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Tap clearance 100%

E25UNF1"1/4 E25UNF1/2 E25UNF1/4 E25UNF3/4 E25UNF5/16 E25UNF7/16 M10 LEFT HAND Metric Coarse Machine M10 Metric Coarse Machine Taps M10 Metric Coarse Machine Taps M2 Metric Coarse Machine Taps M2.5 Metric Coarse Machine Taps M3 Metric Coarse Machine Taps M3 Metric Coarse Machine Taps M4 Metric Coarse Machine Taps M4 Metric Coarse Machine Taps M4 LEFT HAND Metric Coarse Machine M4 Metric Coarse Machine Taps M4 Metric Coarse Machine Taps M5 Metric Coarse Machine Taps M5 LEFT HAND Metric Coarse Machine M5 Metric Coarse Machine Taps M5 Metric Coarse Machine Taps M6 Metric Coarse Machine Taps M6 Metric Coarse Machine Taps M6 LEFT HAND Metric Coarse Machine M6 Metric Coarse Machine Taps M8 Metric Coarse Machine Taps M8 LEFT HAND Metric Coarse Machine M8 Metric Coarse Machine Taps M8 Metric Coarse Machine Taps M10X1 Metric Fine Machine Taps M10X1.25 Metric Fine Machine Taps 6-32 UNC Machine Taps 832 UNC Machine Taps 10-32 UNF Machine Taps 1/4 UNF Machine Taps 6-40 UNF Machine Taps 8-36 UNF Machine Taps M12 Metric Coarse Machine Taps M12 Metric Coarse Machine Taps M12 LEFT HAND Metric Coarse Machine M12 Metric Coarse Machine Taps M12 Metric Coarse Machine Taps M14 Metric Coarse Machine Taps M14 Metric Coarse Machine Taps M14 LEFT HAND Metric Coarse Machine M14 Metric Coarse Machine Taps M14 Metric Coarse Machine Taps M16 Metric Coarse Machine Taps M16 LEFT HAND Metric Coarse Machine M16 Metric Coarse Machine Taps M16 Metric Coarse Machine Taps M18 Metric Coarse Machine Taps M18 Metric Coarse Machine Taps M20 Metric Coarse Machine Taps M20 Metric Coarse Machine Taps M12X1.5 Metric Fine Machine Taps M14X1.5 Metric Fine Machine Taps M27X1.5 Metric Fine Machine Taps UNC Machine Taps 1/2 UNC Machine Taps 3/4 UNC Machine Taps 5/16 UNC Machine Taps 7/16 UNC Machine Taps UNF Machine Taps UNF Machine Taps 1/2 UNF Machine Taps 1/4 UNF Machine Taps 3/4 UNF Machine Taps 5/16 UNF Machine Taps 7/16 UNF Machine Taps £19.99 £15.78 £10.48 £11.91 £11.91 £8.02 £9.54 £8.02 £13.62 £15.15 £12.33 £9.54 £8.02 £15.15 £13.18 £9.60 £8.02 £13.93 £15.15 £13.18 £8.18 £17.22 £13.26 £8.70 £13.39 £12.94 £10.54 £10.54 £11.73 £13.29 £11.58 £11.58 £13.49 £23.28 £25.72 £21.66 £14.10 £17.82 £29.70 £33.06 £26.84 £18.42 £33.45 £33.06 £29.86 £20.23 £40.69 £40.69 £35.16 £46.48 £15.54 £19.75 £75.93 £98.84 £20.82 £35.53 £12.17 £16.73 £64.34 £103.78 £22.91 £13.29 £39.05 £13.38 £18.42 £2.50 £1.97 £1.31 £1.49 £1.49 £1.00 £1.19 £1.00 £1.70 £1.89 £1.54 £1.19 £1.00 £1.89 £1.65 £1.20 £1.00 £1.74 £1.89 £1.65 £1.02 £2.15 £1.66 £1.09 £1.67 £1.62 £1.32 £1.32 £1.47 £1.66 £1.45 £1.45 £1.69 £2.91 £3.22 £2.71 £1.76 £2.23 £3.71 £4.13 £3.36 £2.30 £4.18 £4.13 £3.73 £2.53 £5.09 £5.09 £4.40 £5.81 £1.94 £2.47 £9.49 £12.36 £2.60 £4.44 £1.52 £2.09 £8.04 £12.97 £2.86 £1.66 £4.88 £1.67 £2.30 E60M10LH E60M10T E60M2.5T E60M2.5TXC E60M2T E60M2TXC E60M3 E60M3LH E60M3T E60M3TXC E60M4LH E60M4T E60M4TXC E60M5LH E60M5T E60M5TXC E60M6 E60M6LH E60M6T E60M6TXC E60M8 E60M8LH E60M8T E60M8TXC E60UNC10-24 E60UNC1/4 E60UNC6-32 E60UNC8-32 E60UNF10-32 E60UNF1/4 E60UNF6-40 E60UNF8-36 E61M12LH E61M12T E61M12TXC E61M14 E61M14LH E61M14TXC E61M16 E61M16LH E61M20 E61M20LH E61M30 E61MF12X1.25 E61MF22X1.5 E61MF27X1.5 E61UNC1"

https://www.pdf-archive.com/2015/05/29/tap-clearance/

29/05/2015 www.pdf-archive.com

05633842 96%

They used metric tools and methods to be able to get the software characteristics and compare them with other software applications or with standards.

https://www.pdf-archive.com/2011/09/08/05633842/

08/09/2011 www.pdf-archive.com

IJWLTT Alsmadi 95%

They used metric tools and methods to be able to get the software characteristics and compare them with known standards.

https://www.pdf-archive.com/2011/10/30/ijwltt-alsmadi/

30/10/2011 www.pdf-archive.com

2015 Mitsubishi Hitachi US 93%

3 NEW ITEMS 0” 10” | IASPV/ASPV Face Mill Style Shank Style 3.0 PAGE Modular Style | 2.0” - 2.5” SIZE RANGE 2.0” - 6.0” PROJECTION 0.625” - 1.5” SIZE RANGE 1.25” - 2.0” PROJECTION 0.625” - 1.5” SIZE RANGE 2.0” - 7.0” PROJECTION 39 0” 10” | 6.0 Face Mill Style | SIZE RANGE 2.5” - 6.0” PROJECTION 2.0” - 6.0” 10° ∼  30° IASDF 3.0 IASM/ASM IRV/RV IASM/ASM POCKET MILLING APPLICATION POCKET MILLING APPLICATION PAGE 49 metric only Shank Style PAGE PAGE PAGE 59 59 r5 r6 PAGE PAGE PAGE SIZE RANGE RANGE SIZE | MODULAR IARPF/ARPF IARPF/ARPF SHANK || || 0.375” -|- 0.75” 0.75” | |0.375” || | PROJECTION PROJECTION SIZE RANGE || || || || | | | | | 0.394” - 0.787” SIZE RANGE PROJECTION | 1.5” - 3.0” 1.75” -- 7.0” 7.0” 1.75” 1.0” - 1.5” 5.5” - 6.0” PROJECTION metric only | 2.0” - 6.0” 1.75” - 7.0” SIZE RANGE Modular Style 10”| | 10” 10” 0.75” - 4.0” 0.394” -- 0.787” 0.787” 0.394” PROJECTION SIZE RANGE RANGE PROJECTION SIZE PROJECTION PROJECTION || 0.75” -- 4.0” 4.0” 0.75” 0.375” - 0.75” PROJECTION 0” SIZE RANGE RANGE | SIZE 1.0” - 1.5” 2.0” - 7.0” 76 62 76 0” 0” ||| 0” Face Mill Style Face Mill Style metric only Style Face Mill SIZE RANGE RANGE SIZE SIZE RANGE | PROJECTION PROJECTION SIZE RANGE PROJECTION Shank Shank Style Style metric Shank Style metric only only metric only PROJECTION SIZE RANGE RANGE SIZE SIZE RANGE PROJECTION PROJECTION SIZE RANGE PROJECTION metric only Modular Modular Style Style metric Modular metric only onlyStyle PROJECTION SIZE RANGE RANGE SIZE SIZE RANGE PROJECTION PROJECTION SIZE RANGEN PROJECTIO metric only || || || || | | | | || || 1.969” | - 3.937” | 1.969” - 3.937” 2.0” - 4.0” || || || | | | Shank Style Shank Style Modular Style metric onlyStyle Modular Modular Style metric only | 2.0” - 6.0” 2.0” - 6.0” 0.984” - 1.575” 0.984” --1.575” 0.984” 1.575” 1.0” -- 4.0” 4.0” 1.0” 0.984” - 1.575” 1.0” - 4.0” 1.0” - 4.0” 0.984” -- 1.260” 1.260” 0.984” 0.984” - 1.260” 5.5” -- 7.0” 7.0” 5.5” 0.984” - 1.260” 5.5” - 7.0” 5.5” - 7.0” 0” 10” 0” || 0” 10” || 10” | SIZE RANGE RANGE SIZE 10” 10” || 10”| 2.0” -- 6.0” 6.0” 1.969” - 3.937” 2.0” PROJECTION FINISHING FINISHING APPLICATION APPLICATION 4 || 53 SIDE SIDE MILLING MILLING APPLICATION APPLICATION AHU IAHU/AHU AHU Shank Style Shank Style Modular Style metric only Modular Face MillStyle Style 0” || 0” | | || || || || || || || || 0.375”| -- 1.0” 1.0” | | 0.375” || | | | | | | PROJECTION PROJECTION SIZE RANGE 0.375” - 1.0” PROJECTION SIZE RANGE RANGE SIZE SIZE RANGE RANGE PROJECTION PROJECTION SIZE 0.787” -- 0.984” 0.984” 0.787” | 2.0” -- 5.0” 5.0” 2.0” 2.0” - 5.0” 0.25” - 1.5” 0.787” - 0.984” 2.0” -- 7.0” 7.0” 2.0” 3.0” 2.0” - 7.0” PROJECTION PROJECTION - 8.0” 163 PAGE PAGE PAGE 86 86 Shank Style Shank Style Modular Style SIZE RANGE RANGE SIZE 0” || 0” || || || || || || || || || 10” || 10” 0.313” 1.0” | | 0.313” | -- 1.0” | | | | | | Ltd.| ©| 2015 Mitsubishi Hitachi Tool Engineering, PROJECTION SIZE RANGE PROJECTION PROJECTION SIZE RANGE RANGE SIZE 0.313” - 1.0” 0.787”- 0.984” 0.984” 0.787”- 2.0” -- 7.0” 7.0” 2.0” 2.0” - 7.0” APPLICATION TOOL LIST FACE MILLING APPLICATION 0” IASF/ASF Face Mill Style PAGE 10” | | PROJECTION | | | | | | | | | | | | | | | | 70 07 Face Mill Style Shank Style | | | 1.25” - 1.5” SIZE RANGE PROJECTION 1.75” - 2.75” 17 80 IASRT Face Mill Style | | | | | | | 2.0” - 4.0” PROJECTION 2.0” - 6.0” 21 84 | Face Mill Style Shank Style IASR/ASR MULTI 10” | SIZE RANGE 0” Modular Style metric only SIZE RANGE | | | | | | PROJECTION SIZE RANGE 2.0” - 6.0” 0.625” - 1.5” PROJECTION SIZE RANGE | 2.0” - 2.5” 2.0” - 5.0” 0.630” - 1.575” PROJECTION 2.0” - 7.0” 25 88 Multi Flute High Feed Type Economical Type Programming Radius Long Projection High Precision Multi Flute | 2.0” - 6.0” PROJECTION | PAGE 10” 2.0” - 4.0” SIZE RANGE 0” PAGE | 4.0” - 8.0” | IASRF | 2.5” - 10.0” SIZE RANGE 0” PAGE | High Feed Type Economical Type Projection High Precision 2013 Programming © 2009 Hitachi ToolRadius Engineering, Ltd.

https://www.pdf-archive.com/2015/10/23/2015-mitsubishi-hitachi-us/

23/10/2015 www.pdf-archive.com

10.1.1.133.5904 93%

Metric tools achieve this by gathering and analyzing the software or the application through a metric tool.

https://www.pdf-archive.com/2011/09/14/10-1-1-133-5904/

14/09/2011 www.pdf-archive.com

bare conf 90%

E XTENDED R ESULTS 0.95 Specificity In Table I we present the sensitivity and specificity for each studied correlation metric.

https://www.pdf-archive.com/2015/07/28/bare-conf/

28/07/2015 www.pdf-archive.com

final report on personal site assignment 88%

 I   am  unsure  as  to  the  reasoning  why  Google’s  metric  system  did  not  track  correctly,  but  I  will  be  analyzing   Alex Osborne MC3504;

https://www.pdf-archive.com/2013/05/02/final-report-on-personal-site-assignment/

02/05/2013 www.pdf-archive.com

End of Semester 1 Evaluation - Andrew Rausch 87%

Werner H. Kirsten Student Intern Program Student Evaluation Intern:

https://www.pdf-archive.com/2018/02/10/end-of-semester-1-evaluation-andrew-rausch/

10/02/2018 www.pdf-archive.com

J M T - Hero Synergies - DOTABUFF - Dota 2 Stats 87%

7/31/2015 J M T - Hero Synergies - DOTABUFF - Dota 2 Stats  DOTABUFF  errgh  JMT Hero Synergies 19 minutes ago 877 ‑ 785 ‑ 31 51.80% LAST MATCH RECORD  GIFT  FOLLOW Overview Matches WIN RATE  ESPORTS PROFILE Matchups More ▾ LAST 3 MONTHS, ALL SKILL BRACKETS, ALL LOBBIES, ALL MODES, ANY FACTION, ANY DURATION, SIGNIFICANT Last 3 Months ▾ Any Faction ▾ All Lobbies Hero Synergies ▾ All Heroes ▾ All Modes ▾ All Skill Brackets Any Duration ▾ ▾ More ▾ Hero Win Rate With Matches Played Visage 100.00% 3 Brewmaster 100.00% 1 Shadow Shaman 85.71% 7 Phantom Assassin 83.33% 6 Crystal Maiden 81.82% 22 Enchantress 80.00% 5 Chaos Knight 80.00% 5 Treant Protector 80.00% 5 Sand King 77.78% 9 Drow Ranger 75.00% 4 Alchemist 75.00% 4 Terrorblade 75.00% 4 Bristleback 71.43% 14 http://www.dotabuff.com/players/119608468/matchups?metric=hero_synergies 1/6 7/31/2015 J M T - Hero Synergies - DOTABUFF - Dota 2 Stats Disruptor 70.00% 10 Centaur Warrunner 66.67% 9 Templar Assassin 66.67% 12 Spectre 66.67% 9 Kunkka 66.67% 6 Elder Titan 66.67% 3 Lycan 66.67% 3 Oracle 66.67% 3 Morphling 66.67% 3 Wraith King 66.67% 9 Vengeful Spirit 64.71% 17 Naga Siren 62.50% 16 Viper 62.50% 8 Lifestealer 62.50% 8 Phoenix 61.54% 13 Ember Spirit 61.54% 13 Leshrac 61.29% 31 Night Stalker 60.00% 5 Axe 60.00% 15 Tusk 60.00% 15 Silencer 60.00% 10 Lone Druid 60.00% 5 Undying 58.82% 17 Jakiro 58.33% 12 http://www.dotabuff.com/players/119608468/matchups?metric=hero_synergies 2/6 7/31/2015 J M T - Hero Synergies - DOTABUFF - Dota 2 Stats Windranger 58.33% 36 Timbersaw 58.33% 12 Lina 57.69% 26 Anti‑Mage 57.63% 59 Ogre Magi 57.14% 14 Omniknight 57.14% 7 Tiny 57.14% 7 Magnus 56.25% 16 Shadow Fiend 55.88% 34 Earth Spirit 55.56% 9 Dazzle 55.56% 9 Spirit Breaker 55.00% 20 Necrophos 54.55% 11 Zeus 53.85% 13 Bloodseeker 53.85% 39 Mirana 52.38% 21 Meepo 50.00% 4 Dragon Knight 50.00% 8 Phantom Lancer 50.00% 20 Weaver 50.00% 10 Abaddon 50.00% 10 Tinker 50.00% 8 Beastmaster 50.00% 4 Storm Spirit 49.25% 67 http://www.dotabuff.com/players/119608468/matchups?metric=hero_synergies 3/6 7/31/2015 J M T - Hero Synergies - DOTABUFF - Dota 2 Stats Legion Commander 47.83% 23 Rubick 47.37% 19 Skywrath Mage 47.06% 17 Lion 46.43% 28 Earthshaker 46.43% 28 Faceless Void 46.15% 13 Huskar 46.15% 13 Techies 45.95% 37 Witch Doctor 45.45% 11 Bounty Hunter 44.44% 36 Ancient Apparition 44.44% 9 Ursa 43.75% 16 Broodmother 42.86% 7 Clockwerk 42.86% 21 Riki 42.86% 7 Nature's Prophet 42.11% 19 Pudge 41.67% 24 Enigma 40.00% 10 Sniper 40.00% 5 Outworld Devourer 40.00% 5 Medusa 40.00% 10 Sven 40.00% 10 Slark 38.89% 18 Juggernaut 38.89% 18 http://www.dotabuff.com/players/119608468/matchups?metric=hero_synergies 4/6 7/31/2015 J M T - Hero Synergies - DOTABUFF - Dota 2 Stats 37.50% 8 Lich 37.50% 16 Invoker 36.36% 11 Keeper of the Light 36.36% 11 Clinkz 36.36% 11 Queen of Pain 35.71% 28 Gyrocopter 33.33% 30 Batrider 33.33% 6 Luna 33.33% 3 Nyx Assassin 30.77% 13 Winter Wyvern 28.57% 14 Bane 28.57% 7 Warlock 25.00% 4 Venomancer 25.00% 8 Slardar 20.00% 5 Pugna 20.00% 5 Tidehunter 16.67% 6 Dark Seer 12.50% 8 Troll Warlord 0.00% 2 Death Prophet 0.00% 2 Puck 0.00% 2 Doom 0.00% 1 Shadow Demon 0.00% 4 Io http://www.dotabuff.com/players/119608468/matchups?metric=hero_synergies 5/6

https://www.pdf-archive.com/2015/08/01/j-m-t-hero-synergies-dotabuff-dota-2-stats/

01/08/2015 www.pdf-archive.com

04021350 84%

A software metric tool helps us know the required information to build such models.

https://www.pdf-archive.com/2011/09/08/04021350/

08/09/2011 www.pdf-archive.com

Examples of Symplectic Manifolds (22) 84%

Let us consider a Riemannian metric h and define ∀q ∈ M , ∀X, Y ∈ Tq M , g(X, Y ) = h(X, Y ) + h(JX, JY ) The Riemannian metric g verifies g(X, Y ) = g(JX, JY ).

https://www.pdf-archive.com/2019/02/04/examplesofsymplecticmanifolds-22/

04/02/2019 www.pdf-archive.com

Final Order 2008 Electric SQ 1-26-11 82%

Nantucket Electric Company d/b/a National Grid (“Nantucket Electric”) reports that it failed to meet its benchmark in its SAIDI, Lost Work-Time Accident Rate, and Service Appointments Met metrics, but exceeded its benchmark in the Consumer Division Cases metric, resulting in an offset.

https://www.pdf-archive.com/2011/02/26/final-order-2008-electric-sq-1-26-11/

26/02/2011 www.pdf-archive.com

CV, Misha Tsvik, 2020 81%

ONBOARDING 01/2019 - 04/2020 (1 yr 4 mos) Revolut, https://revolut.com/business London, United Kingdom For the 2019 year, Revolut Business has grown 4 times (and became the biggest player on the market) — our main target metric was a number of new businesses per day (successfully onboarded and activated).

https://www.pdf-archive.com/2020/05/07/cv-misha-tsvik-2020/

07/05/2020 www.pdf-archive.com

notes 81%

The minimal compactification N p,q is equipped with the seimi-Riemannian metric.

https://www.pdf-archive.com/2016/01/23/notes/

23/01/2016 www.pdf-archive.com

Overview of Mathematics 81%

scalar product Add commutativity Add inverse METRIC MANIFOLDS COMPLEX MANIFOLDS HILBERT SPACES Define charts and atlases REAL Add ordering, least upper bound NUMBERS property Define .

https://www.pdf-archive.com/2016/01/07/overview-of-mathematics/

07/01/2016 www.pdf-archive.com

dissertation 81%

  Modelling the flight of starlings  By  Simon Byford ‐ sjb17u@cs.nott.ac.uk  Supervised by  Dr. Jason Atkin ‐ jaa@cs.nott.ac.uk      School of Computer Science  University of Nottingham      Submitted May 2011, in partial fulfilment of the conditions of the award of the degree:  BSc (Hons) Mathematics and Computer Science  I hereby declare that this dissertation is all my own work, except as indicated in the text  Signature:      May 6th, 2011  Abstract    A  project  was  undertaken  to  build  a  software  model  capable  of  accurately  simulating  the flocking behaviour of starlings. After reviewing the relevant literature and studying  the mechanics of flocking, such a model was carefully designed and implemented in the  Java  programming  language.  The  model  is  capable  of  exhibiting  a  range  of  flocking  behaviours  with  simulations  comprising  upwards  of  200  individual  birds.  A  great  number of behavioural parameters are available to edit before and during simulations,  where  their  effects  can  be  viewed  in  real  time.  The  ability  to  spawn  virtual  falcons  as  well as starlings introduces the notion of a predator which is an area largely unexplored  in  previous  models.  A  number  of  interesting  observations  were  made  during  the  analysis phase of this project, including the fact that simulations employing metric and  topological distances induce much the same flocking behaviour, and that the application  can  typically  handle  simulations  comprising  up  to  500  individual  birds  before  experiencing  significant  drops  in  performance.  In  summary,  the  project  was  deemed  highly successful and a number of possible future extensions were proposed.    1      Table of contents  Abstract ................................................................................................................................................... 1  1 ‐ Introduction and motivation .............................................................................................................. 5  1.1 ‐ Aims and objectives .................................................................................................................... 5  1.2 ‐ Motivation .................................................................................................................................. 6  2 ‐ Related work ...................................................................................................................................... 7  2.1 ‐ Literature .................................................................................................................................... 7  2.1.1 ‐ Flocks, Herds, and Schools: A Distributed Behavioral Model .............................................. 7  2.1.2 ‐ An empirical study of large, naturally occurring starling flocks: a benchmark in collective  animal behaviour ............................................................................................................................ 8  2.1.3 ‐ Self‐organised complex aerial displays of thousands of starlings: a model ........................ 8  2.1.4 ‐ Interaction ruling animal collective behavior depends on topological rather than metric  distance: Evidence from a field study ............................................................................................. 9  2.1.5 ‐ Steering Behaviors for Autonomous Characters ................................................................. 9  2.1.6 ‐ An efficient algorithm to find k‐nearest neighbours in flocking behaviour ....................... 10  2.1.7 ‐ Aerial flocking patterns of wintering starlings, Sturnus vulgaris, under different predation  risk ................................................................................................................................................. 10  2.1.8 ‐ Parallel Bird Flocking Simulation ........................................................................................ 10  2.1.9 ‐ Simulating and Visualizing Natural Flocking Behaviour ..................................................... 11  2.1.10 ‐ Less related work ............................................................................................................. 11  2.2 ‐ Models ...................................................................................................................................... 12  2.2.1 ‐ Boids model ....................................................................................................................... 12  2.2.2 ‐ NetLogo Flocking model .................................................................................................... 13  2.2.3 ‐ 3D Flocking Boids II ............................................................................................................ 14  2.3 ‐ Other sources ............................................................................................................................ 14  3 ‐ Some theory ..................................................................................................................................... 15  3.1 ‐ The three urges ......................................................................................................................... 15  3.1.1 ‐ Separation .......................................................................................................................... 15  3.1.2 ‐ Alignment ........................................................................................................................... 15  3.1.3 ‐ Cohesion ............................................................................................................................ 15  3.2 ‐ Additional urges ........................................................................................................................ 16  3.2.1 ‐ Predator avoidance ............................................................................................................ 16  3.2.2 ‐ Randomness ....................................................................................................................... 16  3.2.3 ‐ Migration and obstacle avoidance ..................................................................................... 16  3.3 ‐ Combining urges ....................................................................................................................... 17  2    3.4 ‐ Steering processing chains ........................................................................................................ 18  3.4.1 ‐ Falcons ............................................................................................................................... 19  3.4.2 ‐ Starlings .............................................................................................................................. 20  3.5 ‐ Metric vs topological distance .................................................................................................. 21  4 ‐ Description of the work ................................................................................................................... 23  5 ‐ Design............................................................................................................................................... 26  5.1 ‐ Language, libraries and platform .............................................................................................. 26  5.2 ‐ Prototyping ............................................................................................................................... 27  5.3 ‐ GUI Design................................................................................................................................. 28  5.4 ‐ Class diagram ............................................................................................................................ 31  6 ‐ Implementation ............................................................................................................................... 32  6.1 ‐ Design changes ......................................................................................................................... 32  6.1.1 ‐ Awareness circle ................................................................................................................ 32  6.1.2 ‐ Save/load functionality ...................................................................................................... 33  6.1.3 ‐ Removal of viewing angle attribute ................................................................................... 33  6.1.4 ‐ Anti‐aliasing ....................................................................................................................... 33  6.1.5 ‐ FPS counter ........................................................................................................................ 34  6.1.6 ‐ Sizable window .................................................................................................................. 34  6.2 ‐ Classes ....................................................................................................................................... 35  6.2.1 ‐ AwarenessCircle ................................................................................................................. 35  6.2.2 ‐ Bird ..................................................................................................................................... 35  6.2.3 ‐ DynamicSimProperties ....................................................................................................... 36  6.2.4 ‐ FPSCounter......................................................................................................................... 36  6.2.5 ‐ Falcon ................................................................................................................................. 37  6.2.6 ‐ FlockManager .................................................................................................................... 38  6.2.7 ‐ GUIPanel ............................................................................................................................ 41  6.2.8‐ SimDims .............................................................................................................................. 42  6.2.9‐ SimulationManager ............................................................................................................ 42  6.2.10 ‐ SimulationPanel ............................................................................................................... 43  6.2.11 ‐ Starling ............................................................................................................................. 43  6.2.12 ‐ StaticSimProperties .......................................................................................................... 44  6.2.13 ‐ Window ............................................................................................................................ 44  6.3 ‐ Algorithms of interest ............................................................................................................... 46  6.3.1 ‐ Calculating the distance between birds ............................................................................. 46  3    6.3.2 ‐ Calculating the average bearing ........................................................................................ 47  6.3.3 ‐ Calculating the nearest n birds (topological distance) ...................................................... 49  6.3.4 ‐ Drawing the "awareness circle" ......................................................................................... 50  6.4 ‐ Notable problems faced ........................................................................................................... 51  6.4.1 ‐ Bias towards flocking in one particular direction .............................................................. 51  6.5 ‐ Testing ....................................................................................................................................... 52  6.5.1 ‐ “Continuous testing”.......................................................................................................... 52  6.5.2 ‐ Unit testing ........................................................................................................................ 52  7 ‐ Analysis and evaluation ................................................................................................................... 53  7.1 ‐ Analysis ..................................................................................................................................... 53  7.1.1 ‐ Tests involving starlings ..................................................................................................... 53  7.1.2 ‐ Tests involving starlings and falcons .................................................................................. 62  7.1.3 ‐ Metric vs topological distance ........................................................................................... 67  7.1.4 ‐ Performance testing .......................................................................................................... 68  7.2 ‐ Evaluation ................................................................................................................................. 70  8 ‐ Summary and further work .............................................................................................................. 74  8.1 ‐ Summary ................................................................................................................................... 74  8.2 ‐ Further work ............................................................................................................................. 75  8.2.1 ‐ 3D modelling ...................................................................................................................... 75  8.2.2 ‐ Obstacles ............................................................................................................................ 75  8.2.3 ‐ Walls................................................................................................................................... 75  8.2.4 ‐ More intelligent steering algorithms ................................................................................. 75  8.2.5 ‐ Larger scenes ..................................................................................................................... 76  8.2.6 ‐ Viewing angle attribute ..................................................................................................... 76  8.2.7 ‐ Collision penalty ................................................................................................................. 76  8.2.8 ‐ Wind ................................................................................................................................... 76  8.2.9 ‐ Separate behavioural attributes for falcons and starlings................................................. 77  8.2.10 ‐ Killing and evolution modelling ....................................................................................... 77  8.2.11 ‐ Variable speeds ................................................................................................................ 77  8.2.12 ‐ Migration urge ................................................................................................................. 78  8.2.13 ‐ Custom initial bird placement .......................................................................................... 78  8.2.14 ‐ Algorithmic optimisations ................................................................................................ 78  Appendix A – Related work ................................................................................................................... 79  Bibliography .......................................................................................................................................... 80  4   

https://www.pdf-archive.com/2011/05/07/dissertation/

07/05/2011 www.pdf-archive.com

se1b 80%

Annually, the leading emitter in the region is Iran, which contributes 49.6 million metric tons, followed in decreasing order by Saudi Arabia (40.25 million metric tons), United Arab Emirates (13.56 million metric tons), Iraq (10.01 million metric tons), Kuwait (8.2 million metric tons), Qatar (6.3 million metric tons), Oman (3.73 million metric tons) and Bahrain (2.25million metric tons) [17].

https://www.pdf-archive.com/2017/04/20/se1b/

20/04/2017 www.pdf-archive.com

RIP report 79%

• RIP sends out periodic routing updates (every 30 seconds) • RIP sends out the full routing table every periodic update • RIP uses a form of distance as its metric (in this case, hopcount) • RIP uses the Bellman-Ford Distance Vector algorithm to determine the best “path” to a particular destination Other characteristics of RIP include:

https://www.pdf-archive.com/2016/12/25/rip-report/

24/12/2016 www.pdf-archive.com