Choice by sequential procedures

We propose a rule of decision-making, the sequential procedure guided byroutes, and show that three influential boundedly rational choice models can be equivalentlyunderstood as special cases of this rule. In addition, the sequential procedure guidedby routes is instrumental in showing that the three models are intimately related. We showthat choice with a status-quo bias is a refinement of rationalizability by game trees, which, inturn, is also a refinement of sequential rationalizability. Thus, we provide a sharp taxonomyof these choice models, and show that they all can be understood as choice by sequentialprocedures.

Information acquisition and entry

Before firms decide whether to enter a new market or not, they havethe opportunity to buy information about several variables that might affectthe profitability of this market. Our model differs from the existing literatureon endogenous information acquisition in two respects: (1) there is uncertaintyabout more than one variable, and (2) information is acquired secretly. Whenthe cost of acquiring information is small, entry decisions will be as ifthere was perfect information. Equilibria where each firm acquires only asmall amount of information are more robust than the socially undesirableequilibria where all firms gather all information. Examples illustrate theimportance of assumptions (1) and (2).

Secret information acquisition in Cournot markets

Two-stage game models of information acquisition in stochastic oligopoliesrequire the unrealistic assumption that firms observe the precision ofinformation chosen by their competitors before determining quantities. Thispaper analyzes secret information acquisition as a one-stage game. Relativeto the two-stage game firms are shown to acquire less information. Policyimplications based on the two-stage game yield, therefore, too high taxes ortoo low subsidies for research activities. For the case of heterogeneousduopoly it is shown that comparative statics results partly depend on theobservability assumption.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

External technology sources: Embodied or disembodied technology acquisition

This paper analyzes the choice between different innovationactivities of a firm. In particular, we study the technologyacquisition decision of the firm, i.e. its technology BUYdecision as part of the firm's innovation strategy. We take a closer look at the different types of external technologyacquisition where we distinguish two broad types of technologybuy decisions. On the one hand, the firm can acquire new technology which is embodied in an asset that is acquired suchas new personnel or (parts of) other firms or equipment. On the other hand, the firm can obtain new technology disembodiedthrough a licensing agreement or by outsourcing the technologydevelopment from an R&D contractor or consulting agency. Through a series of Probit regressions, we discuss variables that might affect external technology acquisition choices of the firm andpay special attention to the firm's abilities to scan the market for technology and to absorb the technology acquired. Furthermore, we analyze the effect of different appropriationregimes on the decision of the firm to source technology.

Comparing and validating hypothesis test procedures: Graphical and numerical tools

When the behaviour of a specific hypothesis test statistic is studied by aMonte Carlo experiment, the usual way to describe its quality is by givingthe empirical level of the test. As an alternative to this procedure, we usethe empirical distribution of the obtained \emph{p-}values and exploit itsinformation both graphically and numerically.

Transferencia en la adquisición de segundas lenguas. Un estudio con alumnado rumano en un contexto bilingüe = Transfer in second language acquisition. A study with Romanian schoolchildren in a bilingual context

Situados en el contexto catalán, el artículo estudia la influencia de la L1 (rumano) en algunos aspectos morfosintácticos de la adquisición de las L2s. Para ello se analizan las competencias lingüísticas en catalán y castellano de un grupo de escolares cuya L1 es el rumano y que cursan 2.º y 4.º de ESO. Los datos muestran que los alumnos cuya L1 es el rumano, a pesar de dominar una lengua románica cercana a las lenguas de aprendizaje (L2/L3), presentan dificultades comparables a otros colectivos con otras lenguasde origen. Por otra parte, nuestra investigación confirma que la L1 de este alumnado juega un importante papel en la adquisición de ambas lenguas, concluyendo que parte de los errores hallados son aquellos que se basan en estructuras de la lengua propia

Spanish unemployment : normative versus analytical regionalisation procedures

In applied regional analysis, statistical information is usually published at different territorial levels with the aim providing inforamtion of interest for different potential users. When using this information, there are two different choices: first, to use normative regions ( towns, provinces, etc.) or, second, to design analytical regions directly related with the analysed phenomena. In this paper, privincial time series of unemployment rates in Spain are used in order to compare the results obtained by applying yoy analytical regionalisation models ( a two stages procedure based on cluster analysis and a procedure based on mathematical programming) with the normative regions available at two different scales: NUTS II and NUTS I. The results have shown that more homogeneous regions were designed when applying both analytical regionalisation tools. Two other obtained interesting results are related with the fact that analytical regions were also more estable along time and with the effects of scales in the regionalisation process

Spanish unemployment : normative versus analytical regionalisation procedures

In applied regional analysis, statistical information is usually published at different territorial levels with the aim providing inforamtion of interest for different potential users. When using this information, there are two different choices: first, to use normative regions ( towns, provinces, etc.) or, second, to design analytical regions directly related with the analysed phenomena. In this paper, privincial time series of unemployment rates in Spain are used in order to compare the results obtained by applying yoy analytical regionalisation models ( a two stages procedure based on cluster analysis and a procedure based on mathematical programming) with the normative regions available at two different scales: NUTS II and NUTS I. The results have shown that more homogeneous regions were designed when applying both analytical regionalisation tools. Two other obtained interesting results are related with the fact that analytical regions were also more estable along time and with the effects of scales in the regionalisation process

Language Resources Factory: case study on the acquisition of Translation Memories

This paper demonstrates a novel distributed architecture to facilitate the acquisition of Language Resources. We build a factory that automates the stages involved in the acquisition, production, updating and maintenance of these resources. The factory is designed as a platform where functionalities are deployed as web services, which can be combined in complex acquisition chains using workflows. We show a case study, which acquires a Translation Memory for a given pair of languages and a domain using web services for crawling, sentence alignment and conversion to TMX.

Versatile iPad forensic acquisition using the Apple Camera Connection Kit

Peer reviewed

Threading libraries performance when applied to image acquisition and processing in a forensic application

Peer-reviewed

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%.

Waveform-independent frame-timing acquisition for UWB signals

In this paper, the problem of frame-level symboltiming acquisition for UWB signals is addressed. The main goalis the derivation of a frame-level timing estimator which does notrequire any prior knowledge of neither the transmitted symbolsnor the received template waveform. The independence withrespect to the received waveform is of special interest in UWBcommunication systems, where a fast and accurate estimation ofthe end-to-end channel response is a challenging and computationallydemanding task. The proposed estimator is derived under theunconditional maximum likelihood criterion, and because of thelow power of UWB signals, the low-SNR assumption is adopted. Asa result, an optimal frame-level timing estimator is derived whichoutperforms existing acquisition methods in low-SNR scenarios.