Application of fuzzy-rule-based postprocessing to correlation methods in pattern recognition

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

Shallow-transfer rule-based machine translation for Czech to Polish

This article describes the developmentof an Open Source shallow-transfer machine translation system from Czech to Polish in theApertium platform. It gives details ofthe methods and resources used in contructingthe system. Although the resulting system has quite a high error rate, it is still competitive with other systems.

Automatic acquisition of Named Entities for Rule-Based Machine Translation

This paper proposes to enrich RBMTdictionaries with Named Entities(NEs) automatically acquired fromWikipedia. The method is appliedto the Apertium English-Spanishsystem and its performance comparedto that of Apertium with and withouthandtagged NEs. The system withautomatic NEs outperforms the onewithout NEs, while results vary whencompared to a system with handtaggedNEs (results are comparable forSpanish to English but slightly worstfor English to Spanish). Apart fromthat, adding automatic NEs contributesto decreasing the amount of unknownterms by more than 10%.

Bootstrapping a statistical speech translator from a rule-based one

We describe a series of experiments in which we start with English to French and English to Japanese versions of an Open Source rule-based speech translation system for a medical domain, and bootstrap correspondign statistical systems. Comparative evaluation reveals that the rule-based systems are still significantly better than the statistical ones, despite the fact that considerable effort has been invested in tuning both the recognition and translation components; also, a hybrid system only marginally improved recall at the cost of a los in precision. The result suggests that rule-based architectures may still be preferable to statistical ones for safety-critical speech translation tasks.

Regression-based techniques for statistical decision making in single-case designs

The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.

Rule-based machine translation between Bulgarian and Macedonian

This paper describes the development of a two-way shallow-transfer rule-based machine translation system between Bulgarian and Macedonian. It gives an account of the resources and the methods used for constructing the system, including the development of monolingual and bilingual dictionaries, syntactic transfer rules and constraint grammars. An evaluation of thesystem's performance was carried out and compared to another commercially available MT system for the two languages. Some future work was suggested.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

An Analysis of black-box optimization problems in reinsurance: evolutionary-based approaches

Black-box optimization problems (BBOP) are de ned as those optimization problems in which the objective function does not have an algebraic expression, but it is the output of a system (usually a computer program). This paper is focussed on BBOPs that arise in the eld of insurance, and more speci cally in reinsurance problems. In this area, the complexity of the models and assumptions considered to de ne the reinsurance rules and conditions produces hard black-box optimization problems, that must be solved in order to obtain the optimal output of the reinsurance. The application of traditional optimization approaches is not possible in BBOP, so new computational paradigms must be applied to solve these problems. In this paper we show the performance of two evolutionary-based techniques (Evolutionary Programming and Particle Swarm Optimization). We provide an analysis in three BBOP in reinsurance, where the evolutionary-based approaches exhibit an excellent behaviour, nding the optimal solution within a fraction of the computational cost used by inspection or enumeration methods.

Caution, children crossing: Heterogeneity of victim's cost of care and negligence rule

The paper deals with a bilateral accident situation in which victims haveheterogeneous costs of care. With perfect information,efficient care bythe injurer raises with the victim's cost. When the injurer cannot observeat all the victim's type, and this fact can be verified by Courts, first-bestcannot be implemented with the use of a negligence rule based on thefirst-best levels of care. Second-best leads the injurer to intermediate care,and the two types of victims to choose the best response to it. This second-bestsolution can be easily implemented by a negligence rule with second-best as duecare. We explore imperfect observation of the victim's type, characterizing theoptimal solution and examining the different legal alternatives when Courts cannotverify the injurers' statements. Counterintuitively, we show that there is nodifference at all between the use by Courts of a rule of complete trust and arule of complete distrust towards the injurers' statements. We then relate thefindings of the model to existing rules and doctrines in Common Law and Civil Lawlegal systems.

The Pelosi-type versus the modified Misgav-Ladach: a randomized trial of two surgical techniques for cesarean section

Cesarean section (CS) is now the most common major surgical procedure performed on women worldwide. A quarter of deliveries in Spain are performed by cesarean section. With the increasing rates of the operation, there is the need to use evidence-based techniques to optimize outcomes and minimize complications. The goal of this study is to employ a well-designed randomized controlled trial to evaluate the intraoperative blood loss of two surgical techniques for cesarean section, the Pelosi-type and the modified Misgav-Ladach. The trial will take place in Hospital Universitari de Girona Dr. Josep Trueta From 2014 to 2015, 512 pregnant women undergoing delivery by their first lower segment cesarean section in this center will be selected through a consecutive nonprobability sampling. We will collect the main obstetrical characteristics, intraoperative outcomes, short-term outcomes for the baby and postoperative outcomes. We will evaluate the intraoperative blood loss by comparing the changes in hemoglobin levels, pre and postoperatively. Patients will be followed during the postoperative period and in a two-week postoperative appointment. We will analyze the continuous variables, such as the differences in hemoglobin levels, using an unpaired two-sided Student’s t-test, while for the categorical variables Fischer’s exact test will be used

Brain dynamics sustaining rapid rule extraction from speech

Language acquisition is a complex process that requires the synergic involvement of different cognitive functions, which include extracting and storing the words of the language and their embedded rules for progressive acquisition of grammatical information. As has been shown in other fields that study learning processes, synchronization mechanisms between neuronal assemblies might have a key role during language learning. In particular, studying these dynamics may help uncover whether different oscillatory patterns sustain more item-based learning of words and rule-based learning from speech input. Therefore, we tracked the modulation of oscillatory neural activity during the initial exposure to an artificial language, which contained embedded rules. We analyzed both spectral power variations, as a measure of local neuronal ensemble synchronization, as well as phase coherence patterns, as an index of the long-range coordination of these local groups of neurons. Synchronized activity in the gamma band (2040 Hz), previously reported to be related to the engagement of selective attention, showed a clear dissociation of local power and phase coherence between distant regions. In this frequency range, local synchrony characterized the subjects who were focused on word identification and was accompanied by increased coherence in the theta band (48 Hz). Only those subjects who were able to learn the embedded rules showed increased gamma band phase coherence between frontal, temporal, and parietal regions.

Development of specific ITS markers for plant DNA identification within herbivorous insects

DNA based techniques have proved to be very useful methods to study trophic relationships 17 between pests and their natural enemies. However, most predators are best defined as omnivores, 18 and the identification of plant-specific DNA should also allow the identification of the plant 19 species the predators have been feeding on. In this study, a PCR approach based on the 20 development of specific primers was developed as a self-marking technique to detect plant DNA 21 within the gut of one heteropteran omnivorous predator (Macrolophus pygmaeus) and two 22 lepidopteran pest species (Helicoverpa armigera and Tuta absoluta). Specific tomato primers 23 were designed from the ITS 1-2 region, which allowed the amplification of a tomato DNA 24 fragment of 332 bp within the three insect species tested in all cases (100% of detection at t = 0) 25 and did not detect DNA of other plants nor of the starved insects. Plant DNA half-lives at 25ºC 26 ranged from 5.8h, to 27.7h and 28.7h within M. pygmaeus, H. armigera and T. absoluta, 27 respectively. Tomato DNA detection within field collected M. pygmaeus suggests dietary mixing 28 in this omnivorous predator and showed a higher detection of tomato DNA in females and 29 nymphs than males. This study provides a useful tool to detect and to identify plant food sources 30 of arthropods and to evaluate crop colonization from surrounding vegetation in conservation 31 biological control programs.

Mejorando la robustez de aplicaciones frente a fallos transitorios

Computer chips implementation technologies evolving to obtain more performance are increasing the probability of transient faults. As this probability grows and on-chip solutions are expensive or tend to degrade processor performance, the efforts to deal with these transient faults in higher levels (such as the operating system or even at the application level) are increasing. Mostly, these efforts are trying to avoid silent data corruptions using hardware, software and hybrid based techniques to add redundancy to detect the errors generated by the transient faults. This work presents our proposal to improve the robustness of applications with source code based transformation adding redundancy. Also, our proposal takes account of the tradeoff between the improved robustness and the overhead generated by the added redundancy.

Xat Segur

En aquest treball de final de carrera es procura resoldre el problema de la seguretat informàtica en les comunicacions entre dues entitats per a poder protegir la informació sensible quan viatgi per la xarxa. Per fer-ho, s?utilitzen una sèrie de tècniques basades en la criptografia.