A bacterial colony growth algorithm for mobile robot localization

Achieving robot autonomy is a fundamental objective in Mobile Robotics. However in order to realize this goal, a robot must be aware of its location within an environment. Therefore, the localization problem (i.e.,the problem of determining robot pose relative to a map of its environment) must be addressed. This paper proposes a new biology-inspired approach to this problem. It takes advantage of models of species reproduction to provide a suitable framework for maintaining the multi-hypothesis. In addition, various strategies to track robot pose are proposed and investigated through statistical comparisons. The Bacterial Colony Growth Algorithm (BCGA) provides two different levels of modeling: a background level that carries on the multi-hypothesis and a foreground level that identifies the best hypotheses according to an exchangeable strategy. Experiments, carried out on the robot ATRV-Jr manufactured by iRobot, show the effectiveness of the proposed BCGA.

A covert attention P300-based brain-computer interface: Geospell

The Farwell and Donchin P300 speller interface is one of the most widely used brain-computer interface (BCI) paradigms for writing text. Recent studies have shown that the recognition accuracy of the P300 speller decreases significantly when eye movement is impaired. This report introduces the GeoSpell interface (Geometric Speller), which implements a stimulation framework for a P300-based BCI that has been optimised for operation in covert visual attention. We compared the Geospell with the P300 speller interface under overt attention conditions with regard to effectiveness, efficiency and user satisfaction. Ten healthy subjects participated in the study. The performance of the GeoSpell interface in covert attention was comparable with that of the P300 speller in overt attention. As expected, the effectiveness of the spelling decreased with the new interface in covert attention. The NASA task load index (TLX) for workload assessment did not differ significantly between the two modalities. PRACTITIONER SUMMARY: This study introduces and evaluates a gaze-independent, P300-based brain-computer interface, the efficacy and user satisfaction of which were comparable with those off the classical P300 speller. Despite a decrease in effectiveness due to the use of covert attention, the performance of the GeoSpell far exceeded the threshold of accuracy with regard to effective spelling.     

Diffusive Behavior of Bedform-Induced Hyporheic Exchange in Rivers

Solute transport in natural streams is a complex phenomenon that involves both in-stream dispersion and mass exchange with the porous zones surrounding the water body. Due to the complex nature of the riverine systems several models may be used to simulate and analyze the transport of solutes with different degrees of complexity. The bedform-induced hyporheic transport is a stream-subsurface exchange mechanism that can be reproduced in controlled systems, such as laboratory flumes. Application of a simple Fickian diffusion model to laboratory data obtained with passive solutes and stationary bedforms proves successful within a range of durations of the contamination process. A dimensionless form of the diffusion coefficient, scaled with dynamic, physical, and geometric properties of the system is derived by comparison with another physically based model. A prediction of the dimensionless diffusion coefficient is obtained as a function of the timescale of the exchange process and is validated with a few sets of results from laboratory tests.     

The use of EEG modifications due to motor imagery for brain-computer interfaces

The opening of a communication channel between brain and computer [brain-computer interface (BCI)] is possible by using changes in electroencephalogram (EEG) power spectra related to the imagination of movements. In this paper, we present results obtained by recording EEG during an upper limb motor imagery task in a total of 18 subjects by using low-resolution surface Laplacian, different linear and quadratic classifiers, as well as a variable number of scalp electrodes, from 2 to 26. The results (variable correct classification rate of mental imagery between 75% and 95%) suggest that it is possible to recognize quite reliably ongoing mental movement imagery for BCI applications.     

Compact InP-based HBT VCOs with a wide tuning range at W- andD-band

Compact monolithic integrated differential voltage-controlled oscillators (VCOs) operating in W-band were realized using InP-based heterojunction bipolar transistors (HBTs). The oscillators, with a total chip size of 0.6 by 0.35 mm², are based on a balanced Colpitts-type topology with a coplanar transmission-line resonator. By varying the voltage across the base-collector junction of the HBT in the current mirror and by changing the current in the VCO, the oscillation frequency can be tuned between 84 and 106 GHz. At 100 GHz, a differential voltage swing of 400 mV is obtained, which should be sufficient to drive 100 Gb/s digital logic. By combining the balanced outputs of a similar differential VCO in a push-push configuration, a compact source with close to -10 dBm output power and a tuning range between 138 and 150 GHz is obtained     

Gene regulatory networks reconstruction from time series datasets using genetic programming: a comparison between tree-based and graph-based approaches

Genetic programming researchers have shown a growing interest in the study of gene regulatory networks in the last few years. Our team has also contributed to the field, by defining two systems for the automatic reverse engineering of gene regulatory networks called GRNGen and GeNet. In this paper, we revise this work by describing in detail the two approaches and empirically comparing them. The results we report, and in particular the fact that GeNet can be used on large networks while GRNGen cannot, encourage us to pursue the study of GeNet in the future. We conclude the paper by discussing the main research directions that we are planning to investigate to improve GeNet.     

A variational integrators approach to second order modeling and identification of linear mechanical systems

The theory of variational integration provides a systematic procedure to discretize the equations of motion of a mechanical system, preserving key properties of the continuous time flow. The discrete-time model obtained by variational integration theory inherits structural conditions which in general are not guaranteed under general discretization procedures. We discuss a simple class of variational integrators for linear second order mechanical systems and propose a constrained identification technique which employs simple linear transformation formulas to recover the continuous time parameters of the system from the discrete-time identified model. We test this approach on a simulated eight degrees of freedom system and show that the new procedure leads to an accurate identification of the continuous-time parameters of second-order mechanical systems starting from discrete measured data.     

DNA barcoding as a new tool for food traceability

Food safety and quality are nowadays a major concern. Any case of food alteration, especially when reported by the media, has a great impact on public opinion. There is an increasing demand for the improvement of quality controls, hence addressing scientific research towards the development of reliable molecular tools for food analysis. DNA barcoding is a widely used molecular-based system, which can identify biological specimens, and is used for the identification of both raw materials and processed food. In this review the results of several researches are critically analyzed, in order to exploit the effectiveness of DNA barcoding in food traceability, and to delineate some best practices in the application of DNA barcoding throughout the industrial pipeline. The use of DNA barcoding for food safety and in the identification of commercial fraud is also discussed.