Assessing the Novelty of Computer-Generated Narratives Using Empirical Metrics

Novelty is a key concept to understand creativity. Evaluating a piece of artwork or other creation in terms of novelty requires comparisons to other works and considerations about the elements that have been reused in the creative process. Human beings perform this analysis intuitively, but in order to simulate it using computers, the objects to be compared and the similarity metrics to be used should be formalized and explicitly implemented. In this paper we present a study on relevant elements for the assessment of novelty in computer-generated narratives. We focus on the domain of folk-tales, working with simple plots and basic narrative elements: events, characters, props and scenarios. Based on the empirical results of this study we propose a set of computational metrics for the automatic assessment of novelty. Although oriented to the implementation of our own story generation system, the measurement methodology we propose can be easily generalized to other creative systems.     

Hot metal pretreatment by powder injection of lime‐based reagents

A mathematical model earlier proposed has been improved to predict the kinetics of multicomponent reactions in the hot metal pretreatment through the injection of reactive fluxes. It is assumed that there are two reaction zones along the flux injection operation: a transitory reaction between the rising particles and the bulk metal, and the permanent reaction between the metal and the top slag. A criterion to estimate the fraction of solids which will react with molten iron in a three‐phase jet (gas‐solid‐liquid) was considered; this fraction of solids carries out the transitory reaction. The model also takes into account the thermodynamic changes produced in the metal and slag due to the chemical reactions. Calculated results of the model are in good agreement with experimental results for the desulfurization of hot metal through the injection of CaO‐SiO₂‐CaF₂‐FeO‐Na₂O reagents at 1400 ‐ 1450 °C. Two kinds of hot metal were tested, one with a low carbon mass content of 3 % and the other with a high carbon mass content of 4.5 %.     

Influence of mediator immobilization on the electrochemically assisted microbial dechlorination of trichloroethene (TCE) and cis‐dichloroethene (cis‐DCE)

BACKGROUND: A bioelectrochemical process for trichloroethene (TCE) dechlorination was developed. In this new process, a solid‐state electrode polarized to ?450 mV versus the standard hydrogen electrode (SHE), in combination with a redox mediator (i.e., methyl viologen, MV) is employed as an electron donor for the microbial reductive dechlorination of TCE. In this study we compared the performance of the process with the redox mediator immobilized at the surface of electrodes or dissolved in the bulk liquid, using both a culture highly enriched in Desulfitobacterium spp., capable of dechlorinating TCE to cis‐dichloroethene (cis‐DCE), and a culture highly enriched in Dehalococcoides spp. capable of dechlorinating cis‐DCE to ethene. RESULTS: Short‐term potentiostatic (?450 mV versus SHE) experiments showed that TCE or cis‐DCE was dechlorinated both in the presence of soluble (500 µmol L^?1) and immobilized MV. However, TCE or cis‐DCE dechlorination rates with MV‐modified electrodes were remarkably lower than with soluble MV. Both cultures produced significant amounts of H₂ in the presence of electrically reduced, soluble MV, whereas no H₂ was produced when the mediator was immobilized at the electrode surface, regardless of the potential applied to the electrode, in the range ?425 to ?500 mV versus SHE. CONCLUSIONS: The process, operated with modified electrodes, supports the microbial dechlorination of TCE to ethene. Immobilization not only allows retention of the mediator within the system, but also increases process efficiency by preventing bioelectrochemical H₂ formation. On the other hand, strategies to increase dechlorination rates with modified electrodes need to be developed. Copyright © 2009 Society of Chemical Industry     

Strain sensing fabric for hand posture and gesture monitoring.

In this paper, we report on a new technology used to implement strain sensors to be integrated in usual garments. A particular conductive mixture based on commercial products is realized and directly spread over a piece of fabric, which shows, after the treatment, piezoresistive properties, i.e., a change in resistance when it is strained. This property is exploited to realize sensorized garments such as gloves, leotards, and seat covers capable of reconstructing and monitoring body shape, posture, and gesture. In general, this technology is a good candidate for adherent wearable systems with excellent mechanical coupling with body surface. Here, we mainly focused on a sensorized glove able to detect posture and movements of the fingers. It could be used in several fields of application. We report on experimental results of a sensorized glove used as movements recorder for rehabilitation therapies and medicine. Furthermore, we describe a dedicated methodology used to read the output sensors which allowed to avoid using metallic wires for the connections. The price to be paid for all these advantages is a nonlinear electric response of the fabric sensor and a too long settling time, that in principle, make these sensors not suitable for real-time applications. Here we propose a hardware and computational solution to overcome this limitation.     

Multi-stage modeling using fuzzy multi-criteria feature selection to improve survival prediction of ICU septic shock patients

In many binary medical classification problems, the cost of misclassifying one category is higher than the other, and in these applications it is desirable to employ a classifier with selective sensitivity or specificity. This work explores the utility of a fuzzy multi–criteria function for performance evaluation during knowledge–based medical classification and prediction. The method presented here uses fuzzy optimization to combine the sensitivity, specificity, and accuracy of classification as goals in a single objective function. This approach is used to assign flexible goals, which can be used to maximize the outcome in terms of each one of the goals. The proposed approach significantly increases the sensitivity and the specificity while maintaining or increasing accuracy. The versatility of the method is further exploited in a multi-model approach, using individual structures of multi-objective optimization of sensitivity and specificity separately, and then combining their outcomes through a decision-making module. Among various medical benefits derived from applying this technique, the divergent feature sets selected by high sensitivity and specificity models lend insight into factors more integrally connected to what causes risk of death for patients.     

Generality and legibility in mobile manipulation

This article investigates methods for achieving more general manipulation capabilities for mobile manipulation platforms, which produce legible behavior in human living environments. To achieve generality and legibility, we combine two control mechanisms. First of all, experience- and observation-based learning of skills is applied to routine tasks, so that the repetitive and stereotypical character of everyday activity is exploited. Second, we use planning, reasoning, and search for novel tasks which have no stereotypical solution. We apply these ideas to the learning and use of action-related places, to the model-based visual recognition and localization of objects, and the learning and application of reaching strategies and motions from humans. We demonstrate the integration of these mechanisms into a single low-level control system for autonomous manipulation platforms.     

Influences of data filtering on human–computer interaction by gaze-contingent display and eye-tracking applications

We describe an interactive gaze-contingent display (GCD) applied to clinical applications; the system uses a simple texture hole to inhibit peripheral vision, to test and stress overt mechanisms of visual searching in normal subjects. The correct use of GCD in vision research is affected by tremor of the hole, due to system noise, nystagmus, eye blinking, calibration and subject reactivity. These issues compromise the execution of task. In order to obtain a stable GCD hole, we implemented a predictive gaze-contingent display (PGCD), fitting through dispersion of fixations and modulating a filter. The paper describes the PGCD and compare it with the common technique, providing evidence that humans fit exploration based on the characteristics of the computer system; in particular we found significant difference applying PGCD or a simple finite impulse response filter. We suggest that a correct human–computer interaction applied to neuropsychological context must be developed taking in consideration both technical point of view and human behavior.     

Image Analysis Techniques for Automated Hazelnut Peeling Determination

According to FAO statistics, in 2000, Italy was the second largest hazelnut (Corylus avellana, L. 1753) producer in the world. The price of the stock depends on the nut quality (kernel/nut ratio, nut and seed defect, percentage of peeling, and taste panel scores). The evaluation of peeling efficiency after toasting is generally conducted by trained operators in sight on 100 kernels. This work tests two alternative objective methods of after toasting peeling evaluation based on image analysis. Eleven hazelnut cultivars were analyzed and results were compared with the ones assessed by trained operators. Images were analyzed with two statistical approaches: fixed values of RGB thresholding and trained K Nearest Neighbors (KNN). Root mean squared error (RMSE), estimating the comparison between operators and the two image analysis-based techniques, shows better results for KNN (6.6) with respect to fixed threshold (15.9).     

Influence of the alkyl chain length of HSO3-R-MCM-41 on the esterification of glycerol with fatty acids

Ordered mesoporous materials functionalized with alkyl sulfonic acid groups have been proved to be efficient catalysts for esterification. In this paper we report on the synthesis and characterization of new materials containing simultaneously alkyl groups (vinyl, chloromethyl), that have been sulfonated in a post-synthesis step, and methyl groups. Different techniques have been used to characterize the obtained materials: XRD, TEM, elemental analysis, nitrogen adsorption, TGA, ²⁹Si and ¹³C MAS NMR. Finally, the influence of the different synthesis parameters and functional groups on the behavior of the catalysts in the reaction of esterification of glycerol with lauric and oleic acids has been studied. The catalytic performance of the resulting HSO₃-ethyl-MCM-41, HSO₃-ethyl/methyl-MCM-41 and HSO₃-methyl-MCM-41 new materials is also compared to those of HSO₃-phenyl/methyl-MCM-41 and HSO₃-propyl/methyl-MCM-41 synthesized previously. It has been demonstrated that an optimum balance among parameters such as nature of the organic group which support the sulfonic acid, distance between the sulfonic group and the silica surface, average pore size of the material, etc., allows to obtain catalysts with improved activity and selectivity for these reactions.