5,238 research outputs found
Revenue Elasticity of the Main federal Taxes in Mexico
An inelastic tax system increases the uncertainty associated with tax revenue collection. This results in continuous short-term adjustments to maintain the stability of tax collection. In this paper, we estimate the revenue elasticity of the principal taxes in Mexico, finding a much greater elasticity than that found in previous studies. A cointegration model between the revenue and taxes is used which satisfies strong exogeneity, providing a basis for congruent and reliable projections. Using this model, the tax revenue projected for 2011 is much lower than the estimates prepared by Mexico’s federal government.Federal taxes, long-term revenue elasticity, cointegration, strong exogeneity, forecasts
João Calvino (1509-1564) : entre a erudição e o zelo, a excelência para a Glória de Deus
Revista Lusófona de Ciência das Religiõe
History in Songs and Songs in History
[Abstract] Through music Ireland expresses its culture like no other nation in the world. Important events and the people involved in them are recorded in music to preserve them in people´s memory. Ireland has a long history of conflict between the the Irish and the British and music, as an expression of culture, provides so much information about the different ideologies. The objective of this work is to explore the connection that exists between music and history in the isle of Ireland. The first part of the work focuses on different types of songs and styles that are used to express certain ideas and ideologies like rebel songs or emigration songs. This part helps to classify some of the songs that are presented in the work. After this, a few events and some of the protagonists that were involved are analysed from a historical perspective in order to see how they are represented in music. The events analysed have a relevant role in Irish history. Namely, they are the Great Famine, the emigration, the Easter Rising, the Irish War of Independence and the Irish Civil War. In the third part of the work I focus on three Irish songs and analyse their backgrounds and story as a way to show these songs in their historical and cultural context and see how they became so important. The analysis of the songs is carried out using with a bibliography that deals, mainly, with history and Irish music separately. However, some sources about music and history together are used too. As a result, music proved to be a good mechanism to explore history from a different perspective to the narrative that can be found in classic history books. The relationship between music and history works in both ways, since one part gives depth to the other. Finally, in Ireland, music has a great symbolical power and the use of language, for instance, can produce political reactions, as can be seen with the Irish Anthem.Traballo fin de grao (UDC.FIL). Inglés: estudios lingüísticos y literarios. Curso 2019/202
Uniqueness of the Fock quantization of scalar fields under mode preserving canonical transformations varying in time
We study the Fock quantization of scalar fields of Klein-Gordon type in
nonstationary scenarios propagating in spacetimes with compact spatial
sections, allowing for different field descriptions that are related by means
of certain nonlocal linear canonical transformations that depend on time. More
specifically, we consider transformations that do not mix eigenmodes of the
Laplace-Beltrami operator, which are supposed to be dynamically decoupled. In
addition, we assume that the canonical transformations admit an asymptotic
expansion for large eigenvalues (in norm) of the Laplace-Beltrami operator in
the form of a series of half integer powers. Canonical transformations of this
kind are found in the study of scalar perturbations in inflationary
cosmologies, relating for instance the physical degrees of freedom of these
perturbations after gauge fixing with gauge invariant canonical pairs of
Bardeen quantities. We characterize all possible transformations of this type
and show that, independently of the initial field description, the combined
criterion of requiring (i) invariance of the vacuum under the spatial
symmetries and (ii) a unitary implementation of the dynamics, leads to a unique
equivalence class of Fock quantizations, all of them related by unitary
transformations. This conclusion provides even further robustness to the
validity of the proposed criterion, completing the results that have already
appeared in the literature about the uniqueness of the Fock quantization under
changes of field description when one permits exclusively local time dependent
canonical transformations that scale the field configuration.Comment: 12 pages, submitted to Phys. Rev.
Musical Cross Synthesis using Matrix Factorisation
The focus of this work is to explore a new method for the creative analysis and manipulation of musical audio content. Given a target song and a source song, the goal is reconstruct the harmonic and rhythmic structure of the target with the timbral components from the source, in such a way that so that both the target and the source material are recognizable by the listener. We refer to this operation as musical cross-synthesis. For this purpose, we propose the use of a Matrix Factorisation method, more specifically, Shift-Invariant Probabilistic Latent Component Analysis (PLCA). The input to the PLCA algorithm are beat synchronous CQT basis functions of the source whose temporal activations are used to approximate the CQT of the target. Using the shift invariant property of the PLCA allows each basis function to be subjected to a range of possible pitch shifts which increases the flexibility of the source to represent the target. To create the resulting musical cross-synthesis the beat synchronous, pitch-shifted CQT basis functions are inverted and concatenated in time
Sistemas Não Cooperativos para Registo de Assiduidade em Ambiente de Sala de Aula
Over the years, high school dropout, college dropout, in particular, has always been a hot
topic. With the advancement of technology and Artificial Intelligence and Machine Learning, we necessarily have to think of ways to help mitigate this problem. If there are factors
that we cannot control, such as the economic ones, there are others where our actions can
be directed. One factor that allows us to evaluate the risk of dropping out of school is student attendance. Although this data can be manually analyzed to make these detections,
it would be more efficient to have a capable system of recording this attendance, since the
human capacity to analyze data is finite, and often can only infer this situation too late. Of
course, a system that only registers attendance will not give a definitive answer, but it will
be an essential first step. Thus, a system that can reconcile the detection of a subject and
his face while being able to constantly monitor where the subject is, always to be able to
identify him even if he moves from one place to another, together with facial recognition,
seem to be determining factors to bring a system of this calibre to a successful conclusion.
This type of system is generally very much related to the quality of the data and its annotations, so it is vital to collect or obtain quality data to help solve the various problems
presented.
Considering what has been described, the main goal of this dissertation is to try to start
solving the problem of school dropout, namely through the study, validation and testing of
several stateoftheart methods in the area of object detection, namely people and faces,
but also tracking. The same work will have to be done on face recognition methods, being able to indicate the best stateoftheart methods for each task. As mentioned in the
previous paragraph, a significant limitation to this type of task is the data quality since it
is not always possible to find a set that perfectly fits our context. Thus, to solve this gap,
we will also present a dataset with about 40,000 images, thoroughly annotated frame by
frame and that we believe to be an asset in solving this problem. In addition to the above,
and in order not only to give a more meaningful and targeted response to our detailed
data but also to provide a preliminary view of how one of the system’s tasks might work,
we will present two experiments with our data in the area of detection. The first will involve finetuning our data, while the second will involve training it from scratch and then
presenting its results as proof of the correct choice of the stateoftheart method.Ao longo dos anos, o abandono escolar, o universitário em particular, tem sido sempre
um tema em grande destaque. Com o avanço de várias áreas tecnológicas, assim como da
Inteligência Artificial e da Aprendizagem Automática temos necessariamente de pensar
em maneiras de ajudar a mitigar este problema. Se há fatores que não podemos controlar, como os económicos, há outros onde a nossa ação pode ser dirigida. Um dos fatores
que permite avaliar o risco de abandono escolar é a assiduidade dos estudantes. Embora,
naturalmente, estes dados possam ser analisados manualmente para fazer estas deteções,
seria mais eficiente ter um sistema que fosse capaz de registar esta assiduidade, uma vez
que a capacidade humana para os analisar é finita e muitas vezes apenas consegue inferir esta situação demasiado tarde. Naturalmente que um sistema que registe apenas
assiduidade não irá ser capaz de dar uma resposta definitiva, mas será um primeiro passe
importante. Deste modo, um sistema que seja capaz de conciliar a deteção de uma pessoa
e da sua face enquanto é capaz de monitorizar de forma constante o sítio onde a pessoa
está, para ser sempre capaz de a identificar mesmo que mude de sítio em conjunto com
o seu reconhecimento facial, parecem ser fatores determinantes para levar a bom porto
um sistema deste calibre. Este tipo de sistemas está, geralmente, muito relacionado com
a qualidade dos dados e das suas anotações, pelo que é extraordinariamente importante
ser capaz de recolher ou obter dados de qualidade que auxiliem na resolução dos diversos
problemas apresentados.
Tendo em atenção aquilo que foi sendo descrito, o principal objetivo desta dissertação
passa por tentar dar início à resolução do problema do abandono escolar, nomeadamente
através do estudo, validação e teste de diversos métodos estadodaarte no que diz respeito
à área da deteção de objetos, nomeadamente de pessoas e faces, mas também de tracking.
O mesmo trabalho terá de ser realizado nos métodos de reconhecimento facial, sendo capaz no final de poder indicar os melhores métodos estadodaarte de cada tarefa. Como
referido no parágrafo anterior, uma limitação grande a este tipo de tarefas é a respetiva
qualidade dos dados, visto que nem sempre e possível encontrar um conjunto que se adeque perfeitamente ao nosso contexto. Assim, de modo a solucionar esta lacuna iremos
também apresentar um dataset com cerca de 40,000 imagens, completamente anotado
frame a frame e que acreditamos ser uma mais valia na resolução deste problema. Para
além do referido, e de modo não só a dar uma resposta mais significativa e dirigida aos
nossos dados em particular, mas também para que seja possível ter uma visão preliminar
daquilo que poderá ser o funcionamento de uma das tarefas do sistema, iremos apresentar duas experiências com os nossos dados, na área da deteção. A primeira irá envolver o
finetuning dos nossos dados, enquanto que a segunda levará a um treino iniciado de raiz,
apresentando depois os seus resultados como uma prova da escolha acertada do método
de estado da arte
Determinants of Box Products of Paths
Suppose that G is the graph obtained by taking the box product of a path of
length n and a path of length m. Let M be the adjacency matrix of G. If n=m,
H.M. Rara showed in 1996 that det(M)=0. We extend this result to allow n and m
to be any positive integers, and show that, if gcd(n+1,m+1)>1, then det(M)=0;
otherwise, if gcd(n+1,m+1)=1, then det(M)=(-1)^(nm/2)
A New Model to Improve Project Time-Cost Trade-Off in Uncertain Environments
The time–cost trade-off problem (TCTP) is fundamental to project scheduling. Risks in estimation of project cost and duration are significant due to uncertainty. This uncertainty cannot be eliminated by any scheduling or estimation techniques. Therefore, a model that can represent uncertainty in the real world to solve time–cost trade-off problems is needed. In this chapter, fuzzy logic is utilized to consider affecting uncertainties in project duration and cost. An optimization algorithm based on time-driven activity-based costing (TDABC) is applied to provide a trade-off between project time and cost. The presented model could solve the time–cost trade-off problem while accounting for uncertainty in project cost and duration. This could help generate a more reliable schedule and mitigate the risk of projects running overbudget or behind schedule
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