Abstract

Abstract
In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction.

Abstract
This paper proposes a method to detect a reference frame in an ultrasound video of the carotid artery. This reference frame, usually located at the end of the diastole, is used as the location to measure several vascular biomarkers. Our approach is based on the analysis of the movement of the carotid walls in ultrasound images using an optical flow technique. A periodic movement resembling heart beat is observed in the resulting signals. The comparison of these signals with electrocardiograms validates the proposed method for detecting the reference frame.

Abstract
The viStaMPS software is a collaborative scientific project that was created with three major purposes: (1) facilitate the usage by users non familiar with the specificities of the programming language that supports StaMPS; (2) implement several visualization tasks not available in the StaMPS standard approach (avoiding that each user develop its own code for visualization and interpretation purposes) and (3) create a collaborative research project, continuously under development counting on the dynamism of its users to improve and/or add new features.

Abstract
User modelling has become a central subject for anybody interested in understanding how users interact with technology. Personalization is a key issue in an era when there is so much information and so many people interacting in so many ways. Modern users desire a customized experience that adapts itself to their requirements and understands what they need even before they notice it. In order to morph any system into an adapting one, every relevant interaction with its users has to be maintained. Then, a mathematical structure capable of discovering patterns amongst that information is necessary, being able to classify users according to the roles they play. With a correct user categorization, the system knows when, how and what to do to adapt its content, via a mixed-initiative approach. In this paper, an artificial neural network is selected as classifier and users are divided in three roles, from beginners to experts. ADSyS, the target system of this proposal, adapts its content based on who is operating it, providing a higher usability. This guide on how to adapt a system to its users is built as part of ADSyS, but is intended to be generalized as a foundation to other systems. © 2015 AISTI.

Abstract
In this present work we report fabrication of fiber optic liquid refractive index (RI) measurement sensor based on Michelson Interferometer method. This sensor was assembled by using graded index multimode (MM) fiber with core diameter 50 µm and the cladding of fiber was removed by simple chemical method. To perform this experiment a 2×2 3dB coupler is used. The fiber ends are then immersed in solvent and solution to provide reference and refractive index measurements, respectively. This method was successfully used to measure refractive index of Sodium Chloride (NaCl)-Water solution at different concentrations. The fringe contrast sensitivity of device is 92.90 dB/RIU measured in the RI range from 1.34 to 1.42 which is better than Mach-Zehnder Interferometer sensor [1] and Fabry perot based sensor [2]. The fabrication of sensor is simple, low cost and highly sensitive. © 2015 AIP Publishing LLC.