Improving Communication in E-democracy Using Natural Language Processing

E-democracy, the design and development of new techniques for improving communication between public administration and citizens, is a major application field for natural language processing and language engineering. Helping citizens access information in a friendly, intuitive way is the primary objective of a global e-democracy framework. The E-democracy European Network project (EDEN) aimed at discovering whether a particular NLP (natural language processing) approach could further e-democracy by increasing citizens' participation in the decision-making process. The goal was twofold: to test whether e-democracy requirements could be meet using advanced linguistic technology and to test whether augmented phrase structure grammars (APSGs) were robust and well-assessed enough to use in a real-world environment. Also, the aim is to develop two toolsets to improve communication between PAs and citizens in the context of urban planning: a set of NLP-based tools to simplify access to information and knowledge and a set of forum and polling devices     

Measurement selection for parametric IC fault diagnosis

This article presents experimental results which show feedforward neural networks are well-suited for analog IC fault diagnosis. Boundary band data (BBD) measurement selection is used to reduce the computational overhead of the FFN training phase. We compare the diagnostic accuracy between traditional statistical classifiers and feedforward neural networks trained with various measurement selection criteria. The feedforward networks consistently perform as well as or better than the other classifiers in term of accuracy. Training using BBD consistently reduces the FFN training efforts without degrading the performance. Experimental results suggest that feedforward networks provide a cost efficient method for IC fault diagnosis in a large scale production testing environment.This work is supported by NSF-IUC CDADIC, Project 90-1.     

What is being masked in object substitution masking?

Object substitution masking (OSM) is said to occur when a perceptual object is hypothesized that is mismatched by subsequent sensory evidence, leading to a new hypothesized object being substituted for the first. For example, when a brief target is accompanied by a longer lasting display of nonoverlapping mask elements, reporting of target features may be impaired. J. T. Enns and V. Di Lollo (2000) considered it an outstanding question whether OSM masks some or all aspects of a target. The authors report three experiments demonstrating that OSM can selectively affect target features. Participants may be able to detect a target while being unable to report other aspects of it or to report the color but not the orientation of a target (or vice versa). We discuss these findings in relation to two other visual phenomena. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Product and process parameters determination for quality and cost

The purpose of this study is to conduct a concurrent product and process parameters determination for further cost reduction and quality enhancement. The process design-related parameters, such as process mean, process tolerance and product design-related parameters, such as product tolerance, are considered simultaneously in the proposed approach. To reflect the response from these three key controllable characteristics: process mean, process tolerance and product tolerance, the key measurement score, which is the sum of the mean cost, tolerance cost, quality loss and failure cost, is used to evaluate the present model. Two examples are provided for demonstrating the application of single and multiple quality characteristics.     

Bright-field scanning confocal electron microscopy using a double aberration-corrected transmission electron microscope

Scanning confocal electron microscopy (SCEM) offers a mechanism for three-dimensional imaging of materials, which makes use of the reduced depth of field in an aberration-corrected transmission electron microscope. The simplest configuration of SCEM is the bright-field mode. In this paper we present experimental data and simulations showing the form of bright-field SCEM images. We show that the depth dependence of the three-dimensional image can be explained in terms of two-dimensional images formed in the detector plane. For a crystalline sample, this so-called probe image is shown to be similar to a conventional diffraction pattern. Experimental results and simulations show how the diffracted probes in this image are elongated in thicker crystals and the use of this elongation to estimate sample thickness is explored.     

Reaching the Fundamental Limitation in CO2 Reduction to CO with Single Atom Catalysts

The electrochemical CO₂ reduction reaction (CO₂RR) to value-added chemicals with renewable electricity is a promising method to decarbonize parts of the chemical industry. Recently, single metal atoms in nitrogen-doped carbon (MNC) have emerged as potential electrocatalysts for CO₂RR to CO with high activity and faradaic efficiency, although the reaction limitation for CO₂RR to CO is unclear. To understand the comparison of intrinsic activity of different MNCs, two catalysts are synthesized through a decoupled two-step synthesis approach of high temperature pyrolysis and low temperature metalation (Fe or Ni). The highly meso-porous structure results in the highest reported electrochemical active site utilization based on in situ nitrite stripping; up to 59±6% for NiNC. Ex situ X-ray absorption spectroscopy (XAS) confirms the penta-coordinated nature of the active sites. The catalysts are amongst the most active in the literature for CO₂ reduction to CO. The density functional theory calculations (DFT) show that their binding to the reaction intermediates approximates to that of Au surfaces. However, it is found that the turnover frequencies (TOFs) of the most active catalysts for CO evolution converge, suggesting a fundamental ceiling to the catalytic rates.     

The effect on lower spine muscle activation of walking on a narrow beam in virtual reality

To what extent do people behave in immersive virtual environments as they would in similar situations in a physical environment? There are many ways to address this question, ranging from questionnaires, behavioral studies, and the use of physiological measures. Here, we compare the onsets of muscle activity using surface electromyography (EMG) while participants were walking under three different conditions: on a normal floor surface, on a narrow ribbon along the floor, and on a narrow platform raised off the floor. The same situation was rendered in an immersive virtual environment (IVE) Cave-like system, and 12 participants did the three types of walking in a counter-balanced within-groups design. The mean number of EMG activity onsets per unit time followed the same pattern in the virtual environment as in the physical environment-significantly higher for walking on the platform compared to walking on the floor. Even though participants knew that they were in fact really walking at floor level in the virtual environment condition, the visual illusion of walking on a raised platform was sufficient to influence their behavior in a measurable way. This opens up the door for this technique to be used in gait and posture related scenarios including rehabilitation.     

A Convergent-Divergent Approach to Context Processing, General Intellectual Functioning, and the Genetic Liability to Schizophrenia.

Convergent and divergent validity are critically important in developing psychological measures that reveal interpretable deficits in disordered populations. This article reports on 2 studies that evaluated the validity of context processing measures. In Experiment 1, a confirmatory factor analysis of data from 481 healthy adults established the convergent validity of 2 context processing measures and showed that context processing accounted for significant amounts of variance in standard IQ and working memory measures. In Experiment 2, 20 schizophrenia patients, 16 of their healthy siblings, and 28 controls were evaluated using a novel, short context processing measure, the dot pattern expectancy (DPX) task. The DPX was sensitive to specific deficits in schizophrenia patients and their healthy siblings. These findings support the construct validity of context processing measures, suggest context processing is a component of intellectual functioning, and demonstrate that brief context processing measures remain sensitive to psychopathological deficits. (PsycINFO Database Record (c) 2010 APA, all rights reserved)