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## Desenvolvimento financeiro e restrição financeira nas decisões de investimento da firma: evidências para o Brasil; Financial development and financial constraint on firm's investment decisions: evidence for Brazil

Castro, Fernanda de
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Dissertação de Mestrado Formato: application/pdf
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Este trabalho tem como objetivo examinar os efeitos do desenvolvimento financeiro e das restrições financeiras nas decisões de investimento da firma considerando um conjunto de informações de 659 firmas brasileiras no período de 1998 a 2006. A investigação é realizada dentro de um contexto teórico e aplicado, considerando um modelo econométrico com dados longitudinais e assumindo que o desenvolvimento financeiro exerce impacto substancial nas restrições financeiras das firmas, o que está diretamente relacionado às suas decisões de investimento. Com o propósito de contribuir para a escassa literatura internacional e à inexistente literatura para o Brasil, este trabalho utilizou o índice KZ para classificação das firmas como financeiramente restritas e não restritas. Por meio do uso de dados macroeconômicos em uma análise microeconômica, empregou-se o modelo probabilístico logit para encontrar os principais fatores determinantes da probabilidade de restrição financeira das firmas brasileiras. Já para analisar a relação entre desenvolvimento financeiro, restrições financeiras e investimento da firma, estimou-se uma versão do modelo acelerador do investimento pelo método dos momentos generalizados (GMM) devido seu caráter dinâmico e à presença do problema de endogeneidade. Os principais resultados indicaram que...

## Topic maps constraint specification languages : comparing AsTMa!, OSL, and XTche

Librelotto, Giovani Rubert; Azevedo, Renato Preigschadt de; Ramalho, José Carlos; Henriques, Pedro Rangel
Tipo: Conferência ou Objeto de Conferência
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Topic maps are an ISO standard for the representation and interchange of knowledge, with an emphasis on the findability of information. A topic map can represent information using topics (representing any concept), associations (which represent the relationships between them), and occurrences (which represent relationships between topics and information resources relevant to them). They are thus similar to semantic networks and both concept and mind maps in many respects. According to Topic Map Data Model (TMDM), Topic Maps are abstract structures that can encode knowledge and connect this encoded knowledge to relevant information resources. In order to cope with a broad range of scenarios, a topic is a very wide concept. On one hand, this makes Topic Maps a convenient model for knowledge representation; but on the other hand, this can also put in risk the topic map consistency. A set of semantic constraints must be imposed to the topic map in order to grant its consistency. Currently, we can find three approaches to constrain Topic Maps -- AsTMa!, OSL, and XTche -- that allow us to specify constraints and to validate the instances of a family of topic maps against that set of rules. With these resemblances it is easy to conclude that they are quite similar. However they differ in some fundamental concepts. These three Topic Maps constraint specification languages were hardly tested and benchmarked with a huge test suite. The most significant results will be discussed in this paper. In this article...

## Constraint-aware schema transformation

Alves, Tiago L.; Silva, Paulo F.; Visser, Joost
Tipo: Artigo de Revista Científica
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Ninth International Workshop on Rule-Based Programming (Rule 2008); Data schema transformations occur in the context of software evolution, refactoring, and cross-paradigm data mappings. When constraints exist on the initial schema, these need to be transformed into constraints on the target schema. Moreover, when high-level data types are refined to lower level structures, additional target schema constraints must be introduced to balance the loss of structure and preserve semantics. We introduce an algebraic approach to schema transformation that is constraint-aware in the sense that constraints are preserved from source to target schemas and that new constraints are introduced where needed. Our approach is based on refinement theory and point-free program transformation. Data refinements are modeled as rewrite rules on types that carry point-free predicates as constraints. At each rewrite step, the predicate on the reduct is computed from the predicate on the redex. An additional rewrite system on point-free functions is used to normalize the predicates that are built up along rewrite chains. We implemented our rewrite systems in a type-safe way in the functional programming language Haskell. We demonstrate their application to constraint-aware hierarchical-relational mappings.

## Algorithms to infer metabolic flux ratios from fluxomics data

Carreira, Rafael; Rocha, Miguel; Villas-Boas, S. G.; Rocha, I.
Tipo: Conferência ou Objeto de Conferência
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In silico cell simulation approaches based in the use of genome-scale metabolic models (GSMMs) and constraint-based methods such as Flux Balance Analysis are gaining importance, but methods to integrate these approaches with omics data are still greatly needed. In this work, the focus relies on fluxomics data that provide valuable information on the intracellular fluxes, although in many cases in an indirect, incomplete and noisy way. The proposed framework enables the integration of fluxomics data, in the form of 13C labeling distribution for metabolite fragments, with GSMMs enriched with carbon atom transition maps. The algorithms implemented allow to infer labeling distributions for fragments/metabolites not measured and to build expressions for the relevant flux ratios that can be then used to enrich constraint-based methods for flux determination. This approach does not require any assumptions on the metabolic network and reaction reversibility, allowing to compute ratios originating from coupled joint points of the network. Also, when enough data do not exist, the system tries to infer ratio bounds from the measurements.

## A Parallel and Distributed Framework for Constraint Solving

Fonte: Università degli Studi di Perugia Publicador: Università degli Studi di Perugia
Tipo: Artigo de Revista Científica
ENG
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With the increased availability of affordable parallel and dis- tributed hardware, programming models for these architectures has be- come the focus of significant attention. Constraint programming, which can be seen as the encoding of processes as a Constraint Satisfaction Problem, because of its data-driven and control-insensitive approach is a prime candidate to serve as the basis for a framework which effectively exploits parallel architectures. To effectually apply the power of distributed computational systems, there must be an effective sharing of the work involved in the search for a solution to a Constraint Satisfaction Problem (CSP) between all the participating agents, and it must happen dynamically, as it is hard to predict the effort associated with the exploration of some part of the search space. We describe and provide an initial experimental assessment of an imple- mentation of a work stealing-based approach to distributed CSP solving, which relies on multiple back-ends for the distributed computing mecha- nisms – from the multicore CPU to supercomputer clusters running MPI or other interprocess communication platforms.

## Towards constraint-informed information systems

Pimenta Rodrigues, Irene; Matos, Nuno; Pinto Abreu, Salvador; Deneckere, Rebecca; Diaz, Daniel
Tipo: Artigo de Revista Científica
POR
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Declarative techniques such as Constraint Programming are very useful in modeling complex requirements. They have the added benefit of being executable specifications and, when properly tuned, high-performance ones. In this paper we argue that Information Systems ought to include constraint-based techniques in their design and implementation. We support this claim by introducing tools based on constraint programming, which we apply to an actual use-case: the academic timetable construction and maintenance problem, as developed at the University of Evora. The system we built was implemented using the GNU Prolog language. Moreover, Constraints have the potential to describe global properties that a model must observe, which makes them a semantically very interesting extension to the capabilities of present model-driven techniques and tools.

## Geolocation of Data in the Cloud

Gondree, Mark; Peterson, Zachary N. J.
Tipo: Artigo de Revista Científica
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We introduce and analyze a general framework for authentically binding data to a location while providing strong assurances against cloud storage providers that (either accidentally or maliciously) attempt to re-locate cloud data. We then evaluate a preliminary solution in this framework that combines constraint-based host geolocation with proofs of data possession, called constraint-based data geolocation (CBDG). We evaluate CBDG using a combination of experiments with PlanetLab and real cloud storage services, demonstrating that we can bind fetched data to the location originally hosting it with high precision. We geolocate data hosted on the majority of our PlanetLab targets to regions no larger than 118,000 km2, and we geolocate data hosted on Amazon S3 to an area no larger than 12,000 km2, sufficiently small to identify the state or service region.; Partial support for this work was provided by the National Science Foundation under award No. 1143573.

## What Matters to African Firms? The Relevance of Perceptions Data

Gelb, Alan; Ramachandran, Vijaya; Shah, Manju Kedia; Turner, Ginger
Fonte: World Bank, Washington, DC Publicador: World Bank, Washington, DC
Tipo: Publications & Research :: Policy Research Working Paper; Publications & Research
ENGLISH
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Can perceptions data help us understand investment climate constraints facing the private sector? Or do firms simply complain about everything? In this paper, the authors provide a picture of how firms' views on constraints differ across countries in Sub-Saharan Africa. Using the World Bank's Enterprise Surveys database, they find that reported constraints reflect country characteristics and vary systematically by level of income-the most elemental constraints to doing business (power, access to finance, ability to plan ahead) appear to be most binding at low levels of income. As countries develop and these elemental constraints are relaxed, governance-related constraints become more problematic. As countries move further up the income scale and the state becomes more capable, labor regulation is perceived to be more of a problem-business is just one among several important constituencies. The authors also consider whether firm-level characteristics-such as size, ownership, exporter status, and firms' own experience-affect firms' views on the severity of constraints. They find that...

## DSM-PM2 adequacy for distributed constraint programming

Almas, Luís Pedro Parreira Galito Pimenta
ENG
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## Hybrid tractability of soft constraint problems

Cooper, Martin C.; Zivny, Stanislav
Tipo: Artigo de Revista Científica
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The constraint satisfaction problem (CSP) is a central generic problem in computer science and artificial intelligence: it provides a common framework for many theoretical problems as well as for many real-life applications. Soft constraint problems are a generalisation of the CSP which allow the user to model optimisation problems. Considerable effort has been made in identifying properties which ensure tractability in such problems. In this work, we initiate the study of hybrid tractability of soft constraint problems; that is, properties which guarantee tractability of the given soft constraint problem, but which do not depend only on the underlying structure of the instance (such as being tree-structured) or only on the types of soft constraints in the instance (such as submodularity). We present several novel hybrid classes of soft constraint problems, which include a machine scheduling problem, constraint problems of arbitrary arities with no overlapping nogoods, and the SoftAllDiff constraint with arbitrary unary soft constraints. An important tool in our investigation will be the notion of forbidden substructures.; Comment: A full version of a CP'10 paper, 26 pages

## Improved Parameterized Algorithms for Constraint Satisfaction

Kim, Eun Jung; Williams, Ryan
Tipo: Artigo de Revista Científica
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For many constraint satisfaction problems, the algorithm which chooses a random assignment achieves the best possible approximation ratio. For instance, a simple random assignment for {\sc Max-E3-Sat} allows 7/8-approximation and for every $\eps >0$ there is no polynomial-time ($7/8+\eps$)-approximation unless P=NP. Another example is the {\sc Permutation CSP} of bounded arity. Given the expected fraction $\rho$ of the constraints satisfied by a random assignment (i.e. permutation), there is no $(\rho+\eps)$-approximation algorithm for every $\eps >0$, assuming the Unique Games Conjecture (UGC). In this work, we consider the following parameterization of constraint satisfaction problems. Given a set of $m$ constraints of constant arity, can we satisfy at least $\rho m +k$ constraint, where $\rho$ is the expected fraction of constraints satisfied by a random assignment? {\sc Constraint Satisfaction Problems above Average} have been posed in different forms in the literature \cite{Niedermeier2006,MahajanRamanSikdar09}. We present a faster parameterized algorithm for deciding whether $m/2+k/2$ equations can be simultaneously satisfied over ${\mathbb F}_2$. As a consequence, we obtain $O(k)$-variable bikernels for {\sc boolean CSPs} of arity $c$ for every fixed $c$...

## Filtering Algorithms for the Multiset Ordering Constraint

Frisch, Alan; Hnich, Brahim; Kiziltan, Zeynep; Miguel, Ian; Walsh, Toby
Tipo: Artigo de Revista Científica
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35.96%
Constraint programming (CP) has been used with great success to tackle a wide variety of constraint satisfaction problems which are computationally intractable in general. Global constraints are one of the important factors behind the success of CP. In this paper, we study a new global constraint, the multiset ordering constraint, which is shown to be useful in symmetry breaking and searching for leximin optimal solutions in CP. We propose efficient and effective filtering algorithms for propagating this global constraint. We show that the algorithms are sound and complete and we discuss possible extensions. We also consider alternative propagation methods based on existing constraints in CP toolkits. Our experimental results on a number of benchmark problems demonstrate that propagating the multiset ordering constraint via a dedicated algorithm can be very beneficial.

## Discovering Archipelagos of Tractability for Constraint Satisfaction and Counting

Ganian, Robert; Ramanujan, M. S.; Szeider, Stefan
Tipo: Artigo de Revista Científica
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The Constraint Satisfaction Problem (CSP) is a central and generic computational problem which provides a common framework for many theoretical and practical applications. A central line of research is concerned with the identification of classes of instances for which CSP can be solved in polynomial time; such classes are often called "islands of tractability." A prominent way of defining islands of tractability for CSP is to restrict the relations that may occur in the constraints to a fixed set, called a constraint language, whereas a constraint language is conservative if it contains all unary relations. This paper addresses the general limit of the mentioned tractability results for CSP and #CSP, that they only apply to instances where all constraints belong to a single tractable language (in general, the union of two tractable languages isn't tractable). We show that we can overcome this limitation as long as we keep some control of how constraints over the various considered tractable languages interact with each other. For this purpose we utilize the notion of a \emph{strong backdoor} of a CSP instance, as introduced by Williams et al. (IJCAI 2003), which is a set of variables that when instantiated moves the instance to an island of tractability...

## Parameterized Algorithms for Constraint Satisfaction Problems Above Average with Global Cardinality Constraints

Chen, Xue; Zhou, Yuan
Tipo: Artigo de Revista Científica
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Given a constraint satisfaction problem (CSP) on $n$ variables, $x_1, x_2, \dots, x_n \in \{\pm 1\}$, and $m$ constraints, a global cardinality constraint is in the form of $\sum_{i = 1}^{n} x_i = (1-2p)n$, where $p \in (\Omega(1), 1 - \Omega(1))$ and $pn$ is an integer. Let $AVG$ be the expected number of constraints satisfied by randomly choosing an assignment to $x_1, x_2, \dots, x_n$, complying with the global cardinality constraint. The CSP above average with the global cardinality constraint problem asks whether there is an assignment (complying with the cardinality constraint) that satisfies more than $(AVG+t)$ constraints, where $t$ is an input parameter. In this paper, we present an algorithm that finds out a valid assignment satisfying more than $(AVG+t)$ constraints (if there exists one) in time $(2^{O(t^2)} + n^{O(d)})$. Therefore, the CSP above average with the global cardinality constraint problem is fixed-parameter tractable.; Comment: 36 pages

## Clustering by soft-constraint affinity propagation: Applications to gene-expression data

Leone, Michele; Sumedha; Weigt, Martin
Tipo: Artigo de Revista Científica
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Motivation: Similarity-measure based clustering is a crucial problem appearing throughout scientific data analysis. Recently, a powerful new algorithm called Affinity Propagation (AP) based on message-passing techniques was proposed by Frey and Dueck \cite{Frey07}. In AP, each cluster is identified by a common exemplar all other data points of the same cluster refer to, and exemplars have to refer to themselves. Albeit its proved power, AP in its present form suffers from a number of drawbacks. The hard constraint of having exactly one exemplar per cluster restricts AP to classes of regularly shaped clusters, and leads to suboptimal performance, {\it e.g.}, in analyzing gene expression data. Results: This limitation can be overcome by relaxing the AP hard constraints. A new parameter controls the importance of the constraints compared to the aim of maximizing the overall similarity, and allows to interpolate between the simple case where each data point selects its closest neighbor as an exemplar and the original AP. The resulting soft-constraint affinity propagation (SCAP) becomes more informative, accurate and leads to more stable clustering. Even though a new {\it a priori} free-parameter is introduced, the overall dependence of the algorithm on external tuning is reduced...

## An n-ary Constraint for the Stable Marriage Problem

Unsworth, Chris; Prosser, Patrick
Tipo: Artigo de Revista Científica
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We present an n-ary constraint for the stable marriage problem. This constraint acts between two sets of integer variables where the domains of those variables represent preferences. Our constraint enforces stability and disallows bigamy. For a stable marriage instance with $n$ men and $n$ women we require only one of these constraints, and the complexity of enforcing arc-consistency is $O(n^2)$ which is optimal in the size of input. Our computational studies show that our n-ary constraint is significantly faster and more space efficient than the encodings presented in \cite{cp01}. We also introduce a new problem to the constraint community, the sex-equal stable marriage problem.; Comment: 7 pages. The Fifth Workshop on Modelling and Solving Problems with Constraints, held at the 19th International Joint Conference on Artificial Intelligence (IJCAI 2005)

## Consistency Techniques for Flow-Based Projection-Safe Global Cost Functions in Weighted Constraint Satisfaction

Lee, J. H. M.; Leung, Ka Lun
Tipo: Artigo de Revista Científica
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Many combinatorial problems deal with preferences and violations, the goal of which is to find solutions with the minimum cost. Weighted constraint satisfaction is a framework for modeling such problems, which consists of a set of cost functions to measure the degree of violation or preferences of different combinations of variable assignments. Typical solution methods for weighted constraint satisfaction problems (WCSPs) are based on branch-and-bound search, which are made practical through the use of powerful consistency techniques such as AC*, FDAC*, EDAC* to deduce hidden cost information and value pruning during search. These techniques, however, are designed to be efficient only on binary and ternary cost functions which are represented in table form. In tackling many real-life problems, high arity (or global) cost functions are required. We investigate efficient representation scheme and algorithms to bring the benefits of the consistency techniques to also high arity cost functions, which are often derived from hard global constraints from classical constraint satisfaction. The literature suggests some global cost functions can be represented as flow networks, and the minimum cost flow algorithm can be used to compute the minimum costs of such networks in polynomial time. We show that naive adoption of this flow-based algorithmic method for global cost functions can result in a stronger form of null-inverse consistency. We further show how the method can be modified to handle cost projections and extensions to maintain generalized versions of AC* and FDAC* for cost functions with more than two variables. Similar generalization for the stronger EDAC* is less straightforward. We reveal the oscillation problem when enforcing EDAC* on cost functions sharing more than one variable. To avoid oscillation...

## Dictionary learning under global sparsity constraint

Meng, Deyu; Leung, Yee; Zhao, Qian; Xu, Zongben
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
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A new method is proposed in this paper to learn overcomplete dictionary from training data samples. Differing from the current methods that enforce similar sparsity constraint on each of the input samples, the proposed method attempts to impose global sparsity constraint on the entire data set. This enables the proposed method to fittingly assign the atoms of the dictionary to represent various samples and optimally adapt to the complicated structures underlying the entire data set. By virtue of the sparse coding and sparse PCA techniques, a simple algorithm is designed for the implementation of the method. The efficiency and the convergence of the proposed algorithm are also theoretically analyzed. Based on the experimental results implemented on a series of signal and image data sets, it is apparent that our method performs better than the current dictionary learning methods in original dictionary recovering, input data reconstructing, and salient data structure revealing.; Comment: 27 pages, 9 figures, 1 table

## Constraint satisfaction parameterized by solution size

Bulatov, Andrei A.; Marx, Dániel
In the constraint satisfaction problem (CSP) corresponding to a constraint language (i.e., a set of relations) $\Gamma$, the goal is to find an assignment of values to variables so that a given set of constraints specified by relations from $\Gamma$ is satisfied. The complexity of this problem has received substantial amount of attention in the past decade. In this paper we study the fixed-parameter tractability of constraint satisfaction problems parameterized by the size of the solution in the following sense: one of the possible values, say 0, is "free," and the number of variables allowed to take other, "expensive," values is restricted. A size constraint requires that exactly $k$ variables take nonzero values. We also study a more refined version of this restriction: a global cardinality constraint prescribes how many variables have to be assigned each particular value. We study the parameterized complexity of these types of CSPs where the parameter is the required number $k$ of nonzero variables. As special cases, we can obtain natural and well-studied parameterized problems such as Independent Set, Vertex Cover, d-Hitting Set, Biclique, etc. In the case of constraint languages closed under substitution of constants, we give a complete characterization of the fixed-parameter tractable cases of CSPs with size constraints...