Computational Methods for Nonlinear Systems

Size: px
Start display at page:

Download "Computational Methods for Nonlinear Systems"

Transcription

1 Computational Methods for Nonlinear Systems Cornell Physics 7682 Fall 2015! Chris Myers Physical Sciences Building 424

2 Computational Methods for Nonlinear Systems Graduate computational science laboratory course developed by Myers, Sethna & Mueller, starting in developed originally to support interdisciplinary IGERT program on Nonlinear Systems - class work focused on implementation of computer programs from papers, hints and skeletal code

3 Computational Methods for Nonlinear Systems Hands-on introduction to computational science & scientific computing: modeling, algorithms, data structures, programming, simulation techniques, data analysis, etc. - a broad variety of scientific themes: complex networks, biomechanics, pattern formation, chemical kinetics, statistical mechanics, molecular dynamics, chaos, random matrix theory, constraint satisfaction, infectious diseases, etc. - a broad variety of numerical methods: ODEs, PDEs, graph theory, Monte Carlo, data analysis, fitting, root finding, etc. - many exercises incorporated into Sethna s textbook, Statistical Mechanics: Entropy, Order Parameters, and Complexity - complementary to Physics 4480 / 7680 ( Computational Physics with Numerical Recipes ) which focuses more specifically on algorithms and numerical analysis

4 Course structure Primary focus is working on course modules in class Periodic lectures on science and/or computation to complement work on course modules Self-paced and autonomous: work on those modules you are most interested in, or propose other topics of interest you would like to explore in more detail Can work in groups if desired, although be sure to take turns driving Students can use PECF workstations in Rockefeller B3 (computing.physics.cornell.edu), or bring own laptop for use in class

5 Course structure No homework assignments no graded assignments; reading background material outside of class is useful Attendance, engagement and participation are paramount Ask questions if you are confused, need help debugging, or want to discuss material Students will be expected to deliver at least one short lecture (~15 minutes) on a subject of interest, and to participate in other initiatives that might unfold (e.g., Bring your problems to class day ) Opportunities to bring relevant projects of interest to class (e.g., related to research), or to work with me to implement some new modules for the course - random graphs, forest fires, flocking, parameter estimation, sloppiness, zombies, mosh pits, etc.

6 Recommended to take S/U Course structure If a letter grade is needed for a particular program, we will conduct oral examination / review of work done at end of semester (can be based in part on extra project) Flexible within reason: can accommodate absences due to occasional conflicts (e.g., special lab meeting, travel to a conference); can make up missed time outside of class - talk to instructor if conflicts arise

7 Programming all programming done in Python 3rd party Python libraries for numerics, graphics, visualization, etc. graphical tools provided to give feedback, help debug, etc. why Python? - interpreted: rapid program development and interactive access - built-in data structures & high-level syntax - rich standard library and 3rd party libraries (for science, visualization, databases, internet programming, etc.) - supports procedural programming, object-oriented programming, functional programming, scripting, large systems - free software (monetarily and intellectually) - good job skill

8 Goals for semester Yours? - get exposed to a broad set of interesting scientific and computational problems and methods - learn how to integrate a variety of tools to solve problems - learn how to conduct research that integrates computation with theory, data, analysis, etc. Mine - teach you all of the above, and learn from all of you - convey how to think computationally: abstraction, interface & information - add new course modules (suggestions are welcome!) - new features/modules to be rolled out over the course of the semester (and you are welcome to help if you are interested in such things) - continue to improve the course website and workflow

9 Scientific topics Networks Biological dynamics & patterns Dynamics & Dynamical Systems Statistical mechanics etc.

10 Course modules Small-world networks Invariant measure Cardiac dynamics NP-completeness Percolation Chaos & Lyapunov Random matrix theory Ising model Pendulum Fractal dimensions Stochastic cells Molecular dynamics Walker Period doubling Repressilator Infectious diseases

11 Small-world networks Science - small world networks (Watts & Strogatz) - six degrees of separation - shortest path lengths in randomly wired graphs Computing - data structure for undirected graphs good introduction to built-in Python containers (lists and dictionaries) - object-oriented encapsulation of complex data structures - graph traversal algorithms (breadth-first search) for shortest path and betweenness - simple graph visualization software supports debugging and provides quick feedback

12 Percolation Science - statistical mechanics of percolation connected clusters in randomly wired graphs (e.g., bond percolation on a lattice) universality of phase transitions Computing - reuse of objects with generic interface (reuse of UndirectedGraph class from small-world network module) - graph traversal algorithms (breadth-first search) for cluster finding - scaling collapses

13 Walker Science - Simple model of bipedal walker (Ruina and coworkers) double pendulum with impulse for heelstrike single pendulum as warmup - period-doubling bifurcations in physical system Computing - integration of ODEs finite differences, time-step dependence, integration schemes (stability, fidelity, accuracy) calling 3rd party numerical libraries - change of integration variables for event detection (heelstrike) - tracking unstable periodic orbit - visualization tools for animation

14 Maps & dynamical systems Science - bifurcations and chaos in iterated maps - period doubling in logistic map - density (invariant measure) in chaotic regime - Lyapunov exponents: divergence of nearby trajectories - fractal dimensions of attractors - renormalization group of logistic map & universality of period doubling route to chaos Computing - iterating maps - root-finding - fitting

15 Cardiac dynamics Science - pattern formation in excitable medium - FitzHugh-Nagumo model (type of reaction-diffusion equation) - spiral defects forming in electrical pulsing can lead to cardiac arrythmias - model extensions to simulate dead tissue, cardiac chambers, etc. Computing - numerical solution of PDEs finite-differences, operator stencils - nullcline analysis for single cell (rootfinding) - simple animation tool allows interactive steering of simulation (needed to provide targeted electrical pulses and defribrillator shock)

16 Cell dynamics: stochastic cells and Repressilator Science - Repressilator (Elowitz & Leibler): genetic oscillator from realm of synthetic biology oscillatory mrna/protein dynamics from mutually repressing proteins - telegraph noise and shotgun noise in stochastic systems Computing - chemical kinetics and reaction networks Petri nets synthesis of aggregate kinetic equations from network - Monte Carlo algorithms (Gillespie) - stochastic vs. deterministic descriptions Additional projects exploring other gene regulatory networks (switches, feed-forward loops, etc.)

17 NP-completeness & constraint satisfaction Science - NP-complete problems - phase transitions in 3SAT and parametric complexity - integer partitioning problem Computing - algorithms for NP-complete problems - backtracking, recursion

18 Random matrix theory Science - eigenvalue spacings in random matrices - developed originally to describe energy level spacings in quantum systems Computing - random matrix generation - eigenvalue computation (numpy)

19 Molecular dynamics Science - thermodynamics: emergence of effective properties from molecular chaos Computing - design of large software systems - geometric data structures - integration of ODEs - thermodynamics pressure pair distribution functions

20 Ising model Science - phase transitions in simple model of magnetic system nucleation self-similarity fluctuation-dissipation Computing - Monte Carlo algorithms heat bath Metropolis cluster flipping

21 Randomness: random walks & Gumbel distributions Science - ensembles and distributions averages extremal behavior emergent symmetries Computing - random number generation - statistical analysis of ensembles

22 The Python for Science Ecosystem SciPy and NumPy [ - NumPy: provides (in a compiled library) high-level array syntax, linear algebra, random number generation, Fourier transforms - Python interfaces to well-tested compiled numerical routines, interfaced to work with NumPy arrays - provides routines for integration of functions and differential equations, root-finding, minimization, etc. matplotlib (a.k.a. pylab) [matplotlib.org] - provides 2D (x-y) plotting, histograms, etc. (modeled after MATLAB plotting) ipython [ipython.org] - enhancement of the standard python interpreter: command completion & history, magic functions, etc. - notebook mode for integrated programs, documentation, results

23 The Python for Science Ecosystem (continued) Python standard library: pickle, time, os, collections, multiprocessing, string, url lib, xml, json, etc. Python Imaging Library (PIL, Pillow): image processing and analysis scikit-learn: machine learning NetworkX: graph theory and network analysis sympy: symbolic mathematics Pandas: data analysis mpmath: multiple precision mathematics h5py: HDF5 interface (btw, also interface to MATLAB.mat files) SWIG, Cython, weave, theano, : tools for integrating compiled code with interpreted Python code etc.

24 Course mechanics & information Course web page - Module web pages - ComputerExercises - linked from Computer Exercises on course web page Navigation bar on course web page - News & Updates: information about new modules, bug fixes, special projects, etc. - Lecture Notes: copies of in-class lecture slides - Python Resources: tutorials, documentation, guides, etc.

25 Course mechanics: working with modules For a given module: - possibly some background reading (e.g., journal paper) - text describing an exercise (pdf or on web page) read this first! - a Hints file (e.g., SmallWorldHints.py) Hints files have skeletal Python code with comments (docstrings) Hints files have minimal Python code body consisting of keyword pass Copy Hints file to new file (e.g., SmallWorld.py) and then fill in code body to implement desired functionality %run Python code file within IPython notebook to test code, run analyses, make plots, document work, etc.

26 Python installations Encourage use of Anaconda Scientific Python distribution (unless you are already a seasoned Python user with your own setup)! If using your own laptop: Anaconda distribution (free): download & install Python Physics Educational Computing Facility (PECF) - python, ipython, scipy, etc. all installed - add ~myers/anaconda3/bin to beginning of shell path - let me know if packages are missing or broken! Text editors have auxiliary python editing mode: syntax highlighting, indenting, etc. (e.g., python-mode in emacs)

27 Development Environments, Workflows & Interpreters python interpreter ( python ) - bare bones interpreter of Python code - useful to run programs in background/batch once fully developed ipython interpreter ( ipython or ipython qtconsole ) - enhanced Python interpreter with help, autocompletion, editing, etc. - extra functionality ( magics ) outside of Python language - magics prepended by % - %who : list of what variables, functions, etc. defined in namespace - %timeit : provide timing information of specific command ipython notebooks ( ipython notebook ) - graphical interface integrating code, documentation, analyses, plots, etc. (a la Mathematica notebooks)

28 Some new twists this year Python 3 - core numerical code for all the modules has been updated - some of the visualization tools will need to be updated and/or replaced (anyone interested in helping?) Encouraging use of Anaconda python v. 3.4 by everyone IPython notebooks to organize and summarize analyses and results

School of Innovative Technologies and Engineering

School of Innovative Technologies and Engineering School of Innovative Technologies and Engineering Department of Applied Mathematical Sciences Proficiency Course in MATLAB COURSE DOCUMENT VERSION 1.0 PCMv1.0 July 2012 University of Technology, Mauritius

More information

Instructional Approach(s): The teacher should introduce the essential question and the standard that aligns to the essential question

Instructional Approach(s): The teacher should introduce the essential question and the standard that aligns to the essential question 1 Instructional Approach(s): The teacher should introduce the essential question and the standard that aligns to the essential question 2 Instructional Approach(s): The teacher should conduct the Concept

More information

Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence

Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence COURSE DESCRIPTION This course presents computing tools and concepts for all stages

More information

Python Machine Learning

Python Machine Learning Python Machine Learning Unlock deeper insights into machine learning with this vital guide to cuttingedge predictive analytics Sebastian Raschka [ PUBLISHING 1 open source I community experience distilled

More information

Software Maintenance

Software Maintenance 1 What is Software Maintenance? Software Maintenance is a very broad activity that includes error corrections, enhancements of capabilities, deletion of obsolete capabilities, and optimization. 2 Categories

More information

ACTL5103 Stochastic Modelling For Actuaries. Course Outline Semester 2, 2014

ACTL5103 Stochastic Modelling For Actuaries. Course Outline Semester 2, 2014 UNSW Australia Business School School of Risk and Actuarial Studies ACTL5103 Stochastic Modelling For Actuaries Course Outline Semester 2, 2014 Part A: Course-Specific Information Please consult Part B

More information

GACE Computer Science Assessment Test at a Glance

GACE Computer Science Assessment Test at a Glance GACE Computer Science Assessment Test at a Glance Updated May 2017 See the GACE Computer Science Assessment Study Companion for practice questions and preparation resources. Assessment Name Computer Science

More information

EGRHS Course Fair. Science & Math AP & IB Courses

EGRHS Course Fair. Science & Math AP & IB Courses EGRHS Course Fair Science & Math AP & IB Courses Science Courses: AP Physics IB Physics SL IB Physics HL AP Biology IB Biology HL AP Physics Course Description Course Description AP Physics C (Mechanics)

More information

Generative models and adversarial training

Generative models and adversarial training Day 4 Lecture 1 Generative models and adversarial training Kevin McGuinness kevin.mcguinness@dcu.ie Research Fellow Insight Centre for Data Analytics Dublin City University What is a generative model?

More information

Radius STEM Readiness TM

Radius STEM Readiness TM Curriculum Guide Radius STEM Readiness TM While today s teens are surrounded by technology, we face a stark and imminent shortage of graduates pursuing careers in Science, Technology, Engineering, and

More information

Statewide Framework Document for:

Statewide Framework Document for: Statewide Framework Document for: 270301 Standards may be added to this document prior to submission, but may not be removed from the framework to meet state credit equivalency requirements. Performance

More information

Probability and Statistics Curriculum Pacing Guide

Probability and Statistics Curriculum Pacing Guide Unit 1 Terms PS.SPMJ.3 PS.SPMJ.5 Plan and conduct a survey to answer a statistical question. Recognize how the plan addresses sampling technique, randomization, measurement of experimental error and methods

More information

Designing a Computer to Play Nim: A Mini-Capstone Project in Digital Design I

Designing a Computer to Play Nim: A Mini-Capstone Project in Digital Design I Session 1793 Designing a Computer to Play Nim: A Mini-Capstone Project in Digital Design I John Greco, Ph.D. Department of Electrical and Computer Engineering Lafayette College Easton, PA 18042 Abstract

More information

University of Illinois

University of Illinois Overview At The Frederick Seitz Materials Research Laboratory NSF-supported FRG P.I. R. Martin (Physics) and D.D. Johnson(MatSE, Physics) Develop infrastructure to support and foster advances in multidisciplinary

More information

GRADUATE STUDENT HANDBOOK Master of Science Programs in Biostatistics

GRADUATE STUDENT HANDBOOK Master of Science Programs in Biostatistics 2017-2018 GRADUATE STUDENT HANDBOOK Master of Science Programs in Biostatistics Entrance requirements, program descriptions, degree requirements and other program policies for Biostatistics Master s Programs

More information

Biology 1 General Biology, Lecture Sections: 47231, and Fall 2017

Biology 1 General Biology, Lecture Sections: 47231, and Fall 2017 Instructor: Rana Tayyar, Ph.D. Email: rana.tayyar@rcc.edu Website: http://websites.rcc.edu/tayyar/ Office: MTSC 320 Class Location: MTSC 401 Lecture time: Tuesday and Thursday: 2:00-3:25 PM Biology 1 General

More information

Ansys Tutorial Random Vibration

Ansys Tutorial Random Vibration Ansys Tutorial Random Free PDF ebook Download: Ansys Tutorial Download or Read Online ebook ansys tutorial random vibration in PDF Format From The Best User Guide Database Random vibration analysis gives

More information

Seminar - Organic Computing

Seminar - Organic Computing Seminar - Organic Computing Self-Organisation of OC-Systems Markus Franke 25.01.2006 Typeset by FoilTEX Timetable 1. Overview 2. Characteristics of SO-Systems 3. Concern with Nature 4. Design-Concepts

More information

Physics 270: Experimental Physics

Physics 270: Experimental Physics 2017 edition Lab Manual Physics 270 3 Physics 270: Experimental Physics Lecture: Lab: Instructor: Office: Email: Tuesdays, 2 3:50 PM Thursdays, 2 4:50 PM Dr. Uttam Manna 313C Moulton Hall umanna@ilstu.edu

More information

Grade 6: Correlated to AGS Basic Math Skills

Grade 6: Correlated to AGS Basic Math Skills Grade 6: Correlated to AGS Basic Math Skills Grade 6: Standard 1 Number Sense Students compare and order positive and negative integers, decimals, fractions, and mixed numbers. They find multiples and

More information

INTERMEDIATE ALGEBRA PRODUCT GUIDE

INTERMEDIATE ALGEBRA PRODUCT GUIDE Welcome Thank you for choosing Intermediate Algebra. This adaptive digital curriculum provides students with instruction and practice in advanced algebraic concepts, including rational, radical, and logarithmic

More information

Mathematics. Mathematics

Mathematics. Mathematics Mathematics Program Description Successful completion of this major will assure competence in mathematics through differential and integral calculus, providing an adequate background for employment in

More information

Math 121 Fundamentals of Mathematics I

Math 121 Fundamentals of Mathematics I I. Course Description: Math 121 Fundamentals of Mathematics I Math 121 is a general course in the fundamentals of mathematics. It includes a study of concepts of numbers and fundamental operations with

More information

The Moodle and joule 2 Teacher Toolkit

The Moodle and joule 2 Teacher Toolkit The Moodle and joule 2 Teacher Toolkit Moodlerooms Learning Solutions The design and development of Moodle and joule continues to be guided by social constructionist pedagogy. This refers to the idea that

More information

Shockwheat. Statistics 1, Activity 1

Shockwheat. Statistics 1, Activity 1 Statistics 1, Activity 1 Shockwheat Students require real experiences with situations involving data and with situations involving chance. They will best learn about these concepts on an intuitive or informal

More information

CS Machine Learning

CS Machine Learning CS 478 - Machine Learning Projects Data Representation Basic testing and evaluation schemes CS 478 Data and Testing 1 Programming Issues l Program in any platform you want l Realize that you will be doing

More information

A Neural Network GUI Tested on Text-To-Phoneme Mapping

A Neural Network GUI Tested on Text-To-Phoneme Mapping A Neural Network GUI Tested on Text-To-Phoneme Mapping MAARTEN TROMPPER Universiteit Utrecht m.f.a.trompper@students.uu.nl Abstract Text-to-phoneme (T2P) mapping is a necessary step in any speech synthesis

More information

Biology Keystone Questions And Answers

Biology Keystone Questions And Answers Questions And Answers Free PDF ebook Download: Questions And Answers Download or Read Online ebook biology keystone questions and answers in PDF Format From The Best User Guide Database Biology. Literature.

More information

ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF

ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF Read Online and Download Ebook ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY DOWNLOAD EBOOK : ADVANCED MACHINE LEARNING WITH PYTHON BY JOHN HEARTY PDF Click link bellow and free register to download

More information

While you are waiting... socrative.com, room number SIMLANG2016

While you are waiting... socrative.com, room number SIMLANG2016 While you are waiting... socrative.com, room number SIMLANG2016 Simulating Language Lecture 4: When will optimal signalling evolve? Simon Kirby simon@ling.ed.ac.uk T H E U N I V E R S I T Y O H F R G E

More information

Timeline. Recommendations

Timeline. Recommendations Introduction Advanced Placement Course Credit Alignment Recommendations In 2007, the State of Ohio Legislature passed legislation mandating the Board of Regents to recommend and the Chancellor to adopt

More information

Using Virtual Manipulatives to Support Teaching and Learning Mathematics

Using Virtual Manipulatives to Support Teaching and Learning Mathematics Using Virtual Manipulatives to Support Teaching and Learning Mathematics Joel Duffin Abstract The National Library of Virtual Manipulatives (NLVM) is a free website containing over 110 interactive online

More information

Control Tutorials for MATLAB and Simulink

Control Tutorials for MATLAB and Simulink Control Tutorials for MATLAB and Simulink Last updated: 07/24/2014 Author Information Prof. Bill Messner Carnegie Mellon University Prof. Dawn Tilbury University of Michigan Asst. Prof. Rick Hill, PhD

More information

WSU Five-Year Program Review Self-Study Cover Page

WSU Five-Year Program Review Self-Study Cover Page WSU Five-Year Program Review Self-Study Cover Page Department: Program: Computer Science Computer Science AS/BS Semester Submitted: Spring 2012 Self-Study Team Chair: External to the University but within

More information

ME 4495 Computational Heat Transfer and Fluid Flow M,W 4:00 5:15 (Eng 177)

ME 4495 Computational Heat Transfer and Fluid Flow M,W 4:00 5:15 (Eng 177) ME 4495 Computational Heat Transfer and Fluid Flow M,W 4:00 5:15 (Eng 177) Professor: Daniel N. Pope, Ph.D. E-mail: dpope@d.umn.edu Office: VKH 113 Phone: 726-6685 Office Hours:, Tues,, Fri 2:00-3:00 (or

More information

Introduction to Simulation

Introduction to Simulation Introduction to Simulation Spring 2010 Dr. Louis Luangkesorn University of Pittsburgh January 19, 2010 Dr. Louis Luangkesorn ( University of Pittsburgh ) Introduction to Simulation January 19, 2010 1 /

More information

What can I learn from worms?

What can I learn from worms? What can I learn from worms? Stem cells, regeneration, and models Lesson 7: What does planarian regeneration tell us about human regeneration? I. Overview In this lesson, students use the information that

More information

UNIT ONE Tools of Algebra

UNIT ONE Tools of Algebra UNIT ONE Tools of Algebra Subject: Algebra 1 Grade: 9 th 10 th Standards and Benchmarks: 1 a, b,e; 3 a, b; 4 a, b; Overview My Lessons are following the first unit from Prentice Hall Algebra 1 1. Students

More information

Bachelor of Science in Mechanical Engineering with Co-op

Bachelor of Science in Mechanical Engineering with Co-op Bachelor of Science in Mechanical Engineering with Co-op 1 Bachelor of Science in Mechanical Engineering with Co-op Cooperative Education Program A Cooperative Education (Co-Op) is an optional program

More information

Spring 2015 IET4451 Systems Simulation Course Syllabus for Traditional, Hybrid, and Online Classes

Spring 2015 IET4451 Systems Simulation Course Syllabus for Traditional, Hybrid, and Online Classes Spring 2015 IET4451 Systems Simulation Course Syllabus for Traditional, Hybrid, and Online Classes Instructor: Dr. Gregory L. Wiles Email Address: Use D2L e-mail, or secondly gwiles@spsu.edu Office: M

More information

ENME 605 Advanced Control Systems, Fall 2015 Department of Mechanical Engineering

ENME 605 Advanced Control Systems, Fall 2015 Department of Mechanical Engineering ENME 605 Advanced Control Systems, Fall 2015 Department of Mechanical Engineering Lecture Details Instructor Course Objectives Tuesday and Thursday, 4:00 pm to 5:15 pm Information Technology and Engineering

More information

Physics XL 6B Reg# # Units: 5. Office Hour: Tuesday 5 pm to 7:30 pm; Wednesday 5 pm to 6:15 pm

Physics XL 6B Reg# # Units: 5. Office Hour: Tuesday 5 pm to 7:30 pm; Wednesday 5 pm to 6:15 pm Physics XL 6B Reg# 264138 # Units: 5 Department of Humanities & Sciences (310) 825-7093 Quarter:_Spring 2016 Instructor: Jacqueline Pau Dates: 03/30/16 06/15/16 Lectures: 1434A PAB, Wednesday (6:30-10pm)

More information

CS 1103 Computer Science I Honors. Fall Instructor Muller. Syllabus

CS 1103 Computer Science I Honors. Fall Instructor Muller. Syllabus CS 1103 Computer Science I Honors Fall 2016 Instructor Muller Syllabus Welcome to CS1103. This course is an introduction to the art and science of computer programming and to some of the fundamental concepts

More information

Number Line Moves Dash -- 1st Grade. Michelle Eckstein

Number Line Moves Dash -- 1st Grade. Michelle Eckstein Number Line Moves Dash -- 1st Grade Michelle Eckstein Common Core Standards CCSS.MATH.CONTENT.1.NBT.C.4 Add within 100, including adding a two-digit number and a one-digit number, and adding a two-digit

More information

Circuit Simulators: A Revolutionary E-Learning Platform

Circuit Simulators: A Revolutionary E-Learning Platform Circuit Simulators: A Revolutionary E-Learning Platform Mahi Itagi Padre Conceicao College of Engineering, Verna, Goa, India. itagimahi@gmail.com Akhil Deshpande Gogte Institute of Technology, Udyambag,

More information

A Reinforcement Learning Variant for Control Scheduling

A Reinforcement Learning Variant for Control Scheduling A Reinforcement Learning Variant for Control Scheduling Aloke Guha Honeywell Sensor and System Development Center 3660 Technology Drive Minneapolis MN 55417 Abstract We present an algorithm based on reinforcement

More information

DIGITAL GAMING & INTERACTIVE MEDIA BACHELOR S DEGREE. Junior Year. Summer (Bridge Quarter) Fall Winter Spring GAME Credits.

DIGITAL GAMING & INTERACTIVE MEDIA BACHELOR S DEGREE. Junior Year. Summer (Bridge Quarter) Fall Winter Spring GAME Credits. DIGITAL GAMING & INTERACTIVE MEDIA BACHELOR S DEGREE Sample 2-Year Academic Plan DRAFT Junior Year Summer (Bridge Quarter) Fall Winter Spring MMDP/GAME 124 GAME 310 GAME 318 GAME 330 Introduction to Maya

More information

Algebra 1, Quarter 3, Unit 3.1. Line of Best Fit. Overview

Algebra 1, Quarter 3, Unit 3.1. Line of Best Fit. Overview Algebra 1, Quarter 3, Unit 3.1 Line of Best Fit Overview Number of instructional days 6 (1 day assessment) (1 day = 45 minutes) Content to be learned Analyze scatter plots and construct the line of best

More information

Multimedia Application Effective Support of Education

Multimedia Application Effective Support of Education Multimedia Application Effective Support of Education Eva Milková Faculty of Science, University od Hradec Králové, Hradec Králové, Czech Republic eva.mikova@uhk.cz Abstract Multimedia applications have

More information

Dublin City Schools Mathematics Graded Course of Study GRADE 4

Dublin City Schools Mathematics Graded Course of Study GRADE 4 I. Content Standard: Number, Number Sense and Operations Standard Students demonstrate number sense, including an understanding of number systems and reasonable estimates using paper and pencil, technology-supported

More information

LEGO MINDSTORMS Education EV3 Coding Activities

LEGO MINDSTORMS Education EV3 Coding Activities LEGO MINDSTORMS Education EV3 Coding Activities s t e e h s k r o W t n e d Stu LEGOeducation.com/MINDSTORMS Contents ACTIVITY 1 Performing a Three Point Turn 3-6 ACTIVITY 2 Written Instructions for a

More information

EECS 700: Computer Modeling, Simulation, and Visualization Fall 2014

EECS 700: Computer Modeling, Simulation, and Visualization Fall 2014 EECS 700: Computer Modeling, Simulation, and Visualization Fall 2014 Course Description The goals of this course are to: (1) formulate a mathematical model describing a physical phenomenon; (2) to discretize

More information

Natural Sciences, B.S.

Natural Sciences, B.S. Natural Sciences, B.S. 1 Natural Sciences, B.S. The Bachelor of Science (B.S.) in Natural Sciences provides students more breadth than traditional science programs. Many exciting areas of scientific inquiry,

More information

Integrating simulation into the engineering curriculum: a case study

Integrating simulation into the engineering curriculum: a case study Integrating simulation into the engineering curriculum: a case study Baidurja Ray and Rajesh Bhaskaran Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA E-mail:

More information

Mathematics subject curriculum

Mathematics subject curriculum Mathematics subject curriculum Dette er ei omsetjing av den fastsette læreplanteksten. Læreplanen er fastsett på Nynorsk Established as a Regulation by the Ministry of Education and Research on 24 June

More information

SAT MATH PREP:

SAT MATH PREP: SAT MATH PREP: 2015-2016 NOTE: The College Board has redesigned the SAT Test. This new test will start in March of 2016. Also, the PSAT test given in October of 2015 will have the new format. Therefore

More information

Honors Mathematics. Introduction and Definition of Honors Mathematics

Honors Mathematics. Introduction and Definition of Honors Mathematics Honors Mathematics Introduction and Definition of Honors Mathematics Honors Mathematics courses are intended to be more challenging than standard courses and provide multiple opportunities for students

More information

Introduction to Causal Inference. Problem Set 1. Required Problems

Introduction to Causal Inference. Problem Set 1. Required Problems Introduction to Causal Inference Problem Set 1 Professor: Teppei Yamamoto Due Friday, July 15 (at beginning of class) Only the required problems are due on the above date. The optional problems will not

More information

University of Groningen. Systemen, planning, netwerken Bosman, Aart

University of Groningen. Systemen, planning, netwerken Bosman, Aart University of Groningen Systemen, planning, netwerken Bosman, Aart IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document

More information

We are strong in research and particularly noted in software engineering, information security and privacy, and humane gaming.

We are strong in research and particularly noted in software engineering, information security and privacy, and humane gaming. Computer Science 1 COMPUTER SCIENCE Office: Department of Computer Science, ECS, Suite 379 Mail Code: 2155 E Wesley Avenue, Denver, CO 80208 Phone: 303-871-2458 Email: info@cs.du.edu Web Site: Computer

More information

Operational Knowledge Management: a way to manage competence

Operational Knowledge Management: a way to manage competence Operational Knowledge Management: a way to manage competence Giulio Valente Dipartimento di Informatica Universita di Torino Torino (ITALY) e-mail: valenteg@di.unito.it Alessandro Rigallo Telecom Italia

More information

CS 101 Computer Science I Fall Instructor Muller. Syllabus

CS 101 Computer Science I Fall Instructor Muller. Syllabus CS 101 Computer Science I Fall 2013 Instructor Muller Syllabus Welcome to CS101. This course is an introduction to the art and science of computer programming and to some of the fundamental concepts of

More information

Notes on The Sciences of the Artificial Adapted from a shorter document written for course (Deciding What to Design) 1

Notes on The Sciences of the Artificial Adapted from a shorter document written for course (Deciding What to Design) 1 Notes on The Sciences of the Artificial Adapted from a shorter document written for course 17-652 (Deciding What to Design) 1 Ali Almossawi December 29, 2005 1 Introduction The Sciences of the Artificial

More information

Xinyu Tang. Education. Research Interests. Honors and Awards. Professional Experience

Xinyu Tang. Education. Research Interests. Honors and Awards. Professional Experience Xinyu Tang Parasol Laboratory Department of Computer Science Texas A&M University, TAMU 3112 College Station, TX 77843-3112 phone:(979)847-8835 fax: (979)458-0425 email: xinyut@tamu.edu url: http://parasol.tamu.edu/people/xinyut

More information

Foothill College Fall 2014 Math My Way Math 230/235 MTWThF 10:00-11:50 (click on Math My Way tab) Math My Way Instructors:

Foothill College Fall 2014 Math My Way Math 230/235 MTWThF 10:00-11:50  (click on Math My Way tab) Math My Way Instructors: This is a team taught directed study course. Foothill College Fall 2014 Math My Way Math 230/235 MTWThF 10:00-11:50 www.psme.foothill.edu (click on Math My Way tab) Math My Way Instructors: Instructor:

More information

Proposal of a PhD Programme (PhD) managed by the Politecnico di Milano. PhD in: STRUCTURAL, SEISMIC AND GEOTECHNICAL ENGINEERING CYCLE: XXVIII

Proposal of a PhD Programme (PhD) managed by the Politecnico di Milano. PhD in: STRUCTURAL, SEISMIC AND GEOTECHNICAL ENGINEERING CYCLE: XXVIII Proposal of a PhD Programme (PhD) managed by the Politecnico di Milano PhD in: STRUCTURAL, SEISMIC AND GEOTECHNICAL ENGINEERING CYCLE: XXVIII TYPE OF ACTIVATION PROPOSAL: A.) Re-proposal of a PhD already

More information

Physical Versus Virtual Manipulatives Mathematics

Physical Versus Virtual Manipulatives Mathematics Physical Versus Free PDF ebook Download: Physical Versus Download or Read Online ebook physical versus virtual manipulatives mathematics in PDF Format From The Best User Guide Database Engineering Haptic

More information

B.S/M.A in Mathematics

B.S/M.A in Mathematics B.S/M.A in Mathematics The dual Bachelor of Science/Master of Arts in Mathematics program provides an opportunity for individuals to pursue advanced study in mathematics and to develop skills that can

More information

Fourth Grade. Reporting Student Progress. Libertyville School District 70. Fourth Grade

Fourth Grade. Reporting Student Progress. Libertyville School District 70. Fourth Grade Fourth Grade Libertyville School District 70 Reporting Student Progress Fourth Grade A Message to Parents/Guardians: Libertyville Elementary District 70 teachers of students in kindergarten-5 utilize a

More information

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur

Module 12. Machine Learning. Version 2 CSE IIT, Kharagpur Module 12 Machine Learning 12.1 Instructional Objective The students should understand the concept of learning systems Students should learn about different aspects of a learning system Students should

More information

AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS

AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS AGS THE GREAT REVIEW GAME FOR PRE-ALGEBRA (CD) CORRELATED TO CALIFORNIA CONTENT STANDARDS 1 CALIFORNIA CONTENT STANDARDS: Chapter 1 ALGEBRA AND WHOLE NUMBERS Algebra and Functions 1.4 Students use algebraic

More information

MTH 141 Calculus 1 Syllabus Spring 2017

MTH 141 Calculus 1 Syllabus Spring 2017 Instructor: Section/Meets Office Hrs: Textbook: Calculus: Single Variable, by Hughes-Hallet et al, 6th ed., Wiley. Also needed: access code to WileyPlus (included in new books) Calculator: Not required,

More information

STA 225: Introductory Statistics (CT)

STA 225: Introductory Statistics (CT) Marshall University College of Science Mathematics Department STA 225: Introductory Statistics (CT) Course catalog description A critical thinking course in applied statistical reasoning covering basic

More information

ME 443/643 Design Techniques in Mechanical Engineering. Lecture 1: Introduction

ME 443/643 Design Techniques in Mechanical Engineering. Lecture 1: Introduction ME 443/643 Design Techniques in Mechanical Engineering Lecture 1: Introduction Instructor: Dr. Jagadeep Thota Instructor Introduction Born in Bangalore, India. B.S. in ME @ Bangalore University, India.

More information

Course Content Concepts

Course Content Concepts CS 1371 SYLLABUS, Fall, 2017 Revised 8/6/17 Computing for Engineers Course Content Concepts The students will be expected to be familiar with the following concepts, either by writing code to solve problems,

More information

South Carolina College- and Career-Ready Standards for Mathematics. Standards Unpacking Documents Grade 5

South Carolina College- and Career-Ready Standards for Mathematics. Standards Unpacking Documents Grade 5 South Carolina College- and Career-Ready Standards for Mathematics Standards Unpacking Documents Grade 5 South Carolina College- and Career-Ready Standards for Mathematics Standards Unpacking Documents

More information

Answers To Hawkes Learning Systems Intermediate Algebra

Answers To Hawkes Learning Systems Intermediate Algebra Answers To Hawkes Learning Free PDF ebook Download: Answers To Download or Read Online ebook answers to hawkes learning systems intermediate algebra in PDF Format From The Best User Guide Database Double

More information

Rover Races Grades: 3-5 Prep Time: ~45 Minutes Lesson Time: ~105 minutes

Rover Races Grades: 3-5 Prep Time: ~45 Minutes Lesson Time: ~105 minutes Rover Races Grades: 3-5 Prep Time: ~45 Minutes Lesson Time: ~105 minutes WHAT STUDENTS DO: Establishing Communication Procedures Following Curiosity on Mars often means roving to places with interesting

More information

COMPUTER-ASSISTED INDEPENDENT STUDY IN MULTIVARIATE CALCULUS

COMPUTER-ASSISTED INDEPENDENT STUDY IN MULTIVARIATE CALCULUS COMPUTER-ASSISTED INDEPENDENT STUDY IN MULTIVARIATE CALCULUS L. Descalço 1, Paula Carvalho 1, J.P. Cruz 1, Paula Oliveira 1, Dina Seabra 2 1 Departamento de Matemática, Universidade de Aveiro (PORTUGAL)

More information

ICTCM 28th International Conference on Technology in Collegiate Mathematics

ICTCM 28th International Conference on Technology in Collegiate Mathematics DEVELOPING DIGITAL LITERACY IN THE CALCULUS SEQUENCE Dr. Jeremy Brazas Georgia State University Department of Mathematics and Statistics 30 Pryor Street Atlanta, GA 30303 jbrazas@gsu.edu Dr. Todd Abel

More information

LOUISIANA HIGH SCHOOL RALLY ASSOCIATION

LOUISIANA HIGH SCHOOL RALLY ASSOCIATION LOUISIANA HIGH SCHOOL RALLY ASSOCIATION Literary Events 2014-15 General Information There are 44 literary events in which District and State Rally qualifiers compete. District and State Rally tests are

More information

Biology and Microbiology

Biology and Microbiology November 14, 2006 California State University (CSU) Statewide Pattern The Lower-Division Transfer Pattern (LDTP) consists of the CSU statewide pattern of coursework outlined below, plus campus-specific

More information

On-Line Data Analytics

On-Line Data Analytics International Journal of Computer Applications in Engineering Sciences [VOL I, ISSUE III, SEPTEMBER 2011] [ISSN: 2231-4946] On-Line Data Analytics Yugandhar Vemulapalli #, Devarapalli Raghu *, Raja Jacob

More information

SELECCIÓN DE CURSOS CAMPUS CIUDAD DE MÉXICO. Instructions for Course Selection

SELECCIÓN DE CURSOS CAMPUS CIUDAD DE MÉXICO. Instructions for Course Selection Instructions for Course Selection INSTRUCTIONS FOR COURSE SELECTION 1. Open the following link: https://prd28pi01.itesm.mx/recepcion/studyinmexico?ln=en 2. Click on the buttom: continue 3. Choose your

More information

Navigating the PhD Options in CMS

Navigating the PhD Options in CMS Navigating the PhD Options in CMS This document gives an overview of the typical student path through the four Ph.D. programs in the CMS department ACM, CDS, CS, and CMS. Note that it is not a replacement

More information

Automating the E-learning Personalization

Automating the E-learning Personalization Automating the E-learning Personalization Fathi Essalmi 1, Leila Jemni Ben Ayed 1, Mohamed Jemni 1, Kinshuk 2, and Sabine Graf 2 1 The Research Laboratory of Technologies of Information and Communication

More information

Introduction and Motivation

Introduction and Motivation 1 Introduction and Motivation Mathematical discoveries, small or great are never born of spontaneous generation. They always presuppose a soil seeded with preliminary knowledge and well prepared by labour,

More information

Mathematics 112 Phone: (580) Southeastern Oklahoma State University Web: Durant, OK USA

Mathematics 112 Phone: (580) Southeastern Oklahoma State University Web:  Durant, OK USA Karl H. Frinkle Contact Information Research Interests Education Mathematics 112 Phone: (580) 745-2028 Department of Mathematics E-mail: kfrinkle@se.edu Southeastern Oklahoma State University Web: http://homepages.se.edu/kfrinkle/

More information

EDIT 576 DL1 (2 credits) Mobile Learning and Applications Fall Semester 2014 August 25 October 12, 2014 Fully Online Course

EDIT 576 DL1 (2 credits) Mobile Learning and Applications Fall Semester 2014 August 25 October 12, 2014 Fully Online Course GEORGE MASON UNIVERSITY COLLEGE OF EDUCATION AND HUMAN DEVELOPMENT GRADUATE SCHOOL OF EDUCATION INSTRUCTIONAL DESIGN AND TECHNOLOGY PROGRAM EDIT 576 DL1 (2 credits) Mobile Learning and Applications Fall

More information

EECS 571 PRINCIPLES OF REAL-TIME COMPUTING Fall 10. Instructor: Kang G. Shin, 4605 CSE, ;

EECS 571 PRINCIPLES OF REAL-TIME COMPUTING Fall 10. Instructor: Kang G. Shin, 4605 CSE, ; EECS 571 PRINCIPLES OF REAL-TIME COMPUTING Fall 10 Instructor: Kang G. Shin, 4605 CSE, 763-0391; kgshin@umich.edu Number of credit hours: 4 Class meeting time and room: Regular classes: MW 10:30am noon

More information

DOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME

DOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME The following resources are currently available: DOCTORAL SCHOOL TRAINING AND DEVELOPMENT PROGRAMME 2016-17 What is the Doctoral School? The main purpose of the Doctoral School is to enhance your experience

More information

Analysis of Emotion Recognition System through Speech Signal Using KNN & GMM Classifier

Analysis of Emotion Recognition System through Speech Signal Using KNN & GMM Classifier IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-issn: 2278-2834,p- ISSN: 2278-8735.Volume 10, Issue 2, Ver.1 (Mar - Apr.2015), PP 55-61 www.iosrjournals.org Analysis of Emotion

More information

Bittinger, M. L., Ellenbogen, D. J., & Johnson, B. L. (2012). Prealgebra (6th ed.). Boston, MA: Addison-Wesley.

Bittinger, M. L., Ellenbogen, D. J., & Johnson, B. L. (2012). Prealgebra (6th ed.). Boston, MA: Addison-Wesley. Course Syllabus Course Description Explores the basic fundamentals of college-level mathematics. (Note: This course is for institutional credit only and will not be used in meeting degree requirements.

More information

Application of Virtual Instruments (VIs) for an enhanced learning environment

Application of Virtual Instruments (VIs) for an enhanced learning environment Application of Virtual Instruments (VIs) for an enhanced learning environment Philip Smyth, Dermot Brabazon, Eilish McLoughlin Schools of Mechanical and Physical Sciences Dublin City University Ireland

More information

Green Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants)

Green Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants) Green Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants) Notes: 1. We use Mini-Tab in this workshop. Mini-tab is available for free trail

More information

Montana Content Standards for Mathematics Grade 3. Montana Content Standards for Mathematical Practices and Mathematics Content Adopted November 2011

Montana Content Standards for Mathematics Grade 3. Montana Content Standards for Mathematical Practices and Mathematics Content Adopted November 2011 Montana Content Standards for Mathematics Grade 3 Montana Content Standards for Mathematical Practices and Mathematics Content Adopted November 2011 Contents Standards for Mathematical Practice: Grade

More information

Predicting Students Performance with SimStudent: Learning Cognitive Skills from Observation

Predicting Students Performance with SimStudent: Learning Cognitive Skills from Observation School of Computer Science Human-Computer Interaction Institute Carnegie Mellon University Year 2007 Predicting Students Performance with SimStudent: Learning Cognitive Skills from Observation Noboru Matsuda

More information

An Introduction to Simio for Beginners

An Introduction to Simio for Beginners An Introduction to Simio for Beginners C. Dennis Pegden, Ph.D. This white paper is intended to introduce Simio to a user new to simulation. It is intended for the manufacturing engineer, hospital quality

More information

PRODUCT COMPLEXITY: A NEW MODELLING COURSE IN THE INDUSTRIAL DESIGN PROGRAM AT THE UNIVERSITY OF TWENTE

PRODUCT COMPLEXITY: A NEW MODELLING COURSE IN THE INDUSTRIAL DESIGN PROGRAM AT THE UNIVERSITY OF TWENTE INTERNATIONAL CONFERENCE ON ENGINEERING AND PRODUCT DESIGN EDUCATION 6 & 7 SEPTEMBER 2012, ARTESIS UNIVERSITY COLLEGE, ANTWERP, BELGIUM PRODUCT COMPLEXITY: A NEW MODELLING COURSE IN THE INDUSTRIAL DESIGN

More information

BMBF Project ROBUKOM: Robust Communication Networks

BMBF Project ROBUKOM: Robust Communication Networks BMBF Project ROBUKOM: Robust Communication Networks Arie M.C.A. Koster Christoph Helmberg Andreas Bley Martin Grötschel Thomas Bauschert supported by BMBF grant 03MS616A: ROBUKOM Robust Communication Networks,

More information