Efficient paraconsistent reasoning with rules and ontologies for the semantic web

Ontologies formalized by means of Description Logics (DLs) and rules in the form of Logic Programs (LPs) are two prominent formalisms in the field of Knowledge Representation and Reasoning. While DLs adhere to the OpenWorld Assumption and are suited for taxonomic reasoning, LPs implement reasoning under the Closed World Assumption, so that default knowledge can be expressed. However, for many applications it is useful to have a means that allows reasoning over an open domain and expressing rules with exceptions at the same time. Hybrid MKNF knowledge bases make such a means available by formalizing DLs and LPs in a common logic, the Logic of Minimal Knowledge and Negation as Failure (MKNF). Since rules and ontologies are used in open environments such as the Semantic Web, inconsistencies cannot always be avoided. This poses a problem due to the Principle of Explosion, which holds in classical logics. Paraconsistent Logics offer a solution to this issue by assigning meaningful models even to contradictory sets of formulas. Consequently, paraconsistent semantics for DLs and LPs have been investigated intensively. Our goal is to apply the paraconsistent approach to the combination of DLs and LPs in hybrid MKNF knowledge bases. In this thesis, a new six-valued semantics for hybrid MKNF knowledge bases is introduced, extending the three-valued approach by Knorr et al., which is based on the wellfounded semantics for logic programs. Additionally, a procedural way of computing paraconsistent well-founded models for hybrid MKNF knowledge bases by means of an alternating fixpoint construction is presented and it is proven that the algorithm is sound and complete w.r.t. the model-theoretic characterization of the semantics. Moreover, it is shown that the new semantics is faithful w.r.t. well-studied paraconsistent semantics for DLs and LPs, respectively, and maintains the efficiency of the approach it extends.

A DSL for querying building data streams of energy, eeather and occupation data

The superfluous consumption of energy is faced by the modern society as a Socio-Economical and Environmental problem of the present days. This situation is worsening given that it is becoming clear that the tendency is to increase energy price every year. It is also noticeable that people, not necessarily proficient in technology, are not able to know where savings can be achieved, due to the absence of accessible awareness mechanisms. One of the home user concerns is to balance the need of reducing energy consumption, while producing the same activity with all the comfort and work efficiency. The common techniques to reduce the consumption are to use a less wasteful equipment, altering the equipment program to a more economical one or disconnecting appliances that are not necessary at the moment. However, there is no direct feedback from this performed actions, which leads to the situation where the user is not aware of the influence that these techniques have in the electrical bill. With the intension to give some control over the home consumption, Energy Management Systems (EMS) were developed. These systems allow the access to the consumption information and help understanding the energy waste. However, some studies have proven that these systems have a clear mismatch between the information that is presented and the one the user finds useful for his daily life, leading to demotivation of use. In order to create a solution more oriented towards the user’s demands, a specially tailored language (DSL) was implemented. This solution allows the user to acquire the information he considers useful, through the construction of questions about his energy consumption. The development of this language, following the Model Driven Development (MDD) approach, took into consideration the ideas of facility managers and home users in the phases of design and validation. These opinions were gathered through meetings with experts and a survey, which was conducted to the purpose of collecting statistics about what home users want to know.

Degree of disability, pain levels, muscle strength, and electromyographic function in patients with Hansen's disease with common peroneal nerve damage

INTRODUCTION: This study evaluated the degree of disability, pain levels, muscle strength, and electromyographic function (RMS) in individuals with leprosy. METHODS: We assessed 29 individuals with leprosy showing common peroneal nerve damage and grade 1 or 2 disability who were referred for physiotherapeutic treatment, as well as a control group of 19 healthy participants without leprosy. All subjects underwent analyses of degree of disability, electromyographic tests, voluntary muscle force, and the Visual Analog Pain Scale. RESULTS: McNemar's test found higher levels of grade 2 of disability (Δ = 75.9%; p = 0.0001) among individuals with leprosy. The Mann-Whitney test showed greater pain levels (Δ = 5.0; p = 0.0001) in patients with leprosy who had less extension strength in the right and left extensor hallucis longus muscles (Δ = 1.28, p = 0.0001; Δ = 1.55, p = 0.0001, respectively) and dorsiflexion of the right and left feet (Δ = 1.24, p = 0.0001; Δ = 1.45, p = 0.0001, respectively) than control subjects. The Kruskal-Wallis test showed that the RMS score for dorsiflexion of the right (Δ = 181.66 m·s-2, p = 0.001) and left (Δ = 102.57m·s-2, p = 0.002) feet was lower in patients with leprosy than in control subjects, but intragroup comparisons showed no difference. CONCLUSIONS: Leprosy had a negative influence on all of the study variables, indicating the need for immediate physiotherapeutic intervention in individuals with leprosy. This investigation opens perspectives for future studies that analyze leprosy treatment with physical therapeutic intervention.

Common variable immunodeficiency and isosporiasis: first report case

We report a severe case of diarrhea in a 62-year-old female HIV-negative patient from whom Giardia lamblia and Isospora belli were isolated. Because unusual and opportunistic infections should be considered as criteria for further analysis of immunological status, laboratory investigations led to a diagnosis of common variable immunodeficiency (CVID). This is the first reported case of isosporiasis in a patient with CVID and illustrates the importance of being aware of a possible link, particularly in relation to primary immunodeficiency.

Predicting market direction with hidden Markov models

This paper develops the model of Bicego, Grosso, and Otranto (2008) and applies Hidden Markov Models to predict market direction. The paper draws an analogy between financial markets and speech recognition, seeking inspiration from the latter to solve common issues in quantitative investing. Whereas previous works focus mostly on very complex modifications of the original hidden markov model algorithm, the current paper provides an innovative methodology by drawing inspiration from thoroughly tested, yet simple, speech recognition methodologies. By grouping returns into sequences, Hidden Markov Models can then predict market direction the same way they are used to identify phonemes in speech recognition. The model proves highly successful in identifying market direction but fails to consistently identify whether a trend is in place. All in all, the current paper seeks to bridge the gap between speech recognition and quantitative finance and, even though the model is not fully successful, several refinements are suggested and the room for improvement is significant.

Description of microsporidia in simulids: molecular and morphological characterization of microsporidia in the larvae of Simulium pertinax Kollar (Diptera: Simuliidae)

IntroductionMicrosporidia constitute the most common black fly pathogens, although the species' diversity, seasonal occurrence and transmission mechanisms remain poorly understood. Infections by this agent are often chronic and non-lethal, but they can cause reduced fecundity and decreased longevity. The objective of this study was to identify microsporidia infecting Simulium (Chirostilbia) pertinax (Kollar, 1832) larvae from Caraguatatuba, State of São Paulo, Brazil, by molecular and morphological characterization.MethodsLarvae were collected at a single point in a stream in a rural area of the city and were kept under artificial aeration until analysis. Polydispyrenia spp. infection was characterized by the presence of at least 32 mononuclear spores measuring 6.9 ± 1.0 × 5.0 ± 0.7µm in persistent sporophorous vesicles. Similarly, Amblyospora spp. were characterized by the presence of eight uninucleate spores measuring 4.5 × 3.5µm in sporophorous vesicles.ResultsThe molecular analysis confirmed the presence of microsporidian DNA in the 8 samples (prevalence of 0.51%). Six samples (Brazilian larvae) were related to Polydispyrenia simulii and Caudospora palustris reference sequences but in separate clusters. One sample was clustered with Amblyospora spp. Edhazardia aedis was the positive control taxon.ConclusionsSamples identified as Polydispyrenia spp. and Amblyospora spp. were grouped with P. simulii and Amblyospora spp., respectively, corroborating previous results. However, the 16S gene tree showed a considerable distance between the black fly-infecting Amblyospora spp. and the mosquito-infecting spp. This distance suggests that these two groups are not congeneric. Additional genomic region evaluation is necessary to obtain a coherent phylogeny for this group.

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

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Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.

Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

Color change using HSB color system of dental resin composites immersed in different common Amazon region beverages

The purpose of this study is to evaluate in vitro the color stability of composite resins when exposed to beverages with high coloring contents from the Amazon region. 240 samples from four different composite brands (Natural Look, Z350, 4Seasons and Opallis) of hue A3 were fabricated using an acrylic matrix. The samples were stored in distilled water at 37ºC for 24 hours. The initial color (T0) was registered using a Canon EOS Rebel XTi 10 mp camera, and then the samples were divided into four groups (n=15): G1 (coffee), G2 (açaí juice), G3 (energetic guaraná) and G4 (control - distilled water). The samples were exposed to solutions of DES (6hs) and RE (18hs) and placed in a double boiler under constant agitation, at 37ºC for 30 days. The samples were immersed in the coloring solutions for 15 minutes daily. After 7, 15 and 30 days, new photographic registers were made (T1, T2 and T3). The images were analyzed using Corel PHOTO-PAINT 12 software to identify the colors through the HSB system. The Kruskal-Wallis and t tests (p<0.05) demonstrated significant differences in color (hue, saturation and brightness). The results revealed that none of the tested composites showed color stability when exposed to coloring solutions, and that the Amazon region beverages (açaí juice and energetic guaraná) showed to be less coloring than coffee.

New control algorithm for single-phase series active power filter

This paper presents a single-phase Series Active Power Filter (Series APF) for mitigation of the load voltage harmonic content, while maintaining the voltage on the DC side regulated without the support of a voltage source. The proposed series active power filter control algorithm eliminates the additional voltage source to regulate the DC voltage, and with the adopted topology it is not used a coupling transformer to interface the series active power filter with the electrical power grid. The paper describes the control strategy which encapsulates the grid synchronization scheme, the compensation voltage calculation, the damping algorithm and the dead-time compensation. The topology and control strategy of the series active power filter have been evaluated in simulation software and simulations results are presented. Experimental results, obtained with a developed laboratorial prototype, validate the theoretical assumptions, and are within the harmonic spectrum limits imposed by the international recommendations of the IEEE-519 Standard.