On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Plasticidad postlesional en el sistema visual : estrategias experimentales para su incremento en el adulto

196 p. :il.

Image-based delineation and classification of built heritage masonry

[EN]Fundación Zain is developing new built heritage assessment protocols. The goal is to objectivize and standardize the analysis and decision process that leads to determining the degree of protection of built heritage in the Basque Country. The ultimate step in this objectivization and standardization effort will be the development of an information and communication technology (ICT) tool for the assessment of built heritage. This paper presents the ground work carried out to make this tool possible: the automatic, image-based delineation of stone masonry. This is a necessary first step in the development of the tool, as the built heritage that will be assessed consists of stone masonry construction, and many of the features analyzed can be characterized according to the geometry and arrangement of the stones. Much of the assessment is carried out through visual inspection. Thus, this process will be automated by applying image processing on digital images of the elements under inspection. The principal contribution of this paper is the automatic delineation the framework proposed. The other contribution is the performance evaluation of this delineation as the input to a classifier for a geometrically characterized feature of a built heritage object. The element chosen to perform this evaluation is the stone arrangement of masonry walls. The validity of the proposed framework is assessed on real images of masonry walls.

Skeleton based visual pattern recognition. Applications to tabletop interaction

211 p. :il.

A study of the length at maturity and hooks/gill net mesh selection in Clarias lazera from Lake Chad

The minimum length at first maturity of Clarias lazera was found to be 24 cm (4.8%) for females and 20 cm (1.8%) for males. Fifty percent maturity was attained at length of 28 cm to 30 cm for both sexes; there being little difference among the sexes at this level of maturity. The modal retention lengths for gill nets were: 13 cm for 25.5 mm mesh; 18 cm for 32 mm mesh; 28 cm for 57 mm mesh; and 38 cm for 76 mm mesh. Modal lengths of Clarias lazera caught by various hooks sizes were No. 10 (28 cm); No. 11 (33 cm); Nos. 15 and 16 (28 cm). It is recommended that to protect the clarias fishery in Lake Chad, the use of gill nets of less than 57 mm mesh size and fishing hook No. 16 (and smaller sizes) which caught 43.94% of immature fishes should be discouraged

El árbol del arte. Matriz trans-sensorial e intersubjetiva para el arte no visual y el silencio del yo artístico

461 p. : il., col.