Introduction to Coalescent Models. Biostatistics 666

Size: px
Start display at page:

Download "Introduction to Coalescent Models. Biostatistics 666"

Transcription

1 Introducton to Coalescent Models Bostatstcs 666

2 Prevously Allele frequences Hardy Wenberg Equlbrum 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 Makng predctons What allele frequences do we expect? How much varaton n a gene? How are neghborng varants related? Are these predctons unversal? Do they depend on natural selecton or the hstory of a populaton? How can we use genetc varaton to buld models of the past?

4 1000 Genomes Data: Varants per Genome Type Varant stes / genome SNPs ~3,800,000 Indels ~570,000 Moble Element Insertons ~1000 Large Deletons ~1000 CNVs ~150 Inversons ~11

5 1000 Genomes Data: Demographc Models

6 Smple Approach: Smulaton 1. 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 1.

7 Smulatng a Populaton Sequences Tme

8 Today Introduce coalescent approach Framework for studyng genetc varaton Provdes ntuton on patterns of varaton Provdes analytcal solutons

9 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

10 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)

11 Coalescent approach Generate genealogy for a sample of sequences. Introduces computatonal and analytcal convenence. Instead of proceedng forward through tme, go backwards!

12 Hstory of the Populaton

13 Genealogy of Fnal Populaton

14 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!

15 Examples of Typcal Coalescent Trees

16 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)

17 Other Parameters Selecton For gene of nterest For neghborng gene Demographc parameters Mgraton Populaton Structure Populaton Growth

18 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

19 Mutaton Model Focus on nfnte stes model Mutaton rate n genomc DNA s ~10-8 / bp Recurrent mutatons should be very rare Scaled mutaton rate parameter, e.g.: 1000 bp sequence 10-8 mutatons per base par per generaton μ 10-5 per sequence per generaton

20 Neutral Varants Varants that do not affect ftness Accumulate nexorably through tme Lost through genetc drft Do not affect genealogy

21 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?

22 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!

23 A tougher example Sample of two sequences 100 bp each How many dfferences are expected? Populaton of sze, N 1000 Mutaton rate µ 10-8 / bp / generaton µ 10-6 / 100 bp / generaton

24 Genealogy of two sequences MRCA Tme T(2) Sequence 1 Sequence 2 Mutatons between MRCA and Sequence 1?

25 Genealogy of two sequences MRCA Tme T(2) Sequence 1 Sequence 2 Total mutatons n genealogy?

26 Number of mutatons S Dstrbuted as Posson, condtonal on total tree length E(S) µe(t tot ) Var(S) µe(t tot ) + µ²var(t tot ) T tot s the total length of all branches

27 Estmatng Coalescence Tme Probablty that two sequences have dstnct ancestors n prevous generaton PP 2 NN 1 NN 1 1 NN Probablty of dstnct ancestors for t generatons s P(2) t

28 Probablty of MRCA at tme t+1 P(2) t (1 P(2)) 1 N N 1 N t 1 N 1 1 N t 1 N e 1 t N

29 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 1 Pck dstnct ancestor for sequence 2 Pck yet another ancestor for sequence 3

30 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

31 Probablty of Coalescence at Tme t+1 t N n t t e N n N n N n n P n P )) ( (1 ) (

32 Tme to next coalescent event Use an exponental dstrbuton to approxmate tme to next coalescent event Decay Rate Mean λ 1 λ n 2 N N n 2

33 T(j) For convenence, measure tme to next coalescent event n unts: N generatons for haplods 2N generatons for dplods E( T j ) 1/ j 2 How would you calculate tme to MRCA of n sequences?

34 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

35 T MRCA vs. T TOT Relatve Tme to MRCA T MRCA Relatve Sum of Branch Lengt T TOT Number of Sequences Number of Sequences

36 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

37 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 For populaton genetcsts, r s the recombnaton rate ( ) / 1/ 4 ) ( 2 ) ( n n n N T E N S E θ µ µ

38 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 For populaton genetcsts, r s the recombnaton rate ( ) / 1/ 4 ) ( 2 ) ( n n n N T E N S E θ µ µ

39 E(S) as a functon of n Expected Number of Segregatng Stes Parameters N 10,000 ndvduals μ 10-4 θ Sample Sze

40 More about S Very large varance Var( S) θ n 1 1 1/ + θ Most of the varance contrbuted by early coalescent events (.e. wth small n) 2 n 1 1 1/ 2

41 Var(S) as a functon of n Varance n Number of Segregatng Stes Parameters N 10,000 ndvduals μ 10-4 θ Sample Sze

42 Inferences about θ Could be estmated from S Dvde by expected length of genealogy ˆ θ n 1 1 S 1/ Could then be used to: Estmate N, f mutaton rate µ s known Estmate µ, f populaton sze N s known

43 ^ Var(θ) as a functon of n Varance n Estmate of Theta Parameters N 10,000 ndvduals μ 10-4 θ Sample Sze

44 Alternatve Estmator for θ Count parwse dfferences between sequences Compute average number of dfferences ~ θ n 2 1 n n S j 1 j + 1

45 Today Probablty of coalescence events Length of genealogy and ts branches Expected number of mutatons Smple estmates of θ

46 Recommended Readng Rchard R. Hudson (1990) 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 Lecture 4

Introduction to Coalescent Models. Biostatistics 666 Lecture 4 Introducton to Coalescent Models Bostatstcs 666 Lecture 4 Last Lecture Lnkage Equlbrum Expected state for dstant markers Lnkage Dsequlbrum Assocaton between neghborng alleles Expected to decrease wth dstance

More information

Particle Filters. Ioannis Rekleitis

Particle 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 information

Ensemble Evolution of Checkers Players with Knowledge of Opening, Middle and Endgame

Ensemble 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 information

Comparative Analysis of Reuse 1 and 3 in Cellular Network Based On SIR Distribution and Rate

Comparative 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 information

High Speed ADC Sampling Transients

High 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 information

MTBF PREDICTION REPORT

MTBF 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 information

ESTIMATION of population parameters in classical

ESTIMATION 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 information

Comparison of Two Measurement Devices I. Fundamental Ideas.

Comparison 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 information

MODEL ORDER REDUCTION AND CONTROLLER DESIGN OF DISCRETE SYSTEM EMPLOYING REAL CODED GENETIC ALGORITHM J. S. Yadav, N. P. Patidar, J.

MODEL 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 information

A MODIFIED DIFFERENTIAL EVOLUTION ALGORITHM IN SPARSE LINEAR ANTENNA ARRAY SYNTHESIS

A 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 information

Optimal Placement of PMU and RTU by Hybrid Genetic Algorithm and Simulated Annealing for Multiarea Power System State Estimation

Optimal 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 information

Fall 2018 #11 Games and Nimbers. A. Game. 0.5 seconds, 64 megabytes

Fall 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 information

Dynamic Optimization. Assignment 1. Sasanka Nagavalli January 29, 2013 Robotics Institute Carnegie Mellon University

Dynamic 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 information

Uncertainty in measurements of power and energy on power networks

Uncertainty 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 information

Fault Locations in Transmission Systems by Evolutionary Algorithms

Fault 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 information

Machine Learning in Production Systems Design Using Genetic Algorithms

Machine 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 information

Calculation of the received voltage due to the radiation from multiple co-frequency sources

Calculation 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 information

1 GSW Multipath Channel Models

1 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 information

A NSGA-II algorithm to solve a bi-objective optimization of the redundancy allocation problem for series-parallel systems

A 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 information

problems palette of David Rock and Mary K. Porter 6. A local musician comes to your school to give a performance

problems 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 information

The genealogical history of a population The coalescent process. Identity by descent Distribution of pairwise coalescence times

The 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 information

Review: Our Approach 2. CSC310 Information Theory

Review: 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 information

Localization of FACTS Devices for Optimal Power Flow Using Genetic Algorithm

Localization 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 information

Intelligent and Robust Genetic Algorithm Based Classifier

Intelligent 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 information

TECHNICAL 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 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 information

Queen Bee genetic optimization of an heuristic based fuzzy control scheme for a mobile robot 1

Queen 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 information

Revision of Lecture Twenty-One

Revision 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 information

Control Chart. Control Chart - history. Process in control. Developed in 1920 s. By Dr. Walter A. Shewhart

Control 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 information

Open Access Node Localization Method for Wireless Sensor Networks Based on Hybrid Optimization of Differential Evolution and Particle Swarm Algorithm

Open 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 information

A 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 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 information

NEW EVOLUTIONARY PARTICLE SWARM ALGORITHM (EPSO) APPLIED TO VOLTAGE/VAR CONTROL

NEW 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 information

Evolving Crushers. P. Hingston L. Barone L. While

Evolving 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 information

Information-Theoretic Comparison of Channel Capacity for FDMA and DS-CDMA in a Rayleigh Fading Environment

Information-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 information

Utility-based Routing

Utility-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 information

Safety and resilience of Global Baltic Network of Critical Infrastructure Networks related to cascading effects

Safety 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 information

PRACTICAL, COMPUTATION EFFICIENT HIGH-ORDER NEURAL NETWORK FOR ROTATION AND SHIFT INVARIANT PATTERN RECOGNITION. Evgeny Artyomov and Orly Yadid-Pecht

PRACTICAL, 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 information

Coverage Maximization in Mobile Wireless Sensor Networks Utilizing Immune Node Deployment Algorithm

Coverage 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 information

A Comparison of Two Equivalent Real Formulations for Complex-Valued Linear Systems Part 2: Results

A 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 information

Joint Power Control and Scheduling for Two-Cell Energy Efficient Broadcasting with Network Coding

Joint 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 information

A Simple Satellite Exclusion Algorithm for Advanced RAIM

A 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 information

Downloaded from ijiepr.iust.ac.ir at 5:13 IRST on Saturday December 15th 2018

Downloaded 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 information

Multiple Robots Formation A Multiobjctive Evolution Approach

Multiple 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 information

Key-Words: - Automatic guided vehicles, Robot navigation, genetic algorithms, potential fields

Key-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 information

Performance Study of OFDMA vs. OFDM/SDMA

Performance 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 information

Forecasting Stock Returns using Evolutionary Artificial Neural Networks 1

Forecasting 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 information

Network Theory. EC / EE / IN. for

Network 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 information

Adaptive Phase Synchronisation Algorithm for Collaborative Beamforming in Wireless Sensor Networks

Adaptive 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 information

Investigation of Hybrid Particle Swarm Optimization Methods for Solving Transient-Stability Constrained Optimal Power Flow Problems

Investigation 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 information

NATIONAL RADIO ASTRONOMY OBSERVATORY Green Bank, West Virginia SPECTRAL PROCESSOR MEMO NO. 25. MEMORANDUM February 13, 1985

NATIONAL 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 information

A High-Sensitivity Oversampling Digital Signal Detection Technique for CMOS Image Sensors Using Non-destructive Intermediate High-Speed Readout Mode

A 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 information

PSO and ACO Algorithms Applied to Location Optimization of the WLAN Base Station

PSO 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 information

N( E) ( ) That is, if the outcomes in sample space S are equally likely, then ( )

N( 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 information

Modelling Service Time Distribution in Cellular Networks Using Phase-Type Service Distributions

Modelling 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 information

Solving Haplotype Assembly Problem Using Harmony Search

Solving 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 information

Research on the Process-level Production Scheduling Optimization Based on the Manufacturing Process Simplifies

Research 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 information

ASFALT: Ā S imple F āult-tolerant Signature-based L ocalization T echnique for Emergency Sensor Networks

ASFALT: 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 information

Digital Transmission

Digital 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 information

Queuing-Based Dynamic Channel Selection for Heterogeneous Multimedia Applications over Cognitive Radio Networks

Queuing-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 information

A Genetic Algorithm Based Multi Objective Service Restoration in Distribution Systems

A 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 information

Define Y = # of mobiles from M total mobiles that have an adequate link. Measure of average portion of mobiles allocated a link of adequate quality.

Define 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 information

On Operational Availability of a Large Software-Based Telecommunications System

On 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 information

USE OF GPS MULTICORRELATOR RECEIVERS FOR MULTIPATH PARAMETERS ESTIMATION

USE 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 information

Guidelines for CCPR and RMO Bilateral Key Comparisons CCPR Working Group on Key Comparison CCPR-G5 October 10 th, 2014

Guidelines 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 information

An Optimal Model and Solution of Deployment of Airships for High Altitude Platforms

An 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 information

NOVEL ITERATIVE TECHNIQUES FOR RADAR TARGET DISCRIMINATION

NOVEL 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 information

Finding Proper Configurations for Modular Robots by Using Genetic Algorithm on Different Terrains

Finding 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 information

COGNITIVE RADIO ENGINE MODEL UTILIZING SOFT FUSION BASED GENETIC ALGORITHM FOR COOPERATIVE SPECTRUM OPTIMIZATION

COGNITIVE 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 information

ph fax

ph 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 information

COMPARISION OF POTENTIAL PATHS SELECTED BY A MALICIOUS ENTITY WITH HAZARDOUS MATERIALS : MINIMIZATION OF TIME VS. MINIMIZATION OF DISTANCE

COMPARISION 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 information

FEATURE SELECTION FOR SMALL-SIGNAL STABILITY ASSESSMENT

FEATURE 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 information

Algorithms for Genetics: Basics of Wright Fisher Model and Coalescent Theory

Algorithms 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 information

A Predictive QoS Control Strategy for Wireless Sensor Networks

A 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 information

1.0 INTRODUCTION 2.0 CELLULAR POSITIONING WITH DATABASE CORRELATION

1.0 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 information

Development and Performance Evaluation of Mismatched Filter using Differential Evolution

Development 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 information

Power Minimization Under Constant Throughput Constraint in Wireless Networks with Beamforming

Power 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 information

Optimization of Shortest Path of Multiple Transportation Model Based on Cost Analyses

Optimization 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 information

The Impact of Spectrum Sensing Frequency and Packet- Loading Scheme on Multimedia Transmission over Cognitive Radio Networks

The 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 information

Distributed Uplink Scheduling in EV-DO Rev. A Networks

Distributed 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 information

Opportunistic Beamforming for Finite Horizon Multicast

Opportunistic 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 information

A Fuzzy-based Routing Strategy for Multihop Cognitive Radio Networks

A 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 information

Approximating User Distributions in WCDMA Networks Using 2-D Gaussian

Approximating 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 information

Multichannel Frequency Comparator VCH-315. User Guide

Multichannel 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 information

ROBUST IDENTIFICATION AND PREDICTION USING WILCOXON NORM AND PARTICLE SWARM OPTIMIZATION

ROBUST 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 information

Hybrid Differential Evolution based Concurrent Relay-PID Control for Motor Position Servo Systems

Hybrid 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 information

Topology Control for C-RAN Architecture Based on Complex Network

Topology 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 information

Mooring Cost Sensitivity Study Based on Cost-Optimum Mooring Design

Mooring 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 information

To: Professor Avitabile Date: February 4, 2003 From: Mechanical Student Subject: Experiment #1 Numerical Methods Using Excel

To: 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 information

On Evolutionary Programming for Channel Equalization

On Evolutionary Programming for Channel Equalization On Evolutonary Programmng for Channel Equalzaton ADINA BURIAN, ARTO KANTSILA, MIKKO LEHTOKANGAS, JUKKA SAARINEN Dgtal and Computer Systems Laboratory Tampere Unversty of Technology P.O. BOX 553, FIN-33101,

More information

Population Genetics using Trees. Peter Beerli Genome Sciences University of Washington Seattle WA

Population Genetics using Trees. Peter Beerli Genome Sciences University of Washington Seattle WA Population Genetics using Trees Peter Beerli Genome Sciences University of Washington Seattle WA Outline 1. Introduction to the basic coalescent Population models The coalescent Likelihood estimation of

More information

Application of Intelligent Voltage Control System to Korean Power Systems

Application 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 information

A novel immune genetic algorithm based on quasi-secondary response

A novel immune genetic algorithm based on quasi-secondary response 12th AIAA/ISSMO Multdscplnary Analyss and Optmzaton Conference 10-12 September 2008, Vctora, Brtsh Columba Canada AIAA 2008-5919 A novel mmune genetc algorthm based on quas-secondary response Langyu Zhao

More information

Uplink User Selection Scheme for Multiuser MIMO Systems in a Multicell Environment

Uplink User Selection Scheme for Multiuser MIMO Systems in a Multicell Environment Uplnk User Selecton Scheme for Multuser MIMO Systems n a Multcell Envronment Byong Ok Lee School of Electrcal Engneerng and Computer Scence and INMC Seoul Natonal Unversty leebo@moble.snu.ac.kr Oh-Soon

More information

Rational Secret Sharing without Broadcast

Rational 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 information

Resource Control for Elastic Traffic in CDMA Networks

Resource Control for Elastic Traffic in CDMA Networks Resource Control for Elastc Traffc n CDMA Networks Vaslos A. Srs Insttute of Computer Scence, FORTH Crete, Greece vsrs@cs.forth.gr ACM MobCom 2002 Sep. 23-28, 2002, Atlanta, U.S.A. Funded n part by BTexact

More information

Traffic balancing over licensed and unlicensed bands in heterogeneous networks

Traffic 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 information

Analog Circuit Design with Variable Length Chromosomes

Analog 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 information

A Preliminary Study of Information Collection in a Mobile Sensor Network

A Preliminary Study of Information Collection in a Mobile Sensor Network A Prelmnary Study of Informaton ollecton n a Moble Sensor Network Yuemng Hu, Qng L ollege of Informaton South hna Agrcultural Unversty {ymhu@, lqng1004@stu.}scau.edu.cn Fangmng Lu, Gabrel Y. Keung, Bo

More information

Priority based Dynamic Multiple Robot Path Planning

Priority based Dynamic Multiple Robot Path Planning 2nd Internatonal Conference on Autonomous obots and Agents Prorty based Dynamc Multple obot Path Plannng Abstract Taxong Zheng Department of Automaton Chongqng Unversty of Post and Telecommuncaton, Chna

More information

Traffic Modeling and Performance Evaluation in GSM/GPRS Networks

Traffic Modeling and Performance Evaluation in GSM/GPRS Networks Proceedngs of the 3th WSEAS Internatonal Conference on COMMUNICATIONS Traffc Modelng and Performance Evaluaton n GSM/ Networks Cornel Balnt, Georgeta Budura, Marza Eugen Poltehnca Unversty of Tmsoara Bd..

More information

A Tool for Evolving Artificial Neural Networks

A 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 information