Spontaneous Speech and Emotional Response modeling based on One-class classifier oriented to Alzheimer Disease diagnosis

The purpose of our project is to contribute to earlier diagnosis of AD and better estimates of its severity by using automatic analysis performed through new biomarkers extracted from non-invasive intelligent methods. The methods selected in this case are speech biomarkers oriented to Sponta-neous Speech and Emotional Response Analysis. Thus the main goal of the present work is feature search in Spontaneous Speech oriented to pre-clinical evaluation for the definition of test for AD diagnosis by One-class classifier. One-class classifi-cation problem differs from multi-class classifier in one essen-tial aspect. In one-class classification it is assumed that only information of one of the classes, the target class, is available. In this work we explore the problem of imbalanced datasets that is particularly crucial in applications where the goal is to maximize recognition of the minority class as in medical diag-nosis. The use of information about outlier and Fractal Dimen-sion features improves the system performance.

A time-domain method for the analysis of thermal impedance response preserving the convolution form

The study of the thermal behavior of complex packages as multichip modules (MCM¿s) is usually carried out by measuring the so-called thermal impedance response, that is: the transient temperature after a power step. From the analysis of this signal, the thermal frequency response can be estimated, and consequently, compact thermal models may be extracted. We present a method to obtain an estimate of the time constant distribution underlying the observed transient. The method is based on an iterative deconvolution that produces an approximation to the time constant spectrum while preserving a convenient convolution form. This method is applied to the obtained thermal response of a microstructure as analyzed by finite element method as well as to the measured thermal response of a transistor array integrated circuit (IC) in a SMD package.

An instrumental analysis of the European Union's capability to act in conflict response

Descripció i anàlisi dels instruments polítics, econòmics, civils i militars de la Unió Europea per enfrontar qualsevol conflicte.

An Instrumental analysis of the European Union´s capability to act in conflict response

Since its origins, the European Union has striven to be an actor on the International scene and a place in conflict Management. Yet the EU’s lack of activity cannot be justified by a mere lack of capacities. The EU counts with numerous political, economic, and, since 2003, civil and military instruments that should allow it to precede a comprehensive conflict response. This publication consists of a description of these instruments and an analysis of the final use that the Union makes of them in the different stages of a conflict. Examples will show us the EU’s main weakness in providing a comprehensive and timely response when a conflict breaks out.

Multiple correspondence analysis of a subset of response categories

In the analysis of multivariate categorical data, typically the analysis of questionnaire data, it is often advantageous, for substantive and technical reasons, to analyse a subset of response categories. In multiple correspondence analysis, where each category is coded as a column of an indicator matrix or row and column of Burt matrix, it is not correct to simply analyse the corresponding submatrix of data, since the whole geometric structure is different for the submatrix . A simple modification of the correspondence analysis algorithm allows the overall geometric structure of the complete data set to be retained while calculating the solution for the selected subset of points. This strategy is useful for analysing patterns of response amongst any subset of categories and relating these patterns to demographic factors, especially for studying patterns of particular responses such as missing and neutral responses. The methodology is illustrated using data from the International Social Survey Program on Family and Changing Gender Roles in 1994.

Subset correspondence analysis: Visualizing relationships among a selected set of response categories from a questionnaire survey

It is shown how correspondence analysis may be applied to a subset of response categories from a questionnaire survey, for example the subset of undecided responses or the subset of responses for a particular category. The idea is to maintain the original relative frequencies of the categories and not re-express them relative to totals within the subset, as would normally be done in a regular correspondence analysis of the subset. Furthermore, the masses and chi-square metric assigned to the data subset are the same as those in the correspondence analysis of the whole data set. This variant of the method, called Subset Correspondence Analysis, is illustrated on data from the ISSP survey on Family and Changing Gender Roles.

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.

Performance analysis and tuning in multicore environments

Performance analysis is the task of monitor the behavior of a program execution. The main goal is to find out the possible adjustments that might be done in order improve the performance. To be able to get that improvement it is necessary to find the different causes of overhead. Nowadays we are already in the multicore era, but there is a gap between the level of development of the two main divisions of multicore technology (hardware and software). When we talk about multicore we are also speaking of shared memory systems, on this master thesis we talk about the issues involved on the performance analysis and tuning of applications running specifically in a shared Memory system. We move one step ahead to take the performance analysis to another level by analyzing the applications structure and patterns. We also present some tools specifically addressed to the performance analysis of OpenMP multithread application. At the end we present the results of some experiments performed with a set of OpenMP scientific application.

The Role of model uncertainty and learning in the U.S. postwar policy response to oil prices

This paper studies optimal monetary policy in a framework that explicitly accounts for policymakers' uncertainty about the channels of transmission of oil prices into the economy. More specfically, I examine the robust response to the real price of oil that US monetary authorities would have been recommended to implement in the period 1970 2009; had they used the approach proposed by Cogley and Sargent (2005b) to incorporate model uncertainty and learning into policy decisions. In this context, I investigate the extent to which regulator' changing beliefs over different models of the economy play a role in the policy selection process. The main conclusion of this work is that, in the specific environment under analysis, one of the underlying models dominates the optimal interest rate response to oil prices. This result persists even when alternative assumptions on the model's priors change the pattern of the relative posterior probabilities, and can thus be attributed to the presence of model uncertainty itself.

Party competition in regional elections: a framework for analysis

Whilst scholars have long recognised that processes of decentralisation create new regional arenas where distinct patterns of party competition are likely to emerge, there has been little systematic analysis of the dynamics of such competition. This working paper thus proposes a framework for analysing party competition between regional branches of state-wide parties, and autonomist parties, in regional arenas. Firstly, the different strategies political parties may adopt in response to their perceptions of voter preferences and to the strategies pursued by their competitors are identified. Secondly, different factors that impact on parties' strategic choices, and which may constrain a party's ability to select electorally optimal strategies in a given political context, are proposed.

Toxic phytoplankton response to warming in two Mediterranean bays of the Ebro Delta

The analysis of the phytoplankton and environmental parameters of the time series in Alfacs and Fangar bays (north western Mediterranean) from 1990 to 2009 shows some trends. There is an increase in the average water column temperature, 0.11, 0.01, 0.80 and 0.23 ºC for spring, summer, fall and winter respectively in Alfacs Bay and 1.76, 0.71, 1.33, 0.89 ºC for spring, summer, fall and winter in Fangar Bay. The trends in phytoplankton populations show a shift in the timing of occurrence of Karlodinium spp. blooms and an increase of the Pseudo-nitzschia spp. abundances. There is a lack of correlation between the average seasonal temperatures and the toxic phytoplankton abundances.

Proyecto para la identificación de necesidades formativas y posterior implementación de acción docente en el ERIE Psicosocial de C.R.N.

La responsabilidad del ERIE Psicosocial a la hora de realizar su labor en el marco de la intervención en emergencias debe ir necesariamente acompañada de una correcta identificación de las necesidades que el equipo tiene en lo que respecta a su formación e instrucción, de cara a mantener el nivel de respuesta en su labor. El desarrollo de herramientas y métodos capaces de definir estas variables es, pues el primer paso de este proceso. El formato de desarrollo posterior de esas acciones formativas, teniendo en cuenta el carácter grupal y cooperativo del grupo, debe ser estudiado y validado para obtener la máxima eficacia durante su materialización.

The agreement between ipsative and normative questionnaires using compositional data analysis techniques

The main instrument used in psychological measurement is the self-report questionnaire. One of its majordrawbacks however is its susceptibility to response biases. A known strategy to control these biases hasbeen the use of so-called ipsative items. Ipsative items are items that require the respondent to makebetween-scale comparisons within each item. The selected option determines to which scale the weight ofthe answer is attributed. Consequently in questionnaires only consisting of ipsative items everyrespondent is allotted an equal amount, i.e. the total score, that each can distribute differently over thescales. Therefore this type of response format yields data that can be considered compositional from itsinception.Methodological oriented psychologists have heavily criticized this type of item format, since the resultingdata is also marked by the associated unfavourable statistical properties. Nevertheless, clinicians havekept using these questionnaires to their satisfaction. This investigation therefore aims to evaluate bothpositions and addresses the similarities and differences between the two data collection methods. Theultimate objective is to formulate a guideline when to use which type of item format.The comparison is based on data obtained with both an ipsative and normative version of threepsychological questionnaires, which were administered to 502 first-year students in psychology accordingto a balanced within-subjects design. Previous research only compared the direct ipsative scale scoreswith the derived ipsative scale scores. The use of compositional data analysis techniques also enables oneto compare derived normative score ratios with direct normative score ratios. The addition of the secondcomparison not only offers the advantage of a better-balanced research strategy. In principle it also allowsfor parametric testing in the evaluation

Economic structure and key sectors analysis of greenhouse gas emissions in Uruguay

This paper identifies the key sectors in greenhouse gas emissions of the Uruguayan economy through input-output analysis. This allows to precisely determine the role played by the different productive sectors and their relationship with other sectors in the relation between the Uruguayan productive structure and atmospheric pollution. In order to guide policy design for GHG reduction, we decompose sectors liability between the pollution generated through their own production processes and the pollution indirectly generated in the production processes of other sectors. The results show that all the key polluting sectors for the different contaminants considered are relevant because of their own emissions, except for the sector Motor vehicles and oil retail trade, which is relevant in CO2 emissions because of its pure, both backward and forward, linkages. Finally, the best policy channels for controlling and reducing GHGs emissions are identified, and compared with the National Climate Change Response Plan (NCCRP) lines of action.

Diversity of the bacterial community in the surface soil of a pear orchard based on 16S rRNA gene analysis

A cultivation-independent approach based on polymerase chain reaction (PCR)-amplified partial small subunit rRNA genes was used to characterize bacterial populations in the surface soil of a commercial pear orchard consisting of different pear cultivars during two consecutive growing seasons. Pyrus communis L. cvs Blanquilla, Conference, and Williams are among the most widely cultivated cultivars in Europe and account for the majority of pear production in Northeastern Spain. To assess the heterogeneity of the community structure in response to environmental variables and tree phenology, bacterial populations were examined using PCR-denaturing gradient gel electrophoresis (DGGE) followed by cluster analysis of the 16S ribosomal DNA profiles by means of the unweighted pair group method with arithmetic means. Similarity analysis of the band patterns failed to identify characteristic fingerprints associated with the pear cultivars. Both environmentally and biologically based principal-component analyses showed that the microbial communities changed significantly throughout the year depending on temperature and, to a lesser extent, on tree phenology and rainfall. Prominent DGGE bands were excised and sequenced to gain insight into the identities of the predominant bacterial populations. Most DGGE band sequences were related to bacterial phyla, such as Bacteroidetes, Cyanobacteria, Acidobacteria, Proteobacteria, Nitrospirae, and Gemmatimonadetes, previously associated with typical agronomic crop environments