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East Los Angeles College - APS - 323
Big Businesses: Honey Bee Colonies and Oil CompaniesFrancis. L. W. Ratnieks Laboratory of Apiculture & Social Insects, Department of Animal & Plant Sciences University of Sheffield In research it is important to focus on clearly defined and often na
East Los Angeles College - APS - 209
APS 209 Animal BehaviourLecture 11 The Evolution of Reproductive Behaviour1. Evolutionary origin of two sexes 2. Typical sex roles 3. Reversed sex roles 4. Male-male competition 5. Female choiceAims & ObjectivesAims 1. Present a simple model fo
East Los Angeles College - APS - 209
APS 209 Animal BehaviourAPS209: Lecture 11. The Evolution of Reproductive Behaviour (Alcock Chapter 10)Aims 1. Present a simple model for the evolution of male (small gamete) and female (large gamete) roles. 2. How sex differences in parental inve
East Los Angeles College - APS - 323
APS 323, Social Insects, Lecture 7 Kin value: relatedness, reproductive value, mating success Aims 1. To show where regression relatedness, sex-specific reproductive value, and sex-specific mating success come from and how they affect the efficiency
Findlay - NR - 10458
The Oiler OneCard What's Next?Welcome to The University of Findlay. As you may have already heard, the Oiler OneCard is how it's done at Findlay! From receiving your financial aid refunds to purchasing course materials, it's your key to success at T
East Los Angeles College - APS - 209
APS 209 Animal BehaviourAPS209: Lecture 10 The Evolution of Communication (Alcock Chapter 9) Aims 1. Present examples of honest communication in animals. 2. Describe the logic in how natural selection can favour honest communication. 3. Present a d
East Los Angeles College - APS - 209
APS 209 Animal BehaviourMathematical and theoretical insights in animal behaviourAims 1. To introduce the use of simple mathematics in the study of animal behaviour. 2. To show how to combine mathematics with biology. Objectives 1. Understand the
East Los Angeles College - APS - 209
APS 209 Animal BehaviourAPS209: Lecture 9 The Evolution of Feeding Behaviour (Alcock Chapter 7)Aims 1. To describe how animals may help each other in foraging, particularly by sharing information. 2. To present a special reading that builds on the
East Los Angeles College - APS - 209
APS 209 Animal BehaviourAPS209: Lecture 4. The Development of Behaviour: A Focus on EnvironmentAims 1. To show how behaviour can be flexibly adjusted according to environmental conditions; behavioural switches. 2. To show how behavioural developme
East Los Angeles College - APS - 323
APS 323, Social Insects, Aims, Objectives and Other Information 2007APS 323 Social InsectsCourse coordinator, lecturer and times coordinator Professor Francis L. W. Ratnieks e-mail: F.Ratnieks@Sheffield.ac.uk; web site: www.lasi.group.shef.ac.uk;
East Los Angeles College - APS - 301
APS 301, Section taught by Professor Ratnieks, lecture 2A simple model investigating equilibrium levels of PSR in Nasonia vitripennisAims 1. To show how a simple mathematical model of a biological process can be constructed. 2. To model the transf
East Los Angeles College - APS - 323
Title Comic Sans MS Bold 16 pointText Comic Sans MS 10 point. 4-6 paragraphs x x x xx x x x Text Comic Sans MS 10 point x x x x x x Did You Know? 3-4 examples. Comic Sans MS Bold 10 point* text Comic Sans MS 9 point. 1-3 lines each. xx * xxx * xx
East Los Angeles College - APS - 209
APS 209 Animal BehaviourThe Sometimes Counter-Intuitive Darwinian Logic of how Natural Selection Acts on Behaviour (Alcock Chapter 1)Special readings: Andrade 1996; Crudgington & Siva-Jothy 2000; Young & Clutton-Brock 2006) Aims 1. To present the
McGill - MATH - 523
Faculty of Science FINAL EXAMINATION MATH-523B Generalized Linear ModelsExaminer: Professor K.J. Worsley Associate Examiner: Professor A. Vandal Date: Tuesday, April 20, 2004 Time: 14:00 - 17:00 hoursINSTRUCTIONS: Answer all questions. Any books,
Wilfrid Laurier - ENCI - 579
Highway Materials, Soils, and Concrete Aggregates Soil Definition (Engineering) "refers to all unconsolidated material in the earth's crust, all material above the bedrock" mineral particles (gravel, sand, silt, clay) organic material (top soil,
Sveriges lantbruksuniversitet - ENSC - 805
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 45, NO. 5, JULY 19991639the average frequency distributionHavg (s):= (1=N )NThe behavior of the distributions for different values of K is discussed in Fig. 4. For M = 9 and K = 12; 16; 20; 24
East Los Angeles College - PHY - 112
PHY112 - Introductory mathematics for physicists and astronomersUnit 2: Functions and Dierentiation Tutorial - week 5, October 2008Neat solutions to questions 1) 8) should be handed in at the beginning of the tutorial. They will be assessed. You
East Los Angeles College - PHY - 112
PHY112 - Introductory mathematics for physicists and astronomersUnit 5: Dierential equations Tutorial - week 11, December 2008Neat solutions to questions 1) 5) should be handed in at the beginning of the tutorial. They will be assessed. You should
Sveriges lantbruksuniversitet - ENSC - 805
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 43, NO. 1, JANUARY 1997275CorrespondenceReduced Complexity Sequence Detection for Nonminimum Phase Intersymbol Interference ChannelsKrishna Balachandran, Srudent Member, IEEE, and John B. Anderson,
Sveriges lantbruksuniversitet - ENSC - 805
~IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 41, NO. 5, SEPTEMBER 19951265Decomposition of Mary CPM Signals into PAM WaveformsUmberto Mengali, Fellow, IEEE, and Michele MorelliAbstract-It is widely known that minimum shift keying (MSK) may
Sveriges lantbruksuniversitet - ENSC - 805
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 48, NO. 8, AUGUST 20022201Closest Point Search in LatticesErik Agrell, Member, IEEE, Thomas Eriksson, Member, IEEE, Alexander Vardy, Fellow, IEEE, and Kenneth Zeger, Fellow, IEEEAbstract-In this se
McGill - MATH - 556
MATH 556 - EXERCISES 5: SOLUTIONS1 Key is to find the i.i.d random variables X1 , ., Xn such thatnX=i=1Xiand then to use the Central Limit Theorem result for large nnZn =i=1Xi - n d - Z N ormal(0, 1) n 2nX=i=1Xi AN (n, n 2
Sveriges lantbruksuniversitet - ENSC - 805
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 45, NO. 5, JULY 19991361Multilevel Codes: Theoretical Concepts and Practical Design RulesUdo Wachsmann, Member, IEEE, Robert F. H. Fischer, Member, IEEE, and Johannes B. Huber, Member, IEEEAbstract-
Sveriges lantbruksuniversitet - ENSC - 805
1152IEEE TRANSACTIONSON INFORMATIONTHEORY, VOL.34, NO. 5, SEPTEMBER 1988Coset Codes-Part 11: Binary Lattices and Related CodesG. DAVID FORNEY, JR., FELLOW, IEEEInvited PaperAbstract -The family of Barnes-Wall lattices (including D4 and E,)
McGill - MATH - 556
556: M ATHEMATICAL S TATISTICS IS OME NOTES ON C HARACTERISTIC F UNCTIONS The characteristic function for a random variable X with pmf/pdf fX is dened for t R as CX (t) = EfX [eitX ] = EfX [cos(tX) + i sin(tX)] = EfX [cos(tX)] + iEfX [sin(tX)]. In
McGill - MATH - 556
MATH 556 - EXERCISES 4: SOLUTIONS1 (a) This is not an Exponential Family distribution; the support is parameter dependent. (b) This is an EF distribution with k = 1: f (x|) = I{1,2,3,.} (x) -1 exp{x log } = h(x)c() exp{w()t(x)} x log (1 - ) I{1,2,3,
Sveriges lantbruksuniversitet - ENSC - 805
206IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 16, NO. 2, FEBRUARY 1998Bandwidth-Efficient Turbo Trellis-Coded Modulation Using Punctured Component CodesPatrick Robertson, Member, IEEE, and Thomas W rz, Member, IEEE oAbstract- We pre
McGill - MATH - 556
556: M ATHEMATICAL S TATISTICS IC ONVERGENCE I N D ISTRIBUTION : E XAMPLES EXAMPLE 1: Continuous random variable X with range X (0, n] for n > 0 and cdf FXn (x) = 1 - 1 - x nn0<xnand zero otherwise. Then as n , X (0, ), and for all x > 0 FXn
Sveriges lantbruksuniversitet - ENSC - 805
186IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 16, NO. 2, FEBRUARY 1998Concatenated Decoding with a Reduced-Search BCJR AlgorithmVolker Franz and John B. Anderson, Fellow, IEEEAbstract-We apply two reduced-computation variants of the
McGill - MATH - 556
MATH 556 - EXERCISES 5 These exercises are not for assessment1. Using the Central Limit Theorem, construct Normal approximations to probability distribution of a random variable X having (i) (ii) (iii) (iv) a Binomial distribution, X Binomial(n, )
Sveriges lantbruksuniversitet - ENSC - 428
Simon Fraser University School of Engineering Science ENSC 428-4 Data Communications Spring 2001 Calendar Description This course will cover the physical-layer design issues in digital communication systems. The major topics covered are: information
McGill - MATH - 556
556: M ATHEMATICAL S TATISTICS IT HE K ULLBACK -L EIBLER D IVERGENCE The Kullback-Leibler (KL) divergence between two probability distributions with densities f0 and f1 with supports X0 and X1 respectively is defined asK (f0 , f1 ) =logX0f0 (X
McGill - MATH - 556
556: M ATHEMATICAL S TATISTICS IS TOCHASTIC C ONVERGENCE7Convergence ConceptsThe following denitions are stated in terms of scalar random variables, but extend naturally to vector random variables dened on the same probability space with measu
Sveriges lantbruksuniversitet - ENSC - 805
TRANSACTIONS IEEECOMMUNICATIONS, ON COM-32, VOL.NO. 10, OCTOBER 198410791983.[6] L. G . MasonandT.Gavin,An application of optimal control theory [9] B. A.Murtaughand M. A. Saunders, Large-scale lineariy conto modernization problems in telep
Sveriges lantbruksuniversitet - ENSC - 805
1744IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 19, NO. 9, SEPTEMBER 2001Turbo Equalization: Adaptive Equalization and Channel Decoding Jointly OptimizedChristophe Laot, Alain Glavieux, and Jol LabatAbstract-This paper deals with a r
Sveriges lantbruksuniversitet - BUS - 362
BUS 362: The Anal ysi s and Desi gn of Busi ness I nfor mati on Systemshttp:/ / mi s.bus.sfu.ca/ bus362Drew Parkerdr ew@ sfu.cahttp:/ / par ker .bus.sfu.caWeek 4 Agenda Whats new in technology this week? A couple of Interesting Questions to
Wilfrid Laurier - CPSC - 441
Link-State and Distance Vector Routing ExamplesCPSC 441 University of CalgaryLink-State (LS) Routing AlgorithmDijkstra's algorithm topology and link costs known to all nodes accomplished via "link state broadcast" all nodes have same info compute
Wilfrid Laurier - CPSC - 441
Assignment 3Shortest Path and Dijkstras Algorithm On a network, there may be more than paths from a certain node to another one The path with the smallest weight sum is called the shortest path between the two nodes. Dijkstras algorithm offers a
East Los Angeles College - PHY - 112
PHY112 Semester 1IntegrationDr. Tim RichardsonContentsLecture 1 Lecture 2 Lecture 3 Lecture 4 Lecture 5 Lecture 6 Lecture 7 Lecture 8 Indefinite integrals and signed area Definite integrals Improper, complex and symmetric integrals Methods of i
McGill - MATH - 556
556: M ATHEMATICAL S TATISTICS I C OMPUTING THE H YPERBOLIC S ECANT D ISTRIBUTION C HARACTERISTIC F UNCTIONDavid A. Stephens Department of Mathematics and Statistics McGill University October 28, 2006Abstract We give two methods for computing the c
East Los Angeles College - PHY - 112
Vectors Lecture 1INTRODUCTION: SCALAR AND VECTOR QUANTITIES what is a vector? We can divide physical quantities into two main categories: scalar and vector quantities. A scalar quantity is described completely by a single value or number with appro
East Los Angeles College - PHY - 112
LECTURES 4 & 5 METHODS OF INTEGRATIONA Substitution B Logarithmic integration (very brief) C Inspection (very brief) A Substitution This is probably the most common method used to carry out integration. We'll look at various kinds of functions:
Wilfrid Laurier - CPSC - 587
Inverse KinematicsInput:The desired position and possibly orientation of the end effectorOutput:The state of the component joints.
East Los Angeles College - PHY - 112
PHY112 Introductory mathematics for physicists and astronomers 2008/2009ScheduleUnit 1 Introduction 2 Functions and differentiation 3 Complex numbers 4 Integration 5 Differential equations 6 Vectors 7 Functions of two variables 8 Probability Lectu
McGill - MATH - 556
MATH 556 - ASSIGNMENT 4To be handed in not later than 5pm, 27th November 2008. Please hand in during lectures, to Burnside 1235, or to the Mathematics Office Burnside 1005 1 (a) Let r > s 1. Prove that, for convergence in mean, Xn - Xrth=Xn -
East Los Angeles College - PHY - 112
PHY112 Maths for Physicists and AstronomersTutorial Sheet 1 Basic Algebra Revision For the PHY112 Maths tutorial classes in Week 2 (week beginning Monday 6th October).Homework submit your answers to your tutor during the class.1 Expand (remove t
East Los Angeles College - PHY - 112
PHY112 Unit 1: Introduction D J MowbrayPHY112 Introductory mathematics for physicists and astronomersUnit 1: IntroductionPartial fractions and the manipulation of power indicies Partial fractions You will often meet functions of the form 2 x ( x
Allan Hancock College - MINE - 2106
MINE2106Method by Sections Project ReportPractical 4Day Dawn Prospect Method by Sections This practical and associated assignment is based on a gold prospect in north Queensland that was first worked in the 1890's when a shaft and several pits
East Los Angeles College - PHY - 112
Vectors Lecture 2RELATIVE VELOCITY Usually, adding velocity vectors is concerned with combining relative velocities. If an escalator is moving upwards at 1.0 ms-1 relative to the ground floor and a person stood on it is walking up at 1.1 ms-1, then
East Los Angeles College - PHY - 112
PHY112 Unit 3: Complex numbers D J MowbrayPHY112 Introductory mathematics for physicists and astronomersUnit 3: Complex numbersContents 1. Definition of a complex number 2. The Argand diagram 3. Modulus, argument and conjugate of a complex numbe
East Los Angeles College - PHY - 112
PHY112 - Unit 5: Differential equationsV. A. Kudryavtsev Autumn 2008Web-page: http:/kudryavtsev.staff.shef.ac.uk/phy112/ or link from 'list of modules'1Introduction, examplesThe differential equation is an equation which includes one (or mor
Allan Hancock College - ERTH - 3502
ERTH3502Magmatic Ore-forming ProcessesLecture 8Magmatic ore-forming processes:Crystal-liquid fractionation mafic and ultramafic magmas early formed crystals form cumulate layers in magma chamber magma mixing required to explain oxide only c
Sveriges lantbruksuniversitet - CS - 710
Solutions to the second assignment, CMPT 710 Posted: February 23, 2009 1. Let f and g be two functions computable in logarithmic space. Prove that their composition, the function x f (g(x) is also logspace computable. The trick is not to compute g(x
East Los Angeles College - ZOOL - 0601
BMC BiologyResearch articleBioMed CentralOpen AccessCooperation and virulence in acute Pseudomonas aeruginosa infectionsFreya Harrison*1, Lucy E Browning1,2, Michiel Vos3 and Angus Buckling1Address: 1Department of Zoology, University of Oxfo
East Los Angeles College - MAGD - 1129
Reflections on externalism and self-knowledgeIAN PHILLIPS, MindGrad Meeting 13/6/061. Introduction In the mid-nineties a large number of philosophers (most famously, Michael McKinsey, Jessica Brown and Paul Boghossian) raised and discussed a certa
East Los Angeles College - SHUG - 2184
Scallop heavy meromyosin is regulated by calciumDavid Yadin, St. Hugh's College Oxford Work carried out at Division of Physical Biochemistry, NIMR, Mill HillNull Hypothe incre sis: asing thecalciumion conce ntration has no e ct on theactivity of s
East Los Angeles College - BALL - 0888
Work for Week 3Part [A]: Reprise on ValidityTwo extracts from past papers. Exam standards, please. Which you now know to mean Brixel standards. Q.1. Can there be valid arguments where (i) (ii) (iii) (iv) (v) the premisses are all false and so is th
Sveriges lantbruksuniversitet - CS - 710
Second assignment, CMPT 710 Posted: February 5, 2009 Due: February 18, 2009, 11:30am (beginning of class) Try to solve the problems yourself and resist the temptation to look up a solution or to discuss it with other students. It's better to ask me f
Sveriges lantbruksuniversitet - CS - 404
Probability Introduction ReminderCryptography and Protocols Andrei BulatovCryptography and Protocols - Probability3-2Sample Space and OutcomesExperiment s and outcomes Sample space is the set of all possible outcomes Examples - flipping a co
Toledo - BIO - 464
We can use allele frequencies (number of alleles and distributions of alleles over geographical space) to infer whether a species exists in one or many populations. Under the Island Model of Migration, a large population is split into subpopulations