Investigating Retrieval Method Selection with Axiomatic Features

We consider algorithm selection in the context of ad-hoc information retrieval. Given a query and a pair of retrieval methods, we propose a meta-learner that predicts how to combine the methods' relevance scores into an overall relevance score. Inspired by neural models' different properties with regard to IR axioms, these predictions are based on features that quantify axiom-related properties of the query and its top ranked documents. We conduct an evaluation on TREC Web Track data and find that the meta-learner often significantly improves over the individual methods. Finally, we conduct feature and query weight analyses to investigate the meta-learner's behavior

Patent incentives: Returns to patenting and the inducement for research & development (R&D)

The UK has one of the oldest and best regarded intellectual property rights (IPR) regimes in the world. Yet there is little evidence on private returns to patenting for firms operating in the UK, and on the incentive effects of patenting in encouraging R&D investment in patenting firms. Using available data from the UK innovation survey (known as the Community Innovation Survey or CIS) and linked business performance data the report assesses both the additional returns firms achieve by patenting, and the effects on R&D spending. This report tests an economic model built upon the following intuition. The monopoly power conferred by a patent provides a firm a price premium in new product revenue, thus increasing profitability. At the same time this increased profitability also acts as an inducement to increase R&D spending by the firm. Using this idea we try to jointly estimate the extent of the premium and the inducement to R&D. In this way the research builds and extends work in two literature streams, viz. the economic literature on the value of patents and the literature on effect of patents on R&D expenditures

Migration Flows and Their Determinants: A Comparative Study of Internal Migration in Italy and the U.S.A.

This paper has two goals: first to describe a theoretical model which derives relationships among migration decisions explicitly from utility maximization under uncertainty; and second, to examine why nations vary in their internal migration. To explain variation in internal migration, we hypothesize that the degree of monetization and industrialization of an economy is inversely related to the family cohesiveness; hence, a given percentage increase in relative income will have higher migratory effect in a relatively more monetized economy. The availability of higher initial information and better transportation systems in these economies strongly complement this effect. These hypothesis are confirmed by the estimates based on the U.S. and Italian data.

Global optimization methods for engineering design

The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated

Economic growth, innovation systems, and institutional change: A Trilogy in Five Parts

Development and growth are products of the interplay and interaction among heterogeneous actors operating in specific institutional settings. There is a much alluded-to, but under-investigated, link between economic growth, innovation systems, and institutions. There is widespread agreement among most economists on the positive reinforcing link between innovation and growth. However, the importance of institutions as catalysts in this link has not been adequately examined. The concept of innovation systems has the potential to fill this gap. But these studies have not conducted in-depth institutional analyses or focussed on institutional transformation processes, thereby failing to link growth theory to the substantive institutional tradition in economics. In this paper we draw attention to the main shortcomings of orthodox and heterodox growth theories, some of which have been addressed by the more descriptive literature on innovation systems. Critical overviews of the literatures on growth and innovation systems are used as a foundation to propose a new perspective on the role of institutions and a framework for conducting institutional analysis using a multi-dimensional typology of institutions. The framework is then applied to cases of Taiwan and South Korea to highlight the instrumental role played by institutions in facilitating and curtailing economic development and growth.economics of technology ;

Design sensitivity analysis of nonlinear structural response

A unified theory is described of design sensitivity analysis of linear and nonlinear structures for shape, nonshape and material selection problems. The concepts of reference volume and adjoint structure are used to develop the unified viewpoint. A general formula for design sensitivity analysis is derived. Simple analytical linear and nonlinear examples are used to interpret various terms of the formula and demonstrate its use

Strong inapproximability of the shortest reset word

The \v{C}ern\'y conjecture states that every $n$-state synchronizing automaton has a reset word of length at most $(n-1)^2$. We study the hardness of finding short reset words. It is known that the exact version of the problem, i.e., finding the shortest reset word, is NP-hard and coNP-hard, and complete for the DP class, and that approximating the length of the shortest reset word within a factor of $O(\log n)$ is NP-hard [Gerbush and Heeringa, CIAA'10], even for the binary alphabet [Berlinkov, DLT'13]. We significantly improve on these results by showing that, for every $\epsilon>0$, it is NP-hard to approximate the length of the shortest reset word within a factor of $n^{1-\epsilon}$. This is essentially tight since a simple $O(n)$-approximation algorithm exists.Comment: extended abstract to appear in MFCS 201