Abstract
A high-birefringent fiber (HBF) was tapered as adiabatic in sequence steps by utilizing a CO2 laser and its birefringence was measured in fiber loop mirror (FLM) setup. The birefringence of tapered section and total sensor was obtained to be -8.02x10(-2), and 2.46x10(-4), respectively. Then, refractive index (RI) sensitivity increased and temperature sensitivity of the tapered Hi-Bi fiber (THBF) decreased. The sensitivity of the proposed FLM interferometer for RI changes in the range from 1.3380 to 1.3470 was measured to be 389.85 nm/RIU. The temperature sensitivity in the range from 50 degrees C to 90 degrees C was measured to be -1.19nm/degrees C.

Abstract

Abstract
Transcriptional regulation play an important role in every cellular decision. Gaining an understanding of the dynamics that govern how a cell will respond to diverse environmental cues is difficult using intuition alone. We introduce logic-based regulation models based on state-of-the-art work on statistical relational learning, to show that network hypotheses can be generated from existing gene expression data for use by experimental biologists.

Abstract
When users have to choose a learning algorithm to induce a model for a given dataset, a common practice is to select an algorithm whose bias suits the data distribution. In real-world applications that produce data continuously this distribution may change over time. Thus, a learning algorithm with the adequate bias for a dataset may become unsuitable for new data following a different distribution. In this paper we present a meta-learning approach for periodic algorithm selection when data distribution may change over time. This approach exploits the knowledge obtained from the induction of models for different data chunks to improve the general predictive performance. It periodically applies a meta-classifier to predict the most appropriate learning algorithm for new unlabeled data. Characteristics extracted from past and incoming data, together with the predictive performance from different models, constitute the meta-data, which is used to induce this meta-classifier. Experimental results using data of a travel time prediction problem show its ability to improve the general performance of the learning system. The proposed approach can be applied to other time-changing tasks, since it is domain independent. © 2012 IEEE.

Abstract
In this work, fiber in-line Mach-Zehnder Interferometer (MZI) based on triangular-shape suspended core fibers (SCFs) is investigated. The sensitivity of the sensing head was determined for pressure and temperature, respectively. The sensitivities are 0.4 pm/psi and 13 pm/psi for longitudinal and radial pressure, respectively. The sensing head was also subjected to temperature and presented very low sensitivity.

Abstract
In this paper, an adaptive and low-cost robotic coating platform for small production series is presented. This new platform presents a flexible architecture that enables fast/automatic system adaptive behaviour without human intervention. The concept is based on contactless technology, using artificial vision and laser scanning to identify and characterize different workpieces travelling on a conveyor. Using laser triangulation, the workpieces are virtually reconstructed through a simplified cloud of three-dimensional (3D) points. From those reconstructed models, several algorithms are implemented to extract information about workpieces profile (pattern recognition), size, boundary and pose. Such information is then used to on-line adjust the "base" robot programmes. These robot programmes are off-line generated from a 3D computer-aided design model of each different workpiece profile. Finally, the robotic manipulator executes the coating process after its "base" programmes have been adjusted. This is a low-cost and fully autonomous system that allows adapting the robot's behaviour to different manufacturing situations. It means that the robot is ready to work over any piece at any time, and thus, small production series can be reduced to as much as a one-object series. No skilled workers and large setup times are needed to operate it. Experimental results showed that this solution proved to be efficient and can be applied not only for spray coating purposes but also for many other industrial processes (automatic manipulation, pick-and-place, inspection, etc.).