Learning locomotion reflexes: A self-supervised neural system for a mobile robot

This article is concerned with an artificial neural system for a mobile robot reactive navigation in an unknown, cluttered environment. Reactive navigation is a process of immediately choosing locomotion actions in response to measured spatial situations, while no planning occurs. A task of a presented system is to provide a steering angle signal letting a robot reach a goal while avoiding collisions with obstacles. Basic reactive navigation methods are briefly characterized, special attention is paid to a neural approach to the considered problem. The authors describe the system's architecture and important details of the algorithm. The main parts of the system are: the Fuzzy ART neural self-organizing classifier, performing a perceptual space partitioning, and a neural associative memory, memorizing the system's experience and superposing influences of different behaviors. Tests show that the learning process, starting from zero, is efficient, despite some initial fluctuations of its effectiveness.     

A Closed-Loop Automatic Data-Mining Approach for Preventive Network Monitoring

As telecommunication networks grow in size and complexity, monitoring systems need to scale up accordingly. Alarm data generated in a large network are often highly correlated. These correlations can be explored to simplify the process of network fault management, by reducing the number of alarms presented to the network-monitoring operator. This makes it easier to react to network failures. But in some scenarios, it is highly desired to prevent the occurrence of these failures by predicting the occurrence of alarms before hand. This work investigates the usage of data mining methods to generate knowledge from historical alarm data, and using such knowledge to train a machine learning system, in order to predict the occurrence of the most relevant alarms in the network. The learning system was designed to be retrained periodically in order to keep an updated knowledge base.     

High quality TbMnO3 films deposited on YAlO3

High quality thin films of TbMnO₃ were grown by pulsed laser deposition on orthorhombicYAlO₃ (1 0 0). The interface and surface roughness of a 55 nm thick film were probed by X-ray reflectometry and atomic force microscopy, yielding a roughness of 1 nm. X-ray diffraction revealed untwinned films and a small mosaic spread of 0.04° and 0.2° for out-of-plane and in-plane reflections, respectively. This high degree of epitaxy was also confirmed by Rutherford backscattering spectrometry. Using polarized neutron diffraction we could identify a magnetic structure with the propagation vector (0 0.27 0), identical to the bulk magnetic structure of TbMnO₃.     

The effect of selected parameters of formation on properties of alginate/Ca2+/oligochitosan capsules

Optimization of the technological parameters affecting the mechanical properties and permeability of capsules is essential to produce capsules with improved properties for cell immobilization. In the present paper, the effect of different parameters on the technological properties of alginate/Ca²⁺/oligochitosan capsules has been investigated. The correct adjustment of the alginate concentration in the polymer matrix and the oligochitosan molar mass, concentration and coating time, have been found to be key parameters in obtaining porous and mechanically stable alginate/Ca²⁺/oligochitosan capsules. Results showed that an increase in the coating time and concentration of the alginate generated more stable capsules with a reduced membrane cut‐off. Furthermore, we have established some correlations between capsule properties and the effectiveness of chitosan binding within the capsule's membrane. Data addressed herein could be a valid tool to fabricate optimized alginate/Ca²⁺/oligochitosan capsules with a potential for use in cell immobilization technology. Copyright © 2006 Society of Chemical Industry     

Revealing the Role of Anchoring Groups in the Electrical Conduction Through Single‐Molecule Junctions

A combined experimental and theoretical study is presented revealing the influence of metal–molecule coupling on electronic transport through single‐molecule junctions. Transport experiments through tolane molecules attached to gold electrodes via thiol, nitro, and cyano anchoring groups are performed. By fitting the experimental current–voltage characteristics to a single‐level tunneling model, we extract both the position of the molecular orbital closest to the Fermi energy and the strength of the metal–molecule coupling. The values found for these parameters are rationalized with the help of density‐functional‐theory‐based transport calculations. In particular, these calculations show that the anchoring groups determine the junction conductance by controlling not only the strength of the coupling to the metal but also the position of the relevant molecular energy levels.     

Applying process design software for capacity increase and revamp of distillation units

The paper presents the results of feasibility study for increase of crude processing capacity and improves of energy efficiency of crude oil distillation units. Results introduce that boosting up the distillation capacity was solved while keeping the flexibility of units for processing different type crude oils. Analysis of heat exchanger network resulted significant reduction in fuel consumption and in CO₂ emission (93 × 10⁶ GJ year⁻¹ and 3,030 tCO₂ year⁻¹, respectively). Modification of furnace of one of the distillation units showed 63 GJ kt_crude⁻¹ saving in energy and 4.5 tCO₂ kt_crude⁻¹ decrease in emission.     

A model for non-local bonding in bipartite systems

We hypothesize a non-local model for two-component quantum systems based on a non-linear but non-perturbatively solvable operator equation. The equation introduces a meta-structure, which conforms with quantum mechanics but constrains the range of admissible states of the system. According to the proposed model the composite system as a whole may bind into a non-local molecule with an energy gap different than that of free components.     

Digital micromirror device as a spatial illuminator for fluorescence lifetime and hyperspectral imaging

Time-domain fluorescence lifetime imaging (FLIM) and hyper-spectral imaging (HSI) are two advanced microscopy techniques widely used in biological studies. Typically both FLIM and HSI are performed with either a whole-field or raster-scanning approach, which often prove to be technically complex and expensive, requiring the user to accept a compromise among precision, speed, and spatial resolution. We propose the use of a digital micromirror device (DMD) as a spatial illuminator for time-domain FLIM and HSI with a laser diode excitation source. The rather unique features of the DMD allow both random and parallel access to regions of interest (ROIs) on the sample, in a very rapid and repeatable fashion. As a consequence both spectral and lifetime images can be acquired with a precision normally associated with single-point systems but with a high degree of flexibility in their spatial construction. In addition, the DMD system offers a very efficient way of implementing a global analysis approach for FLIM, where average fluorescence decay parameters are first acquired for a ROI and then used as initial estimates in determining their spatial distribution within the ROI. Experimental results obtained on phantoms employing fluorescent dyes clearly show how the DMD method supports both spectral and temporal separation for target identification in HSI and FLIM, respectively.