s, adaptive hypermedia AH tailors what the user sees to the learner s goals, abilities, interests, knowledge, etc. Adaptive hypermedia is the answer to the lost in hyperspace syndrome, where the user ... the most appropriate ones to him her. Adaptive hypermedia thus offers a selection of links or content most appropriate to the current user. Moreover, adaptive hypermedia can also offer the most appropriate ... the information from e.g. hand held device versus desktop, etc. . Adaptive hypermedia is thus ... application field of adaptive hypermedia is adaptive educational hypermedia AEH , which tailors what ... via adaptive hypermedia, where the items offered for purchasing are adapted to the user s detected ..., the use of adaptive hypermedia is not limited to formal or informal education or training endeavours ..., services, and experiences. Thus, systems like Amazon.com Amazon are also examples of adaptive ... of adaptive hypermedia, besides adaptive e learning and adaptive e commerce applications, can be adaptive e government applications. Generally speaking, adaptive hypermedia systems can be useful anywhere where hypertext and hypermedia are used. The most popular adaptive hypermedia systems are World ... commerce and computer engineering are contributing to the development of adaptive hypermedia. Unlike intelligent tutoring systems , however, adaptive educational hypermedia doesn t target stand alone systems, but hypermedia systems. Adaptivity versus adaptability An interesting aspect of adaptive hypermedia ... , whereas an adaptive system that presents intelligence is more surprising and thus more interesting. This conforms with the general preference of the adaptive hypermedia research community, which considers adaptation more interesting. However, the truth of adaptive hypermedia systems is somewhere ... Research Adaptive hypermedia is the object of a number of researches, in particular in conjunction ... www.umuai.org User Modeling and User Adapted Interaction UMUAI http www.ah2008.org Adaptive Hypermedia ... more details
Logic optimization , a part of logic synthesis , is the process of finding an equivalent representation of the specified logic circuit under one or more specified constraints. Generally the circuit is constrained to minimum chip area meeting a prespecified delay. Introduction With the advent of logic synthesis , one of the biggest challenges faced by the Electronic design automation EDA industry was to find the best netlist representation of the given design description. While two level logic optimization had long existed in the form of the Quine McCluskey algorithm , later followed by the Espresso heuristic logic minimizer , the rapidly improving chip densities, and the wide adoption of Hardware description language HDLs for circuit description, formalized the logic optimization domain as it exists today. Today, logic optimization is divided into various categories based on two criteria Based on circuit representation Two level logic optimization Multi level logic optimization Based on circuit characteristics Sequential logic optimization Combinational logic optimization While a two level circuit representation of circuits strictly refers to the flattened view of the circuit in terms of SOPs Canonical form Boolean algebra sum of products &mdash which is more applicable to a Programmable logic array PLA implementation of the design Clarify date February 2010 &mdash a multi level representation is a more generic view of the circuit in terms of arbitrarily connected SOPs, POSs Canonical form Boolean algebra product of sums , factored form etc. Logic optimization algorithms generally work either on the structural SOPs, factored form or functional BDDs, ADDs representation of the circuit. Clarify date February 2010 Two level versus multi level representations If we have two ... diagram Circuit minimization References Synthesis and Optimization of Digital Circuits , by Giovanni ... Digital electronics Category Electronic design automation Category Electronics optimization ... more details
nofootnotes date December 2011 Process optimization is the discipline of adjusting a process so as to optimize some specified set of parameters without violating some constraint. The most common goals are minimizing cost, maximizing throughput, and or efficiency. This is one of the major quantitative property quantitative tools in industrial decision making. When optimizing a process, the goal is to maximize one or more of the process specifications, while keeping all others within their constraints. Areas Fundamentally, there are three parameters that can be adjusted to affect optimal performance. They are Equipment optimization The first step is to verify that the existing equipment is being used to its fullest advantage by examining operating data to identify equipment bottlenecks. Operating procedures Operating procedures may vary widely from person to person or from shift to shift. Automation of the plant can help significantly. But automation will be of no help if the operators take control and run the plant in manual. Control optimization In a typical processing plant, such as a chemical plant or oil refinery , there are hundreds or even thousands of control loops. Each control loop is responsible for controlling one part of the process, such as maintaining a temperature, level, or flow. If the control loop is not properly designed and tuned, the process runs below its optimum. The process will be more expensive to operate, and equipment will wear out prematurely. For each control loop to run optimally, identification of sensor, valve, and tuning problems is important ... supervision. See also Calculation of glass properties , optimization of several properties Deficit irrigation to optimize water productivity Metallurgical Process Optimization Process simulation External links http www.expertune.com r2.asp?f Wikipedia&l learncast.html Tutorials on Process Optimization ... and graph algorithms. Category Process management Category Mathematical optimization de Prozessoptimierung ... more details
Query optimization is a function of many relational database management system s in which multiple query plan s for satisfying a query are examined and a good query plan is identified. This may or not be the absolute best strategy because there are many ways of doing plans. There is a trade off between the amount of time spent figuring out the best plan and the amount running the plan. Different qualities of database management systems have different ways of balancing these two. Cost based query optimizer s evaluate the resource footprint of various query plans and use this as the basis for plan selection. Typically the resources which are costed are CPU path length, amount of disk buffer space, disk storage service time, and interconnect usage between units of parallelism. The set of query plans examined is formed by examining possible access paths e.g., primary index access, secondary index access, full file scan and various relational table join techniques e.g., merge join, hash join, product join . The search space can become quite large depending on the complexity of the SQL query. There are two types of optimization. These consist of logical optimization which generates a sequence of relational algebra to solve the query. In addition there is physical optimization which is used to determine the means of carrying out each operation. External links http www.sql performance tuning.com oracle sql performance tuning Information about query optimization http www.sql performance tuning.com oracle tuning tools Query optimization example Databases Category Database algorithms Category Database management systems Category SQL he ru ... more details
Expert subject Computing date May 2011 Adaptive compression is a type of data compression which changes compression algorithm s based on the type of data being compressed. ref name PCMag Cite web url http www.pcmag.com encyclopedia term 0,2542,t adaptive compression&i 37503,00.asp work PC Magizine Encyclopedia title Adaptive compression accessdate 21 April 2011 ref References reflist Category Data compression Computing stub ... more details
Spiral Optimization is a metaheuristics algorithm developed by Kenichi Tamura and Keiichiro Yasuda. ref name tspiral2011 ref name spiral2011 It was inspired by spiral phenomena in nature. References reflist refs ref name tspiral2011 cite journal last1 Tamura first1 K. last2 Yasuda first2 K. title Primary Study of Spiral Dynamics Inspired Optimization journal IEEJ Transactions on Electrical and Electronic Engineering year 2011 volume 6 issue S1 pages S98&ndash S100 url http onlinelibrary.wiley.com doi 10.1002 tee.20628 abstract doi 10.1002 tee.20628 ref ref name spiral2011 cite journal last1 Tamura first1 K. last2 Yasuda first2 K. title Spiral Dynamics Inspired Optimization journal Journal of Advanced Computational Intelligence and Intelligent Informatics year 2011 volume 15 issue 8 pages 1116&ndash 1122 url http www.fujipress.jp finder xslt.php?mode present&inputfile JACII001500080020.xml ref Category Heuristics algorithm stub ... more details
For algorithms to solve other optimization problems Optimization mathematics Mergefrom Algorithmic efficiency Optimization techniques date September 2009 In computer science , program optimization or software optimization is the process of modifying a software system to make some aspect of it work more ... or other resources, or draw less power. General Although the word optimization shares the same root as optimal , it is rare for the process of optimization to produce a truly optimal system. The optimized ... so the process of optimization may be halted before a completely optimal solution has been reached ... of optimizationOptimization can occur at a number of levels Design level At the highest level ... be decided, arguments against early or premature optimization may be hard to justify. In some cases, however, optimization relies on using more elaborate algorithms, making use of special cases ... itself generates, and few projects need resort to this ultimate optimization step. However, a large ... phase run time optimization exceeding the capability of static compilers by dynamically adjusting parameters ... Code optimization can be also broadly categorized as computer platform platform dependent and platform ... level optimization, platform independent techniques are generic techniques such as loop unrolling, reduction ..., data level parallelism, cache optimization techniques i.e., parameters that differ among various ... The optimization, sometimes performed automatically by an optimizing compiler, is to select a method ... can often be achieved by removing extraneous functionality. Optimization is not always ... and division. Visible anchor Trade offs Pessimization redirects here Optimization will generally focus ... include code clarity and conciseness. There are instances where the programmer performing the optimization ... the code. Bottlenecks Optimization may include finding a Bottleneck engineering bottleneck ..., the Pareto principle can be applied to resource optimization by observing that 80 of the resources ... more details
. These methodologies, or conversion optimization methods, are then taken a step further to run ... the scale and effectiveness of the online campaign. How conversion optimization works Conversion Rate Optimization is the process of increasing website leads and sales without spending money on attracting ... approaches to conversion optimization with two main schools of thought prevailing in the last ... stage of the optimization process. In this second approach, the optimization company will invest ... conversion rates. Elements of the test focused approach to conversion optimization Conversion optimization ..., customer, etc. Optimization goals The official definition of optimization is the discipline of applying .... Business rules Arbitrary business rules must be handled under one optimization framework. Some ... Optimization Category Internet advertising and promotion Category Internet marketing terminology ... more details
In mathematics and computer science , an optimization problem is the Computational problem problem of finding the best solution from all feasible solution s. Optimization problems can be divided into two categories depending on whether the Variable mathematics variables are continuous or discrete. An optimization problem with discrete variables is known as a combinatorial optimization problem . In a combinatorial optimization problem, we are looking for an object such as an integer, permutation or graph from a finite or possibly countable infinite set. Continuous optimization problem The standard form of a continuous optimization problem is ref cite book title Convex Optimization first1 Stephen ... the objective function. Combinatorial optimization problem Formally, a combinatorial optimization ... For each combinatorial optimization problem, there is a corresponding decision problem that asks whether ... mathematics graph math G math which contains vertices math u math and math v math , an optimization ... problems, the problem is more naturally characterized as an optimization problem. ref name Ausiello03 ... and Approximation publisher Springer isbn 978 3540654315 ref NP optimization problem An NP optimization problem NPO is a combinatorial optimization problem with the following additional conditions ... . In computer science, interesting optimization problems usually have the above properties and are therefore NPO problems. A problem is additionally called a P optimization PO problem, if there exists ... NPO, one is interested in optimization problems for which the decision versions are NP hard. Note that hardness ... algorithms and computational optimization problems, reductions which preserve approximation ... s. An example of such a reduction would be the L reduction . For this reason, optimization problems ... last1 Kann first1 Viggo year 1992 title On the Approximability of NP complete Optimization Problems ... properties. References reflist See also Mathematical optimization Semi infinite programming Decision ... more details
Shape optimization is part of the field of optimal control theory. The typical problem is to find the shape ... partial differential equation defined on the variable domain. Topology optimization is, in addition ... are needed since typically shape optimization methods work in a subset of allowable shapes ... optimization techniques can then help work around the limitations of pure shape optimization. Definition Mathematics Mathematically , shape optimization can be posed as the problem of finding a bounded ... to that end to ensure well posedness of the problem and uniqueness of the solution. Shape optimization is an infinite dimensional optimization problem. Furthermore, the space of allowable shapes over which the optimization is performed does not admit a vector space structure, making application of traditional optimization methods more difficult. Examples ul li Among all three dimensional shapes ... of this inverse problem using least squares fit leads to a shape optimization problem. li ul Techniques Shape optimization problems are usually solved numerical analysis numerically , by using ... it, until it morphs into the optimal shape. Keeping track of the shape To solve a shape optimization ... matrix Hessian of the objective functional math mathcal F math . If the shape optimization ... Allaire, G. 2002 Shape optimization by the homogenization method . Applied Mathematical Sciences 146, Springer Verlag. ISBN 0387952985 Ashok D. Belegundu, Tirupathi R. Chandrupatla. 2003 Optimization .... 2003 Topology Optimization Theory, Methods and Applications . Springer. ISBN 3 540 42992 1. Burger ... Analysis, Differential Calculus, and Optimization . SIAM. ISBN 0 89871 489 3. Haslinger, J. M kinen, R. 2003 Introduction to Shape Optimization Theory, Approximation and Computation . Society ... Methods in Sensitivity Analysis and Shape Optimization. Birkh user. ISBN 0 8176 4322 2. Mohammadi, B. Pironneau, O. 2001 Applied Shape Optimization for Fluids . Oxford University Press. ISBN 0 19 850743 ... more details
about iterative method s the modeling and optimization of decisions under uncertainty stochastic programming Stochastic optimization SO methods are optimization mathematics optimization iterative method ... in the formulation of the optimization problem itself, which involve random objective function s or random constraints, for example. Stochastic optimization methods also include methods with random iterates. Some stochastic optimization methods use random iterates to solve stochastic problems, combining both meanings of stochastic optimization. ref name spall2003 Cite book author Spall, J. C. title Introduction to Stochastic Search and Optimization year 2003 publisher Wiley url http www.jhuapl.edu ISSO isbn 0471330523 ref Stochastic optimization methods generalize deterministic system mathematics ... input data arise in such areas as real time estimation and control, simulation based optimization ... fu2002 cite journal author Fu, M. C. title Optimization for Simulation Theory vs. Practice journal ... performance uniformly across many data sets, for many sorts of problems. Stochastic optimization ... ref name kirk1983 cite journal author S. Kirkpatrick coauthors C. D. Gelatt M. P. Vecchi title Optimization ... Probability Collectives in Optimization year 2011 booktitle Handbook of Statistics editor C.R. Rao ... ref Reactive Search Optimization reactive search optimization RSO by Roberto Battiti , G. Tecchiolli ... Optimization last Battiti first Roberto authorlink coauthors Mauro Brunato Franco Mascia ... for global optimization of complex potential energy landscapes journal Phys. Rev. Lett. volume ... book author Goldberg, D. E. title Genetic Algorithms in Search, Optimization, and Machine Learning ... See also Global optimization Machine learning Gaussian process State Space Model Model predictive ... optimization.com home products products sp.html XPRESS SP DEFAULTSORT Stochastic Optimization Category Estimation theory Category Probability theory Category Stochastic optimization it Ottimizzazione ... more details
other uses Optimization disambiguation File MaximumParaboloid.png right thumb Graph of a paraboloid given ... , computational science , or management science , mathematical optimization alternatively, optimization or mathematical programming refers to the selection of a best element from some set .... ref In the simplest case, an optimization problem consists of maxima and minima maximizing or minimizing .... The generalization of optimization theory and techniques to other formulations comprises a large area of applied mathematics . More generally, optimization includes finding best available values ... types of objective functions and different types of domains. Optimization problems main Optimization problem An optimization problem can be represented in the following way Given a function mathematics ... 0 sub f x for all x in A maximization . Such a formulation is called an optimization problem or a mathematical ..., the standard form of an optimization problem is stated in terms of minimization. Generally ... to the actual optimal solution of a non convex problem is called global optimization . Notation Optimization ... proposed iterative methods for moving towards an optimum. Historically, the first term for optimization ... optimization include the following col begin col 2 Richard Bellman Ronald A. Howard Narendra Karmarkar ... did some stuff here , Gauss developed the method of least squares, which is an optimization method ... of quadratic programs. Semidefinite programming SDP is a subfield of convex optimization where ... programming. Fractional programming studies optimization of ratios of two nonlinear functions. The special class of concave fractional programs can be transformed to a convex optimization problem. Nonlinear ... some of the constraints or parameters depend on random variable s. Robust optimization Robust programming is, like stochastic programming, an attempt to capture uncertainty in the data underlying the optimization ... is solved taking into account inaccuracies in the input data. Combinatorial optimization is concerned ... more details
int Omega phi rho , mathrm d Omega right math This is the goal of the optimization study which is to be minimised ... from meshing of the domain. Topology Optimization for Stiff Structures A stiff structure is one that has ... optimization to be a process of selection of micro structure at every point in space so that an objective ... will be the deflection as there is more material to resist the loads. So, the optimization requires ... of these issues. File Topology Optimization with filtereing.tif thumb Topology Optimization result when filtering is used blockquote Distinction Topology optimization is distinct from shape optimization ... Investigation into Structural Topology Optimization Problem Formulations, William Renold, lulu.com ... Implementation of Topology Optimization Uwe Schramm, Ming Zhou IUTAM Symposium on Topological Design Optimization of Structures, Machines and Materials Status and Perspectives, 239 248 2006 Springer. http ... Implementation and Applications of Topology Optimization and Future Needs Claus B.W. Pedersen Peter Allinger IUTAM Symposium on Topological Design Optimization of Structures, Machines and Materials, 229 238 2006 Springer. http www.springerlink.com content ge6gcby65c0gfeg6 A 99 line topology optimization code written in Matlab Ole Sigmund Int Journal of Structural and Multidisciplinary Optimization, Volume 21, 120 127, 2001 Springer http www.springerlink.com content a7653p3h70116666 Topology optimization ... Mary Frecker Int Journal of Structural and Multidisciplinary Optimization, Volume 32, 121 132, 2006 Springer http vrand.com node 48 Modern Structural Optimization Concepts Applied to Topology Optimization ... page containing information on the SIMP optimization method. DEFAULTSORT Topology Optimization Category Mathematical optimization Category Topology fr Optimisation topologique ... more details
Trajectory optimization is the process of designing a trajectory that minimizes or maximizes some figure ..., the goal of solving a trajectory optimization problem is essentially the same as solving an optimal ... Trajectory optimization began in earnest in the 1950s as digital computers became available for the computation ... in the development of optimal control. Early application of trajectory optimization had to do with the optimization of rocket thrust profiles in a vacuum and in an atmosphere. From the early work, much of the givens about rocket propulsion optimization were discovered. Another successful application ... associated with the transonic drag region and the low thrust of early jet aircraft, trajectory optimization ... altitude schedule based on optimal control solutions. In the early phase of trajectory optimization ... H.J. Kelley, R.E. Kopp, and H.G. Moyer, Singular Extremals , Topics in Optimization, G. Leitmann ed ... is the optimization of the thrust of a missile flying at a constant altitude and which is launched at low ... to maximize missile performance. Many of the early triumphs of trajectory optimization have moved ... to the Japanese mathematician Kiyoshi Ito. Solution techniques The techniques available to solve optimization mathematics optimization problems fall into two broad categories the optimal control methodology ... approximates the problem by a finite dimensional problem. Trajectory optimization shares the same optimization algorithms as other optimization problems. The numerical optimal control methodology ... parameter optimization problems. The simplest procedures use the gradient descent technique, sometimes ... a wide variety of rocket trajectory optimization problems. The nonlinear programming approach is generally .... This restriction was a problem in the early days of trajectory optimization when computer computation ... methods have evolved as the optimization algorithms of choice. These algorithms may require orders ... 2004, vol.2 2357 2363 ref ref A hybrid multiagent approach for global trajectory optimization ... more details
onesource date March 2010 Portfolio optimization is the process of changing the set of financial instruments held to meet various criteria most notably Financial risk An Efficient Portfolio Markowitz Modern portfolio theory states that an investor may choose to exchange risk for return along a curve known as the Efficient frontier . Since it is inefficient to incur a given level of risk when one can rearrange the portfolio to achieve a greater expected return for the same risk, there is a strong motivation to optimize. Definition Of Portfolio Portfolios are an appropriate mix or collection of investments held by an institution or an individual. Constraints The Tebow model allows for short position s ie negative in a given instrument, and this may not always be possible. This may be for regulatory reasons, investor preference, or the lack of a liquid market that supports short selling. It may also be the case for a large portfolio Portfolio Optimization The Portfolio Optimization template calculates the optimal capital weightings for a basket of investments that gives the highest return for the least risk. The unique design of the template enables it to be applied to either financial instrument or business portfolios. The ability to apply optimization analysis to a portfolio of businesses ... decisions. Key features of the Portfolio Optimization template include Ease and flexibility of input ... the correlation matrix and portfolio dynamics prior to the optimization process. Set the analysis ... be done by computer. Central to this optimization is the construction of the Covariance matrix for the instruments ... Mixed integer programming Issues with Portfolio optimization Investment is a forward looking activity ... optimization assumes the investor may have some risk aversion and the stock prices may exhibit significant ... Optimization Online Allows users to compare stock performance, make free stock analysis, and optimize stock portfolio. http apps.facebook.com fastocks Facebook Application for Portfolio Optimization ... more details
Robust optimization is a field of optimization mathematics optimization theory that deals with optimization ... in the value of a parameter of the problem. History The origins of robust optimization date back to the establishment ... of math mathbb R 2 math . What makes this a robust optimization problem is the math forall c,d in P ... many elements , then this robust optimization problem itself is a linear programming problem for each ... There are a number of classification criteria for robust optimization problems models. In particular ... probabilistic and non probabilistic models of robustness. Modern robust optimization deals primarily ... with decision math x math . Global robustness Consider the simple abstract robust optimization ... possible values of math u math under consideration. This is a global robust optimization problem .... This yields the following robust optimization problem math max x in X, Y subseteq U size ... because the robust optimization problems that it induces are usually not always very difficult to solve. Example Consider the robust optimization problem math z U max x in X f x g x,u le b, forall ... robust optimization problem math z mathcal N max x in X f x g x,u le b, forall u in mathcal N math ... relaxed robust optimization problem math z mathcal N ,U max x in X f x g x,u le b beta cdot dist u ... probabilistic robust optimization models The dominating paradigm in this area of robust optimization ... referred to as minimax or maximin optimization problem. The non probabilistic deterministic model has been and is being extensively used for robust optimization especially in the field of signal processing ... Robust Pareto Frontier in Multiobjective Optimization Using Fuzzy Set Theory. 51st AIAA ASME ASCE ... a Robust measure in context of multiobjective optimization to find the robust Pareto optimal solutions. Probabilistic robust optimization models These models quantify the uncertainty in the true ... classified as stochastic programming and stochastic optimization models. See also Stability ... more details
Orphan date October 2009 The scenario approach or scenario optimization approach is a technique for obtaining solutions to robust optimization and chance constrained optimization problems based on randomization of the constraints. The technique has existed for decades as a heuristic approach, but the field has been given a systematic theoretical foundation only recently thanks to some important achievements by Marco Campi, Giuseppe Calafiore, Simone Garatti and Maria Prandini. Description In Optimization mathematics optimization , robustness features translate into constraints that are parameterized in the uncertain elements of the problem. The scenario method ref G. Calafiore and M.C. Campi. Uncertain Convex Programs randomized Solutions and Confidence Levels. Mathematical Programming, 102 25&ndash 46, 2005. http www.springerlink.com content qlcbr9eg3dne6ldb ?p ad759ab4ef9f49049f9b5ef14e7b00ee&pi 1 ref ref M.C. Campi and S. Garatti. The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs. SIAM J. on Optimization, 19, no.3 1211&ndash 1230, 2008. http siamdl.aip.org vsearch servlet VerityServlet?KEY SJOPE8&smode strresults&sort chron&maxdisp 25&threshold 0&pjournals ... level the use of randomization in robust and chance constrained optimization. Deleted image removed Image risk return.jpg thumb Figure 1 risk return trade off When the constraints are convex optimization ... Feasibility and Optimality . Available on Optimization Online. http www.optimization online.org ... robust the various solutions are. The final outcome is a risk robustness vs. return optimization value ... and solve the scenario optimization program math max x min i 1, dots,N R delta i x . 1 math .... Addendum Why this example can be seen as an optimization program with uncertain constraints? To better relate this investment problem to the previous discussion where optimization problems with uncertain ... references Category Stochastic optimization Category Decision theory Category Control theory ... more details
Cite check date November 2007 Bandwidth optimization is one of many concerns webmasters deal with when hosting web content. Since most web hosts charge by Bandwidth computing bandwidth used or have an account limit on bandwidth, a prudent webmaster will squeeze and Bandwidth compression compress their files as much as possible without affecting the content s integrity. Lately, most web hosts are offering unlimited bandwidth. Reductions in bandwidth usage are measured in negabytes , a unit akin to other negative units such as negawatts , negavolts , negajoules , negameters , and negagrams . Even the simplest bandwidth optimization techniques can reduce bandwidth costs significantly. Owners of extremely high volume web services are especially diligent, and have been known to employ extreme techniques to save a few bytes per page. For example, many staple pages are highly optimized with whitespace and line breaks removed, unneeded quotes removed around HTML attributes, and images compressed to the limit while maintaining clarity. Most bandwidth optimization techniques can fit into one of three categories Efficiency, Compression, and Omission. Efficiency Efficiency techniques involve changing the web content in order to minimize the number of bytes that need to be sent. For example, use external files which will cache instead of inline styles and scripts, reuse icon images, use semantic markup. Fix any broken images, since these often send a verbose 404 error page. Compression Use compression on the server to squash files before they are sent. Compression is a well established technique in telecommunications, since without significant bandwidth compression, the telephone grid could not handle the amount of data that passes through it. On the web the most popular compression algorithm for real time compression is gzip . The topic of compression also includes image compression e.g. JPG, PNG, GIF Also see Wan optimization WAN Optimization Omission Omit unneeded bytes. Remove ... more details
Extremal Optimization EO is an Optimization mathematics optimization heuristic computer science heuristic .... This heuristic computer science heuristic was designed initially to address combinatorial optimization ... has been demonstrated to function in optimization domains. Relation to self organized criticality ... optimisation problems that lead to the development of Extremal Optimization by Stefan Boettcher and Allon Percus. The technique EO was designed as a local search optimization local search algorithm for combinatorial optimization problems. Unlike genetic algorithms , which work with a population ... colony optimization and evolutionary computation that assign equal fitness to all components ... Optimization GEO was developed to operate on bit strings where component quality is determined ... domains. Another similar extension to EO is Continuous Extremal Optimization CEO . EO has been applied to image rasterization as well as used as a local search after using ant colony optimization ... Optimization Methods derived from Co Evolution , Proceedings of the Genetic and Evolutionary ... optimization of graph partitioning at the percolation threshold , J. Phys. A Math. Gen. 32 , 5201 ... http ieeexplore.ieee.org iel5 5992 19077 00881710.pdf S Boettcher, Extremal Optimization Heuristics ... prola.aps.org abstract PRL v86 i23 p5211 1 Stefan Boettcher and Allon G. Percus, Optimization with Extremal ... Boettcher and Michelangelo Grigni, Jamming Model for the Extremal Optimization Heuristic , J. Phys ... Souham Meshoul and Mohamed Batouche, Robust Point Correspondence for Image Registration Using Optimization ... abs q bio.PE 0410007 Roberto N. Onody and Paulo A. de Castro, Self Organized Criticality, Optimization ... e066703 Stefan Boettcher and Allon G. Percus, Extremal Optimization at the Phase Transition of the 3 ... Middleton, Improved extremal optimization for the Ising spin glass , Phys. Rev. E 69 , 055701 2004 ... possible probability distribution over extremal optimization ranks , Europhys. Lett. 66 , pp. 305 ... more details
WAN optimization is a collection of techniques for increasing data transfer efficiencies across wide area network s. In 2008, the WAN optimization market was estimated to be 1 billion, ref cite web last Machowinski first Matthias title WAN optimization market passes 1 billion in 2008, up 29 enterprise router market down url http www.infonetics.com pr 2009 4q08 enterprise routers market research.asp work Enterprise Routers and WAN Optimization Appliances publisher Infonetics Research accessdate 19 July 2011 ref and it will grow to 4.4 billion when date January 2012 according to Gartner, ref cite web last Skorupa first Joe title Forecast Application Acceleration Equipment, Worldwide, 2006 2014, 2Q10 Update url http www.gartner.com DisplayDocument?id 1387649 publisher Gartner, Inc accessdate 19 ... of TCP data transfer efficiencies i.e., optimization are throughput, bandwidth requirements, latency, protocol optimization, and congestion, as manifested in dropped packets. ref cite web last Cardwell ..., and other Business Continuity Disaster Recovery BC DR flows. WAN optimization has been ... proprietary WAN optimization solutions was the Branch WAN. In recent years, however, the rapid growth ... WAN optimization. Component techniques of Branch WAN Optimization include deduplication, Wide area ... management . Requirements for DC2DC WAN Optimization also center around deduplication and TCP acceleration, however these must occur in the context of multi gigabit data transfer rates. WAN optimization ... hardware or virtual machine based WAN acceleration appliances. Latency optimization Can include TCP ... optimization solutions OpenNOP WANProxy TrafficSqueezer Products and companies implementing WAN optimization ... optimization Maximizing WAN Optimization http www.youtube.com watch?v 3Aj6OlZ3aZI Info Tech Research WAN Optimization for Cloud Storage Access Category Wide area networks Category Network performance Category Network protocols Category Internet protocols Category WAN optimization de WAN Optimierung ... more details
refimprove date June 2007 Adaptive equipment are tool device s that are used to assist with completing activities of daily living . Bathing , dressing, Personal grooming grooming , toileting, and feeding are self care activities that are including in the spectrum of activities of daily living ADLs . Jennifer McLaughlin Maly a P.T. D.P.T. in her article located in the journal Exceptional Parent gives a more complete definition of adapative equipment Typically, a piece of adaptive equipment is utilized to increase a child s function. Examples of adaptive equipment or assistive technology are wheelchairs, lifts, standing frames, gait trainers, augmentative communication devices, bath chairs, and recreational items such as swings or tricycles. ref McLaughlin Maly, J. 2007 . My child needs a piece of adaptive equipment Now what? Well it depends The Exceptional Parent, 11 37 , 46 47 ref A growing market for adaptive equipment is in the use of mobility vans. In this case, adaptive equipment, also known as assistive technology, can help a person with a disability operate a motor vehicle when otherwise they would not be able to. ref http www.clockmobility.com assistive technology Adaptive Equipment ref References Reflist Category Tools disability stub ... more details
Adaptive rowing is a special category of rowing sport rowing race for those with physical Disability disabilities . Under International Rowing Federation FISA rules there are three categories for adaptive rowers LTA Legs, Trunk, Arms Use of at least one leg, trunk and arms. Also for those with visually impaired visual and intellectual impairment s. Rowed with standard boats and sliding seats. TA Trunk and Arms Only use of trunk muscles. Boat has fixed seat. AS Arms and Shoulders Limited trunk control. Boat has fixed seat and rower is strapped at upper chest level to only allow shoulder and arm movements. At FISA events there are 4 boat events standard sport rowing Terminology and event nomenclature nomenclature is used 4 Mixed LTA 2x Mixed TA 1x Men AS 1x Women AS Racing is held over 1,000 m rather than the standard 2,000 m . In mixed events half the crew must be male and other half female coxswain maybe of either gender and may be able bodied . Single shells for the Arms and Shoulders category must have stabilising pontoons attached to the riggers. Adaptive events were added to the World Rowing Championships in 2002 and took place at the 2008 Summer Paralympics in Beijing , China . External links http www.worldrowing.com event report.sps?iType 4138&icustompageid 6618 FISA Adaptive Rowing page http www.rowingcanada.org domestic rowing adaptive Rowing Canada s Domestic Adaptive Rowing Page http www.britishrowing.org taking part adaptive British Rowing s UK Domestic Adaptive Rowing Page http www.usrowing.org Adaptive USRowing s Domestic Adaptive Rowing Page Category Rowing ... more details
orphan date August 2009 An Adaptive website is a website that builds a model of user activity and modifies the information and or presentation of information to the user in order to better address the user s needs. Overview An adaptive website adjusts the structure, content, or presentation of information in response to measured user interaction with the site, with the objective of optimizing future user interactions. Adaptive websites are web sites that automatically improve their organization and presentation by learning from their user access patterns. . ref cite conference last Perkowitz first Mike coauthors Oren Etzioni. title Adaptive Web Sites an AI Challenge booktitle Proc. IJCAI 97 year 1997 url http www.cs.washington.edu research adaptive papers ijcai97.pdf ref User interaction patterns may be collected directly on the website or may be data mining mined from Web server logs. A model or models are created of user interaction using artificial intelligence and statistics statistical methods . The models are used as the basis for tailoring the website for known and specific patterns ... content are not adaptive websites as they rely on the user to select rather than the automation ... that are used on a website do not make it an adaptive website. They are all tools and techniques that may be used toward engineering an adaptive website. See also Collaborative filtering Machine learning Notes reflist References J.D. Vel squez and V. Palade, Adaptive Web Sites A Knowledge Extraction ... research adaptive papers ijcai97.pdf Adaptive Web Sites an AI Challenge , in Proc. IJCAI 97, Nagoya, Japan, 1997. Mike Perkowitz, Oren Etzioni, http www.cs.washington.edu research adaptive papers aij.pdf Towards adaptive Web sites Conceptual framework and case study , Artificial Intelligence 118 1 2 , 2000 External links http www.puremango.co.uk 2009 06 adaptive web sites Adaptive Web Sites , puremango.co.uk ... to A B test and optimize webpages DEFAULTSORT Adaptive Website Category Websites Category Collective ... more details
Advert date July 2011 Notability Companies date November 2011 Infobox company company name Adaptive Planning, Inc. company logo File Adaptive Planning Logo.gif company type Private company Private foundation ... United States US industry Software product Adaptive Planning homepage http www.adaptiveplanning.com www.adaptiveplanning.com Adaptive Planning, Inc. is a privately held Software as a service Software ... CPM solution to over 1,000 clients and 20,000 users worldwide. ref http www.adaptiveplanning.com , Adaptive Planning ,06 24 11 ref Overview In 2003, Robert S. Hull and Richard Dellinger co founded Adaptive .... Adaptive Planning was one of the first entries onto a nascent SaaS Business Intelligence BI and Corporate Performance Management CPM stage. Product File AP screenshot.jpg thumb 200px alt Adaptive Planning Screenshot Screenshots of the Adaptive Planning Interface. Adaptive Planning, Inc. is the maker of the Adaptive Planning application. The Adaptive Planning application is used for corporate ..., and Cost accounting variance analysis . ref http www.itjungle.com fhs fhs110111 story03.html, Adaptive ... based consumer application. But unlike spreadsheets, Adaptive Planning automates consolidations and integration ... rates adaptive planning 1 in customer satisfaction, IntuitiveTEK ,10 26 10 ref As with most SaaS models, Adaptive Planning customers pay an annual subscription fee to maintain their license, and their Instance ... CPM Solutions.pdf, Hurwitz ref On April 4, 2011, Adaptive Planning announced its Spring 2011 Release, ref http finance.yahoo.com news Adaptive Planning Introduces iw 1341246388.html?x 0&.v 1, Yahoo Finance ... to plan and manage their businesses. Awards Adaptive Planning was rated 1 in customer satisfaction ..., Gartner ,09 15 10 ref BPM Partners announced that Adaptive Planning was rated highest in customer satisfaction in its 2011 Pulse Survey. ref http www.adaptiveplanning.com news 92 61 Adaptive Planning ... ,03 07 11 ref Adaptive Planning was ranked 85 Top 10 in Silicon Valley on Deloitte s 2011 Technology ... more details
Unreferenced date December 2009 An adaptive beamformer is a beamforming system which performs adaptive spatial signal processing with an array of radar antennas or phased array in order to transmit or receive signals in different directions without having to mechanically steer the array. The main distinction between an adaptive beamformer and a conventional beamforming system is the ability of the former to adjust its performance to suit differences in its environment. A particularly important feature, in military applications, is the potential for an adaptive beamformer to reduce sensitivity to certain directions of arrival so as to counteract jamming by hostile transmissions. Adaptive Beamforming Schemes Least mean squares filter Least Mean Squares Algorithm Sample Matrix Inversion Algorithm Recursive least squares filter Recursive Least Square Algorithm Conjugate gradient method Constant Modulus Algorithm See also Beamforming is spatial signal processing which makes spatial beam focused on the target direction and spatial beam nulled interference signal. Smart Antennas is multiple antenna systems having one of three structures which are single input and multiple output SIMO , multiple input and single output MISO , and multiple input and multiple output MIMO structures. MIMO is an advanced smart antenna system which has multiple transmit antennas at the transmitter and multiple receive antennas at the receiver. DEFAULTSORT Adaptive Beamformer Category Signal processing ... more details
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