From XML to relational view updates: applying old solutions to solve a new problem

XML has become an important medium for data exchange, and is frequently used as an interface to - i.e. a view of - a relational database. Although lots of work have been done on querying relational databases through XML views, the problem of updating relational databases through XML views has not received much attention. In this work, we give the rst steps towards solving this problem. Using query trees to capture the notions of selection, projection, nesting, grouping, and heterogeneous sets found throughout most XML query languages, we show how XML views expressed using query trees can be mapped to a set of corresponding relational views. Thus, we transform the problem of updating relational databases through XML views into a classical problem of updating relational databases through relational views. We then show how updates on the XML view are mapped to updates on the corresponding relational views. Existing work on updating relational views can then be leveraged to determine whether or not the relational views are updatable with respect to the relational updates, and if so, to translate the updates to the underlying relational database. Since query trees are a formal characterization of view de nition queries, they are not well suited for end-users. We then investigate how a subset of XQuery can be used as a top level language, and show how query trees can be used as an intermediate representation of view de nitions expressed in this subset.

Using irregularly spaced returns to estimate multi-factor models: application to Brazilian equity data

Multi-factor models constitute a useful tool to explain cross-sectional covariance in equities returns. We propose in this paper the use of irregularly spaced returns in the multi-factor model estimation and provide an empirical example with the 389 most liquid equities in the Brazilian Market. The market index shows itself significant to explain equity returns while the US$/Brazilian Real exchange rate and the Brazilian standard interest rate does not. This example shows the usefulness of the estimation method in further using the model to fill in missing values and to provide interval forecasts.

Endogenous transactions costs in multi-seller model

vVe examine the problem of a buyer who wishes to purehase and eombine ti. objeets owned by n individual owners to realize a higher V'illue. The owners are able to delay their entry into the sale proeess: They ean either seU now 01' seU later. Among other assumptions, the simple assumptions of compef'if'irnl, · .. that the presenee of more owners at point of sale reduees their surplus .. · and di..,(Jyun,fúl,g lead to interesting results: There is eostly delay in equilibdum. rvIoreover, with suffidently strong eompetition, the probability of delay inereases with n. Thus, buyers who diseount the future \\i11 faee inereased eosts as the number of owners inereases. The souree of transaetions eosts is the owners' desire to dis-eoordinate in the presenee of eompetition. These eosts are unrelated to transaetions eosts eurrently identified in the literature, spedfieally those due to asymmetrie information, 01' publie goods problems where players impose negative externalities on eaeh other by under-eontributing.

Using irregularly spaced returns to estimate multi-factor models : application to Brazilian equity data

Multi-factor models constitute a use fui tool to explain cross-sectional covariance in equities retums. We propose in this paper the use of irregularly spaced returns in the multi-factor model estimation and provide an empirical example with the 389 most liquid equities in the Brazilian Market. The market index shows itself significant to explain equity returns while the US$/Brazilian Real exchange rate and the Brazilian standard interest rate does not. This example shows the usefulness of the estimation method in further using the model to fill in missing values and to provide intervaI forecasts.

Modelos de negócio na economia compartilhada: uma investigação multi-caso

A economia compartilhada teve origem na década de 1990 nos Estados Unidos impulsionada pelos avanços tecnológicos que propiciaram a redução dos custos das transações on-line peer-to-peer (SHIRKY, 2008), viabilizando a criação de novos modelos de negócio baseados na troca e no compartilhamento de bens e serviços entre pessoas desconhecidas (SCHOR, 2015). A economia compartilhada é constituída por práticas comerciais que possibilitam o acesso a bens e serviços, sem que haja, necessariamente, a aquisição de um produto ou troca monetária (BOTSMAN; ROGERS, 2011). Atualmente, a economia compartilhada está tomando forma no Brasil, por meio da expansão de modelos de negócio que visam ao compartilhamento, à troca e à revenda de produtos e serviços. Assim, objetivando expandir o conhecimento sobre este fenômeno econômico, realizou-se um estudo de caso múltiplo em quatro empresas representantes dessa economia, com o objetivo de conhecer os seus modelos de negócio, enfatizando uma abordagem holística para compreender como essas organizações realizam seus negócios (ZOTT; AMIT; MASSA, 2011). Como resultado deste estudo, constata-se que a economia compartilhada abrange uma extensa gama de modelos de negócio (SCHOR, 2014), dentre os quatro casos estudados foram observados três modelos de negócio distintos. Ademais, por meio dos casos estudados, evidencia-se que as empresas da economia compartilhada tendem a desenvolver sinergias com empresas da economia tradicional para garantir sua sustentabilidade, visto que, das quatro empresas estudadas, três já estão desenvolvendo transações business-to-business com parceiros da economia tradicional, constatando-se assim o surgimento de uma economia híbrida constituída pelo mercado capitalista e pelas iniciativas de compartilhamento (RIFKIN, 2014). Todavia, verifica-se que a aproximação com empresas tradicionais não significa o abandono da essência de compartilhamento e sustentabilidade socioambiental, inerentes às propostas de valor das atividades da economia compartilhada.

Coordenação e governança no Programa Territórios da Cidadania: uma análise multi-level a partir do Vale do Ribeira-SP

Poverty in Brazil has been gradually reduced. Among the main reasons, there are public policies for universalization of rights. On the other hand, the municipalities' Human Development Index indicates scenarios of growing inequality. In other words, some regions, basically of rural character, were left behind in that process of development. In 2008, the “Territórios da Cidadania” (Territories of Citizenship) Program was launched by the federal government, under high expectations. It was proposed to develop those regions and to prioritize the arrival of ongoing federal public policies where they were most demanded. The program has shown an innovative arrangement which included dozens of ministries and other federal agencies, state governments, municipalities and collegialities to the palliative management and control of the territory. In this structure, both new and existing jurisdictions came to support the program coordination. This arrangement was classified as an example of multi-level governance, whose theory has been an efficient instrument to understand the intra- and intergovernmental relations under which the program took place. The program lasted only three years. In Vale do Ribeira Territory – SP, few community leaderships acknowledge it, although not having further information about its actions and effects. Against this background, the approach of this research aims to study the program coordination and governance structure (from Vale Territory, considered as the most local level, until the federal government), based on the hypothesis that, beyond the local contingencies in Vale do Ribeira, the layout and implementation of the Territories of Citizenship Program as they were formulated possess fundamental structural issues that hinder its goals of reducing poverty and inequality through promoting the development of the territory. Complementing the research, its specific goal was to raise the program layout and background in order to understand how the relations, predicted or not in its structure, were formulated and how they were developed, with special attention to Vale do Ribeira-SP. Generally speaking, it was concluded that the coordination and governance arrangement of the Territories of Citizenship Program failed for not having developed qualified solutions to deal with the challenges of the federalist Brazilian structure, party politics, sectorized public actions, or even the territory contingencies and specificities. The complexity of the program, the poverty problem proposed to be faced, and the territorial strategy of development charged a high cost of coordination, which was not accomplished by the proposal of centralization in the federal government with internal decentralization of the coordination. As the presidency changed in 2011, the program could not present results that were able to justify the arguments for its continuation, therefore it was paralyzed, lost its priority status, and the resources previously invested were redirected.

Remote presence: supporting deictic gestures through a handheld multi-touch device

This thesis argues on the possibility of supporting deictic gestures through handheld multi-touch devices in remote presentation scenarios. In [1], Clark distinguishes indicative techniques of placing-for and directing-to, where placing-for refers to placing a referent into the addressee’s attention, and directing-to refers to directing the addressee’s attention towards a referent. Keynote, PowerPoint, FuzeMeeting and others support placing-for efficiently with slide transitions, and animations, but support limited to none directing-to. The traditional “pointing feature” present in some presentation tools comes as a virtual laser pointer or mouse cursor. [12, 13] have shown that the mouse cursor and laser pointer offer very little informational expressiveness and do not do justice to human communicative gestures. In this project, a prototype application was implemented for the iPad in order to explore, develop, and test the concept of pointing in remote presentations. The prototype offers visualizing and navigating the slides as well as “pointing” and zooming. To further investigate the problem and possible solutions, a theoretical framework was designed representing the relationships between the presenter’s intention and gesture and the resulting visual effect (cursor) that enables the audience members to interpret the meaning of the effect and the presenter’s intention. Two studies were performed to investigate people’s appreciation of different ways of presenting remotely. An initial qualitative study was performed at The Hague, followed by an online quantitative user experiment. The results indicate that subjects found pointing to be helpful in understanding and concentrating, while the detached video feed of the presenter was considered to be distracting. The positive qualities of having the video feed were the emotion and social presence that it adds to the presentations. For a number of subjects, pointing displayed some of the same social and personal qualities [2] that video affords, while less intensified. The combination of pointing and video proved to be successful with 10-out-of-19 subjects scoring it the highest while pointing example came at a close 8-out-of-19. Video was the least preferred with only one subject preferring it. We suggest that the research performed here could provide a basis for future research and possibly be applied in a variety of distributed collaborative settings.

Aprendizado por Reforço com Valores deInfluência em Sistemas Multi-Agente

We propose a new paradigm for collective learning in multi-agent systems (MAS) as a solution to the problem in which several agents acting over the same environment must learn how to perform tasks, simultaneously, based on feedbacks given by each one of the other agents. We introduce the proposed paradigm in the form of a reinforcement learning algorithm, nominating it as reinforcement learning with influence values. While learning by rewards, each agent evaluates the relation between the current state and/or action executed at this state (actual believe) together with the reward obtained after all agents that are interacting perform their actions. The reward is a result of the interference of others. The agent considers the opinions of all its colleagues in order to attempt to change the values of its states and/or actions. The idea is that the system, as a whole, must reach an equilibrium, where all agents get satisfied with the obtained results. This means that the values of the state/actions pairs match the reward obtained by each agent. This dynamical way of setting the values for states and/or actions makes this new reinforcement learning paradigm the first to include, naturally, the fact that the presence of other agents in the environment turns it a dynamical model. As a direct result, we implicitly include the internal state, the actions and the rewards obtained by all the other agents in the internal state of each agent. This makes our proposal the first complete solution to the conceptual problem that rises when applying reinforcement learning in multi-agent systems, which is caused by the difference existent between the environment and agent models. With basis on the proposed model, we create the IVQ-learning algorithm that is exhaustive tested in repetitive games with two, three and four agents and in stochastic games that need cooperation and in games that need collaboration. This algorithm shows to be a good option for obtaining solutions that guarantee convergence to the Nash optimum equilibrium in cooperative problems. Experiments performed clear shows that the proposed paradigm is theoretical and experimentally superior to the traditional approaches. Yet, with the creation of this new paradigm the set of reinforcement learning applications in MAS grows up. That is, besides the possibility of applying the algorithm in traditional learning problems in MAS, as for example coordination of tasks in multi-robot systems, it is possible to apply reinforcement learning in problems that are essentially collaborative

O problema do caixeiro viajante alugador : um estudo algorítmico

The Car Rental Salesman Problem (CaRS) is a variant of the classical Traveling Salesman Problem which was not described in the literature where a tour of visits can be decomposed into contiguous paths that may be performed in different rental cars. The aim is to determine the Hamiltonian cycle that results in a final minimum cost, considering the cost of the route added to the cost of an expected penalty paid for each exchange of vehicles on the route. This penalty is due to the return of the car dropped to the base. This paper introduces the general problem and illustrates some examples, also featuring some of its associated variants. An overview of the complexity of this combinatorial problem is also outlined, to justify their classification in the NPhard class. A database of instances for the problem is presented, describing the methodology of its constitution. The presented problem is also the subject of a study based on experimental algorithmic implementation of six metaheuristic solutions, representing adaptations of the best of state-of-the-art heuristic programming. New neighborhoods, construction procedures, search operators, evolutionary agents, cooperation by multi-pheromone are created for this problem. Furtermore, computational experiments and comparative performance tests are conducted on a sample of 60 instances of the created database, aiming to offer a algorithm with an efficient solution for this problem. These results will illustrate the best performance reached by the transgenetic algorithm in all instances of the dataset

The flavor problem and discrete symmetries

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Aggregation-based decomposition for multi-divisional models

The aggregation theory of mathematical programming is used to study decentralization in convex programming models. A two-level organization is considered and a aggregation-disaggregation scheme is applied to such a divisionally organized enterprise. In contrast to the known aggregation techniques, where the decision variables/production planes are aggregated, it is proposed to aggregate resources allocated by the central planning department among the divisions. This approach results in a decomposition procedure, in which the central unit has no optimization problem to solve and should only average local information provided by the divisions.

A branch-and-bound algorithm for the multi-stage transmission expansion planning

This work presents a branch-and-bound algorithm to solve the multi-stage transmission expansion planning problem. The well known transportation model is employed, nevertheless the algorithm can be extended to hybrid models or to more complex ones such as the DC model. Tests with a realistic power system were carried out in order to show the performance of the algorithm for the expansion plan executed for different time frames. © 2005 IEEE.

Multi-areas optimal reactive power flow

This paper describes a method for the decentralized solution of the optimal reactive power flow (ORPF) problem in interconnected power systems. The ORPF model is solved in a decentralized framework, consisting of regions, where the transmission system operator in each area operates its system independently of the other areas, obtaining an optimal coordinated but decentralized solution. The proposed scheme is based on an augmented Lagrangian approach using the auxiliary problem principle (APP). An implementation of an interior point method is described to solve the decoupled problem in each area. The described method is successfully implemented and tested using the IEEE two area RTS 96 test system. Numerical results comparing the solutions obtained by the traditional and the proposed decentralized methods are presented for validation. ©2008 IEEE.

Evaluating genetic algorithms with different population structures on a lot sizing and scheduling problem

This paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated. Copyright 2008 ACM.

Una metodología eficiente para manejo de restricciones en algoritmos evolutivos multi-objetivo

This paper presents a new approach for solving constraint optimization problems (COP) based on the philosophy of lexicographical goal programming. A two-phase methodology for solving COP using a multi-objective strategy is used. In the first phase, the objective function is completely disregarded and the entire search effort is directed towards finding a single feasible solution. In the second phase, the problem is treated as a bi-objective optimization problem, turning the constraint optimization into a two-objective optimization. The two resulting objectives are the original objective function and the constraint violation degree. In the first phase a methodology based on progressive hardening of soft constraints is proposed in order to find feasible solutions. The performance of the proposed methodology was tested on 11 well-known benchmark functions.