Impact of virtual atmospherics and functional qualities on the online gambler's experience

This study empirically tests a stimulus–organism–response (S–O–R) structural model that proposes that an online casino's atmospheric cues and functional qualities influence individuals' affective and cognitive responses, which in turn impact consumer behavioural intentions. Using self-reported data from a primarily US-based sample, analysed elements of the online gambling site stimulus included high and low task-relevant cues, financial trust, and gambling value. Demographic characteristics were found to moderate the relationship between the stimulus and internal satisfaction, with demographic group differences found among all stimulus constructs. Results emphasise the significant role that atmospherics and functional qualities play in generating positive behaviours from online gamblers, with additional implications in marketplace competitiveness and in responsible gambling practices.     

A Multicast-Enabled Delivery Framework for QoE Assurance of Over-The-Top Services in Multimedia Access Networks

Over-The-Top (OTT) video services are becoming more and more important in today’s broadband access networks. While original OTT services only offered short duration medium quality videos, more recently, premium content such as high definition full feature movies and live video are offered as well. For operators, who see the potential in providing Quality of Experience (QoE) assurance for an increased revenue, this introduces important new network management challenges. Traditional network management paradigms are often not suited for ensuring QoE guarantees as the provider does not have any control on the content’s origin. In this article, we focus on the management of an OTT-based video service. We present a loosely coupled architecture that can be seamlessly integrated into an existing OTT-based video delivery architecture. The framework has the goal of resolving the network bottleneck that might occur from high peaks in the requests for OTT video services. The proposed approach groups the existing Hypertext Transfer Protocol (HTTP) based video connections to be multicasted over an access network’s bottleneck and then splits them again to reconstruct the original HTTP connections. A prototype of this architecture is presented, which includes the caching of videos and incorporates retransmission schemes to ensure robust transmission. Furthermore, an autonomic algorithm is presented that allows to intelligently select which OTT videos need to be multicasted by making a remote assessment of the cache state to predict the future availability of content. The approach was evaluated through both simulation and large scale emulation and shows a significant gain in scalability of the prototype compared to a traditional video delivery architecture.     

Formulating the template ILP consistency problem as a constraint satisfaction problem

Inductive Logic Programming (ILP) deals with the problem of finding a hypothesis covering positive examples and excluding negative examples, where both hypotheses and examples are expressed in first-order logic. In this paper we employ constraint satisfaction techniques to model and solve a problem known as template ILP consistency, which assumes that the structure of a hypothesis is known and the task is to find unification of the contained variables. In particular, we present a constraint model with index variables accompanied by a Boolean model to strengthen inference and hence improve efficiency. The efficiency of models is demonstrated experimentally.     

Solving the electricity production planning problem by a column generation based heuristic

This paper presents a heuristic method based on column generation for the EDF (Electricité De France) long-term electricity production planning problem proposed as subject of the ROADEF/EURO 2010 Challenge. This is to our knowledge the first-ranked method among those methods based on mathematical programming, and was ranked fourth overall. The problem consists in determining a production plan over the whole time horizon for each thermal power plant of the French electricity company, and for nuclear plants, a schedule of plant outages which are necessary for refueling and maintenance operations. The average cost of the overall outage and production planning, computed over a set of demand scenarios, is to be minimized. The method proceeds in two stages. In the first stage, dates for outages are fixed once for all for each nuclear plant. Data are aggregated with a single average scenario and reduced time steps, and a set-partitioning reformulation of this aggregated problem is solved for fixing outage dates with a heuristic based on column generation. The pricing problem associated with each nuclear plant is a shortest path problem in an appropriately constructed graph. In the second stage, the reload level is determined at each date of an outage, considering now all scenarios. Finally, the production quantities between two outages are optimized for each plant and each scenario by solving independent linear programming problems.     

Evolving Takagi–Sugeno fuzzy model based on switching to neighboring models

In this paper, we propose a new online identification approach for evolving Takagi–Sugeno (TS) fuzzy models. Here, for a TS model, a certain number of models as neighboring models are defined and then the TS model switches to one of them at each stage of evolving. We define neighboring models for an in-progress (current) TS model as its fairly evolved versions, which are different with it just in two fuzzy rules. To generate neighboring models for the current model, we apply specially designed split and merge operations. By each split operation, a fuzzy rule is replaced with two rules; while by each merge operation, two fuzzy rules combine to one rule. Among neighboring models, the one with the minimum sum of squared errors – on certain time intervals – replaces the current model.To reduce the computational load of the proposed evolving TS model, straightforward relations between outputs of neighboring models and that of current model are established. Also, to reduce the number of rules, we define and use first-order TS fuzzy models whose generated local linear models can be localized in flexible fuzzy subspaces. To demonstrate the improved performance of the proposed identification approach, the efficiency of the evolving TS model is studied in prediction of monthly sunspot number and forecast of daily electrical power consumption. The prediction and modeling results are compared with that of some important existing evolving fuzzy systems.     

A multi-agent legal recommender system

Infonorma is a multi-agent system that provides its users with recommendations of legal normative instruments they might be interested in. The Filter agent of Infonorma classifies normative instruments represented as Semantic Web documents into legal branches and performs content-based similarity analysis. This agent, as well as the entire Infonorma system, was modeled under the guidelines of MAAEM, a software development methodology for multi-agent application engineering. This article describes the Infonorma requirements specification, the architectural design solution for those requirements, the detailed design of the Filter agent and the implementation model of Infonorma, according to the guidelines of the MAAEM methodology.     

Bulk mass flow in a vibratory finisher: mechanisms and effect of process parameters

Vibratory finishing is a widely-used manufacturing process in which a vibrating container filled with granular media becomes fluidized. The resulting bulk flow entrains workpieces and exposes their surfaces to the impacts resulting from the small-scale media vibrations. The bulk flow is responsible for entrainment and mixing, while the media vibration does work on the surfaces. The selection of machine vibration parameters is commonly based on experience due to the difficulty in predicting the fluidized bed behavior. In this work, a discrete element method was used to investigate how the bulk flow in an actual tub finisher filled with steel balls depends on the tub motion parameters through a parametric study. The underlying mechanisms that create and drive the bulk flow were identified by examining the relationships between the bulk flow rates and the wall forces. Finally, the connection between the wall motion and the wall forces was investigated. The tub frequency was the most effective control parameter and there was an optimal phase difference between the horizontal and vertical vibrations to maximize bulk flow. The relationship between the media packing at the walls and the tangential forces between the walls and the media explained the formation and speed of the bulk flow. Lastly, it was shown that the tangential wall forces, unlike the normal forces, cannot be obtained from the known wall motion alone since they also depend on the media velocities relative to the walls.     

Influence of process parameters on average particle speeds in a vibratory finisher

Vibratory finishing (VF) employs vibrationally-fluidized granular media to finish the surfaces of workpieces that are entrained in the flowing media. Its application has been based mostly on experience and trial-and-error due to the complexity of the granular material behavior. The present study used discrete element modeling (DEM) to investigate how the movement of a commercial two-dimensional tub finisher influenced the average particle speed of the media in a bed of smooth, steel, spherical particles, and thus the work that would be done on an entrained workpiece. The parameters governing the tub wall motion (frequency, in-plane amplitudes, and phases of vibration) and the coefficient of friction between the media and the wall were systematically varied in 71 three-dimensional DEM simulations. The average particle speed was affected mostly by the vertical amplitude of tub motion rather than by the frequency, and was mostly independent of other parameters of motion and of the wall friction. A strong relationship was found between the average particle speed and the work done by the wall per cycle of vibration. The normal force on the wall was also found to correlate strongly with the normal component of the wall velocity. Together, these relationships offer the potential to enable the analytical prediction of the average particle speed based on the motion parameters of the tub alone. The paper provides a set of practical guidelines for the control of the average particle speed in VF that are explained by the forces between the media and walls of the tub finisher.     

An Intelligent Man-Machine Dialogue System Based on AI Planning

We describe the modular architecture of a generic dialogue system that assists a user/operator in performing a task with a tool. This coaching system is named CALLIOPE after the Greek goddess of eloquence. It aims at being an active partner in an intelligent man-machine dialogue. The intelligent dimension of the coaching system is reflected by its ability to adapt to the user and the situation at hand. The CALLIOPE system contains an explicit user model and world model to situate its dialogue actions. A plan library allows it to follow loosely predetermined dialogue scenarios.The heart of the coaching system is an AI planning module, which plans a series of dialogue actions. We present a coherent set of three dialogue or speech actions that will make up the physical form of the man-machine communication.The use of the AI planning paradigm as a basis for man-machine interaction is motivated by research in various disciplines, as e.g., AI, Cognitive Science and Social Sciences. Starting from the man-man communication metaphor, we can view the thinking before speaking of a human communication partner as constructing an underlying plan which is responsible for the purposiveness, the organisation and the relevance of the communication.CALLIOPE has been fully implemented and tested on theoretical examples. At present, also three tailored versions of CALLIOPE are in operational use in different industrial application domains: operator support for remedying tasks in chemical process industry, operator support for a combined task of planning, plan execution and process control in the area of chemical process development, and thirdly decision support in production scheduling.