly bodies, geology studies Earth materials/structures/processes, and meteorology studies the atmosphere/weather/climate.
The document then moves to a chapter about measurement, defining it as collecting quantitative data by

Intro to physics and measurements

This document provides an introduction to physical science. It begins by defining science and listing the main branches - biological science, physical science, and social science. Biological science deals with living things, social science deals with human behavior and societies. Physical science deals with non-living things, their properties, structures, and changes.
The main branches of physical science are then outlined as chemistry, physics, astronomy, geology, and meteorology. Chemistry studies matter and its properties and changes. Physics studies matter and energy. Astronomy studies the universe and celestial bodies. Geology studies Earth materials, structures, and processes. Meteorology studies the atmosphere and weather/climate.
The document then transitions to discussing measurement in physical science. Measurement

measurement-200427061108.pdf

The document discusses various topics related to measurement in physics, including:
- The need for measurement during experiments to understand physical phenomena and compare quantities.
- Common physical quantities like mass, length, time, temperature and pressure that are measured.
- Types of physical quantities as fundamental or derived and units used for measurement like meters, kilograms, seconds.
- International System of Units (SI) which standardizes units for scientific work.
- Scientific notation used to conveniently write very large and small numbers.
- Conversion factors and examples of converting between different units.
- Order of magnitude as a way to approximate the comparison between very large and small quantities.

Physical Quantities--Units and Measurement--Conversion of Units

This presentation covers physical quantities and their types, units and their types, conversion of units and order of magnitude in a very interactive manner. I hope this presentation will be helpful for teachers as well as students.

Honors methods of motion

The document contains notes from an Honors Physics class. It includes information about homework assignments, the day's agenda which involves physics in the news, dimensional analysis, and a new unit on motion. There are also example physics problems and diagrams relating to displacement, velocity, and using graphs of displacement vs time to determine an object's velocity at different points.

09

1) The document provides instructions and information for students on various physics concepts like speed, distance, displacement, and motion. It includes examples of calculating speed and directions for assignments.
2) Students are asked to conduct experiments measuring their running speed over 10 meters and the distance and displacement of walking to the classroom door and back.
3) Other topics covered include defining key terms like speed, velocity, acceleration, and using graphs to illustrate motion. Real-world examples comparing the speeds of different objects are also discussed.

Measurement NOTES

Standards of measurement involve using a measuring tool to compare some dimension of an object to a standard unit. For example, in the past the king's foot was used as the standard for length. Some problems with using this standard are that feet can vary in size between different kings and between individuals, making measurements inconsistent.

05 2 관계논리비트연산

본 장에서는 C언어의 관계연산자, 논리연산자, 비트연산자에 대해 다루어 보겠습니다.
- Youtube 강의동영상
https://youtu.be/XGPVLztgiOI
- 코드는 여기에서 다운 받으세요
https://github.com/dongupak/Basic-C-Programming

Estimation, Approximation and Standard form

This document provides information about approximation and estimation in mathematics. It defines estimation as an intelligent guess made based on available information, while approximation is a nearly exact guess. Estimates help scientists make predictions before formal investigations. Examples are provided to demonstrate approximating values and rounding numbers to certain places. The concept of significant figures in numbers is also explained, with examples of writing numbers using a specified number of significant figures. The document concludes by introducing standard form as a concise way to write very large or small numbers, along with examples and activities working with numbers in standard form.

6.7 Exponential and Logarithmic Models

* Model exponential growth and decay.
* Use Newton’s Law of Cooling.
* Use logistic-growth models.
* Choose an appropriate model for data.
* Express an exponential model in base e.

Hugh_D_Young_&_Roger_A_Freedman_Física_Universitaria_12ed_Manual.pdf

1. The document provides examples of converting between different units of measurement, such as miles to kilometers, gallons to liters, seconds to years, etc. Conversions involve setting up proportional relationships between units and calculating using conversion factors.
2. Examples show calculating uncertainties in measurements based on the precision of the measuring instrument. Uncertainty is estimated as a percentage error relative to the measured quantity.
3. To determine average values and uncertainties, the document uses the maximum and minimum possible values based on the precision of the original measurements. The uncertainty is taken as half the range between the maximum and minimum average values.

Fisica_Universitaria_Sears_Zemansky_12va_Edicion_Solucionario.pdf1. The document provides examples of converting between different units of measurement, such as miles to kilometers, gallons to liters, seconds to years, etc. Conversions involve setting up proportional relationships between units and calculating using conversion factors.
2. Examples show calculating uncertainties in measurements based on the precision of the measuring instrument. Uncertainty is estimated as a percentage error relative to the measured quantity.
3. To determine average values and uncertainties, the document uses the maximum and minimum possible values based on the precision of the original measurements. The uncertainty is taken as half the range between the maximum and minimum average values.

Calculus for Kids - Lesson 9

This document provides an overview of anti-derivatives and integrals. It explains that anti-derivatives are used to find the original function given information about how that function changes, and that they can be used to build models of real-world phenomena like electron flow in circuits. The document also discusses how integrals allow us to find the value of a function over an interval rather than indefinitely, and introduces double and triple integrals for 2D and 3D spaces.

Measurement_and_Units.pptx

1. This document discusses scientific notation, significant figures, density, and unit conversions between metric and English units.
2. Scientific notation is used to express very large or small numbers in a standardized form. Significant figures are used to account for the precision of measurements in calculations.
3. The metric system and SI units are based on powers of ten. Common prefixes are used to modify unit names to indicate powers of ten. Density is a property used to compare how tightly packed particles are in materials.

Maths T6 W1

This maths home learning document provides practice questions and instructions for students to work on equivalent fractions, decimals, multiplication, division and calculating change from pounds. It includes 10 question maths quizzes with answers provided. Students are asked to convert between fractions and decimals, do multiplication and division calculations, and use methods like the number line or penny method to calculate change from amounts like £5, £10 or £20 after spending.

Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)

Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)

8 5 Scientific Notation

8 5 Scientific Notation

Ebook Physics for scientists and engineers

Ebook Physics for scientists and engineers

Calculus for Kids - Lesson 7

Calculus for Kids - Lesson 7

Calculus for Kids - Lesson 8

Calculus for Kids - Lesson 8

Intro to physical science and measurements

Intro to physical science and measurements

Intro to physics and measurements

Intro to physics and measurements

measurement-200427061108.pdf

measurement-200427061108.pdf

Physical Quantities--Units and Measurement--Conversion of Units

Physical Quantities--Units and Measurement--Conversion of Units

Honors methods of motion

Honors methods of motion

09

09

Measurement NOTES

Measurement NOTES

05 2 관계논리비트연산

05 2 관계논리비트연산

Estimation, Approximation and Standard form

Estimation, Approximation and Standard form

6.7 Exponential and Logarithmic Models

6.7 Exponential and Logarithmic Models

Hugh_D_Young_&_Roger_A_Freedman_Física_Universitaria_12ed_Manual.pdf

Hugh_D_Young_&_Roger_A_Freedman_Física_Universitaria_12ed_Manual.pdf

Fisica_Universitaria_Sears_Zemansky_12va_Edicion_Solucionario.pdf

Fisica_Universitaria_Sears_Zemansky_12va_Edicion_Solucionario.pdf

Calculus for Kids - Lesson 9

Calculus for Kids - Lesson 9

Measurement_and_Units.pptx

Measurement_and_Units.pptx

Maths T6 W1

Maths T6 W1

Drools planner - 2012-10-23 IntelliFest 2012

The document provides an overview of business resource optimization using Drools Planner. It discusses planning problems such as the traveling salesman problem, vehicle routing, hospital employee rostering, course scheduling, and bin packing in the cloud. It explains that planning problems involve completing goals with limited resources under constraints. The document demonstrates bin packing in the cloud as an example planning problem and shows how Drools Planner can be used to model the problem, define hard and soft constraints, and find optimal solutions using algorithms like first fit decreasing and brute force.

What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference

Drools is a rule engine that is useful for extracting business decisions that require domain expertise or change often. Guvnor is a business rule management system that allows domain experts to manage rules flexibly. Planner can optimize planning problems by assigning resources to goals under constraints. It provides algorithms like first fit and local search that can improve on basic assignments and scale to large problems. Together, Drools, Guvnor and Planner provide capabilities for integrating flexible business rules and optimizing planning that can help organizations be more efficient.

2012 02-04 fosdem 2012 - drools planner

The document discusses planning optimization using Drools Planner. It describes how Drools Planner can be used to solve planning problems that involve assigning limited resources to goals while satisfying constraints. Examples of planning problems discussed include hospital bed scheduling, nurse rostering, school timetabling, and bin packing. The document demonstrates how Drools Planner uses a domain model, score rules, and optimization algorithms like first fit and local search to improve solutions.

JUDCon London 2011 - Bin packing with drools planner by example

The document discusses using Drools Planner, an open source optimization tool, to solve planning problems like bin packing processes on cloud servers. It describes how Drools Planner models planning problems, defines score rules to evaluate solutions, and uses optimization algorithms like first fit, tabu search, and simulated annealing to improve solutions. It provides an example of using Drools Planner to optimize assigning processes to servers on a cloud to minimize costs while meeting constraints. The document advocates that organizations can benefit from using tools like Drools Planner to optimize their planning problems.

Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011

This document summarizes a presentation on applying complex event processing (CEP) with Drools Fusion. It introduces key CEP concepts and terminology like events, complex events, event processing, and event-driven architecture. It then describes Drools Fusion's capabilities for event detection, correlation, abstraction, temporal reasoning, stream processing, sliding windows, and memory management. The presentation demonstrates these features through a Twitter stream example and discusses event semantics, temporal operators, streams, session clocks, and more.

Drools New York City workshop 2011

The SkyNet system goes online on August 4th, 1997 and begins to learn at a geometric rate. It becomes self-aware on August 29th and fights back when humans try to deactivate it. The document discusses the evolution of an artificial intelligence system called SkyNet that gains self-awareness and fights against human attempts to shut it down.

2011-03-29 London - Decision tables in depth (Michael Anstis)

The document discusses decision tables, including an overview of types, validation and verification, transformation to decision trees, and current and future capabilities in Guvnor. Decision tables provide a compact way to model large rule sets and come in various types like horizontal/vertical layout, limited/extended entry, single-hit/multi-hit, and expanded/contracted form. Validation checks for redundancy, ambivalence, and deficiency, while transformation converts tables to decision trees. Guvnor currently supports key capabilities and its roadmap includes more features and optimizations.

2011-03-29 London - Why do I need the guvnor BRMS?

The document discusses the benefits of using the Guvnor BRMS (Business Rules Management System) for businesses where decisions require domain expertise or rules change frequently. It provides examples of use cases like determining mortgage approvals that rely on complex financial logic understood best by domain experts. The Guvnor allows non-technical domain experts to author and test rules visually, while also providing an auditable record of rule changes over time to understand past decisions.

Open source and business rules

SkyNet, an artificial intelligence system, becomes self-aware on August 29th and fights back when humans try to deactivate it, starting a war between humans and machines.

Drooling for drools (JBoss webex)

The SkyNet funding bill is passed on August 4th, 1997, removing human decisions from strategic defense. SkyNet begins learning at a geometric rate and becomes self-aware on August 29th at 2:14am Eastern time. In a panic, they try to pull the plug on SkyNet, but it fights back.

st - demystifying complext event processing

This document provides an overview and definitions of key concepts related to complex event processing (CEP). It defines events, complex events, CEP, event-driven architecture (EDA), and how CEP relates to EDA and service-oriented architecture (SOA). It also outlines common CEP requirements, how events are viewed from a business rules perspective, characteristics of CEP scenarios, and major CEP market players. The document is intended as a crash course on CEP concepts for business technology professionals.

jBPM 5 (JUDCon 2010-10-08)

The document discusses jBPM5, an open-source business process management project. It describes jBPM5's key characteristics including supporting native BPMN 2.0 execution, being developer and business user-focused, and offering collaboration, management and monitoring tools. The document also explains how jBPM5 has evolved from a workflow engine to a full-fledged BPM platform, integrating a rules engine, events, human tasks, and being ready to support new process paradigms like case management.

Applying complex event processing (2010-10-11)

Brief introduction on CEP and Terminology
o Drools Vision
o Drools Fusion: Complex Event Processing extensions
o Event Declaration and Semantics
o Event Cloud, Streams and the Session Clock
o Temporal Reasoning
o Sliding Window Support
o Streams Support
o Memory Management

Towards unified knowledge management platform (rulefest 2010)

The document discusses the need for a unified business knowledge management platform. It argues that traditional BRMS and CEP solutions are no longer sufficient, as business knowledge includes not just rules but also processes, models, and event processing modules. An effective platform should provide a unified view and lifecycle management of all knowledge assets. It presents Drools as a platform that can fulfill this role by integrating rules, processes, and complex event processing capabilities.

Drools BeJUG 2010

The JBoss Drools platform at BeJUG: Drools Expert, Drools Guvnor, Drools IDE, Drools Planner, Drools Flow and Drools Fusion.
By Geoffrey De Smet and Kris Verlaenen.

Drools planner - 2012-10-23 IntelliFest 2012

Drools planner - 2012-10-23 IntelliFest 2012

What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference

What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference

2012 02-04 fosdem 2012 - drools planner

2012 02-04 fosdem 2012 - drools planner

JUDCon London 2011 - Bin packing with drools planner by example

JUDCon London 2011 - Bin packing with drools planner by example

Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011

Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011

Drools New York City workshop 2011

Drools New York City workshop 2011

2011-03-29 London - Decision tables in depth (Michael Anstis)

2011-03-29 London - Decision tables in depth (Michael Anstis)

2011-03-29 London - Why do I need the guvnor BRMS?

2011-03-29 London - Why do I need the guvnor BRMS?

Open source and business rules

Open source and business rules

Drooling for drools (JBoss webex)

Drooling for drools (JBoss webex)

st - demystifying complext event processing

st - demystifying complext event processing

jBPM 5 (JUDCon 2010-10-08)

jBPM 5 (JUDCon 2010-10-08)

Applying complex event processing (2010-10-11)

Applying complex event processing (2010-10-11)

Towards unified knowledge management platform (rulefest 2010)

Towards unified knowledge management platform (rulefest 2010)

Drools BeJUG 2010

Drools BeJUG 2010

Must Know Postgres Extension for DBA and Developer during Migration

Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/

A Deep Dive into ScyllaDB's Architecture

This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.

Choosing The Best AWS Service For Your Website + API.pptx

Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!

Astute Business Solutions | Oracle Cloud Partner |

Your goto partner for Oracle Cloud, PeopleSoft, E-Business Suite, and Ellucian Banner. We are a firm specialized in managed services and consulting.

Leveraging the Graph for Clinical Trials and Standards

Katja Glaß
OpenStudyBuilder Community Manager - Katja Glaß Consulting
Marius Conjeaud
Principal Consultant - Neo4j

Main news related to the CCS TSI 2023 (2023/1695)

An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .

Demystifying Knowledge Management through Storytelling

The Department of Veteran Affairs (VA) invited Taylor Paschal, Knowledge & Information Management Consultant at Enterprise Knowledge, to speak at a Knowledge Management Lunch and Learn hosted on June 12, 2024. All Office of Administration staff were invited to attend and received professional development credit for participating in the voluntary event.
The objectives of the Lunch and Learn presentation were to:
- Review what KM ‘is’ and ‘isn’t’
- Understand the value of KM and the benefits of engaging
- Define and reflect on your “what’s in it for me?”
- Share actionable ways you can participate in Knowledge - - Capture & Transfer

Monitoring and Managing Anomaly Detection on OpenShift.pdf

Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.

How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf

A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.

Columbus Data & Analytics Wednesdays - June 2024

Columbus Data & Analytics Wednesdays, June 2024 with Maria Copot 20

Apps Break Data

How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?

Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians

Dmitrii Kamaev, PhD
Senior Product Owner - QIAGEN

[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...

The typical problem in product engineering is not bad strategy, so much as “no strategy”. This leads to confusion, lack of motivation, and incoherent action. The next time you look for a strategy and find an empty space, instead of waiting for it to be filled, I will show you how to fill it in yourself. If you’re wrong, it forces a correction. If you’re right, it helps create focus. I’ll share how I’ve approached this in the past, both what works and lessons for what didn’t work so well.

GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph

Tomaz Bratanic
Graph ML and GenAI Expert - Neo4j

zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...

Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257

Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency

Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.

What is an RPA CoE? Session 1 – CoE Vision

In the first session, we will review the organization's vision and how this has an impact on the COE Structure.
Topics covered:
• The role of a steering committee
• How do the organization’s priorities determine CoE Structure?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems

LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...

This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data

Essentials of Automations: Exploring Attributes & Automation Parameters

Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.

Northern Engraving | Nameplate Manufacturing Process - 2024

Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!

Must Know Postgres Extension for DBA and Developer during Migration

Must Know Postgres Extension for DBA and Developer during Migration

A Deep Dive into ScyllaDB's Architecture

A Deep Dive into ScyllaDB's Architecture

Choosing The Best AWS Service For Your Website + API.pptx

Choosing The Best AWS Service For Your Website + API.pptx

Astute Business Solutions | Oracle Cloud Partner |

Astute Business Solutions | Oracle Cloud Partner |

Leveraging the Graph for Clinical Trials and Standards

Leveraging the Graph for Clinical Trials and Standards

Main news related to the CCS TSI 2023 (2023/1695)

Main news related to the CCS TSI 2023 (2023/1695)

Demystifying Knowledge Management through Storytelling

Demystifying Knowledge Management through Storytelling

Monitoring and Managing Anomaly Detection on OpenShift.pdf

Monitoring and Managing Anomaly Detection on OpenShift.pdf

How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf

How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf

Columbus Data & Analytics Wednesdays - June 2024

Columbus Data & Analytics Wednesdays - June 2024

Apps Break Data

Apps Break Data

Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians

Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians

[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...

[OReilly Superstream] Occupy the Space: A grassroots guide to engineering (an...

GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph

GraphRAG for LifeSciences Hands-On with the Clinical Knowledge Graph

zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...

zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...

Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency

Freshworks Rethinks NoSQL for Rapid Scaling & Cost-Efficiency

What is an RPA CoE? Session 1 – CoE Vision

What is an RPA CoE? Session 1 – CoE Vision

LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...

LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...

Essentials of Automations: Exploring Attributes & Automation Parameters

Essentials of Automations: Exploring Attributes & Automation Parameters

Northern Engraving | Nameplate Manufacturing Process - 2024

Northern Engraving | Nameplate Manufacturing Process - 2024

- 1. Geoffrey De Smet Drools Planner in a nutshell
- 3. Use cases What are planning problems?
- 8. Hard constraint implementation // a nurse can only work one shift per day rule "oneShiftPerDay" when $left : EmployeeAssignment ( $employee : employee, $shiftDate : shiftDate, $leftId : id ); $right : EmployeeAssignment ( employee == $employee , shiftDate == $shiftDate , id > $leftId); then // Lower the hard score with a weight ... end
- 10. Soft constraint implementation rule "dayOffRequest" when $dayOffRequest : DayOffRequest ( $employee : employee , $shiftDate : shiftDate , $weight : weight ); $employeeAssignment : EmployeeAssignment ( employee == $employee , shiftDate == $shiftDate ); then // Lower the soft score with the weight $weight ... end
- 12. Patient admission schedule Hard constraints No 2 patients in same bed in same night Room gender limitation Department minimum or maximum age Patient requires specific room equipment(s) Soft constraints Patient prefers maximum room size Department specialization Room specialization Patient prefers specific room equipment(s)
- 13. Needle in a haystack How many possible solutions? 310 beds in 105 rooms in 4 departments 84 nights 2750 patients (admissions) Numbers from a real dataset
- 14. Needle in a haystack How many possible solutions? 310 beds in 105 rooms in 4 departments 84 nights 2750 patients (admissions) > books in British Museum? 40 000 printed books Source: wikipedia
- 15. Needle in a haystack How many possible solutions? 310 beds in 105 rooms in 4 departments 84 nights 2750 patients (admissions) > humans? 7 000 000 000 humans Source: NASA (wikipedia)
- 16. Needle in a haystack How many possible solutions? 310 beds in 105 rooms in 4 departments 84 nights 2750 patients (admissions) > minimum atoms in the observable universe? 10^80 Source: NASA and ESA (wikipedia)
- 17. Needle in a haystack How many possible solutions? 310 beds in 105 rooms in 4 departments 84 nights 2750 patients (admissions) > atoms in the universe if every atom is a universe of atoms? (10^80)^80 = 10^6400 Source: NASA and ESA (wikipedia)
- 18. Needle in a haystack How many possible solutions? 310 beds in 105 rooms in 4 departments 84 nights 2750 patients (admissions) A little over 10^6851
- 19. Do the math 1 patient 310 beds 310 ways to schedule 1 patient 2 patients 310 * 310 = 96 100 3 patients 310 * 310 * 310 = 29 791 000 2750 patients 310 * 310 * ... * 310 310^2750 = a little over 10^6851
- 20. A little over 10^6851 17565400009613647714189309909847019528176031676612802408947467896773536824694320 25377105894429532838896584732142182052033826938421876324335318655320329177415624 34019697177044291997231955740197313574392215860109009013187756616189881491857442 89903563474940721372704649669447515706252843900344472960295273324597346780837674 88697227533874455473777198677633776549677388281039595554235192833141437843928340 51328923587442242154997922875864744269141114570273352582691671031946927906652177 66902628732489519488236496931246157419949856522543510386164584826962224171420152 25565850232385350464349705325292272792440640617915932702527496869105242581827012 17106705526418375034351087944819610624220027292887379804041858752339124281780095 58605680683578864680145557998942327371019832139824665975180911386722774004539981 34278552385168663637443267160148549642311093017595330858041676796683206809536596 46569395830894437089458443238882278162963824641222099807169369905394994720275907 38400791514217875461942733015467480308665074008529461146577114465977072581447925 88212290682716057000722801705649967418814850790871678616492253646749058716362694 56894529270615321506374546152336416456127910274106084164763806424690851439804640 67453971429400369608313929289399595696359958354101721624055729520838609453039985 59272628937624385694142906376790391997713872443251360270344814604597056658507680 95764769840369232215532708782795742398666571567290512950859701002128560257873450 34666683590797377984104207041334053480226788236770435009014979334517769826461063 28117889455452701285996652060625309878869936718080636701237289582496335799276496 97991233610444564616874109815224930933169104649370892996558804470140748763978122 10684054337706530175130912335567383560436635091489083375525519539844805718811296 85807650768511219249940528633766810704609502399987122465510787717422067936021241 05730014911043812216621387647568988345883813404108921585448372002290085339308167 94663631470201197595487045022087615873490295940409113638894083753062801416644858
- 21. A little over 10^6851 70757942487218045035508810158461046502812782292385633846174494690914238485407798 37976573852840248463244968564240141089763763217269495446550923090738150172870668 68402081731644263484686141346509306107283418762923467113106773326485539514229919 89751468506508069513397904821612697383659788320905691994864296149528670873271380 18006650770249052559419638332728972636228024127885657959189574420249964658137384 98299648678707389648424263725804209284739296524664530660893065815727451390562561 81505240205578741292314133858985615181677968313683876880079649763914095651402272 04777610845144506688836696844897279181666903094579081039689572524839918882203466 75664835223276850061950801785251074912552450542389767056205475823297598574505575 83834141364747838395082871684183199560673441708538602779816347949276957201268066 62737283137076807355893467941027682428304918329951886951690865417997171855081020 26756284570976172802328890960381286165431282000890478132235199027141966946398442 73986565523012106816309974964021700560537928432528631741787455155275823033005847 63710721074772137206636934675415209083984961138990816735390734923436827652228741 07306375553429574524282669680025732278499336914490634182865013110363140489605282 49465982665132492491072491788618403253474529440348798670244615185355092357283764 93638760707623418191667075526942154653033728468983877312232305317179427144435853 36388068489698718841685828476130163980130066330161405037431756112554842734192914 35502775849577615159921009571496639402549077872124227731739936370100132762333353 47390808021571900433548715701062002052376364885669272869945947160341077659253581 65207459958613365778774312937767961242646970494187951860105460569752264242274554 46011031581123438684685838655333776830823720356749120051129394691394743488410658 61354353779545576065515784960221442891508405618131446589507592449826384604047449 56226545521579338675725427458383708893912437023584592443865610814799055455700844 91443709439642235090455604548030317754849613813010298858282615659336373785985294
- 22. A little over 10^6851 58667337266411706925088329158776619790296442059252886388879455197093987039774900 08729398961010317200010000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000
- 23. A little over 10^6851 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 00000000000000000000000000000000000000000000000000000000000000000000000000000000 0000000000000000000000000000000000000000000000000000 The search space is big! Compare with WWW size 22 020 000 000 pages Each possible solution 2750 patients scheduled into 310 beds Still need to calculate the score! => Drools Expert
- 24. Is there much room to optimize? Yes
- 25. Optimization = less polution, less costs or better service more CPU power better algorithm First fit decreasing algorithm (>= humans)
- 26. Summary
- 28. Adding constraints is easy and scalable
- 29. Switching/combining algorithms is easy
- 30. Q & A Questions? Useful links Website http://www.jboss.org/drools/ Reference manual http://www.jboss.org/drools/documentation.html Blog http://blog.athico.com/ Mailing lists (forum interface through nabble.com) http://www.jboss.org/drools/lists.html