s s st s t r s
play

s ssts t rs - PowerPoint PPT Presentation

Oct 07, 2023 •104 likes •733 views

s ssts t rs t r rst r rs t rs

  1. ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❯♥✐✈❡rs✐t② ♦❢ ❆❜❡r❞❡❡♥ ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ❇✐r♠✐♥❣❤❛♠✱ ✼t❤ ❆✉❣✉st ✷✵✶✼ ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✶ ✴ ✶✺

  2. ❉❡✜♥✐t✐♦♥ ▲❡t ❜❡ ❛ ♣r✐♠❡ ❛♥❞ ❧❡t ❜❡ ❛ ❙②❧♦✇ ✲s✉❜❣r♦✉♣ ♦❢ ✳ ❚❤❡ ❢✉s✐♦♥ ❝❛t❡❣♦r② ♦❢ ♦♥ ✐s t❤❡ ❝❛t❡❣♦r② ✇❤♦s❡ ♦❜❥❡❝ts ❛r❡ t❤❡ s✉❜❣r♦✉♣s ♦❢ ❛♥❞ ✇❤♦s❡ ♠♦r♣❤✐s♠ s❡ts ❛r❡✿ ❢♦r ❡✈❡r② ✳ ❋✉s✐♦♥ ▲❡t G ❜❡ ❛ ✜♥✐t❡ ❣r♦✉♣✳ ❚✇♦ s✉❜❣r♦✉♣s P, Q ≤ G ❛r❡ ❢✉s❡❞ ✐♥ G ✐❢ t❤❡r❡ ❡①✐sts ❛♥ ❡❧❡♠❡♥t g ∈ G s✉❝❤ t❤❛t P g = Q ✳ ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✷ ✴ ✶✺

  3. ❋✉s✐♦♥ ▲❡t G ❜❡ ❛ ✜♥✐t❡ ❣r♦✉♣✳ ❚✇♦ s✉❜❣r♦✉♣s P, Q ≤ G ❛r❡ ❢✉s❡❞ ✐♥ G ✐❢ t❤❡r❡ ❡①✐sts ❛♥ ❡❧❡♠❡♥t g ∈ G s✉❝❤ t❤❛t P g = Q ✳ ❉❡✜♥✐t✐♦♥ ▲❡t p ❜❡ ❛ ♣r✐♠❡ ❛♥❞ ❧❡t S ❜❡ ❛ ❙②❧♦✇ p ✲s✉❜❣r♦✉♣ ♦❢ G ✳ ❚❤❡ ❢✉s✐♦♥ ❝❛t❡❣♦r② ♦❢ G ♦♥ S ✐s t❤❡ ❝❛t❡❣♦r② F S ( G ) ✇❤♦s❡ ♦❜❥❡❝ts ❛r❡ t❤❡ s✉❜❣r♦✉♣s ♦❢ S ❛♥❞ ✇❤♦s❡ ♠♦r♣❤✐s♠ s❡ts ❛r❡✿ Mor F S ( G ) ( P, Q ) = Hom G ( P, Q ) = { c g | P : P → Q | g ∈ G, P g ≤ Q } , ❢♦r ❡✈❡r② P, Q ≤ S ✳ ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✷ ✴ ✶✺

  4. P✐❝❦ ❛ ✜♥✐t❡ ❣r♦✉♣ s✉❝❤ t❤❛t ❙②❧ ✳ ❍♦✇ ♠❛♥② ✇❛②s t♦ ❢✉s❡ ❡❧❡♠❡♥ts ♦❢ ❄ ✳ ❈♦♥s✐❞❡r t❤❡ ❝♦♥❥✉❣❛t✐♦♥ ♠❛♣s ❊ ✭♥♦ ❡ss❡♥t✐❛❧ s✉❜❣r♦✉♣s✮ ❜② ❡❧❡♠❡♥ts t❤❛t ❢✉s❡ s♦♠❡ ❡❧❡♠❡♥ts✴s✉❜❣r♦✉♣s ♦❢ ✳ ✭ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ✭ ❛♥❞ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❛♥❞ ✱ ❛♥❞ P✐❝❦ ❛ p ✲❣r♦✉♣ S ✳ S = D 8 D 8 := � a, x | a 4 = x 2 = 1 , a x = a 3 � D 8 a 3 a a 3 x x ax a 2 x a 2 1 ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✸ ✴ ✶✺

  5. ❍♦✇ ♠❛♥② ✇❛②s t♦ ❢✉s❡ ❡❧❡♠❡♥ts ♦❢ ❄ ✳ ❈♦♥s✐❞❡r t❤❡ ❝♦♥❥✉❣❛t✐♦♥ ♠❛♣s ❊ ✭♥♦ ❡ss❡♥t✐❛❧ s✉❜❣r♦✉♣s✮ ❜② ❡❧❡♠❡♥ts t❤❛t ❢✉s❡ s♦♠❡ ❡❧❡♠❡♥ts✴s✉❜❣r♦✉♣s ♦❢ ✳ ✭ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ✭ ❛♥❞ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❛♥❞ ✱ ❛♥❞ P✐❝❦ ❛ p ✲❣r♦✉♣ S ✳ P✐❝❦ ❛ ✜♥✐t❡ ❣r♦✉♣ G s✉❝❤ t❤❛t S ∈ ❙②❧ p ( G ) ✳ S = D 8 D 8 := � a, x | a 4 = x 2 = 1 , a x = a 3 � D 8 G = D 8 a 3 a a 3 x x ax a 2 x a 2 1 ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✸ ✴ ✶✺

  6. ❍♦✇ ♠❛♥② ✇❛②s t♦ ❢✉s❡ ❡❧❡♠❡♥ts ♦❢ ❄ ✳ ❊ ✭♥♦ ❡ss❡♥t✐❛❧ s✉❜❣r♦✉♣s✮ ✭ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ✭ ❛♥❞ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❛♥❞ ✱ ❛♥❞ P✐❝❦ ❛ p ✲❣r♦✉♣ S ✳ P✐❝❦ ❛ ✜♥✐t❡ ❣r♦✉♣ G s✉❝❤ t❤❛t S ∈ ❙②❧ p ( G ) ✳ S = D 8 D 8 := � a, x | a 4 = x 2 = 1 , a x = a 3 � D 8 G = D 8 a 3 ❈♦♥s✐❞❡r t❤❡ ❝♦♥❥✉❣❛t✐♦♥ ♠❛♣s a ❜② ❡❧❡♠❡♥ts g ∈ G t❤❛t ❢✉s❡ a 3 x x s♦♠❡ ❡❧❡♠❡♥ts✴s✉❜❣r♦✉♣s ♦❢ S ✳ ax a 2 x a 2 ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② Inn(D 8 ) : 1 F D 8 (D 8 ) = � Inn(D 8 ) � ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✸ ✴ ✶✺

  7. ❍♦✇ ♠❛♥② ✇❛②s t♦ ❢✉s❡ ❡❧❡♠❡♥ts ♦❢ ❄ ✳ ❈♦♥s✐❞❡r t❤❡ ❝♦♥❥✉❣❛t✐♦♥ ♠❛♣s ❊ ✭♥♦ ❡ss❡♥t✐❛❧ s✉❜❣r♦✉♣s✮ ❜② ❡❧❡♠❡♥ts t❤❛t ❢✉s❡ s♦♠❡ ❡❧❡♠❡♥ts✴s✉❜❣r♦✉♣s ♦❢ ✳ ✭ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ✭ ❛♥❞ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❛♥❞ ✱ ❛♥❞ P✐❝❦ ❛ p ✲❣r♦✉♣ S ✳ P✐❝❦ ❛ ✜♥✐t❡ ❣r♦✉♣ G s✉❝❤ t❤❛t S ∈ ❙②❧ p ( G ) ✳ S = D 8 S 4 D 8 := � a, x | a 4 = x 2 = 1 , a x = a 3 � b D 8 G = Sym(4) = S 4 a = (1234) , x = (13) . a 3 a a 3 x x ax a 2 x a 2 1 ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✸ ✴ ✶✺

  8. ❍♦✇ ♠❛♥② ✇❛②s t♦ ❢✉s❡ ❡❧❡♠❡♥ts ♦❢ ❄ ✳ ❈♦♥s✐❞❡r t❤❡ ❝♦♥❥✉❣❛t✐♦♥ ♠❛♣s ✭♥♦ ❡ss❡♥t✐❛❧ s✉❜❣r♦✉♣s✮ ❜② ❡❧❡♠❡♥ts t❤❛t ❢✉s❡ s♦♠❡ ❡❧❡♠❡♥ts✴s✉❜❣r♦✉♣s ♦❢ ✳ ✭ ❡ss❡♥t✐❛❧✮ ✭ ❛♥❞ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ✱ ❛♥❞ P✐❝❦ ❛ p ✲❣r♦✉♣ S ✳ P✐❝❦ ❛ ✜♥✐t❡ ❣r♦✉♣ G s✉❝❤ t❤❛t S ∈ ❙②❧ p ( G ) ✳ S = D 8 S 4 D 8 := � a, x | a 4 = x 2 = 1 , a x = a 3 � b D 8 G = Sym(4) = S 4 a = (1234) , x = (13) . a 3 ❊ a b = (123) ( a 2 ) b = ((13)(24)) (123) = (12)(34) = ax a 3 x x ax a 2 x ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② a 2 Inn(D 8 ) ❛♥❞ Aut( E ) ∼ = SL 2 (2) ∼ = S 3 1 F D 8 ( S 4 ) = � Inn(D 8 ) , Aut( E ) � ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✸ ✴ ✶✺

  9. ❍♦✇ ♠❛♥② ✇❛②s t♦ ❢✉s❡ ❡❧❡♠❡♥ts ♦❢ ❄ ❈♦♥s✐❞❡r t❤❡ ❝♦♥❥✉❣❛t✐♦♥ ♠❛♣s ❊ ✭♥♦ ❡ss❡♥t✐❛❧ s✉❜❣r♦✉♣s✮ ❜② ❡❧❡♠❡♥ts t❤❛t ❢✉s❡ s♦♠❡ ❡❧❡♠❡♥ts✴s✉❜❣r♦✉♣s ♦❢ ✳ ✭ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ✭ ❛♥❞ ❡ss❡♥t✐❛❧✮ ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❢✉s✐♦♥ ✐s ❞❡t❡r♠✐♥❡❞ ❜② ❛♥❞ ✱ ❛♥❞ P✐❝❦ ❛ p ✲❣r♦✉♣ S ✳ P✐❝❦ ❛ ✜♥✐t❡ ❣r♦✉♣ G s✉❝❤ t❤❛t S ∈ ❙②❧ p ( G ) ✳ A 6 c S = D 8 S 4 D 8 := � a, x | a 4 = x 2 = 1 , a x = a 3 � b D 8 G = A 6 a = (1234)(56) , x = (13)(56) ✳ a 3 a c = (25)(46) ( a 2 ) c = ((13)(24)) (25)(46) a 3 x x = (13)(56) = x ax a 2 x a 2 1 ❱❛❧❡♥t✐♥❛ ●r❛③✐❛♥ ❋✉s✐♦♥ s②st❡♠s ❝♦♥t❛✐♥✐♥❣ ♣❡❛r❧s ●r♦✉♣s ❙t ❆♥❞r❡✇s ✷✵✶✼ ✸ ✴ ✶✺

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Theoretical Pearl Monads from Comonads, Comonads from Monads An Exercise in Program

Theoretical Pearl Monads from Comonads, Comonads from Monads An Exercise in Program

Theoretical Pearl Monads from Comonads, Comonads from Monads An Exercise in Program Transformation Ralf Hinze Computing Laboratory, University of Oxford Wolfson Building, Parks Road, Oxford, OX1 3QD, England ralf.hinze@comlab.ox.ac.uk

468 views • 11 slides
Proof Pearl: Using Combinators to Manipulate let -Expressions Michael Norrish 1 Konrad Slind 2 1

Proof Pearl: Using Combinators to Manipulate let -Expressions Michael Norrish 1 Konrad Slind 2 1

Proof Pearl: Using Combinators to Manipulate let -Expressions Proof Pearl: Using Combinators to Manipulate let -Expressions Michael Norrish 1 Konrad Slind 2 1 National ICT Australia 2 University of Utah 23 August 2005 Proof Pearl: Using

525 views • 37 slides
WattWatcher: Fine-Grained Power Estimation for Emerging Workloads Michael LeBeane, Jee Ho Ryoo ,

WattWatcher: Fine-Grained Power Estimation for Emerging Workloads Michael LeBeane, Jee Ho Ryoo ,

SBAC-PAD 2015 SBAC-PAD 2015 WattWatcher: Fine-Grained Power Estimation for Emerging Workloads Michael LeBeane, Jee Ho Ryoo , Reena Panda, Lizy K. John The University of Texas at Austin jr45842@utexas.edu SBAC-PAD 2015 Motivation

418 views • 21 slides
s ssts t rs

s ssts t rs

s ssts t rs t r s rs tr rstts r

966 views • 64 slides
Fun with Semirings A functional pearl on the abuse of linear algebra Stephen Dolan Computer

Fun with Semirings A functional pearl on the abuse of linear algebra Stephen Dolan Computer

Fun with Semirings A functional pearl on the abuse of linear algebra Stephen Dolan Computer Laboratory University of Cambridge stephen.dolan@cl.cam.ac.uk September 25, 2013 Linear algebra is magic If your problem can be expressed as vectors

644 views • 26 slides
Lecture 13: Nested Lists, Tuples, and Dictionaries (Sections 11.1-11.5, 12.1-12) CS 1110

Lecture 13: Nested Lists, Tuples, and Dictionaries (Sections 11.1-11.5, 12.1-12) CS 1110

http://www.cs.cornell.edu/courses/cs1110/2019sp Lecture 13: Nested Lists, Tuples, and Dictionaries (Sections 11.1-11.5, 12.1-12) CS 1110 Introduction to Computing Using Python [E. Andersen, A. Bracy, D. Gries, L. Lee, S. Marschner, C. Van

712 views • 23 slides
Identification of Causal Effect in the Presence of Selection Bias Juan D. Correa Jin Tian Elias

Identification of Causal Effect in the Presence of Selection Bias Juan D. Correa Jin Tian Elias

Identification of Causal Effect in the Presence of Selection Bias Juan D. Correa Jin Tian Elias Bareinboim AAAI Honolulu, 2019 Challenge 1: Confounding Bias Age Whats the causal effect of Exercise on Cholesterol ? What about

297 views • 15 slides
Mind the Digital Gap Join the Revolution! Nigel Lewis, CEO AbilityNet Mind The Digital Gap -

Mind the Digital Gap Join the Revolution! Nigel Lewis, CEO AbilityNet Mind The Digital Gap -

Mind the Digital Gap Join the Revolution! Nigel Lewis, CEO AbilityNet Mind The Digital Gap - Its bigger than you think Strategy premise More and more people have to digital self serve Peoples capabilities not keeping pace

593 views • 10 slides
Verified Decision Procedures for Monadic Second-Order Logic on Strings Functional Pearl Dmitriy

Verified Decision Procedures for Monadic Second-Order Logic on Strings Functional Pearl Dmitriy

Verified Decision Procedures for Monadic Second-Order Logic on Strings Functional Pearl Dmitriy Traytel Tobias Nipkow Isabelle = Overview MSO Overview MSO L MSO ( ) = L MSO ( )? Overview Finite Automata MSO

737 views • 62 slides
1 Environmental engineers are concerned with assessing and managing the effects of human and other

1 Environmental engineers are concerned with assessing and managing the effects of human and other

In our last session we started to explore the many different types of engineers. In this session, well take a closer look at environmental engineering. 1 Environmental engineers are concerned with assessing and managing the effects of human

485 views • 19 slides
Pecan Streets Dataport What is Pecan Street Non-Profit Energy, Gas, and Water R&D

Pecan Streets Dataport What is Pecan Street Non-Profit Energy, Gas, and Water R&D

Pecan Streets Dataport What is Pecan Street Non-Profit Energy, Gas, and Water R&D Based out of University of Texas Focus on innovative research Founded 6 years ago Who have we worked with? AND MANY MORE What Pecan Street

213 views • 8 slides
Model Checking Contest results for 2016 Fabrice Kordon LIP6, Univ. P. & M. Curie, France

Model Checking Contest results for 2016 Fabrice Kordon LIP6, Univ. P. & M. Curie, France

Model Checking Contest results for 2016 Fabrice Kordon LIP6, Univ. P. & M. Curie, France Hubert Garavel Inria/LIG, France Lom Messan Hillah LIP6 & Univ. Paris Ouest Nanterre, France Francis Hulin-Hubard LSV, CNRS/ENS de

711 views • 34 slides
New Applications of Moment-SOS Hierarchies Victor Magron , RA Imperial College 12 February 2015

New Applications of Moment-SOS Hierarchies Victor Magron , RA Imperial College 12 February 2015

New Applications of Moment-SOS Hierarchies Victor Magron , RA Imperial College 12 February 2015 Pecan Seminar LIP6 y par + b 3 par + b sin ( b ) b 1 b 1 b 1 b 2 b 3 = 500 par + par b 2 b 3 par b 2 par b 1 V. Magron

1.76k views • 121 slides
Towards a unified standards for smart infrastructure datasets Abdulrahman A. Ahmed Cairo

Towards a unified standards for smart infrastructure datasets Abdulrahman A. Ahmed Cairo

Towards a unified standards for smart infrastructure datasets Abdulrahman A. Ahmed Cairo University a.elsayed@fci-cu.edu.eg Why its important? Commercial and residential buildings in US represent 40% of total energy consumption Residential

200 views • 7 slides
Baumgartner, POLI 203 Spring 2016 Background on the Death Penalty Process January 25, 2016

Baumgartner, POLI 203 Spring 2016 Background on the Death Penalty Process January 25, 2016

Baumgartner, POLI 203 Spring 2016 Background on the Death Penalty Process January 25, 2016 Readings: catch-up on Jost, then Just Mercy Catch-up from last week NC reforms reducing use of DP NC methods of execution Issues Pro and

434 views • 14 slides
Porting U-Boot to a Modular Device FOSDEM 2019 Marek Behn marek.behun@nic.cz 3. 2.

Porting U-Boot to a Modular Device FOSDEM 2019 Marek Behn marek.behun@nic.cz 3. 2.

Porting U-Boot to a Modular Device FOSDEM 2019 Marek Behn marek.behun@nic.cz 3. 2. 2019 Contents About me Introducing the Problem Device tree overlays ft_board_setup Minimizing number of DTS changes Result

387 views • 16 slides
R-Trees Albert-Jan Yzelman October 22, 2007 Albert-Jan Yzelman R-Trees > Introduction

R-Trees Albert-Jan Yzelman October 22, 2007 Albert-Jan Yzelman R-Trees > Introduction

R-Trees R-Trees Albert-Jan Yzelman October 22, 2007 Albert-Jan Yzelman R-Trees > Introduction Outline R-trees Introduction 1 Basics 2 Tree Construction 3 Conclusions 4 Albert-Jan Yzelman R-Trees > Introduction Background

1.23k views • 102 slides
Querying Sensor Networks Sam Madden 1 Sensor Networks Small computers with: Radios

Querying Sensor Networks Sam Madden 1 Sensor Networks Small computers with: Radios

Querying Sensor Networks Sam Madden 1 Sensor Networks Small computers with: Radios Sensing hardware Batteries Remote deployments Long lived 10s, 100s, or 1000s Battery Pack Smart Sensor, aka Mote 2

1.01k views • 54 slides
Adaptive Sampling for Sensor Networks Seminarvortrag von Philippe Bourquin Betreuung: Silvia

Adaptive Sampling for Sensor Networks Seminarvortrag von Philippe Bourquin Betreuung: Silvia

Adaptive Sampling for Sensor Networks Seminarvortrag von Philippe Bourquin Betreuung: Silvia Santini Overview Sensor Networks: an Introduction 1. Problems / Requirements in SNs 2. Adaptive Sampling 3. Example 1: Feedback Control

189 views • 8 slides
CS698T Wireless Networks: Principles and Practice Topic 09 Embedded Wireless Sensors:

CS698T Wireless Networks: Principles and Practice Topic 09 Embedded Wireless Sensors:

CS698T Wireless Networks: Principles and Practice Topic 09 Embedded Wireless Sensors: Application Case Studies Bhaskaran Raman, Department of CSE, IIT Kanpur http://www.cse.iitk.ac.in/users/braman/courses/wless-spring2007/ Jan-Apr 2007

713 views • 28 slides
MAPPING MINIMUM DAILY TEMPERATURE IN SPAIN USING KRIGING WITH EXTERNAL DRIFT Andrs CHAZARRA,

MAPPING MINIMUM DAILY TEMPERATURE IN SPAIN USING KRIGING WITH EXTERNAL DRIFT Andrs CHAZARRA,

10th EUMETNET Data Management Workshop St. Gallen, Switzerland 28th 30th October 2015 MAPPING MINIMUM DAILY TEMPERATURE IN SPAIN USING KRIGING WITH EXTERNAL DRIFT Andrs CHAZARRA, Jos Vicente MORENO, Roser BOTEY Agencia Estatal de

431 views • 21 slides
SUSTAINABLE DEVELOPMENT IN INTERIOR DESIGN INTERIOR DESIGN 2020 SUSTAINABLE DEVELOPMENT IN

SUSTAINABLE DEVELOPMENT IN INTERIOR DESIGN INTERIOR DESIGN 2020 SUSTAINABLE DEVELOPMENT IN

SUSTAINABLE DEVELOPMENT IN INTERIOR DESIGN INTERIOR DESIGN 2020 SUSTAINABLE DEVELOPMENT IN INTERIOR DESIGN Sustainability is embedded in most projects across all three levels of study. Sustainability and Sustainable Development has been

240 views • 4 slides
Video and Audio Convergence Solution International Product and Solution Center Contents

Video and Audio Convergence Solution International Product and Solution Center Contents

Video and Audio Convergence Solution International Product and Solution Center Contents Background Requirement Analysis Solution Introduction Product List Background Background Real-time Deterrent Current situation CCTV systems focus

495 views • 24 slides
Auctions trends for 2020 2 2 1 04/02/2020 Vehicle supply Impact of 2016 new car market

Auctions trends for 2020 2 2 1 04/02/2020 Vehicle supply Impact of 2016 new car market

04/02/2020 Connecting Customers to Cars and Driving the Future of Remarketing with Gary Johnson, Group Account Director 1 Auctions trends for 2020 2 2 1 04/02/2020 Vehicle supply Impact of 2016 new car market Record new car market

228 views • 7 slides

More recommend