A survey of research in deliberative real-time artificial intelligence

This paper surveys recent research in deliberative real-time artificial intelligence (AI). Major areas of study have beenanytime algorithms, approximate processing, and large system architectures. We describe several systems in each of these areas, focusing both on progress within the field, and the costs, benefits and interactions among different problem and algorithm complexity limitations used in the surveyed work.     

Analysis of information exchange activities to actualize and validate situation awareness during shift changeovers in nuclear power plants

Shift work situations occur in almost all safety‐critical organizations, and the investigations of some catastrophes like Chernobyl, Exxon Valdez, and the Gol/Legacy mid‐air collision indicated that shift work information exchange played an important role during the evolution of the situation before the accidents. Inadequate communications during shift changeovers challenged operators' work in the moments that preceded these accidents, because they got inadequate information about the current situation. Our research focuses on the information exchange activities (verbal, written, and nonverbal) of nuclear power plant control operators during shift changeovers. Our aim is to investigate how verbal exchanges and other representations enable operator crews to share information regarding the events that occurred in the previous shift to achieve adequate situation awareness. Our findings indicated the importance and richness of the information exchange during the shift changeover process to update and validate individual and collective situation awareness, showing that information adequately shared enables the ad hoc configurations of regulation loops and a safer use of simplified strategies that can be understood and be validated by other operators, reducing the occurrence of cognitive overloads and contributing to the construction of a common cognitive ground that enhances system resilience. © 2010 Wiley Periodicals, Inc.     

Fuzzy ontologies-based user profiles applied to enhance e-learning activities

Nowadays, the impact of technological developments on improving human activities is becoming more evident. In e-learning, this situation is no different. There are common to use systems that assist the daily activities of students and teachers. Typically, e-learning recommender systems are focused on students; however, teachers can also benefit from these type of tools. A recommender system can propose actions and resources that facilitate teaching activities like structuring learning strategies. In any case, a complete user’s representation is required. This paper shows how a fuzzy ontology can be used to represent user profiles into a recommender engine and enhances the user’s activities into e-learning environments. A fuzzy ontology is an extension of domain ontologies for solving the problems of uncertainty in sharing and reusing knowledge on the Semantic Web. The user profile is built from learning objects published by the user himself into a learning object repository. The initial experiment confirms that the automatically obtained fuzzy ontology is a good representation of the user’s preferences. The experiment results also indicate that the presented approach is useful and warrants further research in recommending and retrieval information.     

Environmental-aware virtual data center network

Cloud computing services have recently become a ubiquitous service delivery model, covering a wide range of applications from personal file sharing to being an enterprise data warehouse. Building green data center networks providing cloud computing services is an emerging trend in the Information and Communication Technology (ICT) industry, because of Global Warming and the potential GHG emissions resulting from cloud services. As one of the first worldwide initiatives provisioning ICT services entirely based on renewable energy such as solar, wind and hydroelectricity across Canada and around the world, the GreenStar Network (GSN) was developed to dynamically transport user services to be processed in data centers built in proximity to green energy sources, reducing Greenhouse Gas (GHG) emissions of ICT equipments. Regarding the current approach, which focuses mainly in reducing energy consumption at the micro-level through energy efficiency improvements, the overall energy consumption will eventually increase due to the growing demand from new services and users, resulting in an increase in GHG emissions. Based on the cooperation between Mantychore FP7 and the GSN, our approach is, therefore, much broader and more appropriate because it focuses on GHG emission reductions at the macro-level. This article presents some outcomes of our implementation of such a network model, which spans multiple green nodes in Canada, Europe and the USA. The network provides cloud computing services based on dynamic provision of network slices through relocation of virtual data centers.     

The importance of the compression test procedure for plastic drums for dangerous goods

Packagings for the transport of dangerous goods are tested by four tests:- free fall, leakproofness, hydraulic pressure and stacking. However, the test procedures can be interpreted in different ways, particularly the stacking test. Some test authorities apply a guided load to the top of the package and others, including the LNE in France, use non-guided loads. The objective of recent research carried out at LNE was to evaluate the risk (in terms of stack stability for dangerous goods packagings) if the stacking tests are performed with guided loads rather than non-guided loads. The stacking tests were carried out on a limited number of plastic drums (200 of four types) submitted for qualification testing using the above four tests, with either guided or non-guided loads. From the results we conclude that:

• i for the transport of dangerous goods of Danger Group I, the field of use is not altered when tested by either procedure.
• ii with goods of Danger Groups II and III, the use of either procedure does not alter the position as far as transport is concerned. However, there is a risk in warehousing: the non-guided procedure being preferred.

     

Overview of Fine-Scale Piezoelectric Ceramic/Polymer Composite Processing

In the past two decades, piezoelectric ceramic/polymer composites with different connectivities have been developed for transducer applications such as hydrophones, biomedical imaging, nondestructive testing, and air imaging. Recently, much attention has been given to fine-scale piezoelectric ceramic/polymer composites. These composites allow higher operating frequencies, and thus increased resolution, in medical imaging transducers. In this review, methods for processing fine-scale piezoelectric ceramic/polymer composites are discussed. The current capabilities, strengths, and weaknesses of each method are compared. The importance of spatial scale in composite performance is also reviewed. Several of the processing methods have demonstrated composites with fine-scale ceramic phases (<50 μm), and others have potential to form composites with a ceramic scale of under 20 μm.     

Biosynthesis of unsaturated fatty acids in the diatomPhaeodactylum tricornutum

The biosynthesis of fatty acids in the diatomPhaeodactylum tricornutum was studied. The diatom was incubated with sodium [1¹⁴C] acetate and the acids [1-¹⁴C] palmitic, [1-¹⁴C] stearic, [1-¹⁴C] linoleic and [1-¹⁴C] α-linolenic. The distribution of radioactivity in the products was determined by gas liquid radiochromatography. The diatom synthesized “de novo” not only saturated and monounsaturated fatty acids, but also linoleic, α-linolenic and other fatty acids including the highly polyunsaturated 20∶5ω3 and 22∶6ω3. When labeled acetate, stearic, α-linolenic or even linoleic acid were incubated with the diatom, the polyunsaturated C₂₀ fatty acids synthesized belonged predominantly to the ω 3 family. The existence of Δ9, Δ6, Δ5, Δ4, ω6 and possibly ω3 desaturases inP. tricornutum is suggested. Member of the Carrera del Investigador Científico of the Comisión de Investigaciones Científicas de la Provincia de Buenos Aires. Member of the Carrera del Investigador Cientifico of the Consejo Nacional de Investigaciones Cientificas y Técnicas.     

Various Scale Levels of the Gel-to-Glass Transformation

The gel-to-glass transition in SiO₂ xerogels prepared by inorganic sol-gel synthesis was studied. The evolution of the molecular structure is traced using the infrared and lowfrequency Raman spectroscopy methods. The elastic moduli of the samples as well as the pore wall moduli at various stages of heat treatment are determined from the data on Brillouin scattering. The formation of monolithic glass on the macroscopic level manifests itself within a narrow temperature range by the dramatic increase of Young's modulus to the accepted value for fused silica. This phenomenon coincides with structural transformations on the molecular scale: (i) the definite correlation radius (the long-range order sphere) appears; (ii) local distortions of the silica network relax. The presence of structural defects influences the kinetics of vitreous SiO₂ formation during xerogel heat treatment.     

Regressing Local to Global Shape Properties for Online Segmentation and Tracking

We propose a novel regression based framework that uses online learned shape information to reconstruct occluded object contours. Our key insight is to regress the global, coarse, properties of shape from its local properties, i.e. its details. We do this by representing shapes using their 2D discrete cosine transforms and by regressing low frequency from high frequency harmonics. We learn this regression model using Locally Weighted Projection Regression which expedites online, incremental learning. After sufficient observation of a set of unoccluded shapes, the learned model can detect occlusion and recover the full shapes from the occluded ones. We demonstrate the ideas using a level-set based tracking system that provides shape and pose, however, the framework could be embedded in any segmentation-based tracking system. Our experiments demonstrate the efficacy of the method on a variety of objects using both real data and artificial data.     

Energieinformatik

Due to the increasing importance of producing and consuming energy more sustainably, Energy Informatics (EI) has evolved into a thriving research area within the CS/IS community. The article attempts to characterize this young and highly dynamic field of research by describing current EI research topics and methods and provides an outlook of how the field might evolve in the future. It is shown that two general research questions have received the most attention so far and are likely to dominate the EI research agenda in the coming years: How to leverage information and communication technology (ICT) to (1) improve energy efficiency, and (2) to integrate decentralized renewable energy sources into the power grid. Selected EI streams are reviewed, highlighting how the respective research questions are broken down into specific research projects and how EI researchers have made contributions based on their individual academic background.