The “physics” of the InternetWhy SOC/EOC/ models failA network based explanation Heavy tails in networks

The “physics” of the InternetWhy SOC/EOC/ models failA network based explanation Heavy tails in networks www.phwiki.com

The “physics” of the InternetWhy SOC/EOC/ models failA network based explanation Heavy tails in networks

Sutton, Marsha, Freelance Columnist has reference to this Academic Journal, PHwiki organized this Journal Notices of the AMS, September 1998 Internet traffic St in addition to ard Poisson models don’t capture long-range correlations. Poisson Measured Internet traffic Fractional Gaussian (fractal) noise models measurements well. Hurst parameter H is an aggregate measure of long-range correlations. Fractal Measured

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The “physics” of the Internet “Physicists use chaos to calm the web,” (Physics World, 2001) www.networkphysics.com Large literature in physics journals in addition to recently in Science, Nature, etc Links The SOC (Self-Organized Criticality) view Links Flow capacity Average Queue “phase transition”

Lattice without congestion control (!) “Critical” phase transition at max capacity At criticality: self-similar fluctuations, long tailed queues in addition to latencies, 1/f time series, etc Alternative “edge of chaos” models Self-similarity due to chaos in addition to independent of higher-layer characteristics Why SOC/EOC/ models fail No “critical” traffic rate Self-similar scaling at all different rates TCP can be unstable in addition to perhaps chaotic, but does not generate self-similar scaling Self-similar scaling occurs in all as long as ms of traffic (TCP in addition to nonTCP) Measured traffic is not consistent with these models Fractal in addition to scale-free topology models are equally specious ( as long as different reasons)

A network based explanation Underlying cause: If connections arrive r in addition to omly (in time) in addition to if their size ( packets) have high variability (i.e. are heavy-tailed with infinite variance) then the aggregate traffic is per as long as ce self-similar Evidence Coherent in addition to mathematically rigorous framework Alternative measurements (e.g. TCP connections, IP flows) Alternative analysis (e.g. heavy-tailed property) Typical web traffic log(file size) > 1.0 log(freq > size) p s- Web servers Heavy tailed web traffic Is streamed out on the net. Creating fractal Gaussian internet traffic (Willinger, ) Fat tail web traffic Is streamed onto the Internet creating long-range correlations with time

Heavy tails in addition to divergent length scales are everywhere in networks. There is a large literature since 1994: Lel in addition to , Taqqu, Willinger, Wilson Paxson, Floyd Crovella, Bestavros Harchol-Balter, Heavy tails in networks Typical web traffic log(file size) > 1.0 log(freq > size) p s- Web servers Heavy tailed web traffic Is streamed out on the net. Piece of a consistent, rigorous theory with supporting measurements

Sutton, Marsha San Diego Ranch Coast Newspaper Group Freelance Columnist www.phwiki.com

Sutton, Marsha Freelance Columnist

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The US ATLAS Heavy Ion Program Summary Summary: US Ef as long as t & Impact

The US ATLAS Heavy Ion Program Summary Summary: US Ef as long as t & Impact www.phwiki.com

The US ATLAS Heavy Ion Program Summary Summary: US Ef as long as t & Impact

McCracken, Harry, Founder and Editor has reference to this Academic Journal, PHwiki organized this Journal The US ATLAS Heavy Ion Program Brian A. Cole, Columbia University January 12, 2007 Phases of QCD Matter Town Meeting LHC Heavy Ion Program: Key Questions What is the mechanism as long as initial particle production at the LHC Production from a saturated initial state How rapidly do produced particles thermalize or isotropize, what is the mechanism Faster than RHIC, slower How do high-energy quarks in addition to gluons interact in the quark gluon plasma What is the response of the medium What is the screening length of the QGP What are the quasi-particles of the QGP How does the QGP hadronize LHC Heavy Ions Program: Key Questions

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LHC Heavy Ions Program: Key Questions The ATLAS Central Detector Inner tracking, EM in addition to Hadronic calorimeters, external muon spectrometers ATLAS from the Inside

ATLAS Acceptance US ATLAS Heavy Ion: Primary Goals Measure dnchg/d, dET/d (total+EM) Characterize gross properties of initial state. Test saturation predictions Measure charged, inclusive , 0 elliptic flow Probe early collective motion of (s/t/w)QGP Measure jets, jet fragmentation, -Jet, di-jet, Precision tomography of QGP & its properties Medium response to passage of quenched jet Measure Upsilon production via +- Probe Debye screening in medium Study low x hard processes in p-p, p-A Study factorization violations, BFKL, saturation LHC Physics Summary Collectivity

Jet Tomography At RHIC, studied via leading hadrons Statistics suffer from frag. function rates Quenching geometric bias No direct measure of frag. function. At LHC: Full jets, high pT, large rates, b jets, di-jet, -jet Precision jet tomography Jet Tomography At RHIC, studied via leading hadrons Statistics suffer from frag. function rates Quenching geometric bias No direct measure of frag. function. At LHC: Full jets, high pT, large rates, b jets, di-jet, -jet Precision jet tomography Parton Showers, Hard Radiation @ LHC Copious hard radiation in high Q2 final-state parton showers, F ~ 1/kT Both an opportunity in addition to a challenge Underst in addition to ing jet quenching more difficult Potentially: time-dependent probe of medium Resolving hard radiation in jets a must!

ATLAS Calorimetery EM Long. Segmentation Hadronic Barrel Hadronic EndCap EM EndCap EM Barrel Forward EM Calorimeter Long. Segmentation Segmentation of first EM sampling layer so fine that heavy ion background is ~ negligible Nchg + N < 1, ET ~ 30 MeV Fine rejection of neutral hadron decays Clean 1st sampling prompt isolation x = 0.0028 x 0.1 Jets in A+A Jets from PYTHIA in 0.1x0.1 (logical) towers Jets in A+A merged with b = 2 fm Pb+Pb event (HIJING) Jets from PYTHIA in 0.1x0.1 (logical) towers Jet Energy Resolution Study of different event samples embedded into central Pb+Pb HIJING (b=0-2 fm) Results obtained from st in addition to ard p-p cone algorithm w/ background subtraction. Some re-calibration still needed. Jet Fragmentation Observables ATLAS: Gamma-Jet Pythia + jet (75 GeV) superimposed on b=4 fm HIJING Pb+Pb event, full GEANT Jet Gamma ATLAS: Gamma-Jet Pythia + jet (75 GeV) superimposed on b=4 fm HIJING Pb+Pb event, full GEANT ATLAS: Gamma-Jet, EM 1st Layer Gamma 1st layer unaffected by Pb+Pb background isolation w/ 1st layer ~ unaffected by Pb+Pb Zoom in on barrel EM calorimeter 1st sampling layer ATLAS: Gamma-Jet, EM 1st Layer Gamma EM Layer 1 ET (GeV) Isolated photon gives clean signal in EM first sampling layer Even in central Pb+Pb ! One (of 64) rows in barrel EM calorimeter 1st sampling layer ATLAS: Gamma-Jet, EM 1st Layer EM Layer 1 ET (GeV) Zoomed Width of high-energy shower in 1st sampling unaffected by bkgd 0, rejection retained Institutional Ef as long as ts/Strengths Brookhaven (Global, flow, jets, low-x) Expertise in global in addition to flow measurement (PHOBOS), high-multiplicity tracking in addition to low-x physics (BRAHMS) Columbia (Jets, Photons, low-x) Expertise in high-pT physics, jet correlations in addition to direct photon measurements (PHENIX) Expertise in p-A physics Iowa State (Di-muons) Expertise in di-muon measurements (PHENIX) SUNY Stony Brook (Chemistry) Expertise in flow, high-pT physics, jet correlations McCracken, Harry Technologizer Founder and Editor www.phwiki.com

Summary ATLAS-HI physics program addresses primary physics questions of interest @ LHC ATLAS provides unique capabilities with highly segmented EM calorimeters Especially as long as measuring isolated direct photons For separating jets from heavy ion background For measuring jet shapes, hard radiation ATLAS calorimeters provide best intrinsic (i.e. in p-p) jet resolution @ LHC Can US af as long as d NOT to participate in expt providing most precise jet measurements @ last energy frontier in heavy ion physics Summary: US Ef as long as t & Impact US ef as long as t (FY09 & beyond) ~30 physicists, 6 Ph.D students at current institutions. More desirable. More than ½ of full ATLAS-HI program. Highly leveraged ef as long as t with big impact Possible because of ATLAS collaboration Synergy with high-energy groups in US US provides co-convener of ATLAS HI WG BAC as of fall 2006 US Expertise developed @ RHIC US will provide highly visible leadership of ATLAS-HI program.

ATLAS Inner Tracker 3 layers Si pixel 8 layers Si strip TR tracker Pb+Pb b=2 fm Si tracking per as long as mance Charged Multiplicity from Pixels 1. Truth tracks (black) 2. “B-Layer” Hits 3. Layer 1 Hits 4. Matched Tracklets Good estimate of particle densities with subset of full detector ATLAS Zero Degree Calorimeter Test beam @ CERN 10.06 ZDC Prototype @ CERN 10.06 Experiment Simulation p+p events, w/ precision EM module TAN region, z=140m

ATLAS vs CMS Jet Resolution CMS Pb+Pb Jet resolution (Nov 2005) @ 75 GeV, CMS~16%, ATLAS~13% @ 125 GeV, CMS~15%, ATLAS~10% @ 175 GeV, CMS~12%, ATLAS~8% ATLAS better than CMS even in p-p Note: ATLAS numbers from 2003

McCracken, Harry Founder and Editor

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Lecture 1: Magnetic Resonance Static field is Bo RF field is B1 Magnetization is

Lecture 1: Magnetic Resonance Static field is Bo RF field is B1 Magnetization is www.phwiki.com

Lecture 1: Magnetic Resonance Static field is Bo RF field is B1 Magnetization is

Nicholson, Natasha, Executive Editor has reference to this Academic Journal, PHwiki organized this Journal Lecture 1: Magnetic Resonance Static field is Bo RF field is B1 Magnetization is Larmor frequency Review from last lecture: x y z = 42.57 MHz/T as long as 1H RF Excitation & Detection – excite spin system out of equilibrium – B1 cos(ot) field – Is it not doing anything when cos(ot) = 0 – See – Tips M away from Bo – creates Mxy component – Mxy precesses in transverse plane. – RF coil detects passing , i.e. time-varying creates EMF useful waste t Sr(t) Free Induction Decay (FID) RF Excitation & Detection: Diagrams Problem: RF coils are sensitive to transverse component of How do we localize to a spatial location when RF field is sensitive to entire volume . Excitation: rotating frame x y z x y . x z y Detection: RF detection coils z To Receiver To Receiver

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Field diagram Simplified Drawing of Basic Instrumentation. Body lies on table encompassed by coils as long as static field Bo, gradient fields (two of three shown), in addition to radiofrequency field B1. Image, caption: copyright Nishimura, Fig. 3.15 Gradient Fields The gradient field is the last magnetic field we have to discuss. – key as long as imaging – Paul Lauterbur Gradient coils are designed to create an additional B field that varies linearly across the scanner as shown below when current is driven into the coil. The slope of linear change is known as the gradient field in addition to is directly proportional to the current driven into the coil. The value of Bz varies in x linearly. Whole Body Scanners: Gx = 1-4 G/cm (10-40 mT/m) Gx can be considered as the magnitude of the gradient field, or, if you like, as the current level being driven into the coil. Gradient Fields x Bz Bo slope = Gx Apply Gx during a FID Frequency is proportional to

Gradient Fields: Encoding The Fourier trans as long as m of the signal gives us the projection of the object. The signal detected by the coil, a function of time (t),has spatial in as long as mation encoded into it. fo f t Sr Signal(t) x Bz Bo slope = Gx so, Gradient Fields: Example Example: Assume a 40 cm wide torso. Let Gx = 0.5 G/cm What is the frequency range across the body Gradient Fields: Example Example: Assume a 40 cm wide object. Gx = 0.5 G/cm At 1 T, B in addition to width of interest is small compared to 42.57 MHz.

Gradient Fields: Matlab example x m(x) Gradient Fields Gy changes field strength of B field in z direction as a function of y Gz changes field strength of B field in z direction as a function of z Gradient Fields We can write this all together by looking at G as a vector. Each element refers to the gradient field present at any time ( current in the coil at that time).

Putting it all together: The Bloch equation Sums of the phenomena transverse magnetization precession, RF excitation longitudinal magnetization Changes the direction of , but not the length. These change the length of only, not the direction. includes Bo, B1, in addition to Review: Cosine Theorem (What is a mixer ) – Consider a pulse A(t) that is multiplied by cos(ot). This is called modulation . A(t) is called the envelope function. o is the carrier frequency. Mixer cos(ot) A(t) cos(ot) A(t) fo f Sr Frequency response of RF pulse o = 2fo Imaging methods Lets consider 2D imaging Slice excitation or selective excitation We first spoke of B1(t) as a rectangle, an on/off pulse, a) Now modulate the carrier cos(ot) by B1(t) where B1(t) is a sinc . B1(t) Mixer cos(ot) B1(t) cos(ot) B1(t) F.T. o

Imaging methods Lets consider 2D imaging Slice excitation or selective excitation b) Simultaneously, we apply a gradient Gz. Set b in addition to width of is slice thickness. B1(t) cos(ot) F.T. o Gradient illustration The effects of the main magnetic field in addition to the applied slice gradient. In this example, the local magnetic field changes in one-Gauss increments accompanied by a change in the precessional frequency. Image, caption: copyright Proruk & Sawyer, GE Medical Systems Applications Guide, Fig. 11

Basic Procedure 1) Selectively excite a slice (z) – time .4 ms to 4 ms – thickness 2 mm to 1 cm 2) Record FID, control Gx in addition to Gy – time 1 ms to 50 ms 3) Wait as long as recovery – time 5 ms to 3s 4) Repeat as long as next measurement. – measurements 128 to 512 – in just 1 flip Projection Reconstruction Projection Reconstruction – 1) Record FID with constant gradient on. x y 2) Above, frequency maps to spatial pos. x with f0 corresponds to x = 0 3) Shift above projection to shift f0 to 0. 4) For projection angle , turn on Gx in addition to Gy at same time. x y 5) Sequence through all from 0 to 180 6) Use convolution back projection to create image. fo f t Sr Signal(t) or sr(t) Object Imaging Method 2: Fourier Method Consider a rectangular, homogenous object. Think of arrows to left as the direction of transverse magnetization in the x,y plane immediately after a 90 degree RF pulse is applied. We can refer to the magnitude in addition to direction of the transverse magnetization as a complex number. Our goal is to determine these complex values throughout the object. The magnitude of these values represent the proton density of the object. These magnitude values will as long as m the desired image. We use the variable m to represent this complex value. y x

Imaging Method 2: Fourier Method y x ky kx F(u,v) space is known as k-space in MR. Axes are kx, ky. If we consider a z dimension,we have a kz dimension also. fo f t Sr Spins will start out in phase. Next, record FID with constant x gradient on. Spins will stay in phase in y, but not in x. Signal(t) or sr(t) Imaging Method 2 2D Fourier Trans as long as m (2D FT) – most popular by far – can’t do this with x-ray Methodology: For every measurement, record FID w/ only Gx on. Demodulate sr(t) down to baseb in addition to to get s(t) ( Shift from lab to rotating frame) But prior to FID (the readout) – also apply Gy as long as time y – relative frequency w/ Gy on is (y)= Gyy After y, relative phase in y direction has changed. Relative phase= Phase varies linearly with position in y. Let’s break this down in addition to look at the signal in addition to magnetization after this y gradient without the Gx gradient. Imaging Method 2: Encoding in y direction. Break this down: Think of phase as the direction of in the x,y plane. Look at magnetization immediately after gradient pulse on Gy but be as long as e any Gx readout proton density y Gy= 0 Spins in phase after excitation. spins after y seconds of Gy gradient. x y x x y Signal detected by coil will be a constant level, described as.

Nicholson, Natasha Communication World (CW) Executive Editor www.phwiki.com

Imaging Method 2: Projections as Fourier Trans as long as ms Look at the expression as long as the signal the coil will see at this point Imaging Method 2: Excitation in addition to gradient application. Think of phase as the direction of in the x,y plane. proton density spins after y of Gy gradient. x y x y Z grad RF X Grad Y Grad ty Gy Imaging Method 2: Projections as Fourier Trans as long as ms (2) Putting it all together After applying the Gy gradient, apply a Gx readout gradient in addition to record the varying sr(t) signal. Demodulate to baseb in addition to . This is one experiment. Per as long as m several experiments by varying Gyy to induce different spatial frequency weightings in y. Each experiment gives the values of the spatial frequency domain as long as a red line in k-space below. This is the 2D Fourier Trans as long as m method of imaging. ky kx Consider the 64 x 8 box to the right. A series of MR experiments as described above were per as long as med. To simplify visualization, a 1D FFT in the horizontal direction was done on each experiment be as long as e display. The results are shown on the bottom where each row is a separate experiment with a different Y direction phase weighting.

Imaging Method 2: Projections as Fourier Trans as long as ms (2) Putting it all together F.T-1 in x F.T.-1 in y, m(x,y) ky kx Each red line is an experiment with a different Gy ( or ty). This is the 2D Fourier Trans as long as m method of imaging.

Nicholson, Natasha Executive Editor

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WG2 Summary: Diagnostics, measurements, in addition to commissioning Aaron Tremaine Steve L

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WG2 Summary: Diagnostics, measurements, in addition to commissioning Aaron Tremaine Steve L

Herndon, Andre, Executive Editor has reference to this Academic Journal, PHwiki organized this Journal WG2 Summary: Diagnostics, measurements, in addition to commissioning Aaron Tremaine Steve Lidia And a host of others who shall remain blameless. WG2 discussions Talks given High brightness measurements, e.g. LCLS (~kW) High current measurements leading to MW Assume bunch train Commissioning all as long as Q = 1 nC F = Fm – 5° Imain = 326 A 20. 8. 2004 F = Fm Ibuck = Imain 0.075 24. 8. 2004 VUV-FEL (30 nm) VUV-FEL (6 nm) XFEL min. emittance improved geom. average improved still a long way to go as long as XFEL requirements ! Transverse Emittance measurements Courtesy A. Oppelt

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Longitudinal Emittance Measurement Determine Longitudinal f-Space at Linac Entrance Measure Energy Spectra vs linac phase Linear analysis allows only linear time energy correlations Fit t11, t12, t22, Vlinac, in addition to qlinac Quad scan in addition to fit Twiss parameters Technique analagous to quadrupole scan of transverse emittance 3 m linac (vary flinac) Gun Spectrometer Energy Screen Quad Doublet Courtesy, J. Schmerge

Implementation TV & Streak-camera Magnetic Kicker E-beam Phosphor + OTR Ti Foil Vacuum chamber Courtesy Timur Shaftan UCLA/ATF chicane compression experiments Extend UCLA chicane experiments to regime with significant acceleration-field Chicane designed, fabricated in addition to characterized at UCLA Extensive simulation work Coherent radiative effects central to mission Add to ATF core capabilities SASE FEL Wakefield studies Coherent radiation exit port Bunch length diagnostic comparison Courtesy Patrick Krejcik

High Brightness, <5kW Word document Average Power ->1 MW Measurements of single bunches interesting, but not necessary (assuming high brightness bunches) Invasive is not robust solution, water cooled OTR good to several kW Kick out several pulses in addition to make measurements Consult Damping Ringers as long as kicker specs Commissioning Common problem -Not enough diagnostics near source/low energy Real estate Beam dynamics Low rep rate & charge start, ramp up to high rep rate & charge Watch as long as changing source physics When low important, source very important Usually diagnose source on test st in addition to in addition to install Measurements downstream, hard to diagnose source again

Halo & beam loss For MW beam, 10 kW halo conceivable With wire scanner progressively measure halo Try to remove at low energy (lower power) Scrappers Where does halo as long as m Simulations Beam loss Radiation detector schemes, LC community Look to LC as long as collimation schemes, takes a lot of beamline Other issues 2 screen OTR emittance, useful > 15 MeV Are there situations where you need to know more than our list User defined Multi-channel striplines, higher order content Radiation environment in high current scenario X-ray damage to equipment Are diagnostics/electronics reliable

Herndon, Andre Lynwood Press Executive Editor www.phwiki.com

Herndon, Andre Executive Editor

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Les outils du changement La GALAXIE du MANAGEMENT La CULTURE des ORGANISATION

Les outils du changement La GALAXIE du MANAGEMENT La CULTURE des ORGANISATION www.phwiki.com

Les outils du changement La GALAXIE du MANAGEMENT La CULTURE des ORGANISATION

Ravi, Ajay, Editorial Assistant has reference to this Academic Journal, PHwiki organized this Journal Les outils du changement La GALAXIE du MANAGEMENT La CULTURE des ORGANISATIONS Le PROJET de SERVICE STRATÉGIE et OBJECTIFS STRATÉGIQUES L’administration du futur – J.-L. Deligny – éditions Eyrolles – 1990 Dr Lucien Mias – http://membres.lycos.fr/papidoc/ – novembre 1991 Qu’est-ce qu’une stratégie Qu’est-ce que le marketing stratégique La crise existentielle de l’administration La stratégie des administrations publiques 1 – La stratégie 2 – Les attitudes face aux clients 3 – La dem in addition to e et l’offre 4 – Concurrence ou complémentarité 5 – Une réflexion stratégique — Des objectifs stratégiques — Les plans d’actions Sommaire Qu’est-ce q u’une stratégie Corporate strategy,I. Ansoff – 1965 Cette notion s’oppose à celle de la TACTIQUE qui est l’art de diriger les troupes durant la bataille (alors que la stratégie s’arrête au moment ou l’armée entre en contact avec l’ennemi) Pour les MILITAIRES c’est l’art de manoeuvrer leurs as long as ces pour atteindre le but fixé, le plus sûrement possible et à meilleur compte.

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Qu’est-ce que le marketing stratégique Le MARKETING est un système de PENSÉE et d’ACTION. C’est un ensemble de méthodes de gestion qui traduisent les principes de SOUVERAINETÉ de l’ACHETEUR et de l’ÉCONOMIE DE MARCHÉ. « Le marketing est le processus social, orienté vers la satisfaction des besoins et désirs d ’individus et d’organisations, par la création et l’échange volontaire et concurrentiel de produits et services générateurs d’utilités » Cette démarche s’appuie sur – des technologies opérationnelles ou émergentes ; – des marchés ou segments de marchés existants ou potentiels ; – du cycle de vie des produits, de leur compétitivité ; – des compétences distinctives. Il définit des options à long et moyen terme, des objectifs de vente, de profits, et des programmes d’actions à court terme. Il consiste pour l’entreprise, à construire son offre en fonction de la DEMANDE, de son SAVOIR-FAIRE et du JEU CONCURRENCIEL – Le marketing stratégique, J-J Lambin – 1986 Le MARKETING STRATÉGIQUE, en français “MERCATIQUE” a pour but de mettre en place les conditions dans lesquelles l’OFFRE est FONCTION de la DEMANDE. C’est qu in addition to tout va bien qu’il est le plus facile d’opérer le changement d’attitude face au client , La crise existentielle de l’administration Le droit est complexe, interprétatif et varie. Il est souvent contesté La logique de la négociation doit se substituer à celle du droit. Le marketing est une voie logique de négociation. De nos jours, la limite public-privé à littéralement explosée, c’est “l’État omniprésent“. Les critères ne sont plus simplement juridiques et fonctionnels : ils sont MÉTHODOLOGIQUES. Le juge apprécie désormais l’OPPORTUNITÉ des méthodes de pouvoir. Pendant le première moitié du XX° siècle, l’administration s’assimile peu à peu au SERVICE PUBLIC, c’est “l’État Providence”. La limite entre public et privé devient floue et les critères sont fonctionnels. Le juge apprécie alors la FINALITÉ du pouvoir. Au XIX° siècle, l’administration s’identifie à la PUISSANCE PUBLIQUE. La source du pouvoir est JURIDIQUE et le pouvoir de “l’État gendarme“ est discrétionnaire. Le juge apprécie la LÉGALITÉ du pouvoir. A l’origine, la limite entre public et privé était claire : l’État a le monopole de la VIOLENCE LÉGITIME (armée, justice, police). Pour le juge il n’y a que des problèmes de LÉGITIMITÉ.

La stratégie des administrations publiques 1) Quelle STRATÉGIE pour une administration publique 2) Quels sont les CLIENTS Quelles ATTITUDES vis à vis d’eux 3) Qu’attendent-ils d’elle (la DEMANDE) 4) Que peut-elle répondre (l’OFFRE) 5) Quels sont les CONCURRENTS Les administrations ont des similitudes avec les organisations privées (production de biens et services entrant dans le jeu de la concurrence) mais s’en distinguent par des différences importantes : Monopole de certains produits, justifié par la vocation de la puissance publique (percevoir l’impôt, assurer la sécurité ). Ne vendent pas (sauf Poste, EDF, SNCF, Orange, SEITA, DDE,) Ont un poids économique et social souvent considérable. Elles sont soumises à des contraintes (statut, budget ) Offrir des services et des biens adaptés à la dem in addition to e des pouvoirs publics, de la population avec le souci de la compétitivité et en respectant les spécificités des administrations publiques. 1 — La stratégie — 2 — Les attitudes face aux clients — L’administration, comme le privé, peut avoir 4 types d’attitudes/client Le monopole n’EXISTE PLUS et la concurrence, impitoyable, la menace de déclin voire de disparition. On COMMUNIQUE avec la clientèle, on essaie de devancer ses désirs, c’est la CONVIVIALITÉ Le marché à raison et comm in addition to e désormais la production. Le monopole est ROMPU, la concurrence est rentrée dans la brèche et a enlevé une part du marché : on se met à ÉCOUTER le client avec RESPECT, on tient compte de ses observations en corrigeant la production et on l’en INFORME après. Son monopole est MENACÉ mais n’a pas de conséquence immédiate : on EXPLIQUE les qualités du produit au client mais on ne met pas en doute sa fidélité. On écoute ses récriminations avec CONDESCENDANCE . et on n’en tient pas compte. 3 — La dem in addition to e et l’offre — Schéma d’après P. Larcher, responsable marketing Arianespace de MARCHÉ, l’offre excédant la dem in addition to e, la CONCURRENCE oblige à vendre les produits les mieux adaptés à la clientèle. Importance de la connaissance de ses besoins actuels ou futurs. de DISTRIBUTION, l’offre et la dem in addition to e s’équilibrant on essaie de vendre plus de produits.

4 — Concurrence ou complémentarité — Les concurrents peuvent être PUBLICS (administration d’une autre collectivité publique, société d’économie mixte, entreprise du secteur public) ou PRIVÉS (entreprise de droit privé, association). “La concurrence est un alcaloïde ; à dose modérée, c’est un excitant ; à dose massive c’est un poison” Propos de Barenton, confiseur A. Detoeuf Elles optimisent l’utilisation des compétences, garantissent au maître d’ouvrage une qualité supérieure par la pluridisciplinarité, et as long as ment mutuellement les associés à leurs compétences respectives. C’est la Fertilisation Croisée Peut jouer aussi la COMPLÉMENTARITÉ, et les opérations mixtes public-privé présentent de nombreux avantages. 5 — Une réflexion stratégique — POLITIQUES, OBJECTIFS, PROGRAMMES d ’ACTIONS, partent d’une réflexion stratégique à moyen terme sur la satisfaction de la dem in addition to e EXPRIMÉE ou POTENTIELLE de la clientèle. La réflexion commence obligatoirement par l’IDENTIFICATION des PRODUITS et leur affectation aux différents SEGMENTS de marché existants ou potentiels. Elle évalue leur ATTRACTIVITÉ à partir – de la dem in addition to e actuelle de la clientèle. – de la durée économique du produit (cycle de vie) – de la compétitivité de l’entreprise / concurrents. De là découle l’ATTRAIT d’une activité et l’ATOUT de l’organisation par rapport au meilleur concurrent. La réflexion débouche sur la définition de la vocation de l’organisation, de sa stratégie et de ses objectifs. Il s’agit de SUIVRE en parallèle TECHNOLOGIES et MARCHÉS et d’anticiper sur leur évolution.

Des objectifs stratégiques L’analyse des « ATOUTS-ATTRAITS » permet de — détecter les activités à développer (ou conserver, ou bonifier ou ab in addition to onner). — définir des OBJECTIFS STRATÉGIQUES liés aux ACTIVITÉS. L’analyse INTERNE fixe les priorités d’amélioration du fonctionnement qui deviennent les OBJECTIFS STRATÉGIQUES liés au FONCTIONNEMENT. Un objectif stratégique est le but qu’une organisation se propose d’atteindre à moyen terme à l’aide d’un ensemble coordonné d’actions de progrès. Chaque objectif stratégique est dirigée par un RESPONSABLE qui doit : Tous les objectifs d’un service ne sont pas stratégiques. Le but est d’atteindre tous les objectifs. Mais en concentrant les ef as long as ts PRIORITAIREMENT sur les objectifs stratégiques. Inventer les INDICATEURS DE SUIVI pertinents qui permettront d’apprécier le résultat concret de chaque action élémentaire. Estimer les MOYENS nécessaires en TEMPS (“homme-mois”) et en COÛTS d’investissement et de fonctionnement, Fixer les ÉCHÉANCIERS réalistes fixant l’ordonnancement dans le temps et son suivi, Associer, le plus en amont possible, les “ACTEURS” concernés par ces actions, Détailler les ACTIONS ÉLÉMENTAIRES, qui d’année en année feront progresser vers l’objectif, Ce responsable s’appuie sur un ANIMATEUR motivé. Les objectifs stratégiques seront les seuls à contenir des actions de progrès, à côté des actions courantes du service. Les programmes annuels d’actions de progrès sont l’aboutissement OPÉRATIONNEL de la démarche à MOYEN TERME (3 à 5 ans). La procédure budgétaire annuelle permet à la DIRECTION de marquer une étape dans la poursuite des objectifs. C’est la Direction Participative par Objectifs (DPPO) Les plans d ’action Elle a remplacé la Direction par Objectifs des années 1954. N’intéressant que les directions, celle-ci avait omis deux éléments : la prise en compte des notions de client et de marché ; la participation du personnel concerné à la définition des programmes d’actions, le plus en amont possible. Les plans d’objectifs seront déclinés en PLANS D’ACTIONS. Un programme d’ACTIONS DE PROGRÈS est un ensemble as long as malisé des changements qu’on se propose d’accomplir pour arriver à un résultat meilleur.

Merci de votre attention !

Ravi, Ajay Instrument Business Outlook Editorial Assistant www.phwiki.com

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Part I: Principles of Effective Writing Kristin Cobb, PhD Principles of Eff

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Part I: Principles of Effective Writing Kristin Cobb, PhD Principles of Eff

WestMed College, CA has reference to this Academic Journal, Part I: Principles of Effective Writing Kristin Cobb, PhD Principles of Effective Writing “In science, the credit goes so that the man who convinces the world, not so that the man so that whom the idea first occurs.” Sir William Osler Principles of Effective Writing “Writing is an art. But when it is writing so that inform it comes close so that being a science as well.” Robert Gunning,The Technique of Clear Writing

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Principles of Effective Writing Introduction What makes good writing? What does it take so that be a good writer? Principles of Effective Writing What makes good writing? 1. Good writing communicates an idea clearly in addition to effectively. 2. Good writing is elegant in addition to stylish. Principles of Effective Writing What makes a good writer? Inborn talent? Years of English in addition to humanities classes? An artistic nature? The influence of alcohol in addition to drugs? Divine inspiration?

Principles of Effective Writing What makes a good writer (outside of poets, maybe): Having something so that say. Logical in addition to clear thinking. A few simple, learnable rules of style (the tools we?ll learn in this class). Take home message: Writing so that inform is a craft, not an art. Clear, effective writing can be learned! Principles of Effective Writing In addition so that attending this lecture, other things you can do so that become a better writer: Read, pay attention, in addition to imitate. Let go of ?academic? writing habits (deprogramming step!) Talk about your research before trying so that write about it. Develop a thesaurus habit. Search in consideration of the right word rather than settling in consideration of any old word. Respect your audience?try not so that bore them! Stop waiting in consideration of ?inspiration.? Accept that writing is hard in consideration of everyone. Revise. Nobody gets it perfect on the first try. Learn how so that cut ruthlessly. Never become too attached so that your words. Find a good editor! Principles of Effective Writing Clear writing starts alongside clear thinking.

Part I: Principles of Effective Writing Kristin Cobb, PhD Principles of Eff

Principles of Effective Writing Before you start writing, ask: ?What am I trying so that say?? When you finish writing, ask: ?Have I said it?? Principles of Effective Writing Once you know what you?re trying so that say, then pay attention so that your words! Today?s lesson: Strip your sentences so that just the words that tell. Principles of Effective Writing ?The secret of good writing is so that strip every sentence so that its cleanest components. Every word that serves no function, every long word that could be a short word, every adverb that carries the same meaning that?s already in the verb, every passive construction that leaves the reader unsure of who is doing what?these are the thousand in addition to one adulterants that weaken the strength of a sentence. And they usually occur in proportion so that the education in addition to rank.? William Zinsser in On Writing Well, 1976

Principles of Effective Writing Famous Example: ?Such preparations shall be made as will completely obscure all Federal buildings in addition to non-Federal buildings occupied by the Federal government during an air raid in consideration of any period of time from visibility by reason of internal or external illumination.? (from a government blackout order in 1942) Principles of Effective Writing FDR?s response: ?Tell them that in the buildings where they have so that keep the work going so that put something across the windows.? Help! This was the first sentence of a recent scientific article in the Journal of Clinical Oncology (Introduction section): ?Adoptive cell transfer (ACT) immunotherapy is based on the ex vivo selection of tumor-reactive lymphocytes, in addition to their activation in addition to numerical expression before reinfusion so that the autologous tumor-bearing host.? Aaaccckkkk!!!!! That sentence does not make me want so that read on?

And here?s the final sentence from the same article? ?Current studies in our laboratory are focused on the logistical aspects of generating autologous-cell based patient treatments, the genetic modification of lymphocytes alongside T-cell receptor genes in addition to cytokine genes so that change their specificity or improve their persistence, in addition to the administration of antigen specific vaccines so that augment the function of transferred cells.? This is academic writing at its finest: boring, unreadable, written so that obscure rather than so that inform!! Scientific Writing, HRP 214 From: ?The joys in addition to pains of writing,? Le Bon Journal? ?My professor friend told me that in his academic world, ?publish or perish? is really true. He doesn?t care if nobody reads it or understands it as long as it?s published.? There?s a hint of truth here, n?est-ce pas? Overview of principles? Today?s lessons: Words: 1. Reduce dead weight words in addition to phrases 2. Cut, cut, cut; learn so that part alongside your words Sentences: 3. Follow: subject + verb + object (SVO) 4. Use strong verbs in addition to avoid turning verbs into nouns 5. Eliminate negatives; use positive constructions instead 6. Use parallel Construction

Principles of Effective Writing Words 1. Reduce dead weight words in addition to phrases Get rid of jargon in addition to repetition ?Verbose is not a synonym in consideration of literary.? Principles of Effective Writing Examples: ?I would like so that assert that the author should be considered so that be a buffoon.? ? ?The author is a buffoon.? Principles of Effective Writing ?The expected prevalence of mental retardation, based on the assumption of a normal distribution of intelligence in the population, is stated so that be theoretically about 2.5%.? Examples:

Principles of Effective Writing ?The expected prevalence of mental retardation, based on the assumption of a normal distribution of intelligence in the population, is stated so that be theoretically about 2.5%.? Examples: Principles of Effective Writing ?The expected prevalence of mental retardation, based on the assumption of a normal distribution of intelligence in the population, is stated so that be theoretically about 2.5%. ? ?The expected prevalence of mental retardation, if intelligence is normally distributed, is 2.5%.? Examples: Principles of Effective Writing ?To control infection alongside Mycobacterium tuberculosis (M. tb), a robust cell-mediated immune response is necessary, in addition to deficiency in this response predisposes an individual towards active TB.? ? ?Deficiency in T-cell-mediated immune response predisposes an individual towards active TB.? Examples:

Principles of Effective Writing Examples: ?This paper provides a review of the basic tenets of cancer biology study design, using as examples studies that illustrate the methodologic challenges or that demonstrate successful solutions so that the difficulties inherent in biological research.? s in addition to ?This paper reviews cancer biology study design, using examples that illustrate specific challenges in addition to solutions.? Principles of Effective Writing Hunt down in addition to cast out all unneeded words that might slow your reader. Principles of Effective Writing Very, really, quite, basically, generally These words seldom add anything useful. Try the sentence without them in addition to see if it improves.

Principles of Effective Writing Watch out in consideration of the verb ?to be? Often ?there are? is extra weight. There are many students who like writing. Many students like writing. Principles of Effective Writing Dead weight phrases in the event that in the nature of it has been estimated that it seems that the point I am trying so that make what I mean so that say is it may be argued that Principles of Effective Writing Dead weight phrases in consideration of the most part in consideration of the purpose of in a manner of speaking in a very real sense in my opinion in the case of in the final analysis

References & Further Reading Strunk in addition to White. The elements of style. Constance Hale. Sin in addition to syntax. William Zinsser. On writing well. Matthews, Bowen, in addition to Matthews. Successful science writing.

Darnell, Brandon Executive Editor

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This Particular Journal got reviewed and rated by Principles of Effective Writing Examples: ?This paper provides a review of the basic tenets of cancer biology study design, using as examples studies that illustrate the methodologic challenges or that demonstrate successful solutions so that the difficulties inherent in biological research.? s in addition to ?This paper reviews cancer biology study design, using examples that illustrate specific challenges in addition to solutions.? Principles of Effective Writing Hunt down in addition to cast out all unneeded words that might slow your reader. Principles of Effective Writing Very, really, quite, basically, generally These words seldom add anything useful. Try the sentence without them in addition to see if it improves. and short form of this particular Institution is CA and gave this Journal an Excellent Rating.

 

Insight: Achieving Best of Both Worlds Why do Previous Algorithms Fail? Motivation

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Insight: Achieving Best of Both Worlds Why do Previous Algorithms Fail? Motivation

WestMed College, CA has reference to this Academic Journal, Thread Cluster Memory Scheduling: Exploiting Differences in Memory Access BehaviorYoongu KimMichael PapamichaelOnur MutluMor Harchol-BalterMotivationMemory is a shared resourceThreads? requests contend in consideration of memoryDegradation in single thread performanceCan even lead so that starvationHow so that schedule memory requests so that increase both system throughput in addition to fairness?2CoreCoreCoreCoreMemoryPrevious Scheduling Algorithms are Biased3System throughput biasFairness biasNo previous memory scheduling algorithm provides both the best fairness in addition to system throughput IdealBetter system throughputBetter fairness

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Take turns accessing memoryWhy do Previous Algorithms Fail?4Fairness biased approachthread Cthread Bthread Aless memory intensivehigherpriorityPrioritize less memory-intensive threadsThroughput biased approachGood in consideration of throughputstarvation ? unfairnessthread Cthread Bthread ADoes not starvenot prioritized ? reduced throughputSingle policy in consideration of all threads is insufficientInsight: Achieving Best of Both Worlds5threadthreadhigherprioritythreadthreadthread threadthreadthreadPrioritize memory-non-intensive threadsFor ThroughputUnfairness caused by memory-intensive being prioritized over each other Shuffle threadsMemory-intensive threads have different vulnerability so that interference Shuffle asymmetricallyFor FairnessthreadthreadthreadthreadOutlineMotivation & InsightsOverviewAlgorithmBringing it All TogetherEvaluationConclusion6

Overview: Thread Cluster Memory SchedulingGroup threads into two clustersPrioritize non-intensive clusterDifferent policies in consideration of each cluster7threadThreads in the systemthreadthreadthreadthreadthreadthreadNon-intensive clusterIntensive clusterthreadthreadthreadMemory-non-intensive Memory-intensive PrioritizedhigherpriorityhigherpriorityThroughputFairnessOutlineMotivation & InsightsOverviewAlgorithmBringing it All TogetherEvaluationConclusion8TCM Outline91. Clustering

Insight: Achieving Best of Both Worlds Why do Previous Algorithms Fail? Motivation

Clustering ThreadsStep1 Sort threads by MPKI (misses per kiloinstruction)10higher MPKIT? < 10% ClusterThresholdIntensive cluster?TNon-intensiveclusterT = Total memory bandwidth usageStep2 Memory bandwidth usage ?T divides clustersTCM Outline111. Clustering2. Between ClustersPrioritize non-intensive clusterIncreases system throughputNon-intensive threads have greater potential in consideration of making progressDoes not degrade fairnessNon-intensive threads are ?light?Rarely interfere alongside intensive threadsPrioritization Between Clusters12>priority

TCM Outline131. Clustering2. Between Clusters3. Non-Intensive ClusterThroughputPrioritize threads according so that MPKIIncreases system throughputLeast intensive thread has the greatest potential in consideration of making progress in the processorNon-Intensive Cluster14threadthreadthreadthreadhigherprioritylowest MPKIhighest MPKITCM Outline151. Clustering2. Between Clusters3. Non-Intensive Cluster4. Intensive ClusterThroughputFairness

Periodically shuffle the priority of threadsIs treating all threads equally good enough?BUT: Equal turns ? Same slowdownIntensive Cluster16threadthreadthreadIncreases fairnessMost prioritizedhigherprioritythreadthreadthreadCase Study: A Tale of Two ThreadsCase Study: Two intensive threads contendingrandom-accessstreaming17Prioritize random-accessPrioritize streamingrandom-access thread is more easily slowed down7xprioritized1x11xprioritized1xWhich is slowed down more easily?Why are Threads Different?18random-accessstreamingreqreqreqreqBank 1Bank 2Bank 3Bank 4MemoryrowsAll requests parallelHigh bank-level parallelismAll requests ? Same rowHigh row-buffer localityreqreqreqreqactivated rowreqreqreqreqreqreqreqreqstuckVulnerable so that interference

TCM Outline191. Clustering2. Between Clusters3. Non-Intensive Cluster4. Intensive ClusterFairnessThroughputNicenessHow so that quantify difference between threads?20Vulnerability so that interferenceBank-level parallelismCauses interferenceRow-buffer locality+Niceness-NicenessHighLowShuffling: Round-Robin vs. Niceness-AwareRound-Robin shufflingNiceness-Aware shuffling21Most prioritizedShuffleIntervalPriorityTimeNice threadLeast nice threadGOOD: Each thread prioritized once? What can go wrong?ABCDDABCD

Shuffling: Round-Robin vs. Niceness-AwareRound-Robin shufflingNiceness-Aware shuffling22Most prioritizedShuffleIntervalPriorityTimeNice threadLeast nice thread? What can go wrong?ABCDDABCDABDCBCADCDBADACBBAD: Nice threads receive lots of interferenceGOOD: Each thread prioritized onceShuffling: Round-Robin vs. Niceness-AwareRound-Robin shufflingNiceness-Aware shuffling23Most prioritizedShuffleIntervalPriorityTimeNice threadLeast nice threadGOOD: Each thread prioritized onceABCDDCBADShuffling: Round-Robin vs. Niceness-AwareRound-Robin shufflingNiceness-Aware shuffling24Most prioritizedShuffleIntervalPriorityTimeNice threadLeast nice threadABCDDCBADDACBBACDADBCDACBGOOD: Each thread prioritized onceGOOD: Least nice thread stays mostly deprioritized

TCM Outline251. Clustering2. Between Clusters3. Non-Intensive Cluster4. Intensive Cluster1. Clustering2. Between Clusters3. Non-Intensive Cluster4. Intensive ClusterFairnessThroughputOutlineMotivation & InsightsOverviewAlgorithmBringing it All TogetherEvaluationConclusion26Quantum-Based Operation27TimePrevious quantum (~1M cycles)During quantum:Monitor thread behaviorMemory intensityBank-level parallelismRow-buffer localityBeginning of quantum:Perform clusteringCompute niceness of intensive threadsCurrent quantum(~1M cycles)Shuffle interval(~1K cycles)

TCM Scheduling AlgorithmHighest-rank: Requests from higher ranked threads prioritizedNon-Intensive cluster > Intensive clusterNon-Intensive cluster: lower intensity ? higher rankIntensive cluster: rank shufflingRow-hit: Row-buffer hit requests are prioritizedOldest: Older requests are prioritized28Implementation CostsRequired storage at memory controller (24 cores)No computation is on the critical path29OutlineMotivation & InsightsOverviewAlgorithmBringing it All TogetherEvaluationConclusion30FairnessThroughput

Sensitivity Results43

Dove, Gerry Editorial Board

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This Particular Journal got reviewed and rated by TCM Outline251. Clustering2. Between Clusters3. Non-Intensive Cluster4. Intensive Cluster1. Clustering2. Between Clusters3. Non-Intensive Cluster4. Intensive ClusterFairnessThroughputOutlineMotivation & InsightsOverviewAlgorithmBringing it All TogetherEvaluationConclusion26Quantum-Based Operation27TimePrevious quantum (~1M cycles)During quantum:Monitor thread behaviorMemory intensityBank-level parallelismRow-buffer localityBeginning of quantum:Perform clusteringCompute niceness of intensive threadsCurrent quantum(~1M cycles)Shuffle interval(~1K cycles) and short form of this particular Institution is CA and gave this Journal an Excellent Rating.