Introduction to Coalescent Models. Biostatistics 666 Lecture 4
|
|
- Oswald Hawkins
- 5 years ago
- Views:
Transcription
1 Introducton to Coalescent Models Bostatstcs 666 Lecture 4
2 Last Lecture Lnkage Equlbrum Expected state for dstant markers Lnkage Dsequlbrum Assocaton between neghborng alleles Expected to decrease wth dstance Measures of lnkage dsequlbrum D, D and ² or r 2
3 Prevously DNA sequence varaton Types of DNA varants Allele frequences Genotype frequences Hardy-Wenberg Equlbrum
4 Makng predctons What allele frequences do we expect? How much varaton n a gene? How are neghborng varants related?
5 Smple Approach: Smulaton. N startng sequences 2. Sample N offsprng sequences Apply mutatons accordng to µ 3. Increment tme 4. If enough tme has passed Generate fnal sample Stop. 5. Otherwse, return to step.
6 Smulatng a Populaton Sequences Tme
7 Today Introduce coalescent approach Framework for studyng genetc varaton Provdes ntuton on patterns of varaton Provdes analytcal solutons
8 Am Gene genealoges: Descrptons of relatedness between sequences Analogous to phylogenetc trees for speces The shape of the genealogy depends on populaton hstory, selecton, etc. Together wth mutaton rate, genealogy predcts DNA varaton
9 Genealogy Hstory of a partcular set of sequences Descrbes ther relatedness Specfes dvergence tmes Includes only a subset of the populaton Most Recent Common Ancestor (MRCA)
10 Coalescent approach Generate genealogy for a sample of sequences. Introduces computatonal and analytcal convenence. Instead of proceedng forward through tme, go backwards!
11 Hstory of the Populaton
12 Genealogy of Fnal Populaton
13 Levels of Complexty Hstory of the populaton Includes sequences that are extnct Hstory of all modern sequences Includes sequences that we haven t sampled Hstory of a subset of modern sequences Mnmalst approach!
14 Parameters we wll focus on Mutaton rate (µ) Populaton Sze Haplod populaton (N chromosomes) Dplod populaton (2N chromosomes) Tme (t) Sample sze (n) Recombnaton rate (r)
15 Other Parameters Selecton For gene of nterest For neghborng gene Demographc parameters Mgraton Populaton Structure Populaton Growth
16 Mutaton Model The mutaton process s complex Rate depends on surroundng sequence Reverse mutatons are possble Two smple models are popular Infnte alleles Every mutaton generates a dfferent allele Infnte stes Every mutaton occurs at a dfferent ste
17 Mutaton Model Focus on nfnte stes model Mutaton rate n genomc DNA s ~0-8 / bp Recurrent mutatons should be very rare Scaled mutaton rate parameter, e.g.: 000 bp sequence 0-8 mutatons per base par per generaton µ 0-5 per sequence per generaton
18 Neutral Varants Varants that have do not affect ftness Accumulate nexorably through tme Lost through genetc drft Do not affect genealogy
19 Example: Modelng Accumulaton of Mutatons Populaton of dentcal sequences Sample one descendant after t generatons How many mutatons have accumulated? Hnt: depends on mutaton rate µ and tme t Tougher questons How many mutatons have been fxed? How much varaton n the total populaton?
20 So far Dvergence of a sngle sequence Accumulaton of mutatons Depends on tme t Depends on mutaton rate µ Does not depend on populaton sze N Does not depend on populaton growth Next: A par of sequences!
21 A tougher example Sample of two sequences 00 bp each How many dfferences are expected? Populaton of sze, N 000 Mutaton rate µ 0-8 / bp / generaton µ 0-6 / 00 bp / generaton
22 Genealogy of two sequences MRCA Tme T(2) Sequence Sequence 2 Mutatons between MRCA and Sequence?
23 Genealogy of two sequences MRCA Tme T(2) Sequence Sequence 2 Total mutatons n genealogy?
24 Number of mutatons S Dstrbuted as Posson, condtonal on total tree length E(S) µe(t tot ) Var(S) E[Var(S T)] + Var[E(S T)] µe(t tot ) + µ²var(t tot ) T tot s the total length of all branches
25 Estmatng T(2) Probablty that two sequences have dstnct ancestors n prevous generaton N P( 2) N N Probablty of dstnct ancestors for t generatons s P(2) t
26 Probablty of MRCA at tme t+ P(2) t ( P(2)) N N N t N N t N e t N
27 For n > 2 Coalescence when two sequences have common ancestor For smplcty, consder the possblty of multple smultaneous coalescent events to be neglgble Requrements for no coalescence: Pck one ancestor for sequence Pck dstnct ancestor for sequence 2 Pck yet another ancestor for sequence 3
28 Estmatng P(n) Probablty that n sequences have n dstnct ancestors n prevous generaton P( n) n N N n 2 N Assume: N s large n s small Terms of order N -2 can be gnored
29 Probablty of Coalescence at Tme t+ t N n t t e N n N n N n n P n P )) ( ( ) (
30 Tme to next coalescent event Use an exponental dstrbuton to approxmate tme to next coalescent event Decay Rate Mean λ λ n 2 N N n 2
31 T(j) For convenence, measure tme to next coalescent event n unts: N generatons for haplods 2N generatons for dplods E( T j ) / j 2 How would you calculate tme to MRCA of n sequences?
32 Total Tme n Tree Sum of all the branch lengths Total evolutonary tme avalable e.g. for mutatons to occur ) ( 2 ) ( ) ( n n n n tot T T E
33 T MRCA vs. T TOT T MRCA T TOT Relatve Sum of Branch Lengths Number of Sequences Number of Sequences Relatve Tme to MRCA
34 Number of Segregatng Stes Commonly named S Total number of mutatons n genealogy Assumng no recurrent mutaton A functon of the total length of the genealogy T tot
35 Expected number of mutatons Factor N for haplods, 2N for dplods Populaton genetcsts defne θ4nµ (for dplods) For gene mappng, θ s usually recombnaton rate Populaton genetcsts, use r for recombnaton rates ( ) 2 / / 4 ) ( 2 ) ( n n n N T E N S E θ µ µ
36 Expected number of mutatons Factor N for haplods, 2N for dplods Populaton genetcsts defne θ4nµ (for dplods) For gene mappers, θ s usually the recombnaton rate Populaton genetcsts, use r for recombnaton rates ( ) 2 / / 4 ) ( 2 ) ( n n n N T E N S E θ µ µ
37 E(S) as a functon of n Expected Number of Segregatng Stes Parameters N 0,000 ndvduals µ 0-4 θ Sample Sze
38 More about S Very large varance Var( S) θ n / + θ 2 n / 2 Most of the varance contrbuted by early coalescent events (.e. wth small n)
39 Var(S) as a functon of n Sample Sze Parameters N 0,000 ndvduals µ 0-4 θ 4 Varance n Number of Segregatng Stes
40 Inferences about θ Could be estmated from S Dvde by expected length of genealogy ˆ θ n S / Could then be used to: Estmate N, f mutaton rate µ s known Estmate µ, f populaton sze N s known
41 ^ Var(θ) as a functon of N Varance n Estmate of Theta Parameters N 0,000 ndvduals µ 0-4 θ Sample Sze
42 Alternatve Estmator for θ Count parwse dfferences between sequences Compute average number of dfferences ~ θ n 2 n n S j j +
43 Today Probablty of coalescence events Length of genealogy and ts branches Expected number of mutatons Smple estmates of θ
44 Recommended Readng Rchard R. Hudson (990) Gene genealoges and the coalescent process Oxford Surveys n Evolutonary Bology, Vol. 7. D. Futuyma and J. Antonovcs (Eds). Oxford Unversty Press, New York.
Introduction to Coalescent Models. Biostatistics 666
Introducton to Coalescent Models Bostatstcs 666 Prevously Allele frequences Hardy Wenberg Equlbrum Lnkage Equlbrum Expected state for dstant markers Lnkage Dsequlbrum Assocaton between neghborng alleles
More informationParticle Filters. Ioannis Rekleitis
Partcle Flters Ioanns Reklets Bayesan Flter Estmate state x from data Z What s the probablty of the robot beng at x? x could be robot locaton, map nformaton, locatons of targets, etc Z could be sensor
More informationEnsemble Evolution of Checkers Players with Knowledge of Opening, Middle and Endgame
Ensemble Evoluton of Checkers Players wth Knowledge of Openng, Mddle and Endgame Kyung-Joong Km and Sung-Bae Cho Department of Computer Scence, Yonse Unversty 134 Shnchon-dong, Sudaemoon-ku, Seoul 120-749
More informationComparative Analysis of Reuse 1 and 3 in Cellular Network Based On SIR Distribution and Rate
Comparatve Analyss of Reuse and 3 n ular Network Based On IR Dstrbuton and Rate Chandra Thapa M.Tech. II, DEC V College of Engneerng & Technology R.V.. Nagar, Chttoor-5727, A.P. Inda Emal: chandra2thapa@gmal.com
More informationMTBF PREDICTION REPORT
MTBF PREDICTION REPORT PRODUCT NAME: BLE112-A-V2 Issued date: 01-23-2015 Rev:1.0 Copyrght@2015 Bluegga Technologes. All rghts reserved. 1 MTBF PREDICTION REPORT... 1 PRODUCT NAME: BLE112-A-V2... 1 1.0
More informationESTIMATION of population parameters in classical
Copyrght Ó 005 by the Genetcs Socety of Amerca DOI: 10.1534/genetcs.104.04040 Lkelhoods From Summary Statstcs: Recent Dvergence Between Speces Scotland C. Leman,* Yuguo Chen,*,1 Jason E. Stach, Mohamed
More informationHigh Speed ADC Sampling Transients
Hgh Speed ADC Samplng Transents Doug Stuetzle Hgh speed analog to dgtal converters (ADCs) are, at the analog sgnal nterface, track and hold devces. As such, they nclude samplng capactors and samplng swtches.
More informationA MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM IN SPARSE LINEAR ANTENNA ARRAY SYNTHESIS
A MODIFIED DIFFERENTIAL EVOLUTION ALORITHM IN SPARSE LINEAR ANTENNA ARRAY SYNTHESIS Kaml Dmller Department of Electrcal-Electroncs Engneerng rne Amercan Unversty North Cyprus, Mersn TURKEY kdmller@gau.edu.tr
More informationFault Locations in Transmission Systems by Evolutionary Algorithms
European Assocaton for the Development of Renewable Energes, Envronment and Power Qualty Internatonal Conference on Renewable Energes and Power Qualty (ICREPQ 09) Valenca (Span), 5th to 7th Aprl, 009 Fault
More informationFall 2018 #11 Games and Nimbers. A. Game. 0.5 seconds, 64 megabytes
5-95 Fall 08 # Games and Nmbers A. Game 0.5 seconds, 64 megabytes There s a legend n the IT Cty college. A student that faled to answer all questons on the game theory exam s gven one more chance by hs
More informationComparison of Two Measurement Devices I. Fundamental Ideas.
Comparson of Two Measurement Devces I. Fundamental Ideas. ASQ-RS Qualty Conference March 16, 005 Joseph G. Voelkel, COE, RIT Bruce Sskowsk Rechert, Inc. Topcs The Problem, Eample, Mathematcal Model One
More informationDynamic Optimization. Assignment 1. Sasanka Nagavalli January 29, 2013 Robotics Institute Carnegie Mellon University
Dynamc Optmzaton Assgnment 1 Sasanka Nagavall snagaval@andrew.cmu.edu 16-745 January 29, 213 Robotcs Insttute Carnege Mellon Unversty Table of Contents 1. Problem and Approach... 1 2. Optmzaton wthout
More informationMODEL ORDER REDUCTION AND CONTROLLER DESIGN OF DISCRETE SYSTEM EMPLOYING REAL CODED GENETIC ALGORITHM J. S. Yadav, N. P. Patidar, J.
ABSTRACT Research Artcle MODEL ORDER REDUCTION AND CONTROLLER DESIGN OF DISCRETE SYSTEM EMPLOYING REAL CODED GENETIC ALGORITHM J. S. Yadav, N. P. Patdar, J. Sngha Address for Correspondence Maulana Azad
More informationMachine Learning in Production Systems Design Using Genetic Algorithms
Internatonal Journal of Computatonal Intellgence Volume 4 Number 1 achne Learnng n Producton Systems Desgn Usng Genetc Algorthms Abu Quder Jaber, Yamamoto Hdehko and Rzauddn Raml Abstract To create a soluton
More informationReview: Our Approach 2. CSC310 Information Theory
CSC30 Informaton Theory Sam Rowes Lecture 3: Provng the Kraft-McMllan Inequaltes September 8, 6 Revew: Our Approach The study of both compresson and transmsson requres that we abstract data and messages
More informationOptimal Placement of PMU and RTU by Hybrid Genetic Algorithm and Simulated Annealing for Multiarea Power System State Estimation
T. Kerdchuen and W. Ongsakul / GMSARN Internatonal Journal (09) - Optmal Placement of and by Hybrd Genetc Algorthm and Smulated Annealng for Multarea Power System State Estmaton Thawatch Kerdchuen and
More informationUncertainty in measurements of power and energy on power networks
Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:
More informationproblems palette of David Rock and Mary K. Porter 6. A local musician comes to your school to give a performance
palette of problems Davd Rock and Mary K. Porter 1. If n represents an nteger, whch of the followng expressons yelds the greatest value? n,, n, n, n n. A 60-watt lghtbulb s used for 95 hours before t burns
More informationTECHNICAL NOTE TERMINATION FOR POINT- TO-POINT SYSTEMS TN TERMINATON FOR POINT-TO-POINT SYSTEMS. Zo = L C. ω - angular frequency = 2πf
TECHNICAL NOTE TERMINATION FOR POINT- TO-POINT SYSTEMS INTRODUCTION Because dgtal sgnal rates n computng systems are ncreasng at an astonshng rate, sgnal ntegrty ssues have become far more mportant to
More informationThe genealogical history of a population The coalescent process. Identity by descent Distribution of pairwise coalescence times
The coalescent The genealogical history of a population The coalescent process Identity by descent Distribution of pairwise coalescence times Adding mutations Expected pairwise differences Evolutionary
More informationCalculation of the received voltage due to the radiation from multiple co-frequency sources
Rec. ITU-R SM.1271-0 1 RECOMMENDATION ITU-R SM.1271-0 * EFFICIENT SPECTRUM UTILIZATION USING PROBABILISTIC METHODS Rec. ITU-R SM.1271 (1997) The ITU Radocommuncaton Assembly, consderng a) that communcatons
More informationA NSGA-II algorithm to solve a bi-objective optimization of the redundancy allocation problem for series-parallel systems
0 nd Internatonal Conference on Industral Technology and Management (ICITM 0) IPCSIT vol. 49 (0) (0) IACSIT Press, Sngapore DOI: 0.776/IPCSIT.0.V49.8 A NSGA-II algorthm to solve a b-obectve optmzaton of
More informationLocalization of FACTS Devices for Optimal Power Flow Using Genetic Algorithm
13 Internatonal Conference on Electrcal Informaton and Communcaton Technology (EICT) Localzaton of ACTS Devces for Optmal Power low Usng Genetc Algorthm A.K.M. Rezwanur Rahman, Md. Shahabul Alam, Md. Zakr
More informationIntelligent and Robust Genetic Algorithm Based Classifier
Intellgent and Robust Genetc Algorthm Based Classfer S. H. Zahr, H. Raab Mashhad and S. A. Seyedn Downloaded from eee.ust.ac.r at :4 IRDT on Monday September 3rd 018 Abstract: The concepts of robust classfcaton
More information1 GSW Multipath Channel Models
In the general case, the moble rado channel s pretty unpleasant: there are a lot of echoes dstortng the receved sgnal, and the mpulse response keeps changng. Fortunately, there are some smplfyng assumptons
More informationRevision of Lecture Twenty-One
Revson of Lecture Twenty-One FFT / IFFT most wdely found operatons n communcaton systems Important to know what are gong on nsde a FFT / IFFT algorthm Wth the ad of FFT / IFFT, ths lecture looks nto OFDM
More informationJoint Power Control and Scheduling for Two-Cell Energy Efficient Broadcasting with Network Coding
Communcatons and Network, 2013, 5, 312-318 http://dx.do.org/10.4236/cn.2013.53b2058 Publshed Onlne September 2013 (http://www.scrp.org/journal/cn) Jont Power Control and Schedulng for Two-Cell Energy Effcent
More informationOpen Access Node Localization Method for Wireless Sensor Networks Based on Hybrid Optimization of Differential Evolution and Particle Swarm Algorithm
Send Orders for Reprnts to reprnts@benthamscence.ae The Open Automaton and Control Systems Journal, 014, 6, 61-68 61 Open Access Node Localzaton Method for Wreless Sensor Networks Based on Hybrd Optmzaton
More informationQueen Bee genetic optimization of an heuristic based fuzzy control scheme for a mobile robot 1
Queen Bee genetc optmzaton of an heurstc based fuzzy control scheme for a moble robot 1 Rodrgo A. Carrasco Schmdt Pontfca Unversdad Católca de Chle Abstract Ths work presents both a novel control scheme
More informationPRACTICAL, COMPUTATION EFFICIENT HIGH-ORDER NEURAL NETWORK FOR ROTATION AND SHIFT INVARIANT PATTERN RECOGNITION. Evgeny Artyomov and Orly Yadid-Pecht
68 Internatonal Journal "Informaton Theores & Applcatons" Vol.11 PRACTICAL, COMPUTATION EFFICIENT HIGH-ORDER NEURAL NETWORK FOR ROTATION AND SHIFT INVARIANT PATTERN RECOGNITION Evgeny Artyomov and Orly
More informationSafety and resilience of Global Baltic Network of Critical Infrastructure Networks related to cascading effects
Blokus-Roszkowska Agneszka Dzula Przemysław Journal of Polsh afety and Relablty Assocaton ummer afety and Relablty emnars, Volume 9, Number, Kołowrock Krzysztof Gdyna Martme Unversty, Gdyna, Poland afety
More informationUSE OF GPS MULTICORRELATOR RECEIVERS FOR MULTIPATH PARAMETERS ESTIMATION
Rdha CHAGGARA, TeSA Chrstophe MACABIAU, ENAC Erc CHATRE, STNA USE OF GPS MULTICORRELATOR RECEIVERS FOR MULTIPATH PARAMETERS ESTIMATION ABSTRACT The performance of GPS may be degraded by many perturbatons
More informationControl Chart. Control Chart - history. Process in control. Developed in 1920 s. By Dr. Walter A. Shewhart
Control Chart - hstory Control Chart Developed n 920 s By Dr. Walter A. Shewhart 2 Process n control A phenomenon s sad to be controlled when, through the use of past experence, we can predct, at least
More informationA Simple Satellite Exclusion Algorithm for Advanced RAIM
A Smple Satellte Excluson Algorthm for Advanced RAIM Juan Blanch, Todd Walter, Per Enge Stanford Unversty ABSTRACT Advanced Recever Autonomous Integrty Montorng s a concept that extends RAIM to mult-constellaton
More informationA TWO-PLAYER MODEL FOR THE SIMULTANEOUS LOCATION OF FRANCHISING SERVICES WITH PREFERENTIAL RIGHTS
A TWO-PLAYER MODEL FOR THE SIMULTANEOUS LOCATION OF FRANCHISING SERVICES WITH PREFERENTIAL RIGHTS Pedro Godnho and oana Das Faculdade de Economa and GEMF Unversdade de Combra Av. Das da Slva 65 3004-5
More informationNEW EVOLUTIONARY PARTICLE SWARM ALGORITHM (EPSO) APPLIED TO VOLTAGE/VAR CONTROL
NEW EVOLUTIONARY PARTICLE SWARM ALGORITHM (EPSO) APPLIED TO VOLTAGE/VAR CONTROL Vladmro Mranda vmranda@nescporto.pt Nuno Fonseca nfonseca@power.nescn.pt INESC Insttuto de Engenhara de Sstemas e Computadores
More informationEvolving Crushers. P. Hingston L. Barone L. While
Evolvng Crushers P. Hngston L. Barone L. Whle School of Computer and Informaton Scence Edth Cowan Unversty Mt Lawley, WA, Australa Department of Computer Scence & Software Engneerng The Unversty of Western
More informationDownloaded from ijiepr.iust.ac.ir at 5:13 IRST on Saturday December 15th 2018
Internatonal Journal of Industral Eng. & roducton Research (2008) pp. 21-29 Volume 19, Number 4, 2008 Internatonal Journal of Industral Engneerng & roducton Research Journal Webste: http://een.ust.ac.r/
More informationPerformance Study of OFDMA vs. OFDM/SDMA
Performance Study of OFDA vs. OFD/SDA Zhua Guo and Wenwu Zhu crosoft Research, Asa 3F, Beng Sgma Center, No. 49, Zhchun Road adan Dstrct, Beng 00080, P. R. Chna {zhguo, wwzhu}@mcrosoft.com Abstract: In
More informationAdaptive Phase Synchronisation Algorithm for Collaborative Beamforming in Wireless Sensor Networks
213 7th Asa Modellng Symposum Adaptve Phase Synchronsaton Algorthm for Collaboratve Beamformng n Wreless Sensor Networks Chen How Wong, Zhan We Sew, Renee Ka Yn Chn, Aroland Krng, Kenneth Tze Kn Teo Modellng,
More informationNATIONAL RADIO ASTRONOMY OBSERVATORY Green Bank, West Virginia SPECTRAL PROCESSOR MEMO NO. 25. MEMORANDUM February 13, 1985
NATONAL RADO ASTRONOMY OBSERVATORY Green Bank, West Vrgna SPECTRAL PROCESSOR MEMO NO. 25 MEMORANDUM February 13, 1985 To: Spectral Processor Group From: R. Fsher Subj: Some Experments wth an nteger FFT
More informationForecasting Stock Returns using Evolutionary Artificial Neural Networks 1
Forecastng Stoc Returns usng Evolutonary Artfcal eural etwors 1 Prsadarng Solpadunget, Keshav Dahal, apat Harnporncha MOSAIC Research Group, Unversty of Bradford, Great Horton Road, Bradford, BD7 1DP,
More informationInformation-Theoretic Comparison of Channel Capacity for FDMA and DS-CDMA in a Rayleigh Fading Environment
WSEAS TRANSATIONS on OMMUNIATIONS Informaton-Theoretc omparson of hannel apacty for FDMA and DS-DMA n a Raylegh Fadng Envronment PANAGIOTIS VARZAAS Department of Electroncs Technologcal Educatonal Insttute
More informationInvestigation of Hybrid Particle Swarm Optimization Methods for Solving Transient-Stability Constrained Optimal Power Flow Problems
Investgaton of Hybrd Partcle Swarm Optmzaton Methods for Solvng Transent-Stablty Constraned Optmal Power Flow Problems K. Y. Chan, G. T. Y. Pong and K. W. Chan Abstract In ths paper, hybrd partcle swarm
More informationUtility-based Routing
Utlty-based Routng Je Wu Dept. of Computer and Informaton Scences Temple Unversty Roadmap Introducton Why Another Routng Scheme Utlty-Based Routng Implementatons Extensons Some Fnal Thoughts 2 . Introducton
More informationA High-Sensitivity Oversampling Digital Signal Detection Technique for CMOS Image Sensors Using Non-destructive Intermediate High-Speed Readout Mode
A Hgh-Senstvty Oversamplng Dgtal Sgnal Detecton Technque for CMOS Image Sensors Usng Non-destructve Intermedate Hgh-Speed Readout Mode Shoj Kawahto*, Nobuhro Kawa** and Yoshak Tadokoro** *Research Insttute
More informationN( E) ( ) That is, if the outcomes in sample space S are equally likely, then ( )
Stat 400, secton 2.2 Axoms, Interpretatons and Propertes of Probablty notes by Tm Plachowsk In secton 2., we constructed sample spaces by askng, What could happen? Now, n secton 2.2, we begn askng and
More informationDigital Transmission
Dgtal Transmsson Most modern communcaton systems are dgtal, meanng that the transmtted normaton sgnal carres bts and symbols rather than an analog sgnal. The eect o C/N rato ncrease or decrease on dgtal
More informationASFALT: Ā S imple F āult-tolerant Signature-based L ocalization T echnique for Emergency Sensor Networks
ASFALT: Ā S mple F āult-tolerant Sgnature-based L ocalzaton T echnque for Emergency Sensor Networks Murtuza Jadlwala, Shambhu Upadhyaya and Mank Taneja State Unversty of New York at Buffalo Department
More informationQueuing-Based Dynamic Channel Selection for Heterogeneous Multimedia Applications over Cognitive Radio Networks
1 Queung-Based Dynamc Channel Selecton for Heterogeneous ultmeda Applcatons over Cogntve Rado Networks Hsen-Po Shang and haela van der Schaar Department of Electrcal Engneerng (EE), Unversty of Calforna
More informationPSO and ACO Algorithms Applied to Location Optimization of the WLAN Base Station
PSO and ACO Algorthms Appled to Locaton Optmzaton of the WLAN Base Staton Ivan Vlovć 1, Nša Burum 1, Zvonmr Špuš 2 and Robert Nađ 2 1 Unversty of Dubrovn, Croata 2 Unversty of Zagreb, Croata E-mal: van.vlovc@undu.hr,
More informationResearch on the Process-level Production Scheduling Optimization Based on the Manufacturing Process Simplifies
Internatonal Journal of Smart Home Vol.8, No. (04), pp.7-6 http://dx.do.org/0.457/sh.04.8.. Research on the Process-level Producton Schedulng Optmzaton Based on the Manufacturng Process Smplfes Y. P. Wang,*,
More informationSolving Haplotype Assembly Problem Using Harmony Search
Internatonal Journal of Computer Networks and Communcatons Securty VOL. 1, NO. 4, SEPTEMBER 013, 110 118 Avalable onlne at: www.jcncs.org ISSN 308-9830 C N C S Solvng Haplotype Assembly Problem Usng Harmony
More informationA Genetic Algorithm Based Multi Objective Service Restoration in Distribution Systems
Journal of Computer Scence 7 (3): 448-453, 2011 ISSN 1549-3636 2011 Scence Publcatons A Genetc Algorthm Based Mult Objectve Servce Restoraton n Dstrbuton Systems Sathsh Kumar Kannaah, Jayabarath Thangavel
More informationA Comparison of Two Equivalent Real Formulations for Complex-Valued Linear Systems Part 2: Results
AMERICAN JOURNAL OF UNDERGRADUATE RESEARCH VOL. 1 NO. () A Comparson of Two Equvalent Real Formulatons for Complex-Valued Lnear Systems Part : Results Abnta Munankarmy and Mchael A. Heroux Department of
More informationGuidelines for CCPR and RMO Bilateral Key Comparisons CCPR Working Group on Key Comparison CCPR-G5 October 10 th, 2014
Gudelnes for CCPR and RMO Blateral Key Comparsons CCPR Workng Group on Key Comparson CCPR-G5 October 10 th, 2014 These gudelnes are prepared by CCPR WG-KC and RMO P&R representatves, and approved by CCPR,
More informationCoverage Maximization in Mobile Wireless Sensor Networks Utilizing Immune Node Deployment Algorithm
CCECE 2014 1569888203 Coverage Maxmzaton n Moble Wreless Sensor Networs Utlzng Immune Node Deployment Algorthm Mohammed Abo-Zahhad, Sabah M. Ahmed and Nabl Sabor Electrcal and Electroncs Engneerng Department
More informationOn Operational Availability of a Large Software-Based Telecommunications System
On Operatonal Avalablty of a Large Software-Based Telecommuncatons System Randy Cramp and Mladen A. Vouk Wendell Jones North Carolna State Unversty BNR Inc. Department of Computer Scence, Box 826 P.O.
More informationA Predictive QoS Control Strategy for Wireless Sensor Networks
The 1st Worshop on Resource Provsonng and Management n Sensor Networs (RPMSN '5) n conjuncton wth the 2nd IEEE MASS, Washngton, DC, Nov. 25 A Predctve QoS Control Strategy for Wreless Sensor Networs Byu
More informationNOVEL ITERATIVE TECHNIQUES FOR RADAR TARGET DISCRIMINATION
NOVEL ITERATIVE TECHNIQUES FOR RADAR TARGET DISCRIMINATION Phaneendra R.Venkata, Nathan A. Goodman Department of Electrcal and Computer Engneerng, Unversty of Arzona, 30 E. Speedway Blvd, Tucson, Arzona
More informationMultiple Robots Formation A Multiobjctive Evolution Approach
Avalable onlne at www.scencedrect.com Proceda Engneerng 41 (2012 ) 156 162 Internatonal Symposum on Robotcs and Intellgent Sensors 2012 (IRIS 2012) Multple Robots Formaton A Multobctve Evoluton Approach
More informationDevelopment and Performance Evaluation of Mismatched Filter using Differential Evolution
Internatonal Journal of Computer Applcatons (975 8887) Development and Performance Evaluaton of Msmatched Flter usng Dfferental Evoluton J. B. Seventlne 1 G. V. K. Sharma 2 K. Srdev 3 D. Elzabath Ran 4
More informationCOGNITIVE RADIO ENGINE MODEL UTILIZING SOFT FUSION BASED GENETIC ALGORITHM FOR COOPERATIVE SPECTRUM OPTIMIZATION
Internatonal Journal of Computer Networks & Communcatons (IJCNC Vol.5, No., arch 3 COGNIIVE RADIO ENGINE ODEL UILIZING SOF FUSION BASED GENEIC ALGORI FOR COOERAIVE SECRU OIIZAION ABSRAC d. Kamal ossan,
More informationAlgorithms for Genetics: Basics of Wright Fisher Model and Coalescent Theory
Algorithms for Genetics: Basics of Wright Fisher Model and Coalescent Theory Vineet Bafna Harish Nagarajan and Nitin Udpa 1 Disclaimer Please note that a lot of the text and figures here are copied from
More informationCOMPARISION OF POTENTIAL PATHS SELECTED BY A MALICIOUS ENTITY WITH HAZARDOUS MATERIALS : MINIMIZATION OF TIME VS. MINIMIZATION OF DISTANCE
Proceedngs of the 2007 Wnter Smulaton Conference S. G. Henderson, B. Bller, M.-H. Hseh, J. Shortle, J. D. Tew, and R. R. Barton, eds. COMPARISION OF POTENTIAL PATHS SELECTED BY A MALICIOUS ENTITY WITH
More informationThe Impact of Spectrum Sensing Frequency and Packet- Loading Scheme on Multimedia Transmission over Cognitive Radio Networks
Ths artcle has been accepted for publcaton n a future ssue of ths journal, but has not been fully edted. Content may change pror to fnal publcaton. The Impact of Spectrum Sensng Frequency and Pacet- Loadng
More informationOptimization of Shortest Path of Multiple Transportation Model Based on Cost Analyses
Optmzaton of Shortest Path of Multple Transportaton Model Based on Cost Analyses Yang Yang 1,2 Ruyng Wang 1 Qanqan Zhang 1 1 Chna Unversty of Mnng & Technology (Bejng), School of Management, Bejng, 100083,
More informationKey-Words: - Automatic guided vehicles, Robot navigation, genetic algorithms, potential fields
Autonomous Robot Navgaton usng Genetc Algorthms F. ARAMBULA COSIO, M. A. PADILLA CASTAÑEDA Lab. de Imágenes y Vsón Centro de Instrumentos, UNAM Méxco, D.F., 451 MEXICO Abstract: - In ths paper s presented
More informationPower Minimization Under Constant Throughput Constraint in Wireless Networks with Beamforming
Power Mnmzaton Under Constant Throughput Constrant n Wreless etworks wth Beamformng Zhu Han and K.J. Ray Lu, Electrcal and Computer Engneer Department, Unversty of Maryland, College Park. Abstract In mult-access
More informationOpportunistic Beamforming for Finite Horizon Multicast
Opportunstc Beamformng for Fnte Horzon Multcast Gek Hong Sm, Joerg Wdmer, and Balaj Rengarajan allyson.sm@mdea.org, joerg.wdmer@mdea.org, and balaj.rengarajan@gmal.com Insttute IMDEA Networks, Madrd, Span
More informationNew Parallel Radial Basis Function Neural Network for Voltage Security Analysis
New Parallel Radal Bass Functon Neural Network for Voltage Securty Analyss T. Jan, L. Srvastava, S.N. Sngh and I. Erlch Abstract: On-lne montorng of power system voltage securty has become a very demandng
More informationA Fuzzy-based Routing Strategy for Multihop Cognitive Radio Networks
74 Internatonal Journal of Communcaton Networks and Informaton Securty (IJCNIS) Vol. 3, No., Aprl 0 A Fuzzy-based Routng Strategy for Multhop Cogntve Rado Networks Al El Masr, Naceur Malouch and Hcham
More informationApproximating User Distributions in WCDMA Networks Using 2-D Gaussian
CCCT 05: INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATIONS, AND CONTROL TECHNOLOGIES 1 Approxmatng User Dstrbutons n CDMA Networks Usng 2-D Gaussan Son NGUYEN and Robert AKL Department of Computer
More informationFEATURE SELECTION FOR SMALL-SIGNAL STABILITY ASSESSMENT
FEAURE SELECION FOR SMALL-SIGNAL SABILIY ASSESSMEN S.P. eeuwsen Unversty of Dusburg teeuwsen@un-dusburg.de Abstract INRODUCION hs paper ntroduces dfferent feature selecton technques for neural network
More informationph fax
www.customron.com ph 800.732.7699 fax 507.732.7837 Balusters, pckets, spndles these are the bones of a star ralng system. At Custom Iron, we commonly refer to these as balusters. And, uncommonly, we nvent
More informationMultichannel Frequency Comparator VCH-315. User Guide
Multchannel Frequency Comparator VCH-315 User Gude Table of contents 1 Introducton... 3 2 The workng prncple of the Comparator... 6 3 The computed functons... 8 3.1 Basc ratos... 8 3.2 Statstcal functons...
More informationTo: Professor Avitabile Date: February 4, 2003 From: Mechanical Student Subject: Experiment #1 Numerical Methods Using Excel
To: Professor Avtable Date: February 4, 3 From: Mechancal Student Subject:.3 Experment # Numercal Methods Usng Excel Introducton Mcrosoft Excel s a spreadsheet program that can be used for data analyss,
More informationModelling Service Time Distribution in Cellular Networks Using Phase-Type Service Distributions
Modellng Servce Tme Dstrbuton n Cellular Networks Usng Phase-Type Servce Dstrbutons runa Jayasurya, Davd Green, John senstorfer Insttute for Telecommuncaton Research, Cooperatve Research Centre for Satellte
More informationHybrid Differential Evolution based Concurrent Relay-PID Control for Motor Position Servo Systems
Hybrd Dfferental Evoluton based Concurrent Relay-PID Control for Motor Poston Servo Systems B.Sartha 1, Dr. L. Rav Srnvas P.G. Student, Department of EEE, Gudlavalleru Engneerng College, Gudlavalleru,
More informationROBUST IDENTIFICATION AND PREDICTION USING WILCOXON NORM AND PARTICLE SWARM OPTIMIZATION
7th European Sgnal Processng Conference (EUSIPCO 9 Glasgow, Scotland, August 4-8, 9 ROBUST IDENTIFICATION AND PREDICTION USING WILCOXON NORM AND PARTICLE SWARM OPTIMIZATION Babta Majh, G. Panda and B.
More informationMooring Cost Sensitivity Study Based on Cost-Optimum Mooring Design
Proceedngs of Conference 8 Korean Socety of Ocean Engneers May 9-3, Cheju, Korea Moorng Cost Senstvty Study Based on Cost-Optmum Moorng Desgn SAM SANGSOO RYU, CASPAR HEYL AND ARUN DUGGAL Research & Development,
More informationTopology Control for C-RAN Architecture Based on Complex Network
Topology Control for C-RAN Archtecture Based on Complex Network Zhanun Lu, Yung He, Yunpeng L, Zhaoy L, Ka Dng Chongqng key laboratory of moble communcatons technology Chongqng unversty of post and telecommuncaton
More informationRational Secret Sharing without Broadcast
Ratonal Secret Sharng wthout Broadcast Amjed Shareef, Department of Computer Scence and Engneerng, Indan Insttute of Technology Madras, Chenna, Inda. Emal: amjedshareef@gmal.com Abstract We use the concept
More informationApplication of Intelligent Voltage Control System to Korean Power Systems
Applcaton of Intellgent Voltage Control System to Korean Power Systems WonKun Yu a,1 and HeungJae Lee b, *,2 a Department of Power System, Seol Unversty, South Korea. b Department of Power System, Kwangwoon
More informationTraffic balancing over licensed and unlicensed bands in heterogeneous networks
Correspondence letter Traffc balancng over lcensed and unlcensed bands n heterogeneous networks LI Zhen, CUI Qme, CUI Zhyan, ZHENG We Natonal Engneerng Laboratory for Moble Network Securty, Bejng Unversty
More informationFinding Proper Configurations for Modular Robots by Using Genetic Algorithm on Different Terrains
Internatonal Journal of Materals, Mechancs and Manufacturng, Vol. 1, No. 4, November 2013 Fndng Proper Confguratons for Modular Robots by Usng Genetc Algorthm on Dfferent Terrans Sajad Haghzad Kldbary,
More informationAn Optimal Model and Solution of Deployment of Airships for High Altitude Platforms
An Optmal Model and Soluton of Deployment of Arshps for Hgh Alttude Platforms Xuyu Wang, Xnbo Gao, Ru Zong, Peng Cheng. VIPS Lab, School of Electronc Engneerng, Xdan Unversty, X an 77, Chna. Department
More informationAnalog Circuit Design with Variable Length Chromosomes
Analog Crcut Desgn wth Varable Length Chromosomes Shn Ando Unv. of Tokyo, Bunkyo-ku Hongo, Tokyo, Japan ando@mv.t.u-tokyo.ac.jp Htosh Iba Unv. of Tokyo, Bunkyo-ku Hongo, Tokyo, Japan ba@mv.t.u-tokyo.ac.jp
More informationNetwork Theory. EC / EE / IN. for
Network Theory for / / IN By www.thegateacademy.com Syllabus Syllabus for Networks Network Graphs: Matrces Assocated Wth Graphs: Incdence, Fundamental ut Set and Fundamental rcut Matrces. Soluton Methods:
More information1.0 INTRODUCTION 2.0 CELLULAR POSITIONING WITH DATABASE CORRELATION
An Improved Cellular postonng technque based on Database Correlaton B D S Lakmal 1, S A D Das 2 Department of Electronc & Telecommuncaton Engneerng, Unversty of Moratuwa. { 1 shashka, 2 dleeka}@ent.mrt.ac.lk
More informationTHEORY OF YARN STRUCTURE by Prof. Bohuslav Neckář, Textile Department, IIT Delhi, New Delhi. Compression of fibrous assemblies
THEORY OF YARN STRUCTURE by Prof. Bohuslav Neckář, Textle Department, IIT Delh, New Delh. Compresson of fbrous assembles Q1) What was the dea of fbre-to-fbre contact accordng to van Wyk? A1) Accordng to
More informationDefine Y = # of mobiles from M total mobiles that have an adequate link. Measure of average portion of mobiles allocated a link of adequate quality.
Wreless Communcatons Technologes 6::559 (Advanced Topcs n Communcatons) Lecture 5 (Aprl th ) and Lecture 6 (May st ) Instructor: Professor Narayan Mandayam Summarzed by: Steve Leung (leungs@ece.rutgers.edu)
More informationA Tool for Evolving Artificial Neural Networks
A ool for Evolvng Artfcal Neural Networks Efstratos F. Georgopoulos, 3, Adam V. Adamopoulos, 3 and Sprdon D. Lkothanasss 3 Abstract. A hybrd evolutonary algorthm that combnes genetc programmng phlosophy,
More informationTest 2. ECON3161, Game Theory. Tuesday, November 6 th
Test 2 ECON36, Game Theory Tuesday, November 6 th Drectons: Answer each queston completely. If you cannot determne the answer, explanng how you would arrve at the answer may earn you some ponts.. (20 ponts)
More informationEquivalent Circuit Model of Electromagnetic Behaviour of Wire Objects by the Matrix Pencil Method
ERBIAN JOURNAL OF ELECTRICAL ENGINEERING Vol. 5, No., May 008, -0 Equvalent Crcut Model of Electromagnetc Behavour of Wre Objects by the Matrx Pencl Method Vesna Arnautovsk-Toseva, Khall El Khamlch Drss,
More informationSpatio-temporal community dynamics induced by frequency dependent interactions
ecologcal modellng xxx (2006) xxx xxx avalable at www.scencedrect.com journal homepage: www.elsever.com/locate/ecolmodel Spato-temporal communty dynamcs nduced by frequency dependent nteractons Margaret
More informationDistributed Uplink Scheduling in EV-DO Rev. A Networks
Dstrbuted Uplnk Schedulng n EV-DO ev. A Networks Ashwn Srdharan (Sprnt Nextel) amesh Subbaraman, och Guérn (ESE, Unversty of Pennsylvana) Overvew of Problem Most modern wreless systems Delver hgh performance
More informationCoalescence. Outline History. History, Model, and Application. Coalescence. The Model. Application
Coalescence History, Model, and Application Outline History Origins of theory/approach Trace the incorporation of other s ideas Coalescence Definition and descriptions The Model Assumptions and Uses Application
More informationDistributed Channel Allocation Algorithm with Power Control
Dstrbuted Channel Allocaton Algorthm wth Power Control Shaoj N Helsnk Unversty of Technology, Insttute of Rado Communcatons, Communcatons Laboratory, Otakaar 5, 0150 Espoo, Fnland. E-mal: n@tltu.hut.f
More informationDesign of IIR digital filter using Simulated Annealing
Desgn of IIR dgtal flter usng Smulated Annealng Ranjt Sngh *, Sandeep K. Arya * Department of Electroncs and Comm. Engneerng, JMIT Radaur, INDIA Department of Electroncs and Comm. Engneerng, GJU Hsar,
More information