Multimodal behavior realization for embodied conversational agents

Applications with intelligent conversational virtual humans, called Embodied Conversational Agents (ECAs), seek to bring human-like abilities into machines and establish natural human-computer interaction. In this paper we discuss realization of ECA multimodal behaviors which include speech and nonverbal behaviors. We devise RealActor, an open-source, multi-platform animation system for real-time multimodal behavior realization for ECAs. The system employs a novel solution for synchronizing gestures and speech using neural networks. It also employs an adaptive face animation model based on Facial Action Coding System (FACS) to synthesize face expressions. Our aim is to provide a generic animation system which can help researchers create believable and expressive ECAs.     

Proof rules for gotos

Summary We offer a program specification format adapted to statements with multiple exits, and use it to present proof rules to replace the somewhat unsatisfactory treatment of jumps in [3]. We justify the bridled use of gotos in return exits, failure exits, and loops with jumps in the middle. To exemplify our methodology, we prove the function Lookup.     

X-ray diffraction and Fourier transform-infrared analysis of the rust formed by corrosion of steel in aqueous solutions

Chemical and structural properties of the rust formed by corrosion of steel in aqueous solutions were studied by X-ray diffraction and Fourier transform infrared (FT-IR) spectroscopy. The corrosion products of steel were generated in aqueous solutions of different electrolyte compositions at room temperature (20 °C) or in an autoclave at 120 °C. X-ray diffraction analysis showed the presence of different oxide phases in the rust, such as lepidocrocite, magnetite, ferrihydrite, goethite and haematite. In all samples, the presence of an amorphous fraction was detected. Ferrihydrite was detected only in the rust samples formed at 120 °C, The characteristic properties of the FT-IR spectrum of the ferrihydrite component in the rust were investigated. Phase compositions of the corrosion products depended on the formation temperature and the electrolyte composition of the aqueous solutions. The influence of chloride, nitrate or sulphate anions on the phase composition of the rust is discussed.     

Heuristic Modelling of the Water Resources Management in the Guadalquivir River Basin, Southern Spain

A model comprising blocks of artificial neural networks (ANNs) combined in sequence was used to simulate the inflow and outflow in a water resources system under a shortage of water. We assessed the selection of appropriate input data using linear and non-linear cross-correlation functions and sensitivity analysis. The potential model inputs were flow, precipitation and temperature data from various gauging stations throughout the upper watershed of the ‘Guadiana Menor’ River (southern Spain), and the model considered various input time lags. The ANNs based on the selected inputs were effective relative to those with no relevant inputs, and produced more parsimonious models. We also investigated conceptual analogies inherent in the ANN models by analyzing the response profiles of the modelled variables (inflow and outflow) in relation to each of the selected input data. The results demonstrate that the neural approach approximated the behaviour of various components of the water resources system in terms of various hydrologic cycle processes and management rules. Our findings suggest that in dry periods a mean temperature increase of 1°C in low altitude locations of the region will result in a mean decrease of approximately 2% in the inflow to the water resources system, and a mean increase of approximately 12% in the outflow requirements for irrigation purposes.     

Computationally efficient application of the generic shape-illumination invariant to face recognition from video

As a problem of high practical appeal but many outstanding challenges, computer-based face recognition remains a topic of extensive research attention. In this paper we are specifically interested in the task of identifying a person using multiple images both in training and as a query. Thus, a novel method is proposed which advances the state-of-the-art in set-based face recognition. The introduced approach is based on a previously described invariant in the form of generic shape-illumination effects. The contributions include (i) an analysis of the computational demands of the original method and a demonstration of its practical limitations, (ii) a novel representation of personal appearance in the form of linked mixture models in image and pose-signature spaces, and (iii) an efficient (in terms of storage needs and matching time) manifold re-illumination algorithm based on the aforementioned representation. An evaluation and comparison of the proposed method with the original generic shape-illumination algorithm shows that comparably high recognition rates are achieved on a large data set (1.5% error on 700 face sets containing 100 individuals and extreme illumination variation) with a dramatic improvement in matching speed (over 700 times for sets containing 1600 faces) and storage requirements (independent of the number of training images). Theoretical and empirical findings of the present work are used to identify and discuss avenues for future research.     

Additive Spanners and Distance and Routing Labeling Schemes for Hyperbolic Graphs

δ-Hyperbolic metric spaces have been defined by M. Gromov in 1987 via a simple 4-point condition: for any four points u,v,w,x, the two larger of the distance sums d(u,v)+d(w,x),d(u,w)+d(v,x),d(u,x)+d(v,w) differ by at most?2δ. They play an important role in geometric group theory, geometry of negatively curved spaces, and have recently become of interest in several domains of computer science, including algorithms and networking. In this paper, we study unweighted δ-hyperbolic graphs. Using the Layering Partition technique, we show that every n-vertex δ-hyperbolic graph with δ≥1/2 has an additive O(δlog?n)-spanner with at most O(δn) edges and provide a simpler, in our opinion, and faster construction of distance approximating trees of δ-hyperbolic graphs with an additive error O(δlog?n). The construction of our tree takes only linear time in the size of the input graph. As a consequence, we show that the family of n-vertex δ-hyperbolic graphs with δ≥1/2 admits a routing labeling scheme with O(δlog?² n) bit labels, O(δlog?n) additive stretch and O(log?₂(4δ)) time routing protocol, and a distance labeling scheme with O(log?² n) bit labels, O(δlog?n) additive error and constant time distance decoder.     

Protus 2.0: Ontology-based semantic recommendation in programming tutoring system

With the development of the Semantic web the use of ontologies as a formalism to describe knowledge and information in a way that can be shared on the web is becoming common. The explicit conceptualization of system components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration and construction of knowledge rich and intensive systems. Semantic web provides huge potential and opportunities for developing the next generation of e-learning systems. In previous work, we presented tutoring system named Protus (PRogramming TUtoring System) that is used for learning the essence of Java programming language. It uses principles of learning style identification and content recommendation for course personalization. This paper presents new approach to perform effective personalization highly based on Semantic web technologies performed in new version of the system, named Protus 2.0. This comprises the use of an ontology and adaptation rules for knowledge representation and inference engines for reasoning. Functionality, structure and implementation of a Protus 2.0 ontology as well as syntax of SWRL rules implemented for on-the-fly personalization will be presented in this paper.     

Intelligent control of DC motor driven electromechanical fin actuator

In this paper modeling, simulation and control of an electromechanical actuator (EMA) system for aerofin control (AFC) with permanent magnet brush DC motor driven by a constant current driver are investigated. Nonlinear model of the EMA-AFC system has been developed and experimentally verified in actuator test bench. Model has been used as the starting point for PID position controller synthesis. To improve performances of the system, computational intelligence has been applied. Genetic PID optimization, genetic algorithm (GA) optimized fuzzy supervisory PID control and finally GA optimized nonlinear PID algorithm modification are proposed. Improved transient response and system behavior have also been experimentally validated.     

Minor maintenance actions and their impact on diagnostic and prognostic CBM models

Minor maintenance actions can affect condition-monitoring measurements, which may in turn affect the accuracy of diagnostic and prognostic techniques used in condition-based maintenance (CBM). Outputs of a CBM model include the calculation of optimal maintenance decisions, conditional reliability, and the calculation of remaining useful life, among other measures. It is necessary to have a model for the manner in which the condition monitoring data changes over time to produce these output measures; many models have been developed to do so. It is also common to record minor maintenance actions carried out on critical assets, with lubricant changes being one of the most common, but it is unusual for models to consider the impact of such maintenance actions that affect the condition monitoring data. In this paper we discuss the impact of minor maintenance on CBM models. A dataset on a collection of gearboxes, consisting of reliability and oil analysis information, including data on oil changes and oil additions, is used to illustrate the benefit of modelling minor maintenance actions.     

GEOCHEMICAL CHARACTERISTICS OF CRUDE OILS FROM THE SHARARA-C OIL FIELD,MURZUQ BASIN,SOUTHWESTERN LIBYA

Crude oil samples from the Sharara-C oil field (Concession NC-115, Murzuq Basin, SW Libya) were analysed by organic geochemical methods in order to infer the geochemical characteristics of their respective source rocks. Aromatic hydrocarbons were analysed by gas chromatography – mass spectrometry (GC-MS), and gas chromatography – tandem mass spectrometry (GC-MS-MS) was used to analyse saturated biomarkers. The Sharara-C oils are interpreted to have been generated by marine shales containing mixed terrigenous and marine organic materials deposited in an intermediate (suboxic) environment. Age-specific biomarker ratios indicated that the oils are older than Cretaceous, and maturation-related parameters pointed to their high thermal maturity. Consistent with previous studies, source rocks are inferred to be “hot” shales in the Lower Silurian Tanezzuft Formation. Almost all the parameter ratios calculated varied over a very narrow range, indicating that the investigated oils were compositionally similar. The only significant difference that was noted concerned the sterane/hopane ratios whose variation suggested that there was some variability in the composition of the source organic material. The organic geochemical parameters determined for the Sharara-C crude oils were compared with published data on other crude oils from Concession NC-115. Almost all the parameters agreed well with previously published data on oils from this part of the Murzuq Basin. The greatest deviation concerned the values of some of the maturity parameters. This tended to confirm the conclusions of previous studies concerning the presence of a number of distinct oil families and sub-families in the Sharara oil field area which are genetically related but which have different maturities.