"High in omega-3 fatty acids" bologna-type sausages stabilized with an aqueous-ethanol extract of Melissa officinalis

A new formulation of bologna-type sausage enriched in ω-3 polyunsaturated fatty acids (PUFA) (8.75% linseed oil) was developed, using a lyophilized aqueous-ethanolic extract of Melissa officinalis. A comparison with the effectiveness of butylhydroxy anisole (BHA) synthetic antioxidant to decrease the oxidation of PUFAs was performed.     

General static load‐carrying capacity of four‐contact‐point slewing bearings for wind turbine generator actuation systems

Four‐contact‐point slewing bearings are widely used in wind turbine generators (WTGs) to adjust the orientation of the blades and the nacelle to fully exploit wind resources. These bearings must withstand static and fatigue loads; however, at the first stages of the design process, the bearings are commonly selected by considering only static loads. This paper presents a further step of a previous theoretical work published by the authors in the field of the static load‐carrying capacity of four‐contact‐point slewing bearings under axial, radial and tilting‐moment loads. In that work, a generalization of the works by Sjoväll and Rumbarger was presented, providing an acceptance surface of the bearing in the load space. The contact angle of the balls was assumed to be load independent. The present work improves that development by considering the influence of the variability of the contact angle with the applied load, and as a result, the acceptance surface has been redefined. By comparing the results with those of the finite element model published by the authors, it is proven that the new model presented in this work is more realistic than the previous one. Thus, it is believed that this methodology can be easily applied for the initial selection of blade and yaw bearings in WTGs. Copyright © 2012 John Wiley & Sons, Ltd.     

Accurate ball trajectory tracking and 3D visualization for computer-assisted sports broadcast

The application of computer-aided controversial plays resolution in sport events significantly benefits organizers, referees and audience. Nowadays, especially in ball sports, very accurate technological solutions can be found. The main drawback of these systems is the need of complex and expensive hardware which makes them not affordable for less-known regional/traditional sports events. The lack of competitive systems with reduced hardware/software complexity and requirements motivates this research. Visual Analytics technologies permit system detecting the ball trajectory, solving with precision possible controversial plays. Ball is extracted from the video scene exploiting its shape features and velocity vector properties. Afterwards, its relative position to border line is calculated based on polynomial approximations. In order to enhance user visual experience, real-time rendering technologies are introduced to obtain virtual 3D reconstruction in quasi real-time. Comparing to other set ups, the main contribution of this work lays on the utilization of an unique camera per border line to extract 3D bounce point information. In addition, the system has no camera location/orientation limit, provided that line view is not occluded. Testing of the system has been done in real world scenarios, comparing the system output with referees’ judgment. Visual results of the system have been broadcasted during Basque Pelota matches.     

Procedural approach to volumetric terrain generation

The recent outbreak of indie games has popularized volumetric terrains to a new level, although video games have used them for decades. These terrains contain geological data, such as materials or cave systems. To improve the exploration experience and due to the large amount of data needed to construct volumetric terrains, industry uses procedural methods to generate them. However, they use their own methods, which are focused on their specific problem domains, lacking customization features. Besides, the evaluation of the procedural terrain generators remains an open issue in this field since no standard metrics have been established yet. In this paper, we propose a new approach to procedural volumetric terrains. It generates completely customizable volumetric terrains with layered materials and other features (e.g., mineral veins, underground caves, material mixtures and underground material flow). The method allows the designer to specify the characteristics of the terrain using intuitive parameters. Additionally, it uses a specific representation for the terrain based on stacked material structures, reducing memory requirements. To overcome the problem in the evaluation of the generators, we propose a new set of metrics for the generated content.     

A simple and communication-efficient Omega algorithm in the crash-recovery model

This paper presents a new algorithm implementing the Omega failure detector in the crash-recovery model. Contrary to previously proposed algorithms, this algorithm does not rely on the use of stable storage and is communication-efficient, i.e., eventually only one process (the elected leader) keeps sending messages. The algorithm relies on a nondecreasing local clock associated with each process. Since stable storage is not used to keep the identity of the leader in order to read it upon recovery, unstable processes, i.e., those that crash and recover infinitely often, output a special ⊥ value upon recovery, and then agree with correct processes on the leader after receiving a first message from it.     

Apertium: a free/open-source platform for rule-based machine translation

Apertium is a free/open-source platform for rule-based machine translation. It is being widely used to build machine translation systems for a variety of language pairs, especially in those cases (mainly with related-language pairs) where shallow transfer suffices to produce good quality translations, although it has also proven useful in assimilation scenarios with more distant pairs involved. This article summarises the Apertium platform: the translation engine, the encoding of linguistic data, and the tools developed around the platform. The present limitations of the platform and the challenges posed for the coming years are also discussed. Finally, evaluation results for some of the most active language pairs are presented. An appendix describes Apertium as a free/open-source project.     

Assisting non-expert speakers of under-resourced languages in assigning stems and inflectional paradigms to new word entries of morphological dictionaries

This paper presents a new method with which to assist individuals with no background in linguistics to create monolingual dictionaries such as those used by the morphological analysers of many natural language processing applications. The involvement of non-expert users is especially critical for under-resourced languages which either lack or cannot afford the recruitment of a skilled workforce. Adding a word to a morphological dictionary usually requires identifying its stem along with the inflection paradigm that can be used in order to generate all the word forms of the new entry. Our method works under the assumption that the average speakers of a language can successfully answer the polar question “is x a valid form of the word w to be inserted?”, where x represents tentative alternative (inflected) forms of the new word w. The experiments show that with a small number of polar questions the correct stem and paradigm can be obtained from non-experts with high success rates. We study the impact of different heuristic and probabilistic approaches on the actual number of questions.     

Incremental Construction of Minimal Tree Automata

We describe an algorithm that allows the incremental addition or removal of unranked ordered trees to a minimal frontier-to-root deterministic finite-state tree automaton (DTA). The algorithm takes a tree t and a minimal DTA A as input; it outputs a minimal DTA A′ which accepts the language L(A) accepted by A incremented (or decremented) with the tree t. The algorithm can be used to efficiently maintain dictionaries which store large collections of trees or tree fragments.     

Using target-language information to train part-of-speech taggers for machine translation

Although corpus-based approaches to machine translation (MT) are growing in interest, they are not applicable when the translation involves less-resourced language pairs for which there are no parallel corpora available; in those cases, the rule-based approach is the only applicable solution. Most rule-based MT systems make use of part-of-speech (PoS) taggers to solve the PoS ambiguities in the source-language texts to translate; those MT systems require accurate PoS taggers to produce reliable translations in the target language (TL). The standard statistical approach to PoS ambiguity resolution (or tagging) uses hidden Markov models (HMM) trained in a supervised way from hand-tagged corpora, an expensive resource not always available, or in an unsupervised way through the Baum-Welch expectation-maximization algorithm; both methods use information only from the language being tagged. However, when tagging is considered as an intermediate task for the translation procedure, that is, when the PoS tagger is to be embedded as a module within an MT system, information from the TL can be (unsupervisedly) used in the training phase to increase the translation quality of the whole MT system. This paper presents a method to train HMM-based PoS taggers to be used in MT; the new method uses not only information from the source language (SL), as general-purpose methods do, but also information from the TL and from the remaining modules of the MT system in which the PoS tagger is to be embedded. We find that the translation quality of the MT system embedding a PoS tagger trained in an unsupervised manner through this new method is clearly better than that of the same MT system embedding a PoS tagger trained through the Baum-Welch algorithm, and comparable to that obtained by embedding a PoS tagger trained in a supervised way from hand-tagged corpora.     

A novel technique for residence time distribution (RTD) measurements in solids unit operations

This work presents a novel technique with fast response for Residence Time Distribution (RTD) measurements in gas-solid unit operations (e.g., fluidized bed reactors). This technique is based on an optical method which eliminates the requirement of knowing the velocity and concentration profiles at the exit section of the system. Experiments were carried out with SiC particles and a phosphorescent pigment used as a tracer. A concentration measurement system was developed to measure the tracer concentration in SiC/pigment mixtures. The corresponding pigment concentrations were evaluated at the bottom of this system using a photomultiplier. The pigment concentration was derived from the integral of the signal intensity received by the photomultiplier. Then, a calibration curve was established which provided the empirical relationship between the integral and pigment concentration. In order to validate this RTD measurement technique, a series of experiments was performed in a bubbling fluidized bed and the effect of the bed height was studied. It was shown that the experimental RTD curves were in good agreement with the theoretical RTD of bubbling fluidized beds. This solids RTD measurement technique can be used to provide a better understanding of the hydrodynamics of complex solids unit operations.