31 research outputs found
SMS Spam Filtering using Probabilistic Topic Modelling and Stacked Denoising Autoencoder
In This paper we present a novel approach to spam filtering and demonstrate its applicability with respect to SMS messages. Our approach requires minimum features engineering and a small set of labelled data samples. Features are extracted using topic modelling based on latent Dirichlet allocation, and then a comprehensive data model is created using a Stacked Denoising Autoencoder (SDA). Topic modelling summarises the data providing ease of use and high interpretability by visualising the topics using word clouds. Given that the SMS messages can be regarded as either spam (unwanted) or ham (wanted), the SDA is able to model the messages and accurately discriminate between the two classes without the need for a pre-labelled training set. The results are compared against the state-of-the-art spam detection algorithms with our proposed approach achieving over 97 % accuracy which compares favourably to the best reported algorithms presented in the literature
Remarks on the "non-canonicity puzzle": Lagrangian symmetries of the Einstein-Hilbert action
Given the non-canonical relationship between variables used in the
Hamiltonian formulations of the Einstein-Hilbert action (due to Pirani, Schild,
Skinner (PSS) and Dirac) and the Arnowitt-Deser-Misner (ADM) action, and the
consequent difference in the gauge transformations generated by the first-class
constraints of these two formulations, the assumption that the Lagrangians from
which they were derived are equivalent leads to an apparent contradiction that
has been called "the non-canonicity puzzle". In this work we shall investigate
the group properties of two symmetries derived for the Einstein-Hilbert action:
diffeomorphism, which follows from the PSS and Dirac formulations, and the one
that arises from the ADM formulation. We demonstrate that unlike the
diffeomorphism transformations, the ADM transformations (as well as others,
which can be constructed for the Einstein-Hilbert Lagrangian using Noether's
identities) do not form a group. This makes diffeomorphism transformations
unique (the term "canonical" symmetry might be suggested). If the two
Lagrangians are to be called equivalent, canonical symmetry must be preserved.
The interplay between general covariance and the canonicity of the variables
used is discussed.Comment: 23 page
Arnowitt-Deser-Misner representation and Hamiltonian analysis of covariant renormalizable gravity
We study the recently proposed Covariant Renormalizable Gravity (CRG), which
aims to provide a generally covariant ultraviolet completion of general
relativity. We obtain a space-time decomposed form --- an Arnowitt-Deser-Misner
(ADM) representation --- of the CRG action. The action is found to contain time
derivatives of the gravitational fields up to fourth order. Some ways to reduce
the order of these time derivatives are considered. The resulting action is
analyzed using the Hamiltonian formalism, which was originally adapted for
constrained theories by Dirac. It is shown that the theory has a consistent set
of constraints. It is, however, found that the theory exhibits four propagating
physical degrees of freedom. This is one degree of freedom more than in
Ho\v{r}ava-Lifshitz (HL) gravity and two more propagating modes than in general
relativity. One extra physical degree of freedom has its origin in the higher
order nature of the CRG action. The other extra propagating mode is a
consequence of a projectability condition similarly as in HL gravity. Some
additional gauge symmetry may need to be introduced in order to get rid of the
extra gravitational degrees of freedom.Comment: 21 pages, LaTeX. A correction inserted to Hamiltonian formalism in
Sec.
A generic method to develop simulation models for ambulance systems
In this paper, we address the question of generic simulation models and their role in improving emergency care around the world. After reviewing the development of ambulance models and the contexts in which they have been applied, we report the construction of a reusable model for ambulance systems. Further, we describe the associated parameters, data sources, and performance measures, and report on the collection of information, as well as the use of optimisation to configure the service to best effect. Having developed the model, we have validated it using real data from the emergency medical system in a Brazilian city, Belo Horizonte. To illustrate the benefits of standardisation and reusability we apply the model to a UK context by exploring how different rules of engagement would change the performance of the system. Finally, we consider the impact that one might observe if such rules were adopted by the Brazilian system
U(1) Invariant F(R) Horava-Lifshitz Gravity
This paper is devoted to the study of various aspects of projectable F(R)
Horava-Lifshitz (HL) gravity. We show that some versions of F(R) HL gravity may
have stable de Sitter solution and instable flat space solution. In this case,
the problem of scalar graviton does not appear because flat space is not vacuum
state. Generalizing the U(1) HL theory proposed in arXiv:1007.2410, we
formulate U(1) extension of scalar theory and of F(R) Horava-Lifshitz gravity.
The Hamiltonian approach for such the theory is developed in full detail. It is
demonstrated that its Hamiltonian structure is the same as for the
non-relativistic covariant HL gravity. The spectrum analysis performed around
flat background indicates towards the consistency of the theory because it
contains graviton with only transverse polarization. Finally, we analyze the
spatially-flat FRW equations for U(1) invariant F(R) Horava-Lifshitz gravity.Comment: 26 pages, several mysprints correcte
Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers
Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI
Comparison of UWB Dual-Antenna Systems Using Diversity
International audienc