Field report from sediment coring in peat for landscape analysis in Hjaltadalur, Skagafjörður, north Iceland 2010 : Sediment drilling in Hólar, Vidvik and Kolkuós, Hjaltadalur

This field report presents fieldwork undertaken in Hjaltadalur, Skagafjördur, northern Iceland during summer 2010. The main aim was to initiate coring in selected mires in order to determine the composition of organic material and sediments in the mires, sub-sample for sedimentological and palaeoecological analyses, and initiate advanced landscape analysis of Hjaltadalur. Three mires were selected for sediments coring in Hjaltadalur: Ástunga close to Kolkóus, Hólakot at Viðvik, and Hólar. All three represented a landscape transect in NW to SE direction, from close to the coast to valley interior, i.e. close to the old settlement at Hólar.

A dislocation based theory for the deformation hardening behavior of DP steels : Impact of martensite content and ferrite grain size

A dislocation model, accurately describing the uniaxial plastic stress-strain behavior of dual phase (DP) steels, is proposed and the impact of martensite content and ferrite grain size in four commercially produced DP steels is analyzed. It is assumed that the plastic deformation process is localized to the ferrite. This is taken into account by introducing a non-homogeneity parameter, f(e), that specifies the volume fraction of ferrite taking active part in the plastic deformation process. It is found that the larger the martensite content the smaller the initial volume fraction of active ferrite which yields a higher initial deformation hardening rate. This explains the high energy absorbing capacity of DP steels with high volume fractions of martensite. Further, the effect of ferrite grain size strengthening in DP steels is important. The flow stress grain size sensitivity for DP steels is observed to be 7 times larger than that for single phase ferrite.

Soft computing in biometrics : a pragmatic appraisal

The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.