59 resultados para Search Engine Indexing
Resumo:
Iterated Local Search has many of the desirable features of a metaheuristic: it is simple, easy to implement, robust, and highly effective. The essential idea of Iterated Local Search lies in focusing the search not on the full space of solutions but on a smaller subspace defined by the solutions that are locally optimal for a given optimization engine. The success of Iterated Local Search lies in the biased sampling of this set of local optima. How effective this approach turns out to be depends mainly on the choice of the local search, the perturbations, and the acceptance criterion. So far, in spite of its conceptual simplicity, it has lead to a number of state-of-the-art results without the use of too much problem-specific knowledge. But with further work so that the different modules are well adapted to the problem at hand, Iterated Local Search can often become a competitive or even state of the artalgorithm. The purpose of this review is both to give a detailed description of this metaheuristic and to show where it stands in terms of performance.
Resumo:
Open educational resources (OER) promise increased access, participation, quality, and relevance, in addition to cost reduction. These seemingly fantastic promises are based on the supposition that educators and learners will discover existing resources, improve them, and share the results, resulting in a virtuous cycle of improvement and re-use. By anecdotal metrics, existing web scale search is not working for OER. This situation impairs the cycle underlying the promise of OER, endangering long term growth and sustainability. While the scope of the problem is vast, targeted improvements in areas of curation, indexing, and data exchange can improve the situation, and create opportunities for further scale. I explore the way the system is currently inadequate, discuss areas for targeted improvement, and describe a prototype system built to test these ideas. I conclude with suggestions for further exploration and development.
Resumo:
We provide some guidelines for deriving new projective hash families of cryptographic interest. Our main building blocks are so called group action systems; we explore what properties of this mathematical primitives may lead to the construction of cryptographically useful projective hash families. We point out different directions towards new constructions, deviating from known proposals arising from Cramer and Shoup's seminal work.
Resumo:
We accomplish two goals. First, we provide a non-cooperative foundation for the use of the Nash bargaining solution in search markets. This finding should help to close the rift between the search and the matching-and-bargaining literature. Second, we establish that the diversity of quality offered (at an increasing price-quality ratio) in a decentralized market is an equilibrium phenomenon - even in the limit as search frictions disappear.
Resumo:
We study pair-wise decentralized trade in dynamic markets with homogeneous, non-atomic, buyers and sellers that wish to exchange one unit. Pairs of traders are randomly matched and bargaining a price under rules that offer the freedom to quit the match at any time. Market equilbria, prices and trades over time, are characterized. The asymptotic behavior of prices and trades as frictions (search costs and impatience) vanish, and the conditions for (non) convergence to walrasian prices are explored. As a side product of independent interest, we present a self-contained theory of non-cooperative bargaining with two-sided, time-varying, outside options.
Resumo:
Aquest és un projecte que tracta sobre la indexació automàtica de continguts televisius. És una tasca que guanyarà importància amb els imminents canvis que hi haurà en la televisió que coneixem. L'entrada de la nova televisió digital farà que hi hagi una interacció molt més fluida entre l'espectador i la cadena, a més de grans quantitats de canals, cada un amb programes de tipus totalment diferents. Tot això farà que tenir mètodes de cerca basats en els continguts d'aquests programes sigui del tot imprescindible. Així doncs, el nostre projecte està basat plenament en poder extreure alguns d'aquests descriptors que faran possible la categorització dels diferents programes televisius.
Resumo:
A growing literature integrates theories of debt management into models of optimal fiscal policy. One promising theory argues that the composition of government debt should be chosen so that fluctuations in the market value of debt offset changes in expected future deficits. This complete market approach to debt management is valid even when the government only issues non-contingent bonds. A number of authors conclude from this approach that governments should issue long term debt and invest in short term assets. We argue that the conclusions of this approach are too fragile to serve as a basis for policy recommendations. This is because bonds at different maturities have highly correlated returns, causing the determination of the optimal portfolio to be ill-conditioned. To make this point concrete we examine the implications of this approach to debt management in various models, both analytically and using numerical methods calibrated to the US economy. We find the complete market approach recommends asset positions which are huge multiples of GDP. Introducing persistent shocks or capital accumulation only worsens this problem. Increasing the volatility of interest rates through habits partly reduces the size of these simulations we find no presumption that governments should issue long term debt ? policy recommendations can be easily reversed through small perturbations in the specification of shocks or small variations in the maturity of bonds issued. We further extend the literature by removing the assumption that governments every period costlessly repurchase all outstanding debt. This exacerbates the size of the required positions, worsens their volatility and in some cases produces instability in debt holdings. We conclude that it is very difficult to insulate fiscal policy from shocks by using the complete markets approach to debt management. Given the limited variability of the yield curve using maturities is a poor way to substitute for state contingent debt. The result is the positions recommended by this approach conflict with a number of features that we believe are important in making bond markets incomplete e.g allowing for transaction costs, liquidity effects, etc.. Until these features are all fully incorporated we remain in search of a theory of debt management capable of providing robust policy insights.
Resumo:
Report for the scientific sojourn at the University of Linköping between April to July 2007. Monitoring of the air intake system of an automotive engine is important to meet emission related legislative diagnosis requirements. During the research the problem of fault detection in the air intake system was stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem was solved using Interval-based Consistency Techniques. Interval-based consistency techniques are shown to be particularly efficient for checking the consistency of the Analytical Redundancy Relations (ARRs), dealing with uncertain measurements and parameters, and using experimental data. All experiments were performed on a four-cylinder turbo-charged spark-ignited SAAB engine located in the research laboratory at Vehicular System Group - University of Linköping.
Resumo:
Can international trade act as the sole engine of growth for an economy? If yes, what are the mechanisms through which trade operates in transmitting permanent growth? This paper answers these questions with two simple two-country models, in which only one country enjoys sustained growth in autarky. The models differ in the assumptions on technical change, which is either labour- or capital-augmenting. In both cases, the stagnant economy imports growth by trading. In the first model, growth is transmitted because of permanent increases in the trade volume. In the alternative framework, the stagnant economy imports sustained growth because its terms of trade permanently improve.
Resumo:
This paper examines the antecedents and innovation consequences of the methods firms adopt in organizing their search strategies. From a theoretical perspective, organizational search is described using a typology that shows how firms implement exploration and exploitation search activities that span their organizational boundaries. This typology includes three models of implementation: ambidextrous, specialized, and diversified implementation. From an empirical perspective, the paper examines the performance consequences when applying these models, and compares their capacity to produce complementarities. Additionally, since firms' choices in matters of organizational search are viewed as endogenous variables, the paper examines the drivers affecting them and identifies the importance of firms' absorptive capacity and diversified technological opportunities in determining these choices. The empirical design of the paper draws on new data for manufacturing firms in Spain, surveyed between 2003 and 2006.
Resumo:
We evaluate the performance of different optimization techniques developed in the context of optical flowcomputation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we develop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow computation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.
Resumo:
Aplicació web desenvolupada en llenguatge Java per a lareserva online de parcel¿les de càmping.
Resumo:
One of the unresolved questions of modern physics is the nature of Dark Matter. Strong experimental evidences suggest that the presence of this elusive component in the energy budget of the Universe is quite significant, without, however, being able to provide conclusive information about its nature. The most plausible scenario is that of weakly interacting massive particles (WIMPs), that includes a large class of non-baryonic Dark Matter candidates with a mass typically between few tens of GeV and few TeVs, and a cross section of the order of weak interactions. Search for Dark Matter particles using very high energy gamma-ray Cherenkov telescopes is based on the model that WIMPs can self-annihilate, leading to production of detectable species, like photons. These photons are very energetic, and since unreflected by the Universe's magnetic fields, they can be traced straight to the source of their creation. The downside of the approach is a great amount of background radiation, coming from the conventional astrophysical objects, that usually hides clear signals of the Dark Matter particle interactions. That is why good choice of the observational candidates is the crucial factor in search for Dark Matter. With MAGIC (Major Atmospheric Gamma-ray Imaging Cherenkov Telescopes), a two-telescope ground-based system located in La Palma, Canary Islands, we choose objects like dwarf spheroidal satellite galaxies of the Milky Way and galaxy clusters for our search. Our idea is to increase chances for WIMPs detection by pointing to objects that are relatively close, with great amount of Dark Matter and with as-little-as-possible pollution from the stars. At the moment, several observation projects are ongoing and analyses are being performed.
Resumo:
Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task