Study of helical induced anisotropy in amorphous ribbons for sensor applications

Amorphous samples with helical induced anisotropy show magnetization processes that can be controlled by applying a longitudinal magnetic field simultaneously with an alternating current flowing through the sample. By varying the current amplitude and the phase difference between current and applied field, a wide range of coercivity and susceptibility values can be achieved. This work shows that the apparent coercive field and the susceptibility can be controlled in amorphous ribbons with helical anisotropy. These characteristics make these samples very suitable for their application as sensor cores, magnetic amplifiers, variable reluctance transformer cores, etc

Generating Automated News to Explain the Meaning of Sensor Data

An important competence of human data analysts is to interpret and explain the meaning of the results of data analysis to end-users. However, existing automatic solutions for intelligent data analysis provide limited help to interpret and communicate information to non-expert users. In this paper we present a general approach to generating explanatory descriptions about the meaning of quantitative sensor data. We propose a type of web application: a virtual newspaper with automatically generated news stories that describe the meaning of sensor data. This solution integrates a variety of techniques from intelligent data analysis into a web-based multimedia presentation system. We validated our approach in a real world problem and demonstrate its generality using data sets from several domains. Our experience shows that this solution can facilitate the use of sensor data by general users and, therefore, can increase the utility of sensor network infrastructures.