871 resultados para Dynamic Model Averaging
Resumo:
With the shift towards many-core computer architectures, dataflow programming has been proposed as one potential solution for producing software that scales to a varying number of processor cores. Programming for parallel architectures is considered difficult as the current popular programming languages are inherently sequential and introducing parallelism is typically up to the programmer. Dataflow, however, is inherently parallel, describing an application as a directed graph, where nodes represent calculations and edges represent a data dependency in form of a queue. These queues are the only allowed communication between the nodes, making the dependencies between the nodes explicit and thereby also the parallelism. Once a node have the su cient inputs available, the node can, independently of any other node, perform calculations, consume inputs, and produce outputs. Data ow models have existed for several decades and have become popular for describing signal processing applications as the graph representation is a very natural representation within this eld. Digital lters are typically described with boxes and arrows also in textbooks. Data ow is also becoming more interesting in other domains, and in principle, any application working on an information stream ts the dataflow paradigm. Such applications are, among others, network protocols, cryptography, and multimedia applications. As an example, the MPEG group standardized a dataflow language called RVC-CAL to be use within reconfigurable video coding. Describing a video coder as a data ow network instead of with conventional programming languages, makes the coder more readable as it describes how the video dataflows through the different coding tools. While dataflow provides an intuitive representation for many applications, it also introduces some new problems that need to be solved in order for data ow to be more widely used. The explicit parallelism of a dataflow program is descriptive and enables an improved utilization of available processing units, however, the independent nodes also implies that some kind of scheduling is required. The need for efficient scheduling becomes even more evident when the number of nodes is larger than the number of processing units and several nodes are running concurrently on one processor core. There exist several data ow models of computation, with different trade-offs between expressiveness and analyzability. These vary from rather restricted but statically schedulable, with minimal scheduling overhead, to dynamic where each ring requires a ring rule to evaluated. The model used in this work, namely RVC-CAL, is a very expressive language, and in the general case it requires dynamic scheduling, however, the strong encapsulation of dataflow nodes enables analysis and the scheduling overhead can be reduced by using quasi-static, or piecewise static, scheduling techniques. The scheduling problem is concerned with nding the few scheduling decisions that must be run-time, while most decisions are pre-calculated. The result is then an, as small as possible, set of static schedules that are dynamically scheduled. To identify these dynamic decisions and to find the concrete schedules, this thesis shows how quasi-static scheduling can be represented as a model checking problem. This involves identifying the relevant information to generate a minimal but complete model to be used for model checking. The model must describe everything that may affect scheduling of the application while omitting everything else in order to avoid state space explosion. This kind of simplification is necessary to make the state space analysis feasible. For the model checker to nd the actual schedules, a set of scheduling strategies are de ned which are able to produce quasi-static schedulers for a wide range of applications. The results of this work show that actor composition with quasi-static scheduling can be used to transform data ow programs to t many different computer architecture with different type and number of cores. This in turn, enables dataflow to provide a more platform independent representation as one application can be fitted to a specific processor architecture without changing the actual program representation. Instead, the program representation is in the context of design space exploration optimized by the development tools to fit the target platform. This work focuses on representing the dataflow scheduling problem as a model checking problem and is implemented as part of a compiler infrastructure. The thesis also presents experimental results as evidence of the usefulness of the approach.
Resumo:
Rolling element bearings are essential components of rotating machinery. The spherical roller bearing (SRB) is one variant seeing increasing use, because it is self-aligning and can support high loads. It is becoming increasingly important to understand how the SRB responds dynamically under a variety of conditions. This doctoral dissertation introduces a computationally efficient, three-degree-of-freedom, SRB model that was developed to predict the transient dynamic behaviors of a rotor-SRB system. In the model, bearing forces and deflections were calculated as a function of contact deformation and bearing geometry parameters according to nonlinear Hertzian contact theory. The results reveal how some of the more important parameters; such as diametral clearance, the number of rollers, and osculation number; influence ultimate bearing performance. Distributed defects, such as the waviness of the inner and outer ring, and localized defects, such as inner and outer ring defects, are taken into consideration in the proposed model. Simulation results were verified with results obtained by applying the formula for the spherical roller bearing radial deflection and the commercial bearing analysis software. Following model verification, a numerical simulation was carried out successfully for a full rotor-bearing system to demonstrate the application of this newly developed SRB model in a typical real world analysis. Accuracy of the model was verified by comparing measured to predicted behaviors for equivalent systems.
Resumo:
Tämä diplomityö arvioi hitsauksen laadunhallintaohjelmistomarkkinoiden kilpailijoita. Kilpailukenttä on uusi ja ei ole tarkkaa tietoa siitä minkälaisia kilpailijoita on markkinoilla. Hitsauksen laadunhallintaohjelmisto auttaa yrityksiä takaamaan korkean laadun. Ohjelmisto takaa korkean laadun varmistamalla, että hitsaaja on pätevä, hän noudattaa hitsausohjeita ja annettuja parametreja. Sen lisäksi ohjelmisto kerää kaiken tiedon hitsausprosessista ja luo siitä vaadittavat dokumentit. Diplomityön teoriaosuus muodostuu kirjallisuuskatsauksesta ratkaisuliike-toimintaan, kilpailija-analyysin ja kilpailuvoimien teoriaan sekä hitsauksen laadunhallintaan. Työn empiriaosuus on laadullinen tutkimus, jossa tutkitaan kilpailevia hitsauksen laadunhallintaohjelmistoja ja haastatellaan ohjelmistojen käyttäjiä. Diplomityön tuloksena saadaan uusi kilpailija-analyysimalli hitsauksen laadunhallintaohjelmistoille. Mallin avulla voidaan arvostella ohjelmistot niiden tarjoamien primääri- ja sekundääriominaisuuksien perusteella. Toiseksi tässä diplomityössä analysoidaan nykyinen kilpailijatilanne hyödyntämällä juuri kehitettyä kilpailija-analyysimallia.
Resumo:
The challenge the community college faces in helping meet the needs of the living open system of society is examined in this study. It is postulated that internalization student outcomes are required by society to reduce entropy and remain self-renewing. Such behavior is characterized as having an intrinsically motivated energy source and displays the seeking and conquering of challenge, the development of reflective knowledge and skill, full use of all capabilities, internal control, growth orientation, high self-esteem, relativistic thinking and competence. The development of a conceptual systems model that suggests how transactions among students, faculty and administration might occur to best meet the needs of internalization outcomes in students, and intrinsic motivation in faculty is a major purpose of this study. It is a speculative model that is based on a synthesis of a wide variety of variables. Empirical evidence, theoretical considerations, and speculative ideas are gathered together from researchers and theoretici.ans who are working on separate answers to questions of intrinsic motivation, internal control and environments that encourage their development. The model considers the effect administrators·have on faculty anq the corresponding effect faculty may have on students. The major concentration is on the administrator--teacher interface.For administrators the model may serve as a guide in planning effective transactions, and establishing system goals. The teacher is offered a means to coordinate actions toward a specific overall objective, and the administrator, teacher and researcher are invited to use the model to experiment, innovate, verify the assumptions on which the model is based, and raise additional hypotheses. Goals and history of the community colleges in Ontario are examined against current problems, previous progress and open system thinking. The nature of the person as a five part system is explored with emphasis on intrinsic motivation. The nature, operation, conceptualization, and value of this internal energy source is reviewed in detail. The current state of society, education and management theory are considered and the value of intrinsically motivating teaching tasks together with "system four" leadership style are featured. Evidence is reviewed that suggests intrinsically motivated faculty are needed, and "system four" leadership style is the kind of interaction-influence system needed to nurture intrinsic motivation in faculty.
Resumo:
This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.
Resumo:
This paper studies a dynamic-optimizing model of a semi-small open economy with sticky nominal prices and wages. the model exhibits exchange rate overshooting in response to money supply shocks. the predicted variability of nominal and real exchange rates is roughly consistent with that of G7 effective exchange rates during the post-Bretton Woods era.
Resumo:
I study long-term financial contracts between lenders and borrowers in the absence of perfect enforceability and when both parties are credit constrained. Borrowers repeatedly have projects to undertake and need external financing. Lenders can commit to contractual agreements whereas borrowers can renege any period. I show that equilibrium contracts feature interesting dynamics: the economy exhibits efficient investment cycles; absence of perfect enforcement and shortage of capital skew the cycles toward states of liquidity drought; credit is rationed if either the lender has too little capital or if the borrower has too little collateral. This paper's technical contribution is its demonstration of the existence and characterization of financial contracts that are solutions to a non-convex dynamic programming problem.
Resumo:
Dans les études sur le transport, les modèles de choix de route décrivent la sélection par un utilisateur d’un chemin, depuis son origine jusqu’à sa destination. Plus précisément, il s’agit de trouver dans un réseau composé d’arcs et de sommets la suite d’arcs reliant deux sommets, suivant des critères donnés. Nous considérons dans le présent travail l’application de la programmation dynamique pour représenter le processus de choix, en considérant le choix d’un chemin comme une séquence de choix d’arcs. De plus, nous mettons en œuvre les techniques d’approximation en programmation dynamique afin de représenter la connaissance imparfaite de l’état réseau, en particulier pour les arcs éloignés du point actuel. Plus précisément, à chaque fois qu’un utilisateur atteint une intersection, il considère l’utilité d’un certain nombre d’arcs futurs, puis une estimation est faite pour le restant du chemin jusqu’à la destination. Le modèle de choix de route est implanté dans le cadre d’un modèle de simulation de trafic par événements discrets. Le modèle ainsi construit est testé sur un modèle de réseau routier réel afin d’étudier sa performance.
Resumo:
This paper considers an overlapping generations model in which capital investment is financed in a credit market with adverse selection. Lenders’ inability to commit ex-ante not to bailout ex-post, together with a wealthy position of entrepreneurs gives rise to the soft budget constraint syndrome, i.e. the absence of liquidation of poor performing firms on a regular basis. This problem arises endogenously as a result of the interaction between the economic behavior of agents, without relying on political economy explanations. We found the problem more binding along the business cycle, providing an explanation to creditors leniency during booms in some LatinAmerican countries in the late seventies and early nineties.
Combining altimetric/gravimetric and ocean model mean dynamic topography models in the GOCINA region
Resumo:
The use of data reconciliation techniques can considerably reduce the inaccuracy of process data due to measurement errors. This in turn results in improved control system performance and process knowledge. Dynamic data reconciliation techniques are applied to a model-based predictive control scheme. It is shown through simulations on a chemical reactor system that the overall performance of the model-based predictive controller is enhanced considerably when data reconciliation is applied. The dynamic data reconciliation techniques used include a combined strategy for the simultaneous identification of outliers and systematic bias.
Resumo:
DISOPE is a technique for solving optimal control problems where there are differences in structure and parameter values between reality and the model employed in the computations. The model reality differences can also allow for deliberate simplification of model characteristics and performance indices in order to facilitate the solution of the optimal control problem. The technique was developed originally in continuous time and later extended to discrete time. The main property of the procedure is that by iterating on appropriately modified model based problems the correct optimal solution is achieved in spite of the model-reality differences. Algorithms have been developed in both continuous and discrete time for a general nonlinear optimal control problem with terminal weighting, bounded controls and terminal constraints. The aim of this paper is to show how the DISOPE technique can aid receding horizon optimal control computation in nonlinear model predictive control.